Preliminary Report:

Comprehensive Study of Education on the White Earth Indian Reservation

By

Boyd Bradbury, MSUM Professor of Educational Leadership and Project Director Jane Bergland, MSUM Associate Professor of Nursing and Co-investigator James Bergman, MSUM Graduate Assistant and Co-investigator

Donna Brown, MSUM Interim Assistant Vice President of Student Affairs

Tracy Clark, MSUM Assistant Professor of Social Work Layna Cole, MSUM Associate Professor of Early and Elementary Childhood Leslie Darmofal, MSUM Graduate Student of Nursing Terry Dobmeier, Assistant Professor of Nursing Charles Howell, NIU Department Chair of Education Denise Lajimodiere, NDSU Assistant Professor of Educational Leadership Tracy Moshier, MSUM Graduate Student in Nursing Sue Peterson, MSUM Assistant Professor of Social Work Amy Phillips, UND Assistant Professor of Social Work Becky Williams, MSUMAssistant Professor in the School of Teaching & Learning Tracy Wright, MSUM Associate Professor of Nursing

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Table of Contents

Executive Summary ...... 9 Early Childhood and Head Start ...... 9 K-12 Education ...... 10 Adult Basic Education and White Earth Tribal and Community College (WETCC) ...... 10 Social Services ...... 11 Health Care ...... 11 Health disparities...... 11 Unintentional injury...... 12 Substance abuse...... 13 Mental health...... 14 Obesity and diabetes...... 15 Teen Pregnancy...... 16 Justice System ...... 17 Introduction ...... 18 Issue and Needs...... 18 Rationale for Conducting Study...... 19 Literature Review...... 23 Dropout Rates ...... 23 Sanitation ...... 23 Poverty ...... 24 American Indian Health Disparities ...... 25 The American Indian Academic Achievement Gap ...... 26 Testing...... 28 Cultural Factors ...... 30 Curriculum and Teacher Education ...... 33 References……………………………………………………………………………………………38 Implementation Plan of Study ...... 41 Researchers and Roles ...... 41 Responsibility Areas of White Earth Comprehensive Education Study ...... 42 Desired Data and the Collection Process ...... 42 Time Frame ...... 45 P a g e | 2

Historical Overview of the Ojibwe (Chippewa) People, with Emphasis on the White Earth Band of Chippewa ...... 46 The Name ...... 46 Migration...... 48 Clans ...... 50 Traditional Ojibwe Education ...... 51 Manoomin (Wild Rice) ...... 52 European Contact ...... 52 Dawes Act (General Allotment Act, 1887) ...... 54 Indian Reorganization Act (IRA)...... 55 Termination Era ...... 56 Relocation Era ...... 56 Formal education in ojibwe country...... 56 Boarding School Era ...... 57 Historical Trauma ...... 59 White Earth Today ...... 61 Population...... 63 Government services...... 63 Churches...... 64 Casino...... 64 Communities...... 64 The White Earth tragedy...... 64 Minnesota Chippewa tribe...... 65 Contemporary Ojibwe Education...... 65 White Earth Land Recovery Project...... 67 White Earth tribal council...... 68 References ...... 69 Birth-K Education Portion of Study ...... 73 Description of Early Childhood Education Services on White Earth Reservation ...... 73 White Earth Head Start ...... 75 White Earth Child Care Program ...... 79 Summary ...... 82 P a g e | 3

Additional Research Needed ...... 82 References ...... 844 K-12 Education Portion of Study ...... 86 Introduction ...... 86 American Indian Status: A Definition ...... 87 Unique Characteristics of the American Indian Population ...... 90 Reservations...... 92 Contributing Factors Affecting Achievement and Recommendations ...... 94 American Indian Student Population Percentages ...... 101 Teacher Preparation ...... 103 Years of Teaching Experience Chart ...... 106 Average Teacher Salary ...... 107 Federal Highly Qualified Requirements ...... 109 General Fund Revenues and Expenditures ...... 110 Graduation Rate ...... 112 Dropout Rate ...... 114 Special Education...... 116 Free and Reduced Lunch ...... 118 Student Teacher Ratio ...... 119 Contractual Days ...... 120 Academic Achievement Measurements of School Districts (Tests)...... 121 MCA-II...... 121 MTELL...... 121 MCA-II scores for math, reading, science for 2005-09...... 126 Ethnic breakdown for student achievement on MCA-II, MTAS, and MTELL by district.127 Growth Over the 2008-2009 School Year ...... 128 Comparison Among Districts ...... 133 School District Achievement Data Analysis...... 137 Introduction ...... 137 Overview of differences in district passing rate ...... 138 Environmental factors affecting student achievement ...... 144 Comparison with statewide averages ...... 148 Comparisons of grade-level passing rates...... 150 P a g e | 4

Individual School District Statistics...... 154 Bagley ...... 154 Attendance...... 154 Behavior...... 156 Attendance—high school...... 158 Attendance—elementary school...... 159 Discipline...... 159 Bagley Minnesota student survey data...... 161 Bagley elementary percentiles by year, grade, and subject...... 162 Bagley elementary percentile progressions by cohort and subject...... 167 Bagley high school percentiles by year, grade, and subject...... 172 Bagley high school percentile progressions by year, grade, and subject...... 187 Bagley MAP Data...... 203 Bagley NWEA Analysis...... 247 Circle of Life...... 249 Attendance...... 249 Discipline...... 250 Circle of Life Drug and Alcohol Use...... 251 Detroit Lakes...... 252 Detroit Lakes analysis of MAP testing...... 268 Attendance and discipline data...... 269 Fosston...... 270 Fosston Minnesota student survey data...... 270 Analysis of Fosston data...... 271 Mahnomen ...... 272 Attendance...... 272 Attendance analysis...... 275 NWEA Scores...... 276 Reading...... 283 Naytahwaush...... 300 Attendance...... 300 P a g e | 5

NWEA testing...... 301 Pine Point ...... 303 Attendance...... 303 NWEA Scores...... 307 Behavior...... 309 WOWE...... 311 NWEA scores Ogema and Waubun elementary schools...... 311 NWEA scores WOWE high school...... 338 References ...... 353 Literature Review for Native American Curriculum Studies White Earth Consortium Study...... 357 Resources for White Earth Study Curriculum and Professional Development: ...... 360 References ...... 362 Adult Education ...... 363 White Earth Tribal and Technical College ...... 363 History of tribal colleges...... 363 Indian education and tribal colleges...... 363 Student development theory...... 365 American Indian student development...... 365 History of White Earth Technical and Tribal College (WETTC)...... 366 Accreditation...... 366 Mission statement...... 367 Goal of the college...... 367 Adult basic education...... 368 Student profile...... 368 Future research (phase II)...... 369 Qualitative research...... 369 References ...... 370 Human/Social Services Report ...... 372 Method ...... 372 Social Services Data ...... 373 Tribal and county child welfare...... 373 P a g e | 6

White earth truancy and dropout data...... 375 Appendix A ...... 377 Health Services Portion of the Study ...... 381 Abstract ...... 382 Chapter I – Introduction ...... 383 Background ...... 384 Significance of the Problem ...... 386 Purpose Statement ...... 388 Research Questions ...... 388 Conceptual/Scientific Definition of Variables ...... 388 Theoretical Framework ...... 391 Assumptions and Limitations ...... 394 Chapter I Summary ...... 396 Chapter II- Review of Literature...... 396 Literature Review Organization ...... 397 Search Process ...... 397 Age Group: 0-2 Years of Age ...... 398 Search strategy...... 398 National and state data...... 399 White Earth data...... 399 Specific areas of focus/concern...... 400 Age Group: 3-4 Years of Age ...... 403 Search strategy...... 403 National and state data...... 404 White Earth data...... 405 Specific areas of focus/concern...... 405 Age Group: 5-6 Years of Age ...... 409 Search strategy...... 410 National and state data...... 410 White Earth data ...... 410 Age Group: 7-8 Years of Age ...... 411 Search strategy...... 411 P a g e | 7

National and state data...... 412 White Earth data...... 412 Age Group: 9-10 Years of Age ...... 413 Search strategy...... 413 National and state data...... 413 White Earth data...... 413 Summary of Data 1-9 Years of Age ...... 414 Search strategy...... 414 Specific areas of focus/concern...... 414 Age Group: 11-12 Years of Age ...... 422 Search strategy...... 422 National and state data...... 423 White Earth data...... 424 Age Groups: 13-14 Years of Age, 15-16 Years of Age, and17-18 Years of Age ...... 424 Search strategy...... 424 National and state data...... 425 White Earth data...... 425 Summary of Grouped Disparities for Youth 10-18 Years Old ...... 425 Search strategy...... 425 Specific areas of focus/concern...... 427 Gaps in the literature...... 443 Chapter II Summary ...... 444 Chapter III-Research Design, Methods, and Procedures ...... 446 Purpose ...... 446 Population Description...... 446 Target population...... 446 Setting and Sampling Plan ...... 447 Research Design...... 448 Research Questions ...... 451 Research Variables...... 451 Treatment/Intervention ...... 452 P a g e | 8

Measurement Methods/Tools...... 452 Data Collection Process and Logistics ...... 452 Data Analysis ...... 453 Description of Human Subject Protection ...... 454 Plans for Dissemination of Findings ...... 454 Chapter III Summary ...... 455 Chapter IV-Summary of Health Disparities ...... 456 Unintentional Injury ...... 456 Substance Abuse ...... 457 Mental Health...... 458 Obesity and Diabetes ...... 459 Teen Pregnancy ...... 460 Chapter IV Summary ...... 461 Appendix A ...... 462 Appendix B ...... 463 Appendix C ...... 464 Certificate of Completion ...... 464 Appendix D ...... 465 Appendix E ...... 466 References ...... 468 Justice Section ...... 481 References ...... 4889

© Boyd L. Bradbury, 2009

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Executive Summary

Early Childhood and Head Start

In reviewing the pre-K educational experiences for children, early childhood, Head Start, and related programming were examined. While 45% of this population is served by these programs, there is uncertainty as to whether the remaining 55% of the youngest learners are receiving any formalized schooling prior to kindergarten. If a significant number of these youngest learners are not receiving any formalized early childhood instruction, there is a potential that kindergarten readiness is negatively impacted by a lack of formal programming.

In addition to a concern over the absence of early childhood education for some young,

American Indian students, additional research needs to determine the effectiveness of the early childhood and Head Start programs in regard to academic achievement. Whether those students who experience formal early childhood programs benefit from the programming in the K-12 system is a question that must be answered in Phase II of this study. Researchers need to determine the effectiveness of existing program in terms of academic performance in the K-12 system. Also, researchers need to investigate the role of early childhood education in regard to resiliency among youth on the White Earth Indian Reservation.

More examination of the existing programs and their adherence to best practices will occur in Phase II of this study. Whether current programs are assessed against best practices, and whether these assessments are used to inform program changes are questions that will be answered in the next phase of this study.

Finally, researchers will examine whether agencies routinely share assessment information with each other in the interest of program improvement. There is a sense that more collaboration should occur in this regard. P a g e | 10

K-12 Education

The K-12 Education portion of this study is substantial. Existing data from nine school districts have been examined. One section of this report contains aggregated and comparison data. These data include the following: demographic information; teacher preparation; teaching years of experience; average teacher salary; highly qualified status; revenue and expenditure averages; graduation rates; dropout rates; special education rates; free and reduced lunch counts; student/teacher ratios; contractual days; and MCA II proficiency comparisons and analysis.

A second section of this report contains individualized information by school district. The volume and depth of information and analysis are directly related to the amount of information that was submitted to the researchers by the individual school districts. This information varies from a great deal to none. In some cases, attendance, discipline, testing, behavioral, and other data were submitted. In one case, no information was submitted.

Since the volume of information on K-12 schools is too great to summarize in this executive summary, it is recommended that interested parties access the aforementioned sections. Both sections should be reviewed by those who are interested in K-12.

Adult Basic Education and White Earth Tribal and Community College (WETCC)

This report contains a review of adult basic education tribal and community college opportunities on the White Earth Indian Reservation. The WETCC is recently accredited and has ample opportunities to grow programming to serve the needs of the community. Additional survey information will be collected to help determine the best course of action to serve those who are completing graduate equivalency diplomas and those who are seeking postsecondary opportunities.

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Social Services

In Phase 1, human service researchers were interested in determining the availability of public domain data that would illuminate the relationship between social services and the academic success of American Indian children and youth who live on or near the White Earth

Reservation. Researchers met with White Earth tribal child welfare staff and with neighboring county social services personnel to determine the availability of this data. The primary data collection method of county and tribal child welfare programs is the Social Services Information

System. This system does not currently have the capacity to generate service outcome reports relative to academic success. A 2008 Tribal Youth Program Final Evaluation Report does indicate, however, that truancy and dropout intervention services under the auspice of Indian

Child Welfare have had success at improving students‘ school-related attitudes and behaviors.

Researchers plan to generate additional information on the relationship between social services and academic success via interview data in Phase 2 of the Comprehensive Study.

Health Care

Health disparities

A significant gap exists in the overall health of the AI child compared to the health of children in the general population. The marginalization of the AI in the U.S. population has increased the morbidity, mortality, and burden of disease for children in AI communities.

The lack of specific statistical data for the AI youth was most alarming. Often times, documented data simply did not exist to support the expressed concerns by WE stakeholders.

Thus, the scant amount of generalized national data was often the only objective reflection available to identify health disparities for the children on the WE reservation. It is important to note that health disparities do not occur in a vacuum and many impact or overlap others. It is P a g e | 12

strongly believed that children‘s health status is uniquely impacted by biologic, genetic, socioeconomic, environmental, socioculutural, and behavioral factors. In addition, the compounding effects of poverty, stress, and access to health care for children using WE IHS may impact health disparities.

The following list is a summary of key disparities which the authors of the Phase I health arm distinguished as a priority and recommended further investigation in Phase II. The literature review and retrospective data review found the following disparities to be significant for children under the age of 18 years receiving care from WE IHS.

Unintentional injury

The IHS Provider indicated that AI/AN child mortality rates ages 1-19 years is nearly

―40% higher than that of White children in the U.S. (31.94 per 100,000)‖ (Berger et al., 2007, p.

203). Health professionals have worked diligently on campaigns educating the public about the impact of unintentional injury on children. However, the cause of unintentional injury for the AI child varies from that of the general population. The top three causes of death for children under one year old are congenital anomalies, SIDS, and short gestation (Berger et al.). In the White population, SIDS is ranked third (Berger et al.). The preventative nature of prenatal care and education cannot be overstated when addressing health disparities for a population as vulnerable as infants. Further investigation is needed to identify the accessibility of prenatal care and attendance of prenatal classes on the WE reservation.

The second method of preventing unintentional injury in children is education on the use of seatbelts. The Minnesota Department of Public Safety (MDPS) (2008) estimated the WE reservation seat belt usage to be 61%, well below the state average of 85.5%. Not all motor vehicle crashes end in fatality, life-altering injuries can be just as devastating. Children are P a g e | 13

especially vulnerable to caregiver‘s implementation and correct use of car seats. Adolescents participate in risk taking, often combining substance abuse, high speed, and lack of seat belt use increasing the likelihood of death in a motor vehicle crash. Further explanation is needed to explore the perception as well as the facilitators and barriers to seat belt use.

Substance abuse

Statistics identifying an increase in substance abuse among AI adolescents is severely lacking. National and Minnesota reports failed to identify which adolescent age groups showed an increase or link in substance initiation. This is disturbing to health care professionals and educators because preventative programs may need to begin at a younger age than what is being currently implemented. To bridge the lack of data, it may be necessary to coordinate efforts with

WE law enforcement to gather data on motor vehicle accident reports involving alcohol or arrests made of drinking while under the influence of drugs or alcohol involving people under the age of 18 years. The link between alcohol, illicit drug use, delinquent behavior, and other risk factors was identified in the national literature review; however, no literature searches produced evidence of this specifically on the WE reservation. Before initiating changes based on national and state data, school surveys should be performed to assist in providing age-specific information for the WE youth.

The National Institute on Drug Abuse produced the Overview of Key Findings 2007, listing specific results by drug and subgroup. Unfortunately, the AI population was not delineated in the findings. However, the study design and methodology was very specific, analyzing 16 total drugs for trends. This type of comprehensive school survey would be extremely helpful prior to making recommendations to the WE reservation and school districts.

At this point, it is difficult to know if youth on the WE reservation have an increased use of P a g e | 14

alcohol, methamphetamines, cocaine, ecstasy, prescription drugs, or steroids. In order to stem drug use, it is necessary to explore the accessibility and usage of adolescent drug use. The secondary impacts from drug use are equally as devastating. Teen pregnancy, violence, depression, suicide, sexually transmitted diseases, and school performance are all closely linked.

Mental health

The literature review noted the limited information regarding mental health and AI adolescents. The Healing Pathways Longitudinal Study (2009), the Native American Report

(2005), and state and local articles highlighted the impact of mental health on reservations. In summary, the predisposing factors appear to be poverty, stress, exposure to family trauma, and physical and sexual abuse. These factors can lead to depression, suicide, substance abuse, unintentional injury, and other risk taking behaviors. The Healing Pathways Study was the only research specific to youth on the WE reservation and findings supported the need for mental health intervention around ages 10-12 years old before children initiate harmful coping mechanisms.

The concerns about suicide on the WE reservation were not substantiated by statistics.

However, this appeared to be one of the most significant issues surrounding mental health. The barriers to receiving care for depression and other mental health issues may be geographic isolation and lack of mental health professionals for the WE reservation (Klobuchar, 2008, para.

8). This is compounded by the alarming trend of adolescents using suicide as a common remedy to depression after hearing of friends who have attempted suicide. Culturally-appropriate and sustainable suicide prevention initiatives need to be implemented quickly and state and local government need to make suicide prevention a health priority. Already, WE has begun using community members to support and counsel each other through suicide attempts and deaths. P a g e | 15

However, prevention needs to occur much sooner. Funding for school-based mental health services with trained personal can only begin when accurate data and research is made available to legislators.

Obesity and diabetes

The statistics from the Bemidji IHS for WE health services indicated that AI youth ages

5-15 years are in the 95th percentile for BMI. Ages 15-18 years had BMI‘s that were on the lower aspect of the 95th percentile, but still significant for obesity risk. There have been contradicting correlates between genetics, diet, lack of exercise, and poverty in the obesity epidemic in the

United States. AI children appear to be more likely to suffer long-term chronic illnesses related to obesity; these include diabetes, cardiovascular disease, and hypertension (Story et al., 2003, p.

S6). ICD-9 codes indicated only 11 individuals under the age of 13 were seen in the WE Health

Center from 2005-2007 for diabetes related care. Corresponding t-test with comparisons may be possible with Bemidji IHS information for WE youth, diabetes, and obesity. However Phase I time constraints limited statistical analysis and further examination may need to be considered during Phase II of the CSEERSWE. Another method to strengthen the current method of retrospective study would be to use case-control design and select ICD-9 correlates, such as family history or diet-related issues, to establish risk factor within the WE youth population.

Factors for increased risk of obesity and subsequent diabetes need to be considered in the lives of youth on the WE reservation. School lunch programs and after school activities are related preventative factors for obesity. Activities such as walking or biking to school also increase daily exercise. Other factors remain outside of a child‘s control; these include parent‘s ability to afford and community availability of healthy foods. Another method of preventing and identifying diabetes is having regular screenings by school nurse during school hours. Not only P a g e | 16

does testing blood sugar diagnose diabetes, but it also identifies children with high normal blood sugars at risk of developing diabetes.

Teen pregnancy

The MDH PCM (2007) indicated that the AI girls, age 15-19 years, had a three to four times higher teen pregnancy rate than Whites in the state of Minnesota. No statistical data was available for WE besides the ICD-9 codes for prenatal care, these numbers do not reflect the number of youth choosing to terminate a pregnancy or spontaneous abortions/miscarriages.

Pregnancy prevention education needs to address the issues surrounding early initiation of sexual behavior with special attention needs on the impact of early sexual behavior on mental health and self-perception. In Phase II of the CSEERSWE, researchers may consider looking more closely at the association between substance abuse, depression, suicide, and teen pregnancy.

Another consideration may be age and amount of information school health programs are able to disseminated to children regarding sexual health. It may be necessary to begin sexual education earlier and provide birth control for younger ages in school depending on the findings.

To summarize Freudenberg and Ruglis (2007), education is the elixir for increasing life expectancy, reducing the burden of illness, delaying the consequences of aging, decreasing health behavior risks, and reducing health disparities. In order to identify health disparities for youth on the WE reservation it was necessary to first perform a literature review, retrospective data collection, and conduct meetings with tribal leaders so that WE youth can benefit from care that incorporates their cultural values, beliefs, and practices. By creating research that values diversity and respects traditions, researchers can identify the barriers to academic success and work to improve student outcomes.

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Justice System

This report makes clear the fact that American Indian children are disproportionately impacted by matters related to criminal justice. Not only are American Indian youth and adults incarcerated at a disproportionate rate, they are also victims of violent crimes at a disproportionate rate when compared with other ethnic groups. Legal matters that are criminal in nature tend to have an adverse effect on American Indian youth.

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Dr. Boyd Bradbury

Professor of Educational Leadership

And

Program Coordinator of Educational Leadership and Curriculum & Instruction

Minnesota State University, Moorhead

Introduction

Issue and Needs

An analysis of available research and data makes it clear that American Indian children do not achieve academically at the same rate as their Caucasian counterparts. According to the US Department of Education (n.d.), only about one in six American Indian and Alaska Native 8th-graders is proficient in reading and one in seven is proficient in math. Although the smallest minority group in the United States, the academic achievement levels for American Indian children are the lowest among ethnic groups.

Kramer (1998) found that the most severe high school attrition rate is among American Indian students.

Hornette (1990) mentioned that studies dating back to 1970 indicate that beyond grade four, the gap between achievement and normal grade level widens. Strang, von Glatz, and Cahape Hammer (2002) noted that the Meriam Report in 1928 and the Kennedy Report in 1969 have documented the failure of formal education.

American Indian Children on the White Earth Indian Reservation tend to reflect national trends in regard to academic achievement. Potential factors that contribute to this underachievement include poverty, unemployment, health care, legal issues, drug and alcohol use, and lowered expectations.

Available studies regarding academic success among American Indian children on the

White Earth Reservation suggests schools have the capacity to mitigate the effects of poverty and P a g e | 19

related factors in regard to academic achievement (Bradbury, 2005). As a result, nine school districts that serve American Indian children who reside on or near the White Earth Indian

Reservation will be examined as part of this study. Beyond school districts, an assumption is made that no single partner or party with a vested interest in the success of American Indian children solely impacts the success of children. This assumption is made based on available research as detailed in the next section of this proposal. As a result, this study is designed to be comprehensive in that it will examine not only the nine schools, but tribal agencies, and other entities to determine factors that impact the success of American Indian children who live on the

Reservation.

With the assumption that it does take a village to raise a child, a comprehensive study that examines the effectiveness of entities involved in the lives of children is necessary. The researchers of this study believe that there is more value in examining multiple entities than only one (e.g., educational institutions). In addition, this study seeks to examine stakeholders that influence the educational success of children from early childhood through postsecondary education.

Rationale for Conducting Study

The rationale for conducting this study is the result of several factors. First, Bradbury

(2005) conducted a study regarding the underachievement of American Indian children who attended Waubun-Ogema-White Earth Community Schools (WOWE). Although limited to a specific school in terms of applicability, this study identified phenomena that contributed to the underachievement of American Indian children at WOWE. In addition to identification of phenomena, the study included numerous recommendations for interventions. These P a g e | 20

interventions were reviewed and approved by the local school board and enacted by school administration.

To evaluate the effectiveness of the interventions, follow-up data were collected and analyzed in the areas of disciplinary referrals and academic achievement. Comparison of disciplinary data evidenced the effectiveness of the implementation of recommendations as disciplinary referrals were considerably lower after the implementation of the recommendations to raise behavioral expectations when compared with pre-implementation year data. Insubordination dropped 47%, disruptive and disrespectful behavior declined

54%, swearing and offensive language spiked in the first year at a rate of nearly 15 times the previous year due to enforcement of the zero tolerance on the f-word, but it dropped 42% in the second year, verbal abuse declined 82%, harassment decreased by 17%, fighting and disorderly conduct fell 58%, and influence under drugs or alcohol dropped 66% (Kennedy,

2007).

In regard to academics, interventions included school district approval of four additional paid days during the summer of 2005 to allow teachers to use a backward design model to develop a syllabus for every course and grade level in order to ensure scoped and sequenced coverage of state standards (essential learning). By the start of school in the

September of 2005, all classes and grade levels had syllabi on file with administration, and syllabi were sent home to parents. In addition, teachers were required to submit corresponding electronic lesson plans to the building principals. Minnesota Comprehensive

Assessments (MCA) (high stakes) and Northwest Evaluation Association (NWEA)

(nationally normative) test scores rose since the implementation of the syllabi and focus on essential learning. For example, between the fall of 2005 and the fall of 2006, all elementary P a g e | 21

grades showed a decrease of students in the 1-10th percentile on the NWEA tests. In addition, grades 6 to 7, grades 8 to 9, and grades 9 to 10 showed a decrease of students in the

1-30th percentile. Moreover, with the exception of grades 7 to 8, all secondary grades witnessed an increased percentage of students who scored above the 50th percentile

(Bradbury, 2006).

In addition to the WOWE study serving as an impetus to this proposed study, in

2006, former Waubun superintendent, Boyd Bradbury, and former Mahnomen superintendent Brent Gish, approached Dr. Erma Vizenor, Chairwoman of the White Earth

Nation, with a request for consideration of a study involving all school districts, tribal agencies, and other entities serving American Indian children who were residing on the

White Earth Indian Reservation. Both superintendents recognized that the underachievement of American Indian children on the White Earth Indian Reservation mirrored underachievement issues on a national scale. Moreover, both superintendents believed that myriad factors impacted the success of American Indian children, including poverty, health care, education, culture, community, and wellness issues. Chairwoman Vizenor concurred that many factors impacted the success of American Indian children and she and the Tribal

Council endorsed the effort to make this study a reality. Moreover, both Superintendent Gish and Chairwoman Vizenor saw the potential of this study to serve as a model for reservations nationwide as it does not appear that a study of this magnitude and scope has been conducted involving American Indian children residing on a reservation.

Since American Indian youth residing on the White Earth Indian Reservation experience the many of the same issues as American Indian youth nationwide, a final push for the comprehensive nature of this study came from a thorough review of literature P a g e | 22

regarding factors that impact the underachievement and lack of success of American Indian children. This review, which is contained in the following pages, makes it clear why it is so critical to examine multiple entities (e.g., schools, health care, culture, the justice system) to maximize the effectiveness of this study and improve multi-perspective understanding of the issues.

Available literature makes it clear that many factors impact the success of American

Indian children. Through the examination of these factors, it is the hope of the research team that not only would factors impacting the success of American Indian children be identified through the comprehensive nature of this study, but that the interconnectedness of these factors would be elucidated. Once this occurs, recommendations (interventions) would be established to improve not only the success factors at individual schools and agencies, but between these entities as well. For example, if the study were to find absenteeism at school connected to academic underachievement and the absenteeism directly related to a healthcare issue or sanitary issue (e.g., lice and a no-nit policy that prevents attendance), then one would need to find a way to assist families in eradication of lice so that children could attend school. While this sounds simple enough, people often look past the need for cooperation among entities, and entities rarely have capacity to affect change at another agency.

The following literature review by Bradbury (2005) in previous published research provides factual information for the need to conduct a comprehensive education study of

American Indian on the White Earth Indian Reservation since factors impacting the success of American Indian children locally are similar to those found at the national level.

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Literature Review

Dropout Rates

Vanderslice (2004) reported alarming statistics. First, dropout rates vary significantly by socioeconomic factors and racial background, with those from the lowest income families approximately eight times more likely to be dropouts than those from the highest income families. Moreover, minorities have the greatest percentage risk of dropping out of school, including American Indian and Alaska native student who have a dropout rate of 35.5%, about twice the national average. Second, dropouts are more likely than other citizens to draw on welfare and other social programs throughout their lives, in large part because those with high school diplomas earn eight thousand dollars more per year than those without diplomas. Finally, about one half of the incarcerated population in the United States lacks a high school diploma.

Kramer (1998) underscored this final point by noting that ―40% of American Indian dropouts have been involved in criminal behavior by being arrested or involved in substance abuse activities‖ (p. 11). Simply put, educational disparities between the minority and Caucasian populations are contributing to substantial social and economic costs in the United States.

Sanitation

One of the most salient issues pertaining to the disparities between American Indians and the rest of the United States involves the standard of living in regard to basic needs such as sanitation. Statistics from the Bureau of the Census (1995) state that American Indian reservation households of 1990 were as likely as U.S. households of the 1950s to lack complete indoor plumbing in addition to other disparities in sanitation services. Although one might wonder what sanitation on reservations has to do with student achievement, the answer would be ―a great deal.‖ The lack of sanitary conditions on reservations is indicative of larger problems such as P a g e | 24

poverty and the connections between poverty, associated social ills, and reduced levels of parental education are directly related to a lack of student achievement. Although these factors can be generalized to the American Indian population beyond reservation boundaries, reservations seem to harbor and promote attitudes and values that perpetuate underachievement on the part of American Indian youth.

Poverty

Of the number of unique factors related to American Indians living on reservations, perhaps none is greater in terms of influence than poverty. According to Antell, Blevins, Jensen, and Massey (1999), over the past two decades the income disparity between American Indians and other population groups has become more dramatic. The median family income of all

American Indian families declined by 5% from 1979 to 1989, with a median family income of

$21,750 for American Indians, which was 65% of the median family income of $35,225 for all families in the United States. American Indian couples earn $71 for every $100 earned by all married couples in the United States. During this same decade, the percent of American Indian families below the poverty level rose from 24% to 27%, while the poverty rate for all families in the United States was around 13% to 14%. Chinn (2002) noted a poverty level of 25.9% for

American Indians as compared with 7.7% for Caucasians. The outlook for American Indian households with a female head was even more dismal.

Although the poverty outlook for American Indians is dismal, statistics for those living on reservations or trust lands is even worse. Antell et al. (1999) noted that compared to non- reservation American Indians, income for American Indians living on reservations drops by approximately half and poverty levels increase appreciably, to about 51% of all American Indian households. Save the Children (2002) agreed and noted that American Indian reservations are P a g e | 25

pockets of poverty where the child poverty rate is two to three times the national average and where families have been locked in a cycle of poverty for decades. In all likelihood, the lack of employment opportunities on reservations leads to the out-migration of the most talented and better educated American Indians, which exacerbates the already exceptionally high unemployment rates and low incomes among American Indians who live on reservations.

Poverty is directly related to issues that adversely affect student achievement among the

American Indian population. Chinn (2002) noted that,

There are numerous problems associated with poverty including: problems with nutrition; inadequate medical care; environmental hazards (including lead poisoning); and greater likelihood of exposure to drugs, crime, and street gangs. Some variables associated with poverty may even contribute to problems with disability and eventual placement in special education. (¶ 16-17)

American Indian Health Disparities

In addition to poverty, the disparities between American Indian health and other populations (minority and Caucasian) are startling. According to Indian Health Service (2002), upon whom 60% of American Indians and Alaska Native living in the United States rely,

American Indian and Alaska Native people have long experienced lower health status when compared with other Americans. It seems that lower life expectancy and disproportionate disease for American Indians are due to inadequate education, disproportionate poverty, discrimination in the delivery of health services, and cultural differences. The bottom line is that American

Indians experience broad quality of life issues that are rooted in economic adversity and poor social conditions.

Statistics on Native American health are sobering. The Indian Health Service (2002) noted that American Indians and Alaska Natives born today have a life expectancy that is almost P a g e | 26

six years less than the rate for the general United States population. Moreover, American Indians and Alaska Native infants die at a rate of 8.9 per every 1,000 live births, as compared to 7.2 per

1,000 for the United States all races population. Also, American Indians and Alaska Natives die at higher rates from alcoholism (770%), tuberculosis (750%), diabetes (420%), accidents

(280%), suicide (190%), and homicide (210%).

Health-related issues combine with other factors in order to contribute to the lack of achievement on the part of American Indian children. While there is no debate that an academic achievement disparity exists between American Indian children and their Caucasian counterparts, there are differing opinions as to why the disparity exists and how the gap can be narrowed.

The American Indian Academic Achievement Gap

There is general agreement that an achievement gap exists between American Indian children and their Caucasian counterparts. The existence of this achievement gap has been documented for some time. Hornette (1990) noted that studies dating back to 1970 note that beyond grade four, the gap between achievement and normal grade level widens. In reference to

American Indian children, Hornette (1990) cited research and explained,

The longer they stay in school, the more the achievement level of these children declines. Finally, by grade ten, Indian students are typically functioning approximately three years behind age mates, and it is at this time they physically drop-out of school. Based on reports of their early function, it would appear that a lack of intelligence or an inability to function academically is not the primary reason for the drop-out rate. (p. 43)

Strang, von Glatz, and Cahape Hammer (2002) noted that the Meriam Report in 1928 and the Kennedy Report in 1969 documented the failure of formal education and called for more

American Indian involvement, control, and relevancy in the educational process. Pavel (1999) concurred that the quality of the students‘ educational experiences is determined, in large part by P a g e | 27

the learning environment that is created by professional educators. Hornette (1990) cited low self-image as a major factor in academic failure. She explained,

During the middle childhood years, ages 7-11, the child develops a social attitude and begins to form the ideology of his cultural environment and the values and beliefs of the important adults in his life. It is at this time that the influences of a dominant, majority culture affect children‘s self-image and ultimately the ability to achieve academically and socially. (p. 44)

Although the smallest minority group in the United States by far, the academic achievement levels for American Indian children are the lowest. Kramer (1998, p. 7) confirmed that the most severe high school attrition rate is among American Indian students. Although there are many apparent factors that contribute to the decreased achievement levels, Ogbu (1990) believed that

A first step in understanding the relative success or failure of minority students‘ social adjustment and academic performance in school is recognizing that there are different types of minority groups, who each experience and respond to schooling differently. The initial terms of a minority group‘s incorporation into any society affects that groups‘ understanding of their social reality or their cultural model. That understanding, in turn, affects both their general adaptation to minority status and their adaptation to schooling. (p. 46).

Contrary to autonomous minorities such as Jews and Mormons, and immigrant minorities, who have moved more or less voluntarily from their land of origin to another society because they believed that such a move would result in improved economic well-being, better overall opportunities, or greater political freedom, involuntary minorities did not initially choose to become members of a society. Instead, Ogbu (1990) explained that involuntary or caste-like minorities were brought into that society through slavery, conquest, or colonization (e.g., African

Americans and American Indians). P a g e | 28

In America, involuntary minorities‘ perspectives of underserved and institutionalized oppression or discrimination have influenced the ways that they respond to White Americans and to the societal institutions which Whites control. In general, America‘s involuntary minorities experience persistent problems in school adjustment and academic performance. (Ogbu, 1990)

In apparent concurrence with Ogbu, Stago (1998) noted that ―It appears that social ills, such as dropout, sexual abuse, absenteeism, violence, etc. may not be the variables totally responsible for academic failure, as shown by previous studies, but such failure may additionally be the result of cultural domination‖ (p.iii). However, while Ogbu views the situation as a formidable one, Stago suggested that ―Indian-related differences in culture, language, and customs are fixable by designing education programs and pedagogy based on realities held by

American Indians‖ (p.iii).

Testing

As with most minority populations, the academic achievement of American Indian children is negatively represented by standardized tests. Brescia and Fortune (1988) noted that the testing of many American Indian children using exams developed for the majority American society represents a case of cross-cultural testing, which is likely to produce invalid results in the form of underestimation of student performance. Brescia and Fortune found that generally, when standardized tests are used with American Indian students (on reservations or in settings with low levels of acculturation) and produce invalid results, the tests usually produce lower or less desirable scores for the Indian children taking the tests.

The use of standardized tests for purposes of programming for American Indian students can have detrimental effects. Brescia and Fortune (1988) indicated that test results can harm the self-esteem and confidence of the American Indian student, sometimes resulting in the student P a g e | 29

giving up or dropping out. Moreover, the interpretation of achievement test results can lead to false conclusions concerning the American Indian student, resulting in teacher allegations of laziness, disinterest, or stupidity. Underestimation may result in incorrect programmatic placement, as American Indian children are placed in low-achieving groups or do unnecessary remedial work.

A major concern of testing in relation to American Indian children is an inordinately high placement in special education programs. Losen and Ortfield (2003) noted that minority students in general are overrepresented in the public school special education population. While poverty accounts for some of the racial disparities in education placement, the high placement seems to suggest bias. Teachers who have not received proper multicultural training may have low expectations, cultural insensitivity, and they may refer students for special education assessment at an inordinately high percentage rate.

There are a number of reasons that underestimation occurs with American Indian children in regard to testing. According to Brescia and Fortune (1988), these reasons include: students not exhibiting behaviors required for successful test-taking; students not reading the questions accurately; students not having the assumed experience or cognitive structure to respond to certain items; and students lacking the opportunity to practice key behaviors required by the test.

Each of these behavior patterns of American Indian students in the testing situation reflects cultural differences.

Although cultural differences are critical in the discussion of American Indian testing and education in general, it must be noted that there are additional cultural and other factors that contribute to the lack of academic achievement. Brescia and Fortune (1988) noted that factors that contribute to low academic achievement by American Indian children include poverty, low P a g e | 30

parental education, broken homes, limited English, and casual register backgrounds, which involves less formal language.

Cultural Factors

Many American Indian children fail to succeed because of issues tied to culture. Swisher

(1991) noted that American Indian children often hide academic competence to avoid seeming superior. She explained that in many Native societies, the humility of the individual is a position to be respected and preserved. Advancing oneself above others or taking oneself too seriously violates this key value. If Native children learn best cooperatively, they will experience discomfort and conflicts in classrooms that are too competitive or in which the competition is unfair. Brescia and Fortune (1988) concurred and noted that some tribes may bar competitive behaviors in an academic setting. Florey and Tafoya (1988) seemed to agree by noting American

Indian values encourage interdependence, collective decision-making, and group cohesiveness.

Ogbu (1990) explained this attitude among involuntary minorities (e.g. American Indians) as a folk theory by noting:

In their folk theories of getting ahead, America‘s involuntary minorities often express the desire to succeed through education just like White Americans. However, because many generations of them have faced barriers to the opportunity structure as well as severe employment ceilings American involuntary minorities have come to believe that more than education, individual effort, and hard work are required for them to overcome those obstacles. Consequently, the involuntary minorities‘ folk theories of how to get ahead differ in some significant ways from White middle-class American folk theory as well as from that of immigrant minorities. For example, involuntary minorities stress collective effort as the best means of achieving upward mobility. Since America‘s involuntary minorities do not really believe that the societal rules for self-advancement work for them as they do for White Americans, their folk theories exhort them to try to change the rules. Thus, rather than accept inferior educational standards and facilities or inequitable job conditions, American involuntary minorities may try to affect changes in the criteria for school credentialing and for employment. This stands in marked contrast to that of immigrant minorities, who emphasize following the rules of the dominant culture. (p. 49) P a g e | 31

Unlike voluntary minorities, who are willing to follow the rules of dominant culture and view cultural differences as barriers to be overcome, involuntary minorities see differences as markers of group identity to be maintained. Ogbu (1990) explained,

Cultural and language differences become boundary-maintaining mechanisms between themselves and the dominant group. Unlike members of immigrant groups, America‘s involuntary minorities, perhaps unconsciously, may perceive learning or speaking Standard English and practicing other aspects of White middle-class culture as threatening to their own minority cultures, languages, and identities. Consequently, those members of involuntary minority groups who try to cross cultural boundaries may experience social or psychological pressures from other members of their group not to do so. (p. 48)

If Ogbu‘s (1990) theory is correct, nothing short of systemic educational change would be needed to significantly increase student achievement among the American Indian population since a ―buy‖ into the dominant culture‘s system would not happen. Ogbu (1990) believed that

―the relational factor that promotes school success among immigrant minorities involves their degree of acquiescence and trust in the schools and school personnel‖ (p.52). American Indians tend to distrust institutions that have been established by and are controlled by Caucasians. Ogbu explained,

The relationship between involuntary minorities and the public schools (and, subsequently, those who control the schools) does not help to promote academic success among involuntary minorities. Generally, involuntary minorities have acquired a basic distrust for the public schools and for school personnel, and they believe that they are provided inferior education for no other reason than because they belong to involuntary minority groups. (p. 54)

The bottom line is that many experts believe that substantial school reform would be needed in order to create the necessary conditions to reduce the achievement gap between

American Indian and Caucasian children. Beaulieu (2000) noted, P a g e | 32

With a strong belief that all students can learn, the most basic underlying assumption of school reform is the view that schools as organizations can, in fact, be transformed and improved and that this improvement would result in increased levels of student achievement for all learners. This assumption is based on a certain level of stability and continuity with regard to student enrollment and professional staffing during the school year and succeeding school years. It would also require the existence and availability of a corpus of appropriate information and knowledge to guide professional development as well as curriculum development activities. However, schools with predominantly Indian student populations experience, in fact, extremely high student and staff mobility. These schools also tend to serve student populations disproportionately affected by violence and substance abuse that negatively impact school readiness and individual capacity to learn. These problems are also compounded by the fact that schools serving Native students usually lack the appropriate knowledge base for accomplishing the professional development and curricular development objectives necessary for sustained improvement while also meeting unique social linguistic and cultural needs. (p. 30)

Although systemic change seems necessary in order to accommodate unique cultural features and needs of the American Indian population, some research indicates that assimilation would be a better choice for the American Indian population. Leveque (1994) conducted qualitative research with a fully assimilated American Indian population in California. Leveque suggested:

The first variable, the change from caste like to immigrant status via choice, suggests that Ogbu‘s categories of immigrant and non-immigrant minorities are not static: caste like minorities in the U.S. may not be bound to their caste like status. The key element for Native Americans in Barstow was choice. This group chose to leave their reservations and to live in the majority society. They have thus become immigrants by Ogbu‘s definition. Immigrant minorities usually assimilate by the third generation; these Native Americans had assimilated by the third generation. (p. 30)

Apparently the assimilation yielded great educational dividends and the study has ―set the table‖ for future studies that would be similar in nature. Leveque (1994) noted:

This single case study opens questions for further study. The findings have indicated that a small group of Native Americans who came to Barstow from three major tribal P a g e | 33

reservations located in the Southwestern U.S. have assimilated into the majority culture within three generations. As a result, the grandchildren and great-grandchildren of these immigrants have exhibited academic achievement levels comparable to those of their peers in the setting. The major reason that assimilation was successful for this group was that they chose a particular way of life in a particular setting. They have chosen to become a part of the majority culture in Barstow. (p. 33)

Leveque‘s (1994) case study is indeed fascinating in that it raises the question as to whether minorities should forsake cultural identity in order to experience educational and socioeconomic success. Moreover, the study provides an impetus for similar research projects.

Leveque (1994) is clearly provocative in noting,

Several concerns arise as a result of the findings and conclusions of this study. The academic success of the Native students in Barstow was related to the fact that they lived one cultural life: the life of the majority culture. Their Native ways were virtually lost. Must loss of culture be the price paid for academic success for Native Americans or any minority? Replication of this study in other settings, including reservation settings, would further clarify, support, or refute issues raised in this single study. (p. 34)

Curriculum and Teacher Education

Although cultural beliefs may contribute to the lack of academic success by American

Indian children under some circumstances, Swisher (1991) cautioned against overgeneralization.

It must be understood that a lack of cultural understanding and training on the part of teachers and standard curriculum contribute to the lack of academic achievement by American Indian children. Reyhner (1992) suggested that many of the problems faced by students such as drug and alcohol abuse are symptoms of the poor self concepts of Native students who have unresolved internal conflicts resulting from educators asking students to give up their Native culture. He suggests that teaching methods and school curriculum need to be changed to reduce cultural conflict between home and school. Reyhner (1992) believed that Native students are denied a curriculum that includes their heritage and culturally-biased tests are used to label them P a g e | 34

as failures and push them out of academic programs. Rather than dropouts failing the system, the traditional school system has failed the dropouts. Reyhner (1992) saw the idea that Native

Americans are culturally disadvantaged or culturally deprived as an ethnocentric bias that should not be continued.

While erasing ethnocentrism and promoting more culturally-sensitive curricula are admirable ideals, teachers are a major stumbling block to achieving these goals. The vast majority of teachers who teach American Indian children are Caucasian. As a result, Hornette

(1990) believed that schools generally reflect the White, middle-class, Anglo value system. She noted,

This means that the majority of Indian children are taught daily by people who have a cultural frame that is different from that of their students. Due to this fact, culturally dictated responses and behavior attitudes can be misrepresented, misread, or may go completely unnoticed. (p. 46) Teacher education programs must strengthen their curricula to ensure future teachers‘ understanding and skills to work with culturally and linguistically diverse students. This may include developing curricula sensitive to multicultural issues, the infusion of multicultural perspectives into every course, and English as a second language (ESL) and other training and course work in the teacher education program. Public schools will need to develop in-service programs for their instructional staff, many of whom may not have received diversity training in their teacher education preparation programs. Both the teacher education programs and the school-based programs will need to provide training on effective communication techniques with parents and students from diverse backgrounds, and to prepare teachers to be able to understand interracial and interethnic issues. (¶ 14)

Reyhner (1993) noted that teacher education programs for teachers of Native children should integrate information on Native educational history and philosophies into foundations classes, integrate research findings of successful minority education programs into methods classes, introduce pre-service teachers to the wide variety of Native education materials, and provide field experiences with native students in exemplary schools. In addition, Swisher (1991) P a g e | 35

recommended the following steps based on research: assess students‘ preferred ways of learning and the way(s) in which student behaviors change from situation to situation; plan learning experiences that incorporate the students‘ preferred ways of learning—using teaching methods, incentives, materials, and situations that are planned according to student preferences; implement the learning experiences that were planned; evaluate the learning experiences in terms of attainment of conceptual or other goals, as well as in terms of observed student behaviors and involvement; as the year progresses, plan and implement student participation in learning experiences that require behaviors the student has previously avoided; and continue to provide familiar, comfortable, successful experiences, as well as to gradually introduce the children to learning in new ways.

Schools that have experienced success in educating American Indian children have paid attention to the cultural needs of their children. Reese (2000) noted that at Four Winds American

Indian Magnet School in Minneapolis, Minnesota, students made significant gains in reading and mathematics. The school intentionally focuses on traditional American Indian culture with quality teaching and state-of-the art technology to ensure its students are prepared to achieve in

2000 and beyond. Every teacher uses the school-wide theme, Medicine Wheel, which emphasizes a holistic approach to learning that involves reaching the whole child—intellectual, spiritual, emotional and physical. The theme guides instruction and relates the curriculum to children. Students begin to see how subjects are connected and work together in the real world.

Symbolism is very important to American Indian culture; this thematic method of instruction is consistent with American Indian tradition and what teachers know about best teaching practices.

American Indian children at Four Winds are achieving at a higher rate than other American

Indian students in the district, and at a rate that is higher than White students at the school. In P a g e | 36

addition, Four Winds has created a diverse workforce, as 25% of the Four Winds‘ school staff is

American Indian.

Another success in Minnesota has occurred in Moorhead. Baird (2004) reported that early intervention programs are benefiting American Indian students. In addition to early intervention programs, Moorhead School District has done the following: hired a home school liaison for Red

River Area Learning Center to provide academic support for American Indian students; the district is holding a series of American Indian awareness classes for 10 to 12 teachers who will share the information with teachers at their schools; and weekly opportunities are offered throughout the district for all students to learn more about American Indian culture like drumming and beading.

―Indianizing‖ curriculum, however, does not guarantee success. In reference to qualitative research among the Pueblos, Peshkin (2000) wrote,

However much the curriculum of Indian High School has been Indianized, and much time and effort has been invested in this process, it remains a school of the White man‘s world, a school whose origin, language, content, and instrumentality are non-Indian. While students hear repeatedly that they must succeed in school, most people they know succeed only to a limited degree. And those who do succeed risk being accused of acting White. Furthermore, at the same time students attend Indian High School they are learning at home and in their tribal communities to be a Pueblo Indian, and all that that entails in religious and other terms. In short, they are simultaneously involved in learning from both their Indian and non-Indian worlds. The words from several students‘ essays illustrate the tension that learning from both worlds creates:

I am struggling to know my Pueblo language. I feel that I will lose because I am in a point in my life where I have to go on with my education. I am pulled by a huge chain by the white world. Sometimes it gets very confusing and frustrating to choose between the worlds. It is frustrating because you have to give up something else to have the other one.

As a native American I feel like I can‘t really learn my culture because to me the White culture seems to be more dominant and if I start to learn my native culture P a g e | 37

like the old people, I will fall behind in the dominant world. But at the same time, I want to learn my culture. (pp. 7-8)

While it must be recognized that the high percentage of poverty, familial dysfunction, low educational levels of parents, social ills, and a lack of acculturation does account for some of the lack of academic success experienced by American Indian children, not all blame can be explained away by using these factors as a defense. Banks and Neisworth (1995) suggested that systemic change within schools serving American Indian/Alaska Native populations is critical to ensure enculturation rather than assimilation. Pedagogy, teaching and learning methodologies, and curriculum must be adjusted to meet the unique needs of the American Indian population.

Moreover, early intervention strategies must be employed with American Indian children.

Finally, there must be a recognition of and programming for the economic, social, and medical woes that plague American Indians and academic achievement.

P a g e | 38

References

Antell, J., Blevins, A., Jensen, K., & Massey, G. (2002). Residential and household

poverty of American Indians on the Wind River Indian Reservation. Laramie: University

of Wyoming.

Baird, J. (2004, February 10). American Indian education 101. The Fargo Forum, C6.

Banks, S. R., & Neisworth, J. T. (1995, Winter). Dynamic assessment in early

intervention implications for serving American Indian/Alaska Native families. Journal of

American Indian Education, 34(2).

Beaulieu, D. L. (2000). Comprehensive reform and American Indian education. Journal

of American Indian Education, 39(2), 29-38.

Brescia, W., & Fortune, J. C. (1988, March). Standardized testing of American Indian

students. Las Cruces, NM: ERIC Clearinghouse on Rural Education and Small

Schools. (ERIC Document Reproduction Service No. ED 296-813)

Bureau of the Census. (1995, April). Housing of American Indians on reservations—

plumbing. United States Department of Commerce: Washington, DC.

Chinn, P. C. (2002). Facts, statistics, and theories on racial, ethnic, and culture diversity

module 1: Changing demographics. Nashville, TN: Vanderbilt University, The Alliance

Project.

Florey, J., & Tafoya, N. (1988). Identifying gifted and talented American Indian students:

An overview. (ERIC Document Reproduction Service No. ED296810)

Hornette, D. M. (1990, Fall). Diversity in today‘s classroom: Teacher education‘s challenge.

Action in Teacher Education, XII(3), 43-49.

Indian Health Service (2002). Facts on Indian health disparities. Retrieved July 27, 2004 P a g e | 39

from http: //www.anhb.org/documents/hill%20visits/IHS%20Fact%20Sheet.pdf

Kramer, J. A. (1998). Exploring high school dropout causes and educational re-engagement

among race-ethnic and gender groups. (Doctoral dissertation, California State University, Long

Beach, 1998). UMI ProQuest Digital Dissertations. (UMI No. 1392105)

Leveque, D. M. (1994, March). Cultural and parental influences on achievement among

Native American students in Barstow Unified School District. Paper presented at the

National Meeting of the Comparative and International Educational Society. (ERIC

Document Reproduction Service No. ED382416)

Losen, D. J., & Ortfield, G. (2003, January). Special report/racial inequities in special

education. Equity and Opportunity, 60(4), 91.

Ogbu, J. (1990, Winter). Minority education in comparative perspective. The Journal of

Negro Education, 59(1), 45-57.

Pavel, M. D. (1999). Schools, principals, and teachers serving American Indian and

Alaska Native students. Charleston, WV: ERIC Clearinghouse on Rural Education and

Small Schools. (ERIC Document Reproduction Service No. ED425895)

Peshkin, A. (2000, December). The nature of interpretation in qualitative research.

Educational Researcher, 29(9), 5-9.

Reese, C. (2000). Tying tradition to 2000: Student achievement rises at Four Winds

American Indian Magnet School. Retrieved January 15, 2004 from

http://www.mpls.k12.mn.us/news/news_release/four-winds.shtml

Reyhner, J. (1992). Plans for dropout prevention and special school support services for

American Indian and Alaska Native students. [Electronic Version]. Journal of American

Indian Education. P a g e | 40

Reyhner, J. (1993). American Indian language policy and school success. [Electronic

Version]. The Journal of Educational Issues of Language Minority Students, 12, 35-39.

Save the Children. (2003). America‘s forgotten children: Child poverty in rural America.

Retrieved July 23, 2004 from http://www.savethechildren.org/usa/report.asp

Stago, L. M. (1998). The identification and analysis of factors contributing to Navajo

student dropout at Seba Dalkai School (Arizona) (Doctoral dissertation, Northern State

University, 1998). UMI ProQuest Digital Dissertations. (UMI No. 9839548)

Swisher, K. (1991). American Indian/Alaskan Native learning styles: Research and

practice. Charleston, WV: ERIC Clearinghouse on Rural Education and Small

Schools. (ED 335-175)

Vanderslice, R. (2004, Fall). Risky business: Leaving the at-risk child behind. The Delta

Kappa Gamma Bulletin, 15-21.

Strang, W., von Glatz, A. & Cahape Hammer, P. (2002, December). Setting the agenda:

American Indian and Alaska Native education research priorities. Retrieved July 23, 2004 from

http://www.indianeduresearch.net/edorc02-14.htm

U.S. Department of Education. (n.d.). How No Child Left Behind benefits American Indians.

Retrieved September 13, 2007 from http://www.ed.gov/nclb/accountability/achieve/nclb-

amind.htm P a g e | 41

Implementation Plan of Study

The plan to accomplish this study was discussed extensively in committee meetings as evidenced by minutes dating back to January of 2008, and informational meetings with school officials and tribal authorities in the fall of 2007. This study is designed to occur in two phases. The first phase involves the compilation and analysis of existing data. The second phase of the study would entail active field research to gather new data. The assembled research team, qualifications, and process for conducting the research are as follows:

Researchers and Roles

Researcher List for WE Comprehensive Study

Researcher Contact Information Jane Bergland [email protected] Associate Professor of Nursing James Bergman [email protected] Graduate Assistant Boyd Bradbury [email protected] Professor of Educational Leadership Donna Brown [email protected] Interim Assistant Vice President of Student Affairs Tracy Clark [email protected] Assistant Professor of Social Work Layna Cole [email protected] Associate Professor of Early and Elementary Childhood Education Leslie Darmofal, [email protected] Graduate Nursing Student Terry Dobmeier [email protected] Assistant Professor of Nursing Charles Howell [email protected] Department Chair of Education at Northern Illinois University Denise Lajimodiere, Assistant Professor of [email protected] Educational Leadership at North Dakota State University Tracy Moshier [email protected] Graduate Nursing Student P a g e | 42

Susan Peterson [email protected] Assistant Professor of Social Work Amy Phillips [email protected] Assistant Professor of Social Work at the University of North Dakota Becky Williams [email protected] Assistant Professor in the School of Teaching and Learning Tracy Wright [email protected] Associate Professor of Nursing

Responsibility Areas of White Earth Comprehensive Education Study

Health Services—Jane Bergland, Terry Dobmeier, Tracy Moshier, Leslie Darmofal and Tracy Wright K-12 Schools Test Data—Boyd Bradbury and Charlie Howell K-12 Disciplinary Data and Handbooks—Boyd Bradbury K-12 Scoped and Sequenced Curriculum and Professional Development—Becky Williams K-12 Other—Boyd Bradbury Birth-K, Parent Education, Early Childhood, Head Start—Layna Cole WETCC—Donna Brown Justice System—James Bergman Human Services, Indian Child Welfare, Etc.—Amy Phillips, Sue Peterson, and Tracy Clark Historical Document Review—Denise Lajimodiere ABE/Drop-outs, Alternative Learning—Donna Brown Other (Census Data, Etc.)—Charlie Howell

Desired Data and the Collection Process

To isolate factors that impact the success of American Indian children on the White Earth

Indian Reservation, data must be collected and analyzed. While some data already exist, further quantitative and qualitative data are necessary in order to achieve a thick and rich picture of factors that impact the success of American Indian children. Through collection, compilation, and analysis of data, researchers will generate specific recommendations for the stakeholders of this study, including Bagley Public Schools; Circle of Life Schools; Detroit Lakes Public P a g e | 43

Schools; Fosston Public Schools; Mahnomen Public Schools; Naytahwaush Charter School; Park

Rapids Public Schools; Pine Point Public Schools; Waubun-Ogema-White Earth Community

Schools, the White Earth Education Division, the White Earth Health Division, White Earth

Human Services, White Earth Tribal Courts, White Earth Police Department, White Earth Tribal and Community College, Mahube Community Council, Indian Health Services, and Becker,

Mahnomen, Hubbard, and Clearwater County Human Services.

This study seeks the following data:

1. General demographic information regarding the Reservation and American Indian children would be gathered and compiled. This information would provide an understanding of the context within which the study would be collected. This information would be obtained through the major partners of the study and other sources.

2. Historical documents and reputable literature regarding the history of the White Earth

Indian Reservation would be used in order to create an understanding of the dynamics that are present in the 21st century.

3. MCA, NWEA, and other test score data in order to establish both commonalities and differences among schools. The data would not be used to rank schools or place blame. Instead, the data would have the potential to lead researchers to practices and procedures that help

American Indian children to succeed.

4. Minnesota Student Survey data would be analyzed in order to establish attitudinal trends and behavior practices that would contribute to the success or detriment of American Indian children.

5. Survey of Enacted Curriculum (SEC) results will be compiled. SEC is designed to provide insight regarding instructional quality. P a g e | 44

6. Usage rates of services involving health care, the justice system, Indian Child Welfare,

Head Start, and other tribal agencies would be collected in order to establish participation rates.

Moreover, Becker, Clearwater, and Mahnomen Counties would be asked to provide aggregate information regarding participation and cost rates of American Indian children and families who utilize their services.

7. Both quantitative and qualitative data would be gathered from individual partners and their respective agencies. Quantitative data would be gained through the compilation of existing data and Likert-scale or other surveys. Qualitative data would be gathered through in-depth interviews, focus groups, and/or other established tools for gathering qualitative data.

8. Qualitative data would be gathered through interviews of American Indian students who have dropped out. In addition, parents and caregivers of these students could be interviewed.

9. To the extent possible, American Indian students who are high risk in regard to chemical usage and legal issues will be interviewed. The same would be true of low risk students who are succeeding in school.

During the second phase of the study, methods for gathering data would include the following:

1. Interviews and focus groups

2. Surveys

3. Participant observations

4. Review of quantitative data (e.g. MCA and NWEA test results)

P a g e | 45

Time Frame

The study will occur over an approximated period of twenty-four to thirty-six months or as long as necessary to gather useful data.

The preliminary report of Phase I is scheduled for release in June of 2010. Once issued, the preliminary report will summarize findings and conclusions from existing data (Phase I of the study), and it will articulate the areas of focus and methods by which data will be collected actively in Phase II of the study.

By May of 2011, final reports are scheduled for presentation to partners. These reports will specifically identify recommendations (interventions) for each partner. These recommendations will be detailed and specific. Although the researchers would not control the implementation of the recommendations, as the Tribe is sovereign and other partners are autonomous, the researchers would recommend the importance of implementation.

P a g e | 46

Dr. Denise Lajimodiere

Assistant Professor of Educational Leadership

North Dakota State University

Historical Overview of the Ojibwe (Chippewa) People, with Emphasis on the White Earth

Band of Chippewa

―We the Anishinabe people have a history that goes back 50,000 years on this continent which is

now known as North America, but which has been always known to us as Turtle Island. And

50,000 years is a long, long time.‖

Eddie Benton Benai

The Ojibwe word bimaadiziwin refers to the cycle of life, from birth to death, as well as

to the proper way to live life as a considerate, respectful human being, a part of a family and a

community. It defines how relationships between Ojibwe people should be conducted (Peacock

& Wisuri, 2002). The history presented here will attempt to introduce a small part of history the

Ojibwe people lived, and continue to live, as part of a family and community today.

The Name

Peacock and Wisuri (2002) believe that to understand the name of the people of White

Earth, there must be an understanding of how the language evolved,

The linguistic origins of the Ojibwe language (Ojibwemowin or nishinabemowin) are linked to a larger language and cultural group often misnamed the ―Algonquian‖ or ―Algonkin.‖ The common origin of all Lenape people also defines the linguistic relationship with our close relatives, including the P a g e | 47

Mohicans, Nanticokes, Shawnee, Cheyenne, Penobscots, Passamaquaddy, Wampamoag, Odawa Potawatomi Mesquakie, and others. (p. 28)

Vizenor, an enrolled member of the Minnesota Chippewa Tribe, (1984) further explains the language:

Ojibwe and the other languages grouped together in the Algonquian family resemble each other so closely in sound patterns, grammar, and vocabulary that at one time they must have been a single language; as the speakers of this ancient language, no longer spoken, became separated from one another, the way they spoke changed indifferent way until we have the distinct languages spoken today….at the time of the European invasion of North America, the languages of the Algonquian language family were spoken by Indians along the Atlantic coast from what is now North Carolina to Newfoundland, inland cross Canada to the Great Plains, and in the region of the Great Lakes, perhaps ranging as far south as Alabama and Georgia. (p. 16)

In the language of the tribal past, the families of the woodland spoke of themselves as the

Anishinaabeg until the colonists named them the Ojibway and Chippewa. Meyer (1994) explains that the word Anishinaabeg, the singular is Anishinaabe, is a phonetic transcription from the oral tradition,

Modern orthographies translate ―Anishinaabe(g)‖ (the ―e‖ ending is adjectival, the ―g‖ form plural) as ―Indian person.‖ I use this Native reference term in preference to Chippewa or Ojibwe (Chippewa is simply a corruption of Ojibwe), the origins of which has been a matter of debate. Whether these names refer to a puckered style of moccasin construction, a story in which an enemy is burned until ―puckered up,‖ or the practice of making extensive pictographs, they are terms that outsiders would have used to describe the Anishinaabeg. (p. xiv)

Benton-Banai (1988), a full-blood Ojibway, explains in his book ―The Mishomis Book‖ that ―Man was the last form of life to be placed on the Earth. From this Original Man came the

A-nish-i-na-be people. In the Ojibway language if you break down the work Anishinabe, this is what it means: ANI (from whence), NISHINA (lowered), ABE (the male of the species). (p. 3).

The Anishinaabeg are known to most of the world as the Ojibway and Chippewa.

Vizenor (1972) states, ―The Anishinabe lost their land and were renamed. In nine treaties with P a g e | 48

the federal government tie people were given the invented names Chippewa and Ojibway‖ (p. 8).

Although the English name ‗Chippewa‘ is commonly used both for the people and their ancestral language in Michigan, Minnesota, North Dakota, and Wisconsin, in the language itself the people are the Anishinaabeg and the language is called Anishinabemowin or Ojibwemowin.

Other spellings of the name include: Odjibwa, Otchipwe, Ojibway, Ojibwe, Chippewa,

Chippeway and Salteaux.

An enduring misconception among many euro-Americans is that the indigenous people of this continent were illiterate, relying solely on oral stories to pass down the history and culture of their nations. Many tribes, however, including the Ojibwe, possessed complex, highly compressed forms of written language (Peacock & Wisuri, 2002). Ojibwe ancestors used a form of written language to record history and spiritual teachings on rocks, song sticks, birch bark, wood, wampum strings, and belts (sometimes made with sea shells). The Anishinabe did not have a written language. The Anishinabe past was a visual memory and oratorical gesture of dreams and songs and tales incised as pictomyths on birch bark scrolls (Peacock & Wisuri).

McCutchen (1989) explains:

There is a place where the sacred records are deposited in the Indian country. These records are made on one side of bark and board plates, and are examined once every fifteen years, at which time the decaying ones are p replaced by new plates. The guardians had for a long time selected a most unsuspected spot, where they dug, fifteen feet, and sand large cedar trees around the excavation. In the center was placed a large hollow cedar log, besmeared at one end with gum. The open end is uppermost, and in it are placed the records, after being enveloped in the down of geese or swans. (p. 33-34)

Migration

Anishinaabeg ancestors lived on and near the Atlantic Ocean nearly six hundred years ago near the mouth of the St. Lawrence River (Warren, 1974). The westward migration began as a journey as one people with the Ottawa (Odawa, or traders) and Potawatomi (keepers of the P a g e | 49

perpetual fire). Separation of the three peoples came at the Straits of Michilimacinac (where

Lake Michigan Converges with Lake Huron). At that point, some Ojibwe proceeded north and became the first nation Ojibwe of Canada and the ancestors of the people of present-day Grand

Portage in Minnesota and Turtle Mountain in North Dakota. Another group went south and west to the areas now occupied today. The Ottawa chose to stay near Sault Ste. Marie and the

Pottawatomi moved into northern Michigan (Peacock & Wisuri, 2002; Benton-Benai, 1988).

In the original tales of the people the sacred migis shell of the Anishinabe spirit – a shell resembling the cowrie, which is still used to decorate ceremonial vestments – arose from the eastern sea and moved along the inland waters guiding the people through the sleeping sun of the woodland to bawitig – the long rapids in the river (Meyer, 1994). The Anishinabe – the original people of the woodland – believe they were given wisdom and life color from the reflection of the sun on the sacred shell during this long migration. Five hundred years ago the migis shell appeared in the sun for the last time at Mooningwanekaning in anishinabe kitchigame – La

Pointe on Madeline Island in Lake Superior – the great sea of the Anishinabe. Warren (1974) described this migration as he heard it at a Midewiwin ceremony. He was told:

While our forefathers were living on the great salt water toward the rising sun, the great Megis (sea-shell) showed itself above the surface of the great water, and the rays of the sun for a long period were reflected from its glossy back. It gave warmth and light to the Anishinabeg. All at once it sank into the deep, and for a long time our ancestors were not blessed by its light. It rose to the surface and appeared again on the great river which drains the waters of the Great Lakes, and again for a long time it gave life to our forefathers, and reflected back the rays of the sun. Again it disappeared from sight and it rose not, till it appeared to the eyes of Anishinabeg on the shores of the first great lake. Again it sank from sight, and death daily visited the wigwams of our forefathers, till it showed its back, and reflected the rays of the sun once more at Boweting (Sault St. Marie). Here I remained for a long time, but once more, and for the last time, it disappeared, and the Anishinabeg was left in darkness and misery, till it floated and once more showed its bright back at Mooningwanekaning (Madeline Island in Lake Superior), where it has ever since reflected back the rays of the sun, and blessed our ancestors with P a g e | 50

life, light and wisdom. Its rays reach the remotest village of the widespread Ojibways. (p. 78-79)

Vizenor (1984) adds,

The Anishinabe measured their lives in natural mythic time, through the circles of the sun and moon and human heart. The woodland tribes trailed the shores of Anishinabeg Gichigami to the hardwoods and swamps where families drew ziinzibaakwad from the maple trees in the spring, and gathered manoomin, or wild rice, in the autumn, and returned each winter to Mooningwanekaning. There the Anishinabeg told stories of the summer past while the snow fell and the lakes froze. (p. 21)

Peacock and Wisuri (2002) explain the Ojibwe love of place or home,

There is some comfort in believing we have always been in the places that we now call home. We know, however, that the Anishinabe communities, in which we live, be they Odana, Lanse, Red Cliff, White Earth or Turtle Mountain, are all relatively new in the long story of the people. (p. 22)

Clans

The question strangers, when they met, always asked one another, ―Waenaesh

K‘dodaim?‖ (Who are you?). The question and answer reflected the nature and importance of the individual and corporate sense of identity (Johnston, 1976). Within the traditional Ojibwe family, the first delineation of kinship was the dodaim (which some refer to as ―totem‖), or clan system.

The origin of the dodaim is said to have occurred when the Ojibwe lived on the eastern ocean, and six beings emerged from the sea. One being returned to the sea after harsh exposure to the light and heat of the sun. The other five came to shore and lived among the Ojibwe. Dodaim membership in the Ojibwe descended through the father‘s line, and marriage within the same dodaim was not allowed (Peacock & Wisuri, 2002; Warren, 1984; Densmore, 1979).

Johnston (1976) explained the clans and their roles:

Leadership – crane, goose, loon, hawk, sparrow hawk, white headed eagle, black headed eagle, brant, seagull. Defense – bear, wolf, lynx. Sustenance – marten, beaver, moose, caribou, deer, muskrat. Learning – catfish, pike, sucker, sturgeon, whitefish. Medicine – P a g e | 51

turtle, otter, rattlesnake, black snake, frog, merman or mermaid. The crane, catfish, bear, marten, wolf, and loon are the principal clan families (p. 60). The term Dodaim may mean ―that from which I draw my purpose, meaning, and being‖ (Johnston, 1976, p. 61).

Traditional Ojibwe Education

The purposes of traditional Ojibwe education were both to serve the practical needs of the people (to learn life skills) and to enhance the soul (to grow in spiritual ways). Together they were part of the balance on one‘s journey on the path of life. To possess only the skills of living without knowledge of the spirit world be to live a life with purpose depth, and meaning.

Education of the traditional Ojibwe was in three phases. Wisuri (2002) tells us:

Until around the age of seven, children were cared for and nurtured by grandmothers, aunties, and elders. From about that age, young boys went with the men, fathers, uncles and older cousins to learn the way of mean in providing sustenance by hunting and fishing….Girls remained with their grandmothers and aunties to lean the ways of women, to raise crops, to gather plants for sustenance, and to learn to provide for the home in other ways….No one way was considered higher in nature, the process egalitarian. The Ojibwe walked a balanced road. The third phase of education was when people began a search for wisdom – a quest to know the whole story of things (Peacock & Wisuri, 2002).

Johnston (1976) says, ―It was during this final stage in life that the learner realized his want of knowledge, and sought out the wise to teach him. A man or woman begins to learn when

(s)he seeks out knowledge and wisdom.; wisdom will not seek him or her‖ (p. 70). Wisdom is the whole of these things. The path of life was one of gentleness, humbleness and respect. Elders taught Ojibwe children to honor Gitchi Manito, honor elders, honor our elder brothers for all the animals are considered our elder brothers as they were her before us, honor women, our grandmothers, and mothers, aunties, sisters and wives our weedgiwagan (our partners in the path of life); keep our promises and uphold our pledges; kindness should be shown to everyone, even those with whom we disagree; be peaceful in body and spirit; be courageous; be moderate in our dreams, thoughts, words and deeds (Peacock & Wisuri). For guidance Ojibwe people are P a g e | 52

counseled to thank Kitchi Manitou for all his gifts. Honor the elders, in honoring them, you honor life and wisdom. Honor life in all its forms; your own will be sustained. Honor women; in honoring women, you honor the gift of life and love. Honor promises; by keeping your word, you will be true. Honor kindness; by sharing the gifts you will be kind. Be peaceful; thorough peace, all will find the Great Peace. Be courageous; through courage, all will grow in strength.

Be moderate in all things; watch, listen and consider; your deeds will be prudent (Johnston,

1979).

Manoomin (Wild Rice)

Wild rice has always been regarded by the Ojibwe as the sacred gift of their chosen ground (Benton-Banai, 1988). In the earliest of teachings of Anishinabeg history, there is a reference to wild rice, known as the food that grows on the water, the food the ancestors were told to find. The presence of this food, we were told, would signal the end of our migration from the eastern seaboard, where we had left our relatives the Wampanoags, the Lenne Lenapi, and the Abenaki. The Anishinabeg moved over rivers, streams and lakes to the Great Lakes region, where today a hundred or more reservations and reserves on both sides of the U.S.-Canadian border mark Anishinabe Akiing, the land of the People. Wild rice is a centerpiece of our community‘s sustenance. Wild rice offers amino acids, vitamins, fiber, and other essential elements, making it one of the most nutritious grains known to exist. The wealth of rice has ensured that we have not starved over many a cold winter (LaDuke, 2005)).

European Contact

The Ojibwe affirm that long before they became aware of the white man‘s presence on the continent, their coming was prophesied by one of their old men, whose great sanctity and oft- repeated fasts enabled him to commune with spirits and see far in the future (Warren, 1984). P a g e | 53

Written records of Indian-white contact have been kept primarily by non-Indians in Jesuit missionary journals, fur trade journals, personal correspondence, church records, and governmental documents. Partially as a result of the great friendship that developed between the

Ojibwe and the French and the resulting intermarriage, the Ojibwe language became the language of the fur trade in the Great Lakes regions and was even used in the exchanges between the French and other tribes (Peacock & Wisuri, 2002).

Early contact with the French, and later with the English and the Americans, led to profound changes in Ojibwe country, which affected nearly all aspects of traditional life, including tribal boundaries, culture, political systems and economies (Wisuri & Peacock, 2002;

Vizenor, 1984; Warren, 1984). The Ojibwe still suffer from the effects of that period of history, from all of its undeniable oppression and its accompanying depression and dysfunction. The dysfunction manifests itself in high student drop-out rates and low academic achievement, a mistrust of formal schooling, high rates of adolescent pregnancy, poverty, and high rates of crime in Indian country. In some Ojibwe communities, there remains a lingering bitterness and resentment toward Euro-American culture. There is no denying that the taking of their homeland marked the beginnings of many of today‘s social ills among the Ojibwe. The oral history of the

Ojibwe people has no mention of any of these societal ills before colonization (Peacock &

Wisuri).

With the advent of trade goods resulting from the exchange of furs, age-old Ojibwe ways were fore ever changes. Perhaps no single item affected tribal boundaries more than the introduction of the firearm, which was among the first of the trade goods. Tribes who were introduced to firearms soon had an upper hand with their indigenous neighbors. The gun replaced the bow and arrow, resulting in the Ojibwe having superior fire power over the Dakota, P a g e | 54

their traditional enemies (Peacock & Wisuri, 2002). The use of this weaponry contributed heavily to the Dakota removal from Michigan, Wisconsin, and much of Minnesota. Perhaps more tragically, one of the first trade goods introduced into Ojibwe country was alcohol, which is still devastating in many communities (Peacock & Wisuri).

Dawes Act (General Allotment Act, 1887)

―We believe the greatest evil the government ever inflicted on the Indians was to allot land in severalty to them‖ (Peter Graves, long time Red Lake leader, 1950).

Named for its author, Senator Henry Dawes of Massachusetts, under this act congress was authorized to negotiate with Indian nations for a sale of a portion of their lands after they had received allotments. Native American tribal lands were surveyed and divided into sections for an individual male head of each Native American family. He received 160 acres. The

‗surplus‘ reservation lands after the allotment process was completed would be up for sale. This idea of surplus land was obviously a way of rationalizing the theft of Indian land (Lyons,

Deloria, Jr., Berman, Berkey, Mohawk, Hauptman, Grinde, Jr., Venables, 1992; Berkhoffer, Jr.,

1978; Adams, 1995). The act authorized the government to negotiate with Indian tribes for the sale of all tribal lands remaining after allotments were made to individual members. The government often paid less than $1.00 for these so called ―surplus‖ lands, which it then sold to non-Native homesteaders and corporations (Lyons, et al.).

Most often the land allotted to the Indians included desert or near-desert lands unsuitable for farming. The techniques of self-sufficient farming were much different from their tribal way of life. Many Indians did not want to take up agriculture, and those who did want to farm could not afford the tools, animals, seed and other supplies necessary to get started. Further, banks refused loans to them. Multiple heirs are currently causing a huge problem called fractionation – P a g e | 55

where many family members inherited an allotment; the size of the holding became too small for efficient farming (Meyers, 1994, Lyons, et al., 1992).

The Dawes Act was disastrous for Native people. The primary effect was a severe reduction in the quantity of Indian landholdings, from 138 million acres in 1887 to 48 million in

1934, the year Congress passes the Indian Reorganization Act, which ended allotment. In all, tribes lost 90 million acres (Lyons, et al., 1992; Berkhoffer, Jr., 1978).

Indian Reorganization Act (IRA)

In 1928 Congress directed an independent commission to make a full-scale study of

Indian policy. The Indians of this commission, known as the Merriam Report, suggested a whole new direction in government dealings with Indian people. This change was carried out through the Indian Reorganization Act of 1934. The act ended allotment and further sales of Indian land and provided for the buying back of some tribal lands. It also set up machinery for organizing tribal governments on the model of white democratic institutions. The IRA led to the formation of modern tribal governments, as we know them today, with a limited form of self-governance and self-determination (Lyons, et al, 1992; Berkhoffer, Jr., 1978).

Some bands organized into confederated organizations, such as Leech Lake, White Earth,

Mille Lacs Lake, Boise Forte, Grand Portage, and Fond du Lac Reservation, under the Minnesota

Chippewa Tribe. Other Ojibwe didn‘t, including St. Croix, Mole Lake, Lac View Desert, Sault

Ste. Marie and Grand Travers. The IRA eventually led to the most sweeping changes in Ojibwe country since the colonization of tribal homelands by Europeans (Meyers, 1994).

Traditionalists felt quite rightly that the new tribal governments with their written constitutions, elections and formalized legislative procedure resembled White more than Native ways of running their affairs. No matter what Native Americans did under the IRA, funding of P a g e | 56

tribal welfare and economic programs depended upon the federal government as always, and so the decisions of the reorganized tribal governments rested for final authority upon the approval of the Indian bureau (Lyons, et al., 1992).

Termination Era

―I see the following words emblazoned in letters of fire above the heads of Indian - these people shall be free!‖ (Senator Arthur Watkins, Utah)

That termination of federal wardship and services was the official intention of both houses of Congress was declared in House concurrent Resolution 108 adopted in mid-1953. The resolution expressed the design of Congress to free the Indian of the Guardianship of the general government and give him the full responsibilities as well as the privileges of the ordinary citizen as soon as possible (Lyons, et al., 1992; Tyler, 1973). Once termination was completed and proclaimed the tribal members became subject to the same state laws and jurisdiction as other citizens, with corresponding duties and responsibilities as well as rights and privileges. In the eyes of the main proponent of the policy, Senator Arthur Watkins of Utah, the Indian was at long last set free of the federal government (Lyons, et al., 1992; Berkhoffer, Jr., 1978; Tyler, 1973).

Relocation Era

Formal education in Ojibwe country

The federal role in Indian education grew markedly with the passage of the Indian

Civilization Act of 1824, which provided federal funding for the formal schooling of Indians.

Mission schools were soon complemented by federal manual trade and boarding schools. The

Acts main purpose was ―…for introducing among them [Indians] the habits and arts of civilization‖ (Reyhner & Eder, 2004, p. 43). P a g e | 57

Boarding School Era

―A great general has said that the only good Indian is a dead one, and that high sanction of his destruction has been an enormous factor in promoting Indian massacres. In a sense, I agree with the sentiment, but only in this: that all the Indian there is in the race should be dead. Kill the

Indian in him, and save the man‖ Capt. Richard H. Pratt (Official Report of the Nineteenth

Annual Conference of Charities and Correction, 1892, p, 46).

Richard Pratt has been referred to as the ‗red man‘s Moses.‘ He offered Indians a choice that was a terrible problematic one: assimilation or extinction. His choice was assimilation through education (Utley, 2004). Pratt liked Indians, but he had little use for Indian cultures believing that Indian ways were in every way inferior to those of whites, he never questioned the proposition that civilization must eventually triumph over savagery, but this did not require the extinction of the race (Adams, 1995; Reyhner & Eder, 2004). The word was civilization.

European and American societies were civilized; Indians were savages (Adams). Thus Carl

Schurz, former Commissioner of Indian Affairs, concluded in 1881 that Indians were confronted with ―this stern alternative: extermination or civilization‖ (Adams, p. 15). Similarly,

Commissioner of Indian Affairs Henry Price opined: ―Savage and civilized life cannot live and prosper on the same ground. One of the two must die‖ Adams, p. 15). The solution to the ‗Indian problem‘ lay in three areas: land, law, and education.

It was argued that it was less expensive to educate Indians than to kill them. Carl Schurz, for instance, estimated that it ―cost nearly a million dollars to kill an Indian in warfare, whereas it cost only $1,200 to give an Indian child eight years of schooling‖ (Adams, 1995, p. 20). Not the war against savagism would be waged in gentler fashion. The next Indian war would be ideological and psychological, and it would be waged against children. What was needed now P a g e | 58

was an ―army of Christian school-teachers.‖ An important aim of Indian education was

Christianization. Native religious practices were looked upon as primitive and barbaric remnants of a pre-civilized existence.

Ojibwe young people were sent Mission church run schools located on the reservation and to off-reservation boarding schools located in Pipestone, Minnesota; Flandreau, South

Dakota; Carlisle, Pennsylvania and Wahpeton, North Dakota to name a few. The effects of mission and boarding schools on Ojibwe and many Native American tribes were many. Young people who were sent to these schools often did not return home during the entire school year.

Mothers and fathers were not able to parent their children and soon lost the ability to parent

(Peacock & Wisuri, 2002). A particular institutionalized behavior resulted from boarding school education, and some of these young people grew into adults who did not know how to parent children. Loss of culture resulted, with the young losing their link to the elders and to the vast storehouse of traditional knowledge (Adams, 1995; Reyhner & Eder, 2004; Archuleta, Child &

Lomawaima, 2000). When ‗returned‘ home many young people lacked the ability to communicate with elders and other traditional people in the Ojibwe language, so elders were no longer looked to for their knowledge and wisdom (Hamley, 1994). The systematic policy of using education to remove the Ojibwe culture from young Ojibwe people, coupled with the banning of religious practices, resulted in the loss of language, the loss of parenting skills and the low self-esteem in several generations of Indian people (Archuleta, et al., 2000; Adams, 1995).

These remain issues in Ojibwe country today, where drop-out rates of students hover near 40 percent.

The stories of Ojibwe people who attended these schools are just beginning to be written.

These stories are filled with gut-wrenching, heart-breaking episodes of homesickness, sexual P a g e | 59

abuse, forced labor, death, sickness and beatings. Many children died of loneliness, disease, and abuse in boarding schools or while attempting to run away. The majority of boarding schools have cemeteries. Some student‘s bodies were shipped home; most were buried at the school.

Parents were often not notified that their child was even sick, much less near death or dying.

Further, students were subjected to brainwashing to reject one‘s cultural heritage. The National

Boarding School Healing Project is currently recording stories of boarding school survivors. An outcome of this project is to file human a rights abuse case in the UN against the United States

(Lajimodiere, 2009).

Boarding Schools located on White Earth: St. Benedict‘s Mission; White Earth Boarding

School – opened in 1871 with a capacity of 110 students. Pine Point School and Wild Rice River

School. Day Schools: Policymakers saw day schools as a way to allow Indian students to commute, thereby creating more room in the boarding schools for children from more distant areas.

Historical Trauma

There have been a variety of terms used to describe the multigenerational nature of distress in communities, including collective trauma, intergenerational trauma, multigenerational trauma, generational trauma, historical grief, and historical trauma (Evans-

Campbell, 2008). Historical trauma, the term used most often by scholars of Native trauma is a conceptualized as a collective complex trauma inflicted on a group of people who share a specific group identity or affiliation – ethnicity, nationality and religious affiliation. It is the legacy of numerous traumatic events a community experiences over generations and encompasses the psychological and social responses to such events. Historical trauma is collective in that many members of a community view the events as acute losses and experience P a g e | 60

corresponding trauma reactions. Previous scholars have suggested that the effects of these historically traumatic events are transmitted intergenerationally as descendents continue to identify emotionally with ancestral suffering (Brave Heart, 1999a, 1999b, 2000, Brave Heart &

DeBruyn, 1998).

Over successive generations, Native Americans have experience a series of traumatic assaults that have had enduring consequences for families and communities. These assaults have included community massacres, genocidal policies, pandemics from the introduction of new diseases, forced relocation, forced removal of children through Indian boarding school policies and prohibition of spiritual and cultural practices. Together, these events amount to a history of ethnic and cultural genocide (Evans-Campbell, 2008).

Research suggests that responses at the individual level fall within the context of individual mental and physical health and may include symptoms of PTSD and guilt, anxiety, grief and depressive symptomoloy. At the community level, responses may include the breakdown of traditional culture and values, the loss of traditional rites of passage, high rates of alcoholism, high rates of physical illness such as obesity, and internalized racism (Duran, Duran,

Brave Heart, & Yellow Horse-Davis, 1998). Contemporary Native communities suffer from some of the highest rates of lifetime traumatic events, including interpersonal violence, child abuse and neglect, poor health and an ongoing barrage of negative stereotypes and

Microaggressions that disparage and undermine Native society and identity. Research among diverse populations has shown that children and grandchildren of survivors of traumatic events have high levels of current interest in ancestral trauma (Danieli, 1998; Nagata, 1991).

Native scholars have suggested that historical trauma may also play a role in Native family violence. For example, high numbers of Native parents grew up in boarding schools or P a g e | 61

foster care and were thus deprived of traditional parental role models. Individuals living with a traumatized or ‗wounded‘ community might also experience secondary effects (Cross, 1986;

Horejsi, Craig Heavy Runner, & Pablo, 1992). In a community that has lost its spiritual compass, people might be more susceptible to drugs, or children raised in families that have lost their ability to parent might experience increased levels of abuse and neglect. In this way the trauma, like a wave, continues to roll forward over generations leaving an array of effect in its wake

(Duran, Duran, Brave Heart & Yellow Horse-Davis, 1998).

Some form of social healing in which the loss is mourned and perhaps replaced by something new and healthy in the community may be called for. Indeed, early results from an qualitative interview study of sixteen Boarding School survivors for the National Boarding

School Healing Project show that elders, when asked what they would do to ‗heal‘ their reservation, respond by saying they would want to see a stronger return to their Native spirituality, ceremonies and language (Lajimodiere, 2009).

White Earth Today

The White Earth Reservation Gaawasbaa biganikaag, is named for the white clay at the

White Earth Village. Located in northwestern Minnesota, Where There is White Clay is the home to the White Earth nation. The White Earth Reservation was created on March 19, 1867 during a treaty signing in Washington DC. Then Chippewa Indian chiefs met with President Andrew

Johnson at the white house to negotiate the treaty. These chiefs included Hole-In-The-Day II,

White Cloud, Fine Day, Bad Boy, and Attempter. It was to be the home of all the Ojibwe in the state. U.S. policy makers embarked on a program of social engineering designed to concentrate all of the Anishinabeg in Minnesota on the White Earth Reservation. With the 1867 treaty, pressure was put on the bands to get them to move. Mississippi Band members from Gull Lake P a g e | 62

were the first group to come and settle around White Earth Village in 1868. Splinter groups from across northern Minnesota elected to move to White Earth. The 1920 census reflected those who had settled in White Earth: 4856 were from the Mississippi Band including 1,308 from Mille

Lacs, the Pillager Bands had 1218, and Pembina (Turtle Mountain) Band 472, and 113 had come from Fond du Lac of the Superior Band (LaDuke, 1999).

In 1889 the Nelson Act opened up the White Earth reservation to allotment and annexed four townships with the most white pines for the state of Minnesota; in the 1930s more lands were taken to form the Tamarac National Wildlife Refuge (LaDuke, 1999).

White Earth is the largest Indian reservation in Minnesota. The reservation stretches across all of Mahnomen County, plus parts of Becker and Clearwater counties in the northwest part of the state, along the Wild rice and White Earth Rivers. It is about 225 miles from

Minneapolis-St. Paul, and roughly 65 miles from Fargo-Moorhead.

The reservation land area is 2831 (1,093 aw mi) or approximately 990,000 acres, which held a population of 9,192 residents as of the 2000 census. There are 530 lakes and many acres of forest. There are five incorporated cities within the White Earth Reservation all located along

US Highway 59; the cities are Callaway, Ogema, Waubun, Mahnomen and Bejou. Major

Minnesota cities near the Reservation include Detroit Lakes (10 miles south), Bemidji, and Park

Rapids (White Earth Reservation Community Profile).

Currently, the land within the White Earth reservation borders is over 93% privately owned by non-Indian individuals and only 7 % is controlled by the White Earth Tribal

Government (Meyer, 1994). One significant area located adjacent to the eastern boundary of the

Reservation is the Itasca State Park in the Heartland area of Minnesota. The park, which contains the source of the Mississippi River, is the second largest in the State park system. The P a g e | 63

Reservation was established March 19, 1867. The White Earth Band of Ojibwa has 20,225 enrolled members (White Earth Band of Chippewa).

The White Earth Tribal Council is the largest employer in Becker, Clearwater and

Mahnomen Counties with over 1600 employees. The White Earth Indian Reservation is a member of the Minnesota Chippewa Tribe.

Population

The population of the White Earth Reservation is 9,188. The number of enrolled Indians in or near boundaries is 4,055. The population of Mahnomen County is 5,190. The population of

Becker County is 30,000. The population of Clearwater County is 8,423. Minnesota‘s Total

Population is 4,919,479 (White Earth Reservation Community Profile, 2009).

Government services

Tribal Government: The White Earth Tribal Government has elected officials. There is a

Chairperson, a Secretary/Treasurer and three District Representatives. County Government:

Becker, Clearwater and Mahnomen City Government: Callaway, Ogema, Waubun, Mahnomen, and Bejou. Police Protection: Each of the counties has cooperative agreements with the White

Earth Tribal Government. The White Earth Tribe established a Community Policing force in the

1990‘s. Law enforcement is shared between the Tribe and the counties. City Police Services are available in Mahnomen, Waubun, Ogema and Callaway. Fire Protection for each community is through volunteer service. The Bureau of Indian Affairs has Forestry Fire Protection with assistance from DNR.

P a g e | 64

Churches

Predominant religious affiliations within this area are Catholic, Protestant, Lutheran and

Episcopalian. Other churches may be found within the area (White Earth Reservation

Community Profile, 2009).

Casino

A casino is operated by the community, the Shooting Star Casino and Hotel in

Mahnomen, MN. It is said to be the largest employer in the region (White Earth Reservation

Community Profile, 2009).

Communities

Communities on White Earth reservation include: Elbow Lake, Ogema, Pine Point, Rice

Lake, Naytahwaush, and White Earth. There are five incorporated cities within the White Earth

Reservation all located along US Highway 59; the cities are Callaway, Ogema, Waubun,

Mahnomen and Bejou. Major Minnesota cities near the reservation include Detroit Lakes,

Bemidji and Park Rapids (White Earth Reservation Community Profile, 2009).

The White Earth tragedy

―White Earth Is Not For Sale‖

Today only 7 percent of White Earth‘s land base remains under Indian control. Federal, state, and county governments and private landowners share title to the remaining 93 percent.

The white Earth rolls carry the names of more than 11,000 enrolled members of the White earth

Band, but only about 4,000 people actually live there. Many reside in neighboring towns, the

Twin Cities, Duluth and all over the country (Meyer, 1994). Bitter conflict over contested land titles, a legacy of dispossession, has produced ―open sores of community disruption.‖ Heirs of allottees whose private property was illegally conveyed have faced off against well-organized P a g e | 65

Euro-American landowners whose titles are ―clouded.‖ Blame for this ugly situation lays squarely with the federal government for failing to carry out its trust responsibilities (Meyer,

1994).

Minnesota Chippewa tribe

The Minnesota Chippewa Tribe is a centralized government for six Chippewa bands in the U.S. state of Minnesota. It was created on June 18, 1934, and the organization and its constitution were recognized by the Secretary of the Interior two years later on July 24, 1936.

Powers are divided between the state tribal organization and the individual Indian reservations.

The bands that make up the tribe are: Bose Forte Band of Chippewa; Fond du Lac Band of Lake

Superior Chippewa; Grand Portage Band of Chippewa; Leech Lake Band of Ojibwe; Mille Lacs

Band of Ojibwe; White Earth Band of Ojibwe. Notably, the Red Lake Band of Chippewa is not part of the Minnesota Chippewa Tribe (The Minnesota Chippewa Tribe).

Contemporary Ojibwe Education

Self-determination through education

The period of self-determination of American Indians began with a speech with then president Richard Nixon in 1970, beginning a period of self-determination of American Indians.

A study done by the Special Senate Subcommittee on Indian Education was published as Indian

Education: A National Tragedy, A National Challenge. Known as the Kennedy Report, the study led to passage of the Indian Education act of 1972. Title IV, as it came to be known, provided funding for the development of special programs for Indian students in schools (Reyhner & Eder,

2004). P a g e | 66

The 1960s had seen resurgence in ethnic pride and in Ojibwe country there was both a cultural and spiritual awakening. New attention to the educational conditions of American

Indians in public schools sometimes led to conflict between Ojibwe communities and nearby public schools. Many Ojibwe students continued to score lower than their non-Indian peers on standardized achievement tests, had higher droop-out rates, were more likely to be referred for special educational services, and were more often targeted for both in-school and out of school suspension (Peacock & Wisuri, 2002). Parents sought representation on local school boards and pushed for a curriculum that was inclusive of Ojibwe culture and history. Frustrated with the unwillingness or inability of local school officials to respond to their demands, some parents pulled their children out of school and set up all-Indian schools. Indian student walk-outs at Cass

Lake, MN led the Leech Lake Reservation to begin a small store-front school. What began with little funding and few books is now Bugonaygeshig School. Tribal school operating under the auspices of local tribal governments, were founded at Lac Courte Oreilles Reservation, Cass

Lake, White Earth (Circle of Life School), Mille Lac and Fond du Lac. These schools combine both traditional academics and a solid core of Ojibwe curriculum (Peacock & Wisuri).

Current schools

Seven Minnesota public school districts serve Native children: Bagley, Detroit Lakes,

Fosston, Mahnomen, Park Rapids, Waubun, and Naytahwaush. The Pine Point School, K-8, is a part of the State system that was allowed to become an Indian experimental school in 1969.

Under special legislation, the Tribe administers the school. Besides the Pine Point School, educational facilities include: St. Michael‘s Elementary school, Circle of Life, Waubun, Ogema elementary schools, Waubun high school, Mahnomen elementary and high school, Naytahwaush P a g e | 67

charter school, Even Start; Early Childhood; nine Head Start classrooms, and the White Earth

Tribal and Community College (White Earth Reservation Community Profile).

More than half of the Anishinabe students who transfer from the all Anishinabe School at Pine Point to the white public high school in Park Rapids, MN, drop out before they graduate.

The few Native students who have graduated from the white school have bitter memories.

Tribal college

Along with the development of Indian education programs in public schools and tribally operated schools, Indian studies departments in colleges and universities, was the formation of tribal colleges. Tribal colleges serve a unique function in their communities, providing regular two-year transfer programs, certificate programs that allow graduates to enter the work force after two years, and a host of Ojibwe cultural and language offerings (Peacock & Wisuri, 2002).

More importantly they provide the kind of support many Native students need to make it in higher education. In Ojibwe country, one of the first tribal colleges was at Turtle Mountain,

North Dakota. In Wisconsin, Lac Court Oreilles Ojibwa Community College, Soon Fond du Lac

Tribal and Community College opened its doors. Leech Lake Tribal College began and more recently, White Earth Reservation Tribal College began providing locally based community college under the leadership of President Helen Klassen, a White Earth enrollee (Peacock &

Wisuri, 2002).

White Earth Land Recovery Project

Winona LaDuke, an Anishinaabekwe (Ojibwe) member of Mississippi Band.

Anishinabeg, returned to her father's native home, the White Earth Reservation in Minnesota, after graduating from Harvard in 1984. She soon became an activist fighting to return thousands P a g e | 68

of acres of land to the Anishinaabekwe. With money from her 1989 Reebok Human Rights

Award LaDuke began White Earth Land Recovery Project (WELRP), a 2007 Harry Chapin Self

Reliance Award Winner (HCSRA). Winona has long been a supporter of grassroots organizations focusing on teaching self reliance in Native American Communities. Her respected record as an environmental activist and the comprehensive programs offered by WELRP made their inclusion in our 2007 winners an easy decision. The mission of WELRP is to facilitate recovery of the original land base of the White Earth Indian Reservation, while preserving and restoring traditional practices of sound land stewardship, language fluency, community development, and strengthening spiritual and cultural heritage (LaDuke, 2005).

White Earth Tribal Council

As of October, 2009, the White Earth Tribal Council Members include: Erma Vizenor,

Chairwoman; Franklin ―Bud‖ Heisler, Secretary/Treasurer; Irene Auginaush, District I

Representative; Terrance ―Terry‖ Tibbets, District II Representative; Kenneth ―Gus‖ Bevins,

District III Representative (White Earth Tribal Council).

Peacock and Wisuri (2002) tell us the future of Ojibwe people holds great promise.

Ojibwe people are deeply indebted to past generations ―for they have suffered so that we could be here today, still strong in our ways‖ (Peacock & Wisuri 2002, p. 89). The Ojibwe of White

Earth continues to honor their memory by the way they live.

P a g e | 69

References

Adams, D. W. (1995). Education for extinction: American Indians and the boarding school

experience, 1875-1928. Lawrence, Kansas: University Press of Kansas

Archuleta, M. L., Child, B. J, & Lomawaima, T. (2000). Away from home: American Indian

boarding school experiences. Arizona: The Heard Museum.

Benton-Banai, E. (1988). The Mishomis Book: The voice of the Ojibway. Hayward, Wisconsin:

Indian Country Communications, Inc.

Berkhoffer, Jr., R. F. (1979). The White man’s Indian. New York: Vintage Books.

Brave-Heart, M.Y.H. (1999a). Gender differences in the historical trauma response among the

Lakota. Journal of Health and Social Policy, 10(4), 1-21

Brave Heart, M.Y.H. (1999b). Oyate Ptayela: Rebuilding the Lakota Nation through addressing

historical trauma among Lakota parents. Journal of Human Behavior in the social

Environment, 1(1-2), 109-126.

Brave Heart, M.Y.H. (2000). Wakiksuyapi: Carrying the historical trauma of the Lakota. Tulane

Studies in Social Welfare, 21-22, 245-266.

Brave Heart, M.Y.B., & DeBruyn, L.M. (1998). The American Indian Holocaust: Healing

historical unresolved grief. American Indian and Alaska Native Mental Health Research,

8, 56-78.

Berkey, C., Berman, H, Deloria, V. Jr., Grinde, D. Jr., Hauptman, L, Lyons, O., Mohawk, J, &

Venables, R. (1992). Exiled in the land of the free: Democracy, Indian nations, and the

U.S. constitution. Santé Fe: Clear Light Publishers

Child, B. J. (2000). Boarding school seasons: American Indian families, 1900 –1940. Lincoln:

University of Nebraska Press P a g e | 70

Cross, T. (1986). Drawing on cultural traditions in Indian child welfare practice. Social

Casework, 67, 283-289.

Danieli, Y. (Ed). (1998). International handbook of multigenerational legacies of trauma. New

York: Plenum.

Dawes Act (1887). Retrieved 4.16.2009 from

http://www.ourdocuments.gov/doc.php?flash=true&doc=50

Densmore, F. ((1979). Chippewa customs. Saint Paul: Minnesota Historical Society

Press.

Evans-Campbell T. (March, 2008). Historical Trauma in American Indian/Native Alaska

communities: A multilevel framework for exploring impacts on individuals, families, and

communities. Journal of Interpersonal Violence 23(3)

Hamley, J.L. (1994). Cultural genocide in the classroom: A history of the federal boarding

school movement in American Indian education. 1875-1920. Unpublished doctoral

dissertation. Harvard University

Horejsi, C., Craig Heavy Runner, B., & Pablo, J. (1992). Reactions by Native American parents

to child protection agencies: Cultural and community factors. Child Welfare, 62(4), 329-

342).

Johnston, B. (1976). Ojibwe heritage. Lincoln: University of Nebraska Press.

LaDuke, W. (2005). Recovering the sacred: The power of naming and claiming. Cambridge,

MA: South End Press.

Lajimodiere, D. (2009). Kill the Indian, save the man: A qualitative study of 14 boarding school

survivors. Unpublished qualitative study. North Dakota State University, Fargo.

Lambert, D. Trails of Tears, and hope: Collective trauma takes a ferocious toll on human P a g e | 71

societies – yet there are pathways to healing. Retrieved 5.20.08 from

http://harvardmagazine.com/2008/03/trails-of-tears-and-hope.htm.

McCutchen, D. (1989). The Red Record. Garden City, New York: Avery Publishing Group.

Meyer, M. L. (1994). The white earth tragedy: Ethnicity and dispossession at a

Minnesota Anishinaabe reservation. Lincoln: University of Nebraska Press.

Nagata, D. (1991). Intergenerational effects of the Japanese American internment. Clinical issues

in working with children of former internees. Psychotherapy, 28(1), 121-128.

Peacock, T & Wisuri, M. (2002). Ojibwe: Waasa inaabidaa, we look in all

directions. Afton, MN: Afton Historical Society Press.

Quality Education for Minorities Project. (1990). Education that works: An action

plan for the education of minorities. Cambridge: Massachusetts Institute of

Technology

Reyhner, J. & Eder, J. (1992). A history of Indian education. In Jon Reyhner, ed.,

Teaching the American Indian students. Norman: University of Oklahoma

Press

The Minnesota Chippewa Tribe. Retrieved October 20, 2009 from

http://www.mnchippewatribe.org

Tyler, S. L. (1973). A History of Indian Policy. Washington, D.C.: Bureau of Indian Affairs, U.S.

Department of the Interior.

Utley, R. M. (Ed.). (2004) Battlefield and classroom: An autobiography by Richard Henry Pratt.

Vizenor, G. (1965). Anishinabe Nagamon. Minneapolis: Nodin Press

Vizenor, G. (1984). The people named the Chippewa. Minneapolis: University of

Minnesota Press P a g e | 72

Gerald Vizenor. (2000). The everlasting sky: Voices of the Anishinabe people.

Warren, W. (1984). History of the Ojibway people. ST. Paul: Minnesota Historical

Society Press

White Earth Tribal Council. Retrieved October 20, 2009 from: http://www.whiteearth.com.

White Earth Profile Brochure retrieved October 20, 2009 from:

www.whiteearth.com/weedo/PDF/whiteearthprofilebrochure.pdf

P a g e | 73

Birth-K Education Portion of Study

Dr. Layna Cole

Associate Professor of Elementary and Early Childhood Education

Minnesota State University, Moorhead

Description of Early Childhood Education Services on White Earth Reservation

During the 2007-2008 school year, the White Earth Head Start Program completed a community assessment. The following information comes from that report:

The total population of the White Earth Reservation in 2000 was 9,192 people. Of the total population, 44 percent, or 4,029 people, were American Indian. Nearly all of the remaining population were Caucasian. Of the total population, 701 people were under the age of 5 years old (7.6 percent of the total population). Census data indicate that 34 percent of the Native American population over the age of 25 on the White Earth Reservation has no high school diploma (in comparison to the state percentage of 12 percent). Findings from the community assessment indicated that 26 percent of people surveyed did not have a high school education. The report mentions that Even Start is assisting area parents in achieving their GED or high school graduation, however, the Even Start Family Literacy Program closed (due to lack of funding) in the fall of 2008. Head Start staff ―have been encouraged‖ to work towards obtaining their AA degree in early childhood. American Indian children are nearly six times more likely to be poor than are white children. Poverty statistics from 1999 indicate that on the White Earth Reservation: 15.9 % of families with children under 5 are below the poverty line; 28.2% of families with female head of household are below the poverty line; 51.4% of families with a female head of household and children under 5 are below poverty line. P a g e | 74

Sixty-six percent of respondents to the community assessment surveys reported an income of less than $24,000, which is near the 2006 poverty level for a family of 5. Thirty-three percent of respondents were receiving MFIP. The main barriers to education and employment identified by the survey were lack of transportation and affordable childcare. Quality childcare remains a concern for families with young children. There are not enough trained, licensed providers to meet the needs of families. During the 2006-2007 school year, there were 45 children 5 years old or younger with special education diagnoses and active IEPs or IFSPs. The biggest community concerns identified by the surveys were lack of jobs, drug and alcohol abuse, lack of transportation, domestic abuse, and crime. The greatest strengths identified were strong commitment to family and a strong sense of cultural identity. A new 48-unit family apartment complex has been built in Mahnomen to address family house needs.

Early Childhood Education is delivered by several different agencies throughout the

White Earth Reservation including Head Start services in Mahnomen offered by Mahube

Community Action and preschool programming offered by Mahnomen (10 children). In Waubun

Schools (30 children), Head Start services are offered by the White Earth Head Start program, and child care services are offered and overseen by the White Earth Child Care Program. This report examines the two tribal agencies: White Earth Head Start (WEHS) and White Earth Child

Care Program (WECCP). As the literature review shows, access to high quality early childhood education is a primary indicator for positive outcomes for children (Lamb, 1998; Phillips &

Adams, 2001). Both WEHS and WECCP strive to improve both the access to and quality of early childhood education throughout the reservation.

P a g e | 75

White Earth Head Start

White Earth Head Start offers comprehensive early childhood services to low-income families and families with children who have special needs on the reservation. WEHS offers both home and center-based early childhood education, parent education and support, health screenings (including dental, vision, immunizations and mental health) and follow up, nutrition education and support and home safety support. WEHS currently has centers in five White Earth

Reservation communities including Rice Lake, Naytahwaush, Waubun, White Earth, Pine Point, and Mahnomen. WEHS offers home-based programming for more rural families. In addition, they also provide programming and support to three family child care centers. WEHS offers center-based programming during the academic year for 3-5 year old children and year round home-based programming through their Early Head Start program for prenatal families and children from birth to age 3 years. During the 2007-2008 programming year, WEHS served 54 children in its Early Head Start program and 156 children in its Head Start program—for a total of 210 children. Ten of those children were served in family child care settings.

Head Start programming is guided by federally established Head Start Performance

Standards (United States Department of Health and Human Services, n.d.). White Earth Head

Start Curriculum focuses on Language and Literacy Development, Math Concept Development, and Social/Emotional Development. Ongoing observations of children‘s behaviors and skills are documented along with results from multiple formal and informal assessments in order to monitor progress toward 13 specified outcomes for the area addressed within the curriculum.

Table 1 shows child outcomes for the 2007-2008 school year. P a g e | 76

There is a large body of literature indicating that the general education level of early childhood teachers is strongly and consistently correlated with child outcomes (McCartney,

1984; Ulione, 1997; Whitebrook, Howes, & Phillips, 1998). Literature also supports the notion that cultural and linguistic continuity between the home and the child care setting lead to better outcomes for children (Wittmer & Peterson, 2006). White Earth Head Start employs 26 people who are directly involved with teaching children. Of those, 20 (77%) self-identify as American

Indian and 6 (23%) self-identify as white. Just over half of the classroom teachers have a bachelor‘s degree. During the 2007-2008 school year, three teachers left the program with one position remaining vacant for more than three months. Increasing staff education and lowering staff turnover seems to be an ongoing challenge for the field of early education. Table 2 identifies the positions and credentials of these employees.

P a g e | 77

Table 1: 2008 White Earth Head Start Child (age 3-5) Outcomes

During the 2007-2008 school year, 153 Head Start children were assessed to see if they

achieved the identified outcome.

Number Number Language Development (Percent) (Percent) Met Goal Did Not Meet Goal 1. Understands an increasingly complex and varied vocabulary. 129 (84%) 24 (16%)

2. Develops increasing abilities to understand and use language 127 (83%) 26 (17%) to communicate information…. 3. Uses an increasingly complex and varied spoken vocabulary. 105 (69%) 48 (31%)

Literacy Development

4. Phonological Awareness—Associates sounds with written 49 (32%) 104 (68%) words … 5. Book Knowledge and Appreciation—Process of learning 125 (82%) 28 (18%) how to handle a book and demonstrates abilities to retell and dictate stories from books and experiences. 6. Print Awareness and Concepts—Recognizes a word as a unit 92 (60%) 61 (40%) of print. 7. Identifies at least 10 letters of the alphabet, especially those 33 (22%) 120 (78%) in their names. 8. Knows that letters of the alphabet are a special category of visual graphic that can be individually named. 69 (45%) 84 (55%)

Math

9. Number and Operations—Develops increasing ability to 74 (48%) 79 (52%) count in sequence to 10 and beyond; Increasing interest and awareness of numbers and counting as a means for solving problems and determining quantity. Social and Emotional Development

10. Shows an appreciation for their culture and other cultures. 143 (93%) 10 (7%)

11. Demonstrates growing confidence in a range of abilities, 128 (84%) 25 (16%) routines and tasks. 12. Shows progress in expressing feelings, needs and opinions in 101 (66%) 52 (34%) difficult situations or conflicts without harming themselves, others or property. 13. Increases ability to sustain interactions with peers by helping, 119 (78%) 34 (22%) sharing and discussing.

P a g e | 78

Table 2: 2007-2008 White Earth Head Start Staff Demographics

Center-Based Center-Based Family Child Home-Visitors Classroom Assistant Care Teachers for Home- Teachers Teachers Based Programming Total Employed 9 9 2 6 Total with 5 (56%) 0 0 1 (17%) Bachelor-level degree Total with 1 (11%) 0 2 (100%) 0 Associate-level degree Total with 4 (33%) 8 (89 %) 0 5 (83%) Child Development Certification Total with some 9 (100%) 8 (89%) 2 (100%) 6 (100%) ECE training

In response to the findings of the community needs assessment, WEHS has identified three goals for the 2008-2009 school year:

1. Expand current services offered in White Earth Naytahwaush and Mahnomen specifically through seeking an early reading first grant, expanding to year-round services for 3-5 year olds and improving math and science curricula.

2. Decrease the prevalence of obesity through use of the Sparks curriculum, health screenings, improved health, nutrition and exercise curricula and collaboration with other community agencies.

3. Increase the number of parents with high school diplomas through collaboration with other community agencies and the tribal education department.

P a g e | 79

White Earth Child Care Program

The White Earth Child Care Program (WECCP) is under the auspices of the White Earth

Reservation Tribal Council and has been overseen by the Tribal Education Department since

2006. The WECCP distributes support and services made available through the Child Care and

Development Fund (CCDF). The CCDF is part of the United States Department of Health and

Human Services. It provides subsidized child care services for low-income families, funding for improving the quality of childcare, and other services to support parents (United States

Department Health and Human Services, 2009). For fiscal year 2008, the CCDF awarded

$619,485 to the WECCP, which was a five percent decrease from the funding from 2007 (See

Table 3). In addition to funding from the CCDF, WECCP also works to secure grant funding from a variety of other sources to carry out its mission of ―Partnering with all Reservation programs, agencies and schools to help all children be ―ready to learn‖ (White Earth Child Care

Program, 1, n.d.).

Table 3: Annual CCDF Funding for WECCP

2006 $649,368

2007 $650,941

2008 $619,485

The White Earth Child Care Program provides comprehensive child care services throughout the reservation through the following activities:

Licensing Child Care Programs. The WECCP is responsible for overseeing tribally

licensed child care homes and centers on the reservation. In addition to facilitating P a g e | 80

the licensing process, WECCP also provides monthly visits and periodic site inspections. In 2008, WECCP licensed 12 child care homes and 2 child care centers.

Quality Improvement and Technical Assistance grants and support for licensed and unlicensed child care providers. The WECCP provides ongoing visits to both licensed and unlicensed child care providers. They focus heavily on supporting the delivery of quality literacy curriculum for care givers and literacy materials for children.

Child Care Assistance Subsidy Program for Quality Childcare. Each month WECCP processes child care assistance applications, ensuring eligibility and quality care placements. In 2008, WECCP spent $203,104 in direct child care assistance on an average of 121 children per quarter (White Earth Child Care Program, 2008a).

Ongoing community trainings (targeted at providers and parents). WECCP provides ongoing trainings on relevant early childhood topics throughout the reservation. In

2008, they provided over 50 sessions on topics ranging from responsive care giving and curriculum development to behavior management and science for children. They also facilitate quarterly educational celebrations for families and the yearly Brain

Development Conference which has become a nationally known professional development conference with 970 attendees at the 2008 event (White Earth Child

Care Program, 2008a).

Literacy Outreach Services through the Readmobile. WECCP provides literacy materials for children in child care throughout the reservation by making at least monthly to licensed and unlicensed sites and stops in communities. In addition to early childhood literacy development, the Readmobile also includes resources on P a g e | 81

Ojibwe culture and language. The Readmobile checks out an average of 400 books to

140 children each quarter (White Earth Child Care Program, 2008a).

Early Childhood Community Collaboration Coordination. WECCP shows

outstanding leadership and vision in trying to bring community partners together for

the benefit of children. Recognize the significant role that child care and early

education plays in economic development, the WECCP is working to establish

additional child care centers throughout the reservation. WECCP also initiated and

co-facilitated a school success coalition made up of tribal programs and agencies to

promote learning readiness throughout the reservation. Staff also participates in

ongoing state, regional and national tribal child care organizations.

Operating two licensed Child Care Learning Centers—There are two licensed Child

Care Learning Centers; one in White Earth and one in Mahnomen. These two centers

operate year around. The center in White Earth is smaller and has an average of 5

full-time children enrolled. The center in Mahnomen has an average of 71 children

enrolled monthly, with an average daily attendance 23 children (White Earth Child

Care Program, 2008a).

During the 2007-2008 program year, WECCP provided child care services to 128 children. Sixty-eight percent (n=87) children received services because their parent(s) was working, 6 percent (n=8) because their parent was in a training or education program and 26 percent (n=33) because they were in need of protective services. Fifty-six percent (n=72) of children served were at or below the federal poverty threshold. Fifty-nine percent (n=75) were less than 5 years old (White Earth Child Care Program, 2008b). P a g e | 82

Summary

Both White Earth Head Start and White Earth Child Care Program are involved in providing early childhood programming throughout the reservation. Both programs recognize their role in addressing larger community needs. Both are working to assist families in overcoming challenges such as poverty and low graduation rates. However, it is unclear what impact either program‘s efforts are having on improving the overall outcomes of the children and families they are serving.

Additional Research Needed

In order to better understand how the needs of the youngest learners are being met throughout the White Earth Reservation and the impact that early childhood education programs are having, the following questions need to be investigated during Phase II of this study.

If WEHS is serving 210 children and WECCP is serving 75 children under the age of 5

(and 10 are double counted because WEHS served them in a child care home), then 275

children under the age of 5 are receiving some sort of early childhood programming

through WEHS and WECCP. About 40 children participate in either Waubun‘s and

Mahnomen‘s preschool programming. That accounts for 315 children. However, if there

have been no significant population changes since the 2000 census, there are about 700

children under the age of 5 on the reservation. What types of early childhood educational

experiences are the remaining 55 percent of children (n=385) having?

Given the challenges faced by families on the reservations, what role can early childhood

education play in fostering resiliency in young children?

How are the public school systems addressing the needs of the birth to age 5 learner? Are

children being assessed upon enrollment in Kindergarten? What do those assessments P a g e | 83

indicate about the role of early childhood education services throughout the reservation?

Is that information being shared with early childhood education providers throughout the reservation as a process of ongoing quality improvement?

Does current research support that the child outcomes targeted by tribal early education agencies correlate with future educational achievement? Does current research support that the curriculum and teaching methods utilized by early education programs correlates with future educational achievement?

How do child outcomes on the White Earth Reservation in the primary grades differ among children based on their early childhood education experiences?

What can be done to increase the access to and utilization of quality early childhood education throughout the reservation?

What is the nature of collaboration between tribal and non-tribal agencies serving the educational needs of young children on the reservation? How does this enhance or inhibit the success of children in the primary grades?

P a g e | 84

References

Lamb, M. (1998). Nonparental child care: Context, quality, correlates. In W. Damon, I. E. Sigel

& K. A. Renniger (Eds.), Handbook of child psychology: Vol. 4. Child psychology in

practice. New York: Wiley.

McCartney, K. (1984). Effect of quality of day-care environment on children‘s language

development. Developmental Psychology, 20, 244-260.

Phillips, D., & Adams, G. ( 2001). Child care and our youngest children. The Future of Children

Journal: Caring for Infants and Toddlers, 11 (1), 35-52.

Ulione, M. S. (1997). Health promotion and injury prevention in a child development center.

Journal of Pediatric Nursing, 12(3), 148-154.

United States Department of Health and Human Services. (n.d.). Head Start performance

standards and other regulations. Retrieved January 31, 2010 from

http://eclkc.ohs.acf.hhs.gov/hslc/Program%20Design%20and%20Management/Head%20

Start%20Requirements/Head%20Start%20Requirements.

Whitebrook, M., Howes, C., & Phillips, D. (1998). Worthy work, unlivable wages: The national

child care staffing study, 1988-1997. Washington, DC: Center for the Child Care

Workforce.

White Earth Child Care Program (n.d.) White Earth Child Care Program. [Brochure]. White

Earth, MN: White Earth Child Care Program.

White Earth Child Care Program. (2008a). ACF700 Supplemental Narrative Report: FY08—

October 1, 2007 to September 30, 2008. (Grant Report). White Earth, MN: White Earth

Child Care Program. P a g e | 85

White Earth Child Care Program. (2008b). Child Care and Development Fund Annual Report.

(Grant Report). White Earth, MN: White Earth Child Care Program.

Wittmer, D. S., & Petersen, S.H. (2006) Infant and Toddler Development and Responsive

Program Planning: A Relationship-Based Approach. Upper Saddle River, NJ: Pearson.

P a g e | 86

K-12 Education Portion of Study

Dr. Boyd Bradbury

Professor

and

Program Coordinator of Educational Leadership and Curriculum & Instruction

Minnesota State University, Moorhead

Dr. Charles Howell

Chair of Leadership, Educational Psychology, and Foundations

Northern Illinois University, Dekalb

American Indians

Introduction

An analysis of available research and data makes it clear that American Indian children do not achieve academically at the same rate as their Caucasian counterparts. According to the

US Department of Education (n.d.), only about one in six American Indian and Alaska Native

8th-graders is proficient in reading and one in seven is proficient in math. Although the smallest minority group in the United States, the academic achievement levels for American Indian children are the lowest among ethnic groups. Kramer (1998) found that the most severe high school attrition rate is among American Indian students. Hornette (1990) mentioned that studies dating back to 1970 indicate that beyond grade four, the gap between achievement and normal P a g e | 87

grade level widens. Strang, von Glatz, and Cahape Hammer (2002) noted that the Meriam Report in 1928 and the Kennedy Report in 1969 documented the failure of formal education.

What is not clear, however, is why the achievement disparity exists. There are those who are quick to suggest that cultural discontinuity between American Indian students‘ culture and the culture of the school causes the lack of academic achievement. Others point to culturally insensitive curricula and programming and teachers who are not trained to view things from a multicultural perspective. Still others contend that there are social and economic issues beyond the scope of schooling that contribute to academic difficulties experienced by American Indian children.

In order to isolate those factors that contribute to a lack of academic achievement on the part of American Indian children, it is necessary to review the definitions and characteristics associated with American Indian tribes. Most specifically, one must define what it means to be

American Indian, and one must review characteristics involving cultural, social, and economic variables associated with these tribes. Factors that must be considered include rural versus urban status, poverty, health, nutrition, and social ills such as alcoholism.

American Indian Status: A Definition

In order to discuss the unique cultural, social, and economic characteristics of the

American Indian population and their relationship to academic achievement, it is important to define what exactly it means to be classified as American Indian. Snipp (2002) noted that for much of the 20th century, blood quantum was the operational standard for determining who would be officially recognized as an American Indian. By the 1970s, however, a series of legal challenges began to undermine the criterion‘s usefulness and the blood quantum was replaced with earlier congressional action that defined American Indians as members of American Indian P a g e | 88

tribes. Although this definition seems circular, the intent was to allow American Indian tribes the right of self-definition.

As a starting point in the discussion of self-definition, it is important to understand that ethnic classification relies upon self-identification. In other words, one‘s American Indian status is self-proclaimed on a form issued by the Census Bureau or other governmental agency. Self- identification, while liberating in many ways, can prove troublesome. Snipp (2002, p. 1) pointed out that ―comparing the numbers of American Indians reported in the 2000 Census with those from earlier censuses is problematic since there are two sets of numbers for which comparisons can be made.‖ Respondents were able to use both single-race and multiple-race definitions in the

2000 Census, which resulted in an increase of American Indian children by 21% using the single-race definition and by 99% using the multiple-race definition. Whereas 1.4 million children were identified as American Indian in the 2000 Census, only 840,000 children were identified by American Indian status alone. It must be understood that self-identified American

Indians may or may not be eligible for tribal recognition, which creates a significant disparity between those who self-identify as American Indian and those who actually qualify for tribal membership.

The issue of self-identification is an important factor to consider in the discussion of

American Indian status and student achievement. As an example, Waubun-Ogema-White Earth

Community Schools (WOWE), a public school located on the White Earth Indian Reservation in northwestern Minnesota, reports that 68% (415) of students self-identify as American Indian

(Minnesota Department of Education, 2003). At first blush, one would conclude that WOWE is pretty much a public school for American Indian Children. Even though approximately 68% of students who attend WOWE self-identify as American Indian, it should be noted that only about P a g e | 89

15% (90) of WOWE‘s 610 student population qualify for tribal membership, which requires a minimum Chippewa blood quantum of 25%. In order to self-identify as American Indian at

WOWE, one must be no more than two generations removed from an enrolled member. Prior to the early 1960‘s, the White Earth Reservation had no minimum blood quantum requirements for tribal membership. In reviewing student achievement, it would be difficult to generalize achievement concerns and findings regarding American Indian populations, other than locally, since many of those who self-identify as American Indian may possess a small American Indian blood quantum (e.g., 1/64 American Indian and 63/64 English or German).

In addition to recognizing differences that exist within identification criteria, it is important to understand that there are many tribes lumped under the American Indian umbrella.

North Central Regional Education Library (n.d.) noted that although the American Indian school population comprises only 1.2% of the enrollment in public elementary and secondary schools, these students represent 280 different tribal groups. Since tribal groups vary widely in regard to linguistic, cultural, social, political, and economic dimensions, it is fairly easy to recognize why the designation of American Indian is problematic in terms of generalizations. The National

Center for the Dissemination of Disability Research (2003) went so far as to suggest that the term American Indian can be viewed as an imposed social and political ethnic category with little relevant meaning in that it represents a range of cultural orientations. To the extent that there can to be said to exist a native American culture, it must be seen as the product of three centuries of contact with the United States mainstream culture and the imposition of alien forms of government, philosophy, and social organization on varying traditional cultures of Native

American peoples. P a g e | 90

To further complicate the definition of native peoples, it should be noted that distinctions are drawn between the American Indian population, Alaska Natives, and Hawaiian Natives.

Unique Characteristics of the American Indian Population

Although the cultural variations from tribe to tribe make is difficult to generalize unique cultural characteristics to the American Indian population as a whole, there are certain shared characteristics that seem common among American Indians. These characteristics include reservations, health care, poverty, and a lack of academic success. The significance of these factors is emphasized by Deyhle and Swisher (1997) who noted that the physical, social, and cultural environments in which a person grows and matures significantly influence behaviors, learning preferences, perceptions and other human characteristics.

Government control, influence, and intervention. A historical review of American

Indian populations would be replete with government intervention. As Snipp (2002) noted, the

American Indian population occupies a singular and unique position in that this minority group was the first to occupy the land that is now the United States, and the relationship between

American Indians and the federal government has grown out of a long history of conflict and struggle. Federal offices and agencies, an entire volume of the Code of Federal Regulations, and a lengthy history of Supreme Court case law are all devoted to issues pertaining to the American

Indian population. No other ethnic minority group in the United States can claim similar political or legal status.

The federal government‘s treatment of the American Indian population, while viewed as tragic and brutal by many, has changed greatly over two centuries. According to Snipp (2002), the American Indian population was not considered part of the nation until the latter part of the P a g e | 91

nineteenth century. Smith (1997) concurred that American Indians were viewed as separate from other Americans. For the most part, American Indians were treated as foreigners.

By the end of the nineteenth century, the military power of the United States had successfully overwhelmed the American Indian population. Snipp (2002) noted that with military containment achieved, the United States Government faced the task of assimilating American

Indians into mainstream culture. An attempt was made to indoctrinate Indian children with

Anglo-American cultural ideals while at the same time teaching basic academic skills. In many cases, the education included boarding schools far from their home. Beaulieu (2000, p. 37) noted that ―the avowed purpose of schooling was to eliminate the distinctive cultural and linguistic traditions of American Indian people.‖ One particularly poignant account of education at the turn of the twentieth century is put forth by Ah-nen-la-di-ni (1903) and reads as follows:

There were four Indian day schools on the reservation, all taught by young white women. I sometimes went to one of these, but learned practically nothing. The teachers did not understand our language, and we knew nothing of theirs so much progress was not possible. The Indian parents were disgusted with the schools, and did not urge their children to attend. When I was thirteen a great change occurred, for the honey- tongued agent of a new Government contract school appeared on the reservation, drumming up boys and girls for his institution. All that a wild Indian boy had to do, according to the agent, was to attend this school for a year or two, and he was sure to emerge therefrom with all the knowledge and skill of the white man. My father was away from the reservation at the time of the agent‘s arrival, but mother and grandmother heard him with growing wonder and interest, as I did myself, and we all finally decided that I ought to go to this wonderful school and become a great man. Until I arrived at the school I had never heard that there were any other Indians in the country. My surprise, therefore, was great when I found myself surrounded in the school yard by strange Indian boys belonging to tribes of which I had never heard. I had left home for the school with a great deal of hope, having said to my mother: ‗Do not worry. I shall soon return to you a better boy and with a good education!‘ Little did I dream that that was the last time I would ever see her kind face. She died two years later, and I was not allowed to go to her funeral. (pp. 1781-1787).

P a g e | 92

The idea of assimilation was a widely held belief for much of the history of the United

States. According to Snipp (2002), however, the assimilationist policies were replaced with new self-determination policies in the late 1960s and early 1970s, and these policies acknowledged the rights of American Indians to decide their own future and to have the principal responsibility for overseeing their own affairs. Although policies were put into place to allow self- determination, minority students struggle with the perceived need to assimilate in order to succeed educationally.

Reservations

Prior and juxtaposed to assimilationist policies that were designed to ―melt‖ the

American Indian into mainstream society, reservations were used as places to isolate and contain

American Indian tribes. Prior to assimilationist policies, Smith (1997) explained that reservations were created by the federal government to segregate American Indians from the general population to prevent further conflicts. Reservations, which are a unique characteristic of the

American Indian population, are tracts of public land reserved by the federal government for use by American Indians, and the size and characteristics of reservations vary greatly. Smith (1997) noted that American Indians were forced to adapt to a lifestyle very different from that to which they were accustomed. As assimilation replaced segregation most people believed that the reservation system would disappear within a generation, and that American Indians would enter mainstream society. While some of the former is true, the latter never came to be.

Although reservations are a significantly unique feature of the American Indian population and they are a factor in student achievement, most people harbor misconceptions about reservations. Those who believe that reservations are home only to American Indians are mistaken. According to Snipp (2002), there were 610 reservations and Alaska Native Villages in P a g e | 93

the United States in 2000, but these reservations are home to only 29% of all American Indian and Alaska Native children. Smith (1997) added that 45.9% of the total population on reservations is non-American Indian. Moreover, if the large and predominantly American Indian

Navajo reservation is excluded from the calculations, non-American Indians comprise 55.4% of the population on the remaining reservations. In fact, more non-American Indians than American

Indians reside on reservations in California, Colorado, Idaho, Michigan, Minnesota, Nebraska,

New York, Oklahoma, Utah, Washington, Wisconsin, and Wyoming, and there are 55 reservations that have between 0 and 25 American Indian residents. Nevertheless, Snipp (2002) pointed out that about 87% of American Indian children living on reservations reported only one race, compared with 61% of American Indian children as a whole.

Even though reservations may not reflect the substantial ethnic disparities that many believe exist between reservations and the ―rest of the world,‖ there are characteristics specific to living on a reservation that are not experienced to the same degree in non-reservation settings.

One of the most salient issues involves the standard of living in regard to basic needs such as sanitation. According to the Bureau of the Census (1995), American Indian reservation households of 1990 were as likely as U.S. households of the 1950s to lack complete indoor plumbing. In fact, 20% of American Indian households on reservations lacked complete indoor plumbing. In addition, the sewage disposal situation on reservations also resembles that of the

United States in the 1950s. Eighteen percent of households on reservations used a means of sewage disposal other than a public sewer, septic tank, or cesspool in 1990. Finally, 7% of

American Indian households on reservations secured water through a source other than a public system, private company, or individual well, as compared with 1% of all households in the

United States in 1990. The Indian Health Service (2002) concurred. P a g e | 94

Contributing Factors Affecting Achievement and Recommendations

While there is no panacea for the lack of academic achievement on the part of American

Indian children, there are changes that have the potential to mitigate the achievement disparity between the American Indian and Caucasian populations. These changes involve varied aspects of American Indian life.

In regard to education, the most logical starting point appears to be early childhood programming. As with all living things, human beings must be nurtured during the formative stage of life in order to realize their full potential. Demmert (2001) indicated that research studies point to the critical need for parent-focused early childhood education programs as an avenue for developing the whole child, including improved cognition and academic performance. Cotton and Conklin (2001) agreed by noting that parent involvement is a key aspect of early childhood education, and nearly all successful early childhood programs have parent involvement components.

The benefits of early childhood programming are substantial. Demmert (2001) pointed to a review of thirty-six studies that provided evidence that early childhood programs can affect short-term benefits in intelligence quotients and long-term benefits in school achievement, grade retention, placement in special education, and social adjustment among low-income families.

Cotton and Conklin (2001) concurred and elaborated by noting that preschool graduates outshine non-participants in the following areas: fewer referrals for remedial classes or special education; fewer retentions; higher grades; greater social and emotional maturity; more frequent high school graduation/GED completion; greater academic motivation, on-task behavior, capacity for independent work, and time spent on homework; lower incidence of absenteeism/detentions; better attitudes toward school; better self-esteem, greater locus of control; lower incidence of P a g e | 95

illegitimate pregnancy, drug abuse, and delinquent acts; more sports participation; and higher future aspirations and more post-secondary education. Moreover, once out of school, those who attended preschool demonstrate higher employment rates and better earnings, a lower dependence on welfare, fewer arrests and antisocial acts, better relationships with family members, a higher incidence of volunteer work, and more frequent church attendance.

Although there are many apparent environmental reasons as to why early childhood programming is beneficial, there is a biological basis as well. Caine and Caine (1997) noted that the first years of a child‘s life are critical to brain development, as the brain is a supersponge from birth to approximately age 3 or 4. The brain possesses plasticity, which means that it records all events, good and bad, and negative experiences at an early age can be a blueprint for disaster. Eaton (2003) explained that the brains of infants and young children develop synaptic connections in response to stimuli and they are like the roots of plants; that is, they must be nourished, or they will wither and die like a plant pulled out by its roots. When synapses fail to make connections, that tiny piece of the brain has failed to generate.

The early childhood program is particularly critical for American Indian children, as minority and poverty populations benefit greatly from early programming. While Demmert

(2001) noted that research on the influences of early childhood education and development on

Native children is limited, the studies that exist support mainstream studies. Therefore, it is possible to infer that efforts to improve educational outcomes must begin by paying attention to this critical period of a child‘s life. By ensuring a challenging and stimulating early environment for young children, cognitive development and subsequent academic achievement will follow. In many cases, the parents or caregivers are not able to provide the necessary nourishment due to their own social, economic, and health-related struggles. As a result, those children who do not P a g e | 96

have solid early childhood programs will rarely excel at the same level as those who received the necessary degree of care at home or preschool during the formative year (Demmert, 2001). Since the American Indian population suffers from poverty and associated social ills at a disproportionate rate, early childhood programming provides a glimmer of hope in regard to improved academic achievement for American Indian youth. As Demmert (2001, p.7) noted, ―If improving academic performance for all Native children is a priority, we must take these findings seriously and pay attention to this period in a Native child‘s life.‖

In addition to early childhood programming, there are some key features to educational programming for elementary and secondary children. According to Demmert (2001, p. 9), ―A school curriculum that promotes the language and culture of the community or tribe served— adopted in partnership with that community—holds significant promise for improving academic performance of Native children.‖ Since a majority of research shows a positive association between academic performance and the presence of Native language and cultural programs, schools should give serious consideration to including American Indian language and culture in their curricula. As Whitbeck, Hoyt, Stubben, and LaFromboise (2001, p. 57) noted,

―enculturation is a resiliency factor in the development of their (American Indian) children.‖

Powers, Potthoff, Bearinger, and Resnick (2003) added,

Rather, effective cultural programs validate native culture at a social and psychological level. Optimally, this validation includes redefining Native students as competent learners, negotiating cultural barriers to reach out to native parents as important partners in education, and creating a social climate that is nurturing and accepting of native students‘ cultural identity. (p. 41)

In addition to language and cultural changes in curricula, national and state movements toward standards-based reform may be beneficial for American Indian children. The idea behind P a g e | 97

content standards is that curricula are more uniform and challenging, while performance standards set the levels at which students must learn the content, and assessments measure their learning. According to Fox (2001) the new standards may hold promise for American Indian children in the following ways: the creation of a more common curriculum among schools within states and clearer learning expectations across states, facilitating mobility of American Indian children; since content standards drive the curriculum, educators, parents, and students can refer to them to provide increased focus for teaching and learning; and the content standards may help improve the quality of instruction by allowing for a more holistic, real-life, active-learning sort of pedagogy, which is more consistent with the traditional American Indian ways of teaching and learning. Moreover, standards-based reform can foster less reliance on single tests for decisions about student placement. The caveat, however, is that advocates for American Indian children must be alert to recognize if standards and assessments are not appropriate for American Indian students. In some cases, students may be unfairly compared if they do not receive the necessary financial and technical assistance to improve. Demmert (2001) seemed to concur by noting that standards-based reform holds great potential if tribes and communities become involved in setting culturally responsible standards.

Another recommendation tied to schools involves teachers. It seems evident that in an increasingly multicultural society, teachers must be aware of diversity issues that potentially impact student achievement. In the case of American Indian children, unique cultural characteristics such as discouraged competition and encouraged cooperation must be understood by the teacher. Cognizance of cultural differences on the part of teachers and the restructuring of lesson plans should encourage increased academic achievement on the part of American Indian children. P a g e | 98

In order to teachers to understand cultural nuances, however, adequate training must occur. The task of training pre-service teachers falls on post-secondary teacher education programs, while elementary and secondary staff development programs must emphasize cultural differences to those who are already practitioners. While Wells (1997) would prefer American

Indian teachers to teach American Indian children, he concurred that pre-service and in-service programs are critical by noting,

The education of a cadre of Indian teachers to staff schools which Indian children attend will not be achieved quickly. This should be a matter of high priority in any blueprint for Indian educational reform. In the meantime state and federal schools should develop pre-service and in-service orientation programs for non-native American teachers and administrators who will be working with Indian students. (p. 5)

Although pedagogy, teaching methodology, and curricula are critical elements that must be addressed in order for American Indian children to close the achievement gap, factors extraneous to education must also be considered. The general health of the American Indian population is not good. From an early age onward, American Indians suffer from diseases at a much higher rate that the overall population. According to Cahape, Hammer, and Demmert

(2003), among American Indians, even the youngest school age children are more than twice as likely to be overweight as national patterns and obesity is three times as prevalent.

In a nutshell, unhealthy children are less likely to excel at school. Children must have proper nutrition and regular exercise if their bodies and minds are to function properly.

Moreover, children who are overweight tend to be ostracized. Governmental and tribal agencies and schools must emphasize programming and education that leads to healthier lifestyles. The programming must be directed not only toward children, but parents as well. Emphasis must be placed on prevention and treatment of those diseases and health-related conditions that impact P a g e | 99

achievement. Through parent and student education, the gradual improvement of healthier lifestyles may occur. Healthier lifestyles should translate into improved student achievement among American Indian youth.

In addition to health, there must be acknowledgement that economic and related social factors affect student achievement. Poverty appears to be a major contributor to the lack of academic achievement on the part of American Indian children. Since the American Indian population is plagued by an inordinately high rate of poverty, it stands to reason that the low socioeconomic status of American Indians must be addressed by governmental and tribal agencies if there is any hope to significantly improve student achievement among American

Indian youth. The issue of poverty must be addressed because poverty spawns social ills such as drug abuse, alcoholism, and dysfunctional families. These related social ills can devastate children, as it is difficult to expect children to focus on school when their parents are using drugs or engaging in violence.

Although there are no definitive answers as to how one can best decrease the achievement gap between the American Indian and Caucasian populations, there is overwhelming evidence that an academic achievement gap exists. Unfortunately, this achievement gap does not seem to be diminishing.

While there is no panacea, there is at least a sense of those factors that contribute to the lack of achievement on the part of American Indian youth. Educational, health, and social factors play roles in the lack of academic achievement experienced by American Indian children. These factors appear widespread and significant.

As with a doctor who treats a patient, diagnosis is the first step. In the case of American

Indian children, research points to factors such as culture, curriculum, teachers, lifestyles, health P a g e | 100

issues, poverty, and social ills as culpable. The second step, which is recommended treatment, is more formidable than the diagnosis. Changes in curriculum, teacher training, and pedagogical approaches are needed. Also, the creation of healthier lifestyles is essential. Moreover, improving the socioeconomic status of American Indians is critical. Finally, convincing tribal members and authorities to participate in the entire system-wide change process is necessary for success.

The American Indian population, while the smallest in percentage, is important nonetheless. The characteristics of and challenges faced by American Indians are unique in large part due to the historical treatment of this population by the government. In many respects, no other minority population faces issues such as a lack of academic achievement to the extent of those experienced by American Indians. While the road to closing the achievement gap may be slow to be realized, the journey can only begin with several steps in the right direction.

On a localized basis, one step in the right direction involves this study. In regard to the nine school districts that are part of this study, the following general textual and graphical information provides a springboard for the collection of new data within areas of focus.

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American Indian Student Population Percentages

Native American Population Percentage by School

100 100 100 61 71 22 13 6 7

The percentage of American Indian children attending school in the nine districts in this study varies a great deal. Percentages, however, tell only part of the story. Actual numbers are important as well since the size of the school districts varies considerably. Detroit Lakes is the largest school district with 2,637 students, of which 13% or 343 students are American Indian.

However, Waubun-Ogema White Earth Community Schools has the most American Indian students in attendance with 71% or 437 students. Mahnomen Public Schools is a close second with 429 students or 61%. 22% or 225 students attend Bagley Public Schools. 110 (7%)

American Indian students attend Park Rapids Public Schools. 39 (6%) American Indian students attend Fosston Public Schools. 100% of students attending Circle of Life, Naytahwaush, and

Pine Point Schools are American Indian, as approximately 100, 76, and 64 students attend these schools, respectively (Minnesota Department of Education, 2010).

The population of American Indian students who attend these nine school districts is indeed significant in regard to student achievement. As indicated in the introductory section of P a g e | 102

this report, literature has established the underachievement of American Indian children in aggregate. Moreover, it is known that a disproportionate percentage of American Indian children reside in poverty. Although poverty has been as negatively impacting student achievement, it is possible that factors such as deficit theory thinking that results in lowered expectations and cultural incongruity could negatively impact the academic success of American Indian children.

What needs to be established, however, is whether American Indian children at these nine school districts are underachieving at a lesser or greater rate than what would be expected, and why the underachievement rate is where it is in each school district.

As reported later in this section, data are not conclusive regarding the impact of

American Indian student population percentages on achievement. At first blush, however, it appears that school districts with lower percentages of American Indian children in the overall student population have the most success in terms of American Indian academic achievement. It is possible that the teachers in these schools hold higher expectations for all children, that the curriculum is better aligned with state standards, and that the overall curriculum is taught at a higher level than in districts with larger concentrations of American Indian children. In addition, it is possible that teachers at schools with higher percentages of American Indian children subscribe to deficit theory, which attributes persistent patterns of low achievement to the socioeconomic and cultural backgrounds of children. If this is the case, teachers likely fail to recognize their own capacity to offset cultural (e.g. socioeconomic status) factors that negatively impact student achievement. In Phase II of this study, researchers will examine whether there is any credibility to the aforementioned possibilities. In addition, researchers will continue to analyze test score data by subject, grade, ethnicity, socioeconomic status, and comparison with like-type school districts to determine individual school district success in regard to American Indian P a g e | 103

student achievement. Moreover, researchers will survey and/or interview American Indian parents and children to ascertain perceptions regarding reasons for achievement or lack thereof.

Teacher Preparation

Teacher Degree Preparation Bachelor's %

90 85 87 95 73 69 84 58 51

Teacher Degree Preparation Master's%

49 33 26 26 10 14 0 7 0

While there is no guarantee that teachers who hold higher degrees are better teachers than those who hold bachelor‘s degrees, it stands to reason that those teachers who have received P a g e | 104

advanced degrees should be better prepared from a pedagogical standpoint. Teachers with advanced degrees should possess greater content knowledge and a greater understanding of how students learn. With this increased understanding, teachers should have the capacity to implement strategies in the classroom that will help students achieve at a higher level.

In reviewing the nine school districts involved in this study, Park Rapids Public Schools have a greater percentage (49) of teachers holding an advanced degree than any of the other schools in the study. Bagley Public Schools are second with 33%, followed by Fosston and

Detroit Lakes (26%), Mahnomen (14%), Pine Point (7 %), and Circle of Life, Naytahwaush, and

Waubun-Ogema-White Earth (0%). However, it should be noted that twenty teachers at

Waubun-Ogema-White Earth received master‘s degrees in curriculum and instruction in May of

2009. As a result, the percentage of faculty with master‘s degrees at this school will increase to around 40%.

It would appear that there is no positive connection between the percentage of teachers with advanced degrees and increased student achievement. As noted in Table F, Park Rapids, which has the highest percentage (49) of teachers with a master‘s degree, has medium student achievement for American Indian children and mixed for Caucasian children. Bagley, which has the second highest concentration (33 percent) of teachers with a master‘s degree, records low achievement for both American Indian and Caucasian children. Detroit Lakes, which has demonstrated high achievement for both American Indian and Caucasian children, has only one in four (25%) of teachers with a master‘s degree. Mahnomen, with 14% of master‘s degree level teachers, is listed as improving.

In professional development, best practice requires sustained engagement and support for teachers as they introduce, practice, and refine research-based strategies in curriculum, P a g e | 105

pedagogy, and classroom management in an attempt to increase student achievement. However, generic staff development programs have resulted in lack of relevance and follow-through at the school district level. Research evidence and opinions vary in terms of academic achievement, research in school improvement, student learning, and teacher learning. However, the research that has been done has led to a new consensus about effective professional development. The consensus is that professional development is most likely to advance the goals of schools if it is on-going, site-based, driven by student learning, connected to outside resources, and integrated within a broader school change process (Hawley & Valli, 1999). Newmann et al. (1996) argued that school reform will not produce a lasting impact on teachers‘ classroom practice unless structural changes are complemented by changes in culture, particularly a supportive school- wide professional community. Galucci (2003) found that the strength and openness of professional communities shapes teachers‘ response to standards-based reform, and consequently influence how they address the gap between student performance and goals for student achievement that Thompson and Zeuli (1999) identify as the primary target of professional development goals.

An area of focus in Phase II of this study will involve teacher preparation, on-going professional development, and the relationship between teacher preparedness (advanced degrees), on-going professional development ( course work, degrees, and in-service opportunities), and the relationship between student achievement, preparedness, and professional development. To obtain data regarding this relationship, researchers will rely upon teacher surveys, student surveys, and test score analyses. Survey data will include questions regarding established best practices in regard to professional development and student achievement. In addition, researchers will examine and analyze annual staff development reports. P a g e | 106

Years of Teaching Experience Chart

90%

80%

70%

60%

50% 0-3 Yrs 40% 3-10 Yrs 10+ Yrs 30%

20%

10%

0% Bag COL DL Foss Mahn Nay PR PP WOWE

Years of Teaching Experience Table

0-3 Years 3-10 Years 10+ Yrs Bagley 2% 37% 61% Circle of Life 25% 20% 55% Detroit Lakes 3% 18% 79% Fosston 5% 21% 74% Mahnomen 7% 17% 76% Naytahwaush 59% 29% 12% Park Rapids 4% 25% 71% Pine Point 0% 46% 54% Waubun-Ogema 0% 39% 61%

With the exception of Naytahwaush and Circle of Life Schools, there are very few teachers with 0-3 years of teaching experience. On the flip side, all of the school districts, with P a g e | 107

the exception of Circle of Life, have more than 50% of the teachers with ten or more years of experience. Detroit Lakes, which is the highest performing school district of the nine in this study, has a greater percentage (79) of teachers at ten years or more than any other school district. Mahnomen, which is showing considerable improvement, has 74% of teachers at ten or more years of experience. Naytauhwaush, which has only 12 percent of teachers with ten or more years of experience, has mixed results. While no firm conclusions can be reached regarding years of teaching experience and student achievement, it is possible that years of experience have no substantial impact on student achievement. Researchers will examine any possible connections in Phase II of the study through survey questions.

Average Teacher Salary

Average Teacher Salary 46,952 47,161 43,336 44,758 43,522 45,144 40,516 37,000 36,161

In Minnesota, teacher salaries are determined by the education level of the teacher and longevity. In other words, a teacher who holds a master‘s degree with no experience would be P a g e | 108

paid more than a teacher who has a bachelor‘s degree with no experience. A teacher with a bachelor‘s degree and twenty years of experience, for example, would make more than a teacher with a master‘s degree and little experience.

In reviewing average teacher salaries for the nine school districts in this study,

Naytahwaush has the lowest average teacher salary and the least experienced teachers.

Mahnomen has the highest average teacher salary, and it has the second most experienced staff.

Detroit Lakes has the most experienced teaching staff. Fosston and Park Rapids have very experienced teachers as well. Bagley, Pine Point, and Waubun-Ogema-White Earth have teaching staffs that are more varied in terms of experience. Bagley and Waubun-Ogema-White

Earth have the second and third highest average salary of the nine school districts, but both have demonstrated low achievement. Mahnomen, which has the highest salary, is showing improvement. Nothing definitive can be determined in regard to salaries paid to teachers and student achievement.

In Phase II of this study, researchers will examine the experience and educational levels of faculty. In addition, researchers will administer surveys to faculty to ascertain teaching styles, philosophies, and curricular planning efforts. These surveys will ask for self-reported demographic information as well. Researchers will try to establish whether there is a link between years of experience, educational levels, and instructional practices that are known to be best practices.

P a g e | 109

Federal Highly Qualified Requirements

Federal Highly Qualified Requirements

100% 100% 99% 100% 100% 100% 100% 100% 100%

To receive the status of highly qualified, a teacher must be teaching in compliance with licensure. In other words, teachers must teach classes for which they are licensed. In the case of all of these school districts, there is no issue in regard to teachers and the highly qualified designation. As a result, the researchers will not examine the issue of non-qualified teachers.

P a g e | 110

General Fund Revenues and Expenditures

25,000 General Fund Revenues and Expenditures

20,000

15,000

Revenues

10,000 Expenditures

5,000

0 Bag COL DL Foss Mahn Nay PR PP WOWE MN

General Fund Revenues and Expenditures Table

School Revenues Expenditures Bagley (Bag) 9,453 9,531 Circle of Life (COL) 6,500 6,500 Detroit Lakes (DL) 8,825 8,331 Fosston (Foss) 10,315 9,253 Mahnomen (Mahn) 12,764 11,083 Naytahwaush (Nay) 18,115 10,246 Park Rapids (PR) 8,899 9,070 Pine Point (PP) 21,695 21,465 Waubun-Ogema-White Earth (WOWE) 11,078 11,445 State of Minnesota Average (MN) 9,457 9,364

P a g e | 111

In reviewing General Fund revenues and expenditures, it is evident that there is wide variation in both revenues and expenditures per student by school district. Detroit Lakes and

Park Rapids Public Schools spent and received the least per student, $8,825/$8,331 and

$8,899/$9,070, respectively. Pine Point Public Schools spent received and spent the most per student at $21,695 in revenues and $21,465 in expenditures. Naytahwaush Charter School had the greatest disparity in revenues and expenditures, as the school district received $18,115, but spent only $10,246 per student.

All schools in this study receive more General Fund revenue per student than the state average, with the exception of Bagley, Detroit Lakes, and Park Rapids. All schools spend more than the state average with the exception of Detroit Lakes, Fosston, and Park Rapids.

It is evident from the data that there is no positive correlation between the average amount spent per student and student achievement. Pint Point, which has mixed achievement results, spends three and one-half times as much per student as Detroit Lakes, which has high achievement.

In Phase II of this study, researchers will examine the usage of expenditures, and whether there is wise usage of expenditures in regard to student achievement. This examination will involve a review of expenditures, surveys of administration, staff, and faculty, and a comparison of test scores in contrast to expenditures per student.

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Graduation Rate

2007-08 Graduation Rate

95% 92% 88% 90% 75% 77% 72%

American Indian Graduation Rates

School 06-07 05-06 04-05 03-04 02-03 AVG* Bagley 92.3 100 85.7 100 25 80.6 Circle of Life 85 90 NA 73 NA 82.66 DL 72 65.2 89.5 76.5 88.2 78.28 Fosston 100 100 100 100 87.5 97.5 Mahnomen 58.5 63.3 81.5 71.4 64.5 67.96 PR 58.3 46.2 62.5 50 55.6 54.52 WOWE 85 96.4 X X X 90.7

*Statewide Graduation Rate Average for American Indian Students= 70%

The 2007-08 graduation rate listed in the chart is for all students. However, the graduation rate for American Indian students is considerably lower, as indicated in the table.

Only seven out of ten American Indian students graduate on a statewide basis. In reviewing the school districts with high schools in this study, Park Rapids and Mahnomen Public Schools have P a g e | 113

average American Indian graduation rates that are below state average. Although better than the statewide average, Detroit Lakes is a school of concern as well, as between one in four and one in five American Indian students does not graduate on average. The graduation rate of American

Indian students at Bagley is quite good, with the exception of the 2002-03 school year. The graduation rate at Waubun-Ogema-White Earth Schools is acceptable. There is no concern noted at Fosston.

In Phase II of this study, researchers will try to ascertain the reasons for American Indian students either graduate or drop out of school. This information will be gathered via surveys, interviews, and/or focus groups. The greatest focus will occur in the school districts of Park

Rapids, Mahnomen, and Detroit Lakes Public Schools.

It should be noted that the Annual Yearly Progress (AYP) Graduation rate was used. This rate is calculated in the following manner. From 2005-2008, Minnesota has used the National

Center for Education Statistics (NCES) emulated cohort model to compute graduation rates for

AYP requirements. The formal title of this rate is: Common Core of Data Graduation Leaver

Indicator. This model creates a cohort group by identifying students who graduated in 2007 plus students who dropped out of school as ninth graders in 2004, tenth graders in 2005, eleventh graders in 2006 and twelfth graders in 2007. The cohort group is divided by the number of graduates. This rate is much higher than the NGA rate as it only considers part of the available student group; those who were last reported as graduated and those reported as dropping out. It does not consider students reported as continuing their education or students whose end status is unknown. It also does not limit graduates to only those finishing in four years. Any student who receives a diploma in 2007 is considered a graduate regardless of the number of years spent in school. P a g e | 114

Dropout Rate

2007-08 American Indian Dropout Rate

46%

18% 23% 8% 9% 10% 1%

American Indian Dropout Rates 2002-07

School 06-07 05-06 04-05 03-04 02-03 AVG Bagley 7.7 0 14.3 0 75 19.4 Circle of Life 10.9 4.2 NA 15.7 NA 10.27 DL 28 34.8 10.5 23.5 11.8 21.72 Fosston 0 0 0 0 12.5 2.5 Mahnomen 41.5 36.7 18.5 28.6 35.5 32.04 PR 41.7 53.8 37.5 50 44.4 45.48 WOWE 15 3.6 X X X 9.3

X = cell size too small for reporting

More than 50,000 students graduate annually in Minnesota. Of these students, only 2% is identified as American Indian. Of this 2%, 70.4 percent graduate on a statewide basis, while P a g e | 115

29.6% drop out. This number is quite disturbing since 94.3 percent of Caucasian students graduate.

In reviewing dropout rates of the nine school districts involved in this study, four school districts stand out as districts of concern. Park Rapids exceeds the statewide American Indian dropout average, as nearly one in two American Indian students drop out of school. The

American Indian dropout rate at Park Rapids is unusually high. At Mahnomen Public Schools, nearly one in three American Indian students drop out of school on average. The dropout rate for

American Indian children at Detroit Lakes Public Schools is slightly lower than the state average, but more than one in five students drops out of school on average. Bagley Public

Schools has a dropout rate of nearly one in five American Indian children on average, but this percentage falls into an acceptable range when the 2002-03 school year is removed from consideration. American Indian dropout rates at Circle of Life, Fosston, and Waubun-Ogema-

White Earth Schools are well below state average. Pine Point and Naytahwaush do not have high school populations.

In Phase II of this study, researchers will try to ascertain the reasons for American Indian students dropping out of school. This information will be gathered via surveys, interviews, and/or focus groups. The greatest focus will occur in the school districts of Park Rapids,

Mahnomen, and Detroit Lakes Public Schools.

P a g e | 116

Special Education

Special Education

34% 28% 18% 21% 21% 16% 17% 13% 14%

The percentage of special education students in a school district must be considered in regard to aggregate student achievement scores. In aggregate, special education students tend to underachieve in regard to test scores. The statewide special education average is thirteen percent.

Fosston and Waubun-Ogema-White Earth Public Schools have the lowest rates of special education students, thirteen and fourteen percent, respectively, which mirrors the state average.

Pine Point has the greatest identification, with one in three students labeled as special education.

The remaining school districts have special education populations between sixteen and twenty- one percent.

One common concern related to educational equity is overrepresentation of minority or low-SES students in Special Education programs. There is potential that this over-identification could be a factor in decreased student achievement for American Indian students since misidentification would not necessarily help those students achieve at a proficient level. Rather P a g e | 117

than addressing the underlying causes of the underachievement, American Indian students could be referred for special education services inappropriately.

State report card data do not allow us to identify which students are given individualized education plans (IEP‘s), and hence we cannot determine whether American Indian students within the district are disproportionately labeled as having a disability. However, between districts, there is a moderate correlation between the proportion of American Indian students and the proportion of students on IEP‘s. Pine Point, Circle of Life, and Naytahwash have the highest proportion of American Indian students (100%, 100%, and 99%) and the highest rate of Special

Education referrals (34%, 28%, and 21%); Fosston has the lowest in each category (6%

American Indian students, 13% IEP referrals). The correlation is not as clear, however, in the remaining districts. Furthermore, there is no observable correlation between IEP rates and achievement. The two of three districts with the lowest achievement, Waubun and Bagley, have the slightly lower rates of IEP referrals (16% and 17% respectively) and higher-achieving districts, such as Detroit Lakes (18%) and Mahnomen (19%). Clearly, more investigation is needed to determine whether American Indian students are overrepresented in special education within districts, and if so whether this has an impact on achievement rates.

In Phase II of this study, researchers will review data to determine whether the percentage of American Indian children who are receiving special education services at each school to determine whether a disproportionate percentage of special education students are

American Indian. In addition, researchers will examine aggregate test scores of American Indian students who are receiving special education services to determine the percentage of these students who obtain proficiency on MAP and MCA II tests. Finally, researchers will review P a g e | 118

curriculum to see whether special education students receive curriculum that focuses on the same essential learner outcomes as those of regular education students.

Free and Reduced Lunch

Free and Reduced Lunch

100% 95% 66% 69% 50% 37% 47% 45% 0%

Free and reduced lunch percentages must be taken into consideration in regard to student achievement. Research has demonstrated a link between lowered socioeconomic status and student achievement. As a result, it stands to reason that an increased percentage of students who qualify for free and reduced lunch should result in decreased student achievement.

The state average for free and reduced lunch count is 32%. All schools in this study exceed the state average. Detroit Lakes is closest to the state average with 37%. Nearly all students at Pine Point qualify for free and reduced lunch, while around two out of three qualify and Mahnomen and Waubun-Ogema-White Earth Public Schools. Around one out of two students qualify for free and reduced lunch at Fosston and Bagley. P a g e | 119

In Phase II of this study, researchers will review the percentage of American Indian students who qualify for free and reduced lunch, and whether there is a positive correlation with test scores.

Student Teacher Ratio

Student Teacher Ratio

14 15 16 14 13 12 8 6 5

Although there is not significant research evidence to correlate lower student-teacher ratios to increased achievement, there is a common perception that lower student-teacher ratios are preferable to higher ones.

In the case of the nine school districts in this study, Pine Point, Circle of Life,

Naytahwaush, and Waubun-Ogema-White Earth Schools have the lowest student-teacher ratios with 5, 6, 8, and 12, respectively. However, these four school districts do not have high academic success. As a result, Phase II of this study will look factors other than student-teacher ratios to determine potential contributors to overall achievement.

P a g e | 120

Contractual Days

Contractual Days 250 200 150 100 50 0 Mahno Circle of Detroit Pine Park Naytah Fosston Bagley Waubun men Life Lakes Point Rapids waush Contractual Days 170 178 177 198 177 173 183 179 Student Contact Days 172 171 172 166 171 178 173 169 Work Day/Staff Development 10 5 7 9 9 8 5 8 P/T Conferences 4 4 3 2 2 2 4 4

Of the school districts in this study, Detroit Lakes has the fewest student contact days of any. Interestingly enough, Detroit Lakes is listed as the highest achieving school. However,

Detroit Lakes does have more professional development days than most of the other school districts. In Phase II of this study, researchers will examine the use of student contact time and professional development days to see any possible connections between the seat time usage and student achievement and professional development days, content, and achievement levels.

P a g e | 121

Academic Achievement Measurements of School Districts (Tests)

MCA-II.

The Minnesota Comprehensive Assessments—Series II (MCA-IIs) are the state tests that help districts measure student progress toward Minnesota's academic standards and meet the requirements of No Child Left Behind. The reading and mathematics tests are used to determine whether schools and districts have made adequate yearly progress toward all students being proficient in 2014.

Reading and mathematics tests are given in grades 3-8, 10 and 11. In the spring of 2008 science tests will also be given in grades 5 and 8 and once in high school, depending on when students complete their life sciences curriculum.

MTELL.

The Mathematics Test for English Language Learners (MTELL) is a computer-delivered mathematics test in grades 3-8 and 11 with simplified English that reduces the confounding effects of language on mathematics performance. Students may listen to test items as well as read them. Pictures and diagrams help students understand the language in the test items. The MTELL assesses the same grade level academic standards as the MCA-IIs. P a g e | 122

MCA-II Math Proficiency % 05-06 All Grades

58 57 61 46 43 45 14 16

MCA-II Math Proficiency % 06-07 All Grades

63 56 57 46 39 41 42 23

P a g e | 123

MCA-II Math Proficiency% 07-08 All Grades

60 62 57 55 44 44 46 44 38

MCA-II Math Proficiency % 08-09 All Grades

65 67 59 50 54 40 41 40

P a g e | 124

Math Proficiency %

Waubun- Bagley Circle of Life Detroit Lakes Fosston Mahnomen Park Rapids Naytahwaush Pine Point Ogema 05-06 46 58 57 43 61 14 16 45 06-07 46 63 56 39 57 23 41 42 07-08 44 44 60 62 46 57 55 44 38 08-09 50 65 67 54 59 40 41 40

MCA-II Reading Proficiency % 05-06 All Grades

75 79 64 66 58 61 27 29

P a g e | 125

MCA-II Reading Proficiency % 06-07 All Grades

70 66 70 62 54 54 37 25

MCA-II Reading Proficiency% 07-08 All Grades

76 74 61 61 68 61 67 48 56

P a g e | 126

MCA-II Reading Proficiency % 08-09 All Grades

76 75 69 64 69 46 50 36

Reading Proficiency %

Waubun- Bagley Circle of Life Detroit Lakes Fosston Mahnomen Park Rapids Naytahwaush Pine Point Ogema 05-06 64 75 66 58 79 27 29 61 06-07 62 70 66 54 70 25 37 54 07-08 61 61 76 68 61 74 67 48 56 08-09 69 76 75 64 69 46 36 50

MCA-II scores for math, reading, science for 2005-09.

Location Subject # Tested '06 % Prof. # Tested % Prof. # Tested % Prof. # Tested % Prof. (Amer. Ind.) '05-'06 '06-'07 '06-'07 '07-'08 '07-'08 '08-'09 '08-'09 Bagley Math 110 29 103 28 119 25 113 33 Bagley Reading 111 49 114 44 112 48 111 48 Bagley Science NA NA NA NA 32 6 47 11 Circle of Life Math 55 52 49 44 36 44 50 37 Circle of Life Reading 58 58 46 53 42 61 47 57 Detroit Lakes Math 173 40 172 47 178 48 186 46 P a g e | 127

Detroit Lakes Reading 184 59 174 51 181 64 187 64 Detroit Lakes Science NA NA NA NA 86 22 77 19 Fosston Math 26 42 28 39 25 36 24 54 Fosston Reading 24 58 29 52 23 35 28 50 Fosston Science 11 9 16 25 Mahnomen Math 185 32 195 29 203 37 212 42 Mahnomen Reading 189 49 201 44 200 54 223 57 Mahnomen Science 73 7 99 21 Park Rapids Math 40 45 45 40 49 43 50 40 Park Rapids Reading 45 44 48 60 52 67 53 53 Park Rapids Science 17 6 21 10 Naytahwaush Math 44 14 48 23 33 58 34 41 Naytahwaush Reading 44 27 48 25 33 67 36 47 Naytahwaush Science 4 NA 7 NA Pine Point Math 31 16 32 41 36 44 34 41 Pine Point Reading 35 29 30 37 35 49 33 36 Pine Point Science 11 9 8 NA Waubun Math 192 39 221 38 232 33 216 36 Waubun Reading 204 54 234 49 224 50 218 45 Waubun Science 78 17 92 11

Ethnic breakdown for student achievement on MCA-II, MTAS, and MTELL by district.

Percentage scoring proficient, by subject and district, across all grade levels in 2009. District subject all Am.Ind. Asian Hisp. Black White LEP Special FRP Bagley Reading 69 48 NA NA NA 76 NA 29 62 Bagley Math 50 33 NA NA NA 56 NA 26 44 Bagley Science 32 11 NA NA NA 38 NA 3 24 Circle of Life Reading 57 57 NA NA NA NA NA 20 NA Circle of Life Math 37 37 NA NA NA NA NA 18 NA Circle of Life Science 12 12 NA NA NA NA NA NA NA Detroit Lakes Reading 76 64 NA 57 NA 78 NA 30 68 Detroit Lakes Math 65 46 NA 59 NA 68 NA 32 55 Detroit Lakes Science 41 19 NA NA NA 44 NA 11 30 Fosston Reading 75 50 NA NA NA 78 NA 28 65 Fosston Math 67 54 NA NA NA 68 NA 43 56 Fosston Science 48 25 NA NA NA 51 NA 5 33 Mahnomen Reading 64 57 NA NA NA 80 NA 45 55 Mahnomen Math 54 42 NA NA NA 73 NA 25 44 Mahnomen Science 28 21 NA NA NA 42 NA 14 25 Park Rapids Reading 69 53 NA 71 50 71 NA 34 58 Park Rapids Math 59 40 NA 62 25 61 NA 31 48 Park Rapids Science 30 10 NA NA NA 33 NA 12 20 Naytahwaush Reading 46 47 NA NA NA NA NA 50 44 P a g e | 128

Naytahwaush Math 40 41 NA NA NA NA NA 31 38 Naytahwaush Science NA NA NA NA NA NA NA NA NA Pine Point Reading 36 36 NA NA NA NA NA NA 38 Pine Point Math 41 41 NA NA NA NA NA NA 42 Pine Point Science NA NA NA NA NA NA NA NA NA Waubun Reading 50 45 NA NA NA 63 NA 19 47 Waubun Math 40 36 NA NA NA 52 NA 21 37 Waubun Science 17 11 NA NA NA 32 NA 7 17

Growth Over the 2008-2009 School Year

District Subject Test Grade Population Pft Pft Pft NP NP NP Low* Med.* High* Low* Med.* High* Bagley Math MCA 2 All All 21 25 17 13 14 11 Bagley Math MCA 2 All American Indian 13 26 8 21 16 16 Bagley Math MCA 2 4 All 41 34 6 2 9 9 Bagley Math MCA 2 4 American Indian 47 13 7 7 13 13 Bagley Math MCA 2 5 All 21 21 16 18 20 3 Bagley Math MCA 2 5 American Indian 0 11 11 42 32 5 Bagley Math MCA 2 6 All 8 20 15 11 18 29 Bagley Math MCA 2 6 American Indian NA NA NA NA NA NA Bagley Math MCA 2 7 All 9 17 15 9 20 32 Bagley Math MCA 2 7 American Indian 5 11 5 11 26 42 Bagley Math MCA 2 8 All 13 13 4 22 23 25 Bagley Math MCA 2 8 American Indian 10 10 0 15 40 25 Bagley Math MCA 2 11 All 15 4 6 15 40 19 Bagley Math MCA 2 11 American Indian NA NA NA NA NA NA Bagley Reading MCA 2 All All 18 26 20 7 16 13 Bagley Reading MCA 2 All American Indian 22 20 8 14 24 13 Bagley Reading MCA 2 4 All 27 29 21 0 10 13 Bagley Reading MCA 2 4 American Indian 33 33 0 0 13 20 Bagley Reading MCA 2 5 All 23 31 16 8 15 7 Bagley Reading MCA 2 5 American Indian 21 16 5 11 37 11 Bagley Reading MCA 2 6 All 9 34 21 2 13 21 Bagley Reading MCA 2 6 American Indian NA NA NA NA NA NA Bagley Reading MCA 2 7 All 17 22 28 11 12 10 Bagley Reading MCA 2 7 American Indian 26 16 16 11 21 11 P a g e | 129

Bagley Reading MCA 2 8 All 15 26 12 12 20 16 Bagley Reading MCA 2 8 American Indian 20 20 10 25 20 5 Bagley Reading MCA 2 10 All 20 17 22 9 22 10 Bagley Reading MCA 2 10 American Indian 9 18 9 36 18 9 Detroit Lakes Math MCA 2 All All 20 30 17 8 12 14 Detroit Lakes Math MCA 2 All American Indian 26 18 11 11 18 17 Detroit Lakes Math MCA 2 4 All 37 42 10 3 2 6 Detroit Lakes Math MCA 2 4 American Indian 40 26 11 6 6 11 Detroit Lakes Math MCA 2 5 All 23 37 18 4 6 11 Detroit Lakes Math MCA 2 5 American Indian 33 21 17 13 8 8 Detroit Lakes Math MCA 2 6 All 37 33 7 11 11 2 Detroit Lakes Math MCA 2 6 American Indian 50 21 4 14 7 4 Detroit Lakes Math MCA 2 7 All 8 27 26 7 15 17 Detroit Lakes Math MCA 2 7 American Indian 5 5 21 11 21 37 Detroit Lakes Math MCA 2 8 All 7 19 19 10 20 26 Detroit Lakes Math MCA 2 8 American Indian 4 13 4 17 39 22 Detroit Lakes Math MCA 2 11 All 6 21 22 11 15 25 Detroit Lakes Math MCA 2 11 American Indian 5 14 9 9 36 27 Detroit Lakes Reading MCA 2 All All 21 32 23 5 11 9 Detroit Lakes Reading MCA 2 All American Indian 23 24 14 8 16 16 Detroit Lakes Reading MCA 2 4 All 21 38 27 5 5 4 Detroit Lakes Reading MCA 2 4 American Indian 31 29 14 9 9 9 Detroit Lakes Reading MCA 2 5 All 29 30 23 4 7 8 Detroit Lakes Reading MCA 2 5 American Indian 17 30 13 4 13 22 Detroit Lakes Reading MCA 2 6 All 27 39 23 4 5 2 Detroit Lakes Reading MCA 2 6 American Indian 43 32 18 4 4 0 Detroit Lakes Reading MCA 2 7 All 15 32 25 3 14 11 Detroit Lakes Reading MCA 2 7 American Indian 5 16 21 5 32 21 Detroit Lakes Reading MCA 2 8 All 17 23 21 7 17 14 Detroit Lakes Reading MCA 2 8 American Indian NA NA NA NA NA NA Detroit Lakes Reading MCA 2 10 All 17 28 19 8 14 15 Detroit Lakes Reading MCA 2 10 American Indian 13 9 9 13 22 35 Fosston Math MCA 2 All All 22 27 33 7 11 9 Fosston Math MCA 2 All American Indian 33 24 5 10 14 14 Fosston Math MCA 2 4 All 9 50 38 0 0 3 Fosston Math MCA 2 4 American Indian NA NA NA NA NA NA Fosston Math MCA 2 5 All 50 29 14 2 4 2 Fosston Math MCA 2 5 American Indian NA NA NA NA NA NA P a g e | 130

Fosston Math MCA 2 6 All 19 33 24 0 7 17 Fosston Math MCA 2 6 American Indian NA NA NA NA NA NA Fosston Math MCA 2 7 All 16 12 35 12 14 12 Fosston Math MCA 2 7 American Indian NA NA NA NA NA NA Fosston Math MCA 2 8 All 14 26 18 12 22 8 Fosston Math MCA 2 8 American Indian NA NA NA NA NA NA Fosston Math MCA 2 11 All 20 17 15 17 20 12 Fosston Math MCA 2 11 American Indian NA NA NA NA NA NA Fosston Reading MCA 2 All All 19 32 21 6 11 13 Fosston Reading MCA 2 All American Indian 16 16 12 20 24 12 Fosston Reading MCA 2 4 All 3 34 38 3 13 29 Fosston Reading MCA 2 4 American Indian NA NA NA NA NA NA Fosston Reading MCA 2 5 All 41 37 10 8 4 0 Fosston Reading MCA 2 5 American Indian NA NA NA NA NA NA Fosston Reading MCA 2 6 All 8 27 39 0 10 17 Fosston Reading MCA 2 6 American Indian NA NA NA NA NA NA Fosston Reading MCA 2 7 All 20 33 20 6 6 16 Fosston Reading MCA 2 7 American Indian NA NA NA NA NA NA Fosston Reading MCA 2 8 All 14 35 14 4 14 20 Fosston Reading MCA 2 8 American Indian NA NA NA NA NA NA Fosston Reading MCA 2 10 All 20 24 11 13 19 13 Fosston Reading MCA 2 10 American Indian NA NA NA NA NA NA Mahnomen Math MCA 2 All All 16 22 13 15 17 17 Mahnomen Math MCA 2 All American Indian 14 17 10 19 21 19 Mahnomen Math MCA 2 4 All 35 29 9 12 12 3 Mahnomen Math MCA 2 4 American Indian 37 26 11 15 7 4 Mahnomen Math MCA 2 5 All 23 20 17 14 9 17 Mahnomen Math MCA 2 5 American Indian 15 15 15 15 15 25 Mahnomen Math MCA 2 6 All 15 18 5 18 30 15 Mahnomen Math MCA 2 6 American Indian 8 12 0 24 36 20 Mahnomen Math MCA 2 7 All 12 32 4 24 12 16 Mahnomen Math MCA 2 7 American Indian 9 26 0 31 17 17 Mahnomen Math MCA 2 8 All 12 21 21 9 12 25 Mahnomen Math MCA 2 8 American Indian 10 15 21 10 18 26 Mahnomen Math MCA 2 11 All 5 8 21 16 32 18 Mahnomen Math MCA 2 11 American Indian 6 0 13 19 44 19 Mahnomen Reading MCA 2 All All 18 27 18 10 15 12 Mahnomen Reading MCA 2 All American Indian 18 25 15 14 18 10 P a g e | 131

Mahnomen Reading MCA 2 4 All 32 29 9 9 15 6 Mahnomen Reading MCA 2 4 American Indian 33 30 11 11 7 7 Mahnomen Reading MCA 2 5 All 26 34 11 6 11 11 Mahnomen Reading MCA 2 5 American Indian 20 30 10 10 20 10 Mahnomen Reading MCA 2 6 All 8 38 25 5 18 8 Mahnomen Reading MCA 2 6 American Indian 8 32 16 8 28 8 Mahnomen Reading MCA 2 7 All 26 26 14 22 10 4 Mahnomen Reading MCA 2 7 American Indian 25 22 8 31 11 3 Mahnomen Reading MCA 2 8 All 13 21 23 8 15 21 Mahnomen Reading MCA 2 8 American Indian 11 20 23 11 20 14 Mahnomen Reading MCA 2 10 All 10 19 24 7 21 19 Mahnomen Reading MCA 2 10 American Indian 12 23 19 8 23 15 Park Rapids Math MCA 2 All All 21 25 17 13 14 11 Park Rapids Math MCA 2 All American Indian 13 26 8 21 16 16 Park Rapids Math MCA 2 4 All 7 39 34 1 2 17 Park Rapids Math MCA 2 4 American Indian NA NA NA NA NA NA Park Rapids Math MCA 2 5 All 59 17 7 6 5 5 Park Rapids Math MCA 2 5 American Indian NA NA NA NA NA NA Park Rapids Math MCA 2 6 All 13 29 12 16 22 8 Park Rapids Math MCA 2 6 American Indian NA NA NA NA NA NA Park Rapids Math MCA 2 7 All 22 23 15 20 13 8 Park Rapids Math MCA 2 7 American Indian NA NA NA NA NA NA Park Rapids Math MCA 2 8 All 7 18 18 18 22 18 Park Rapids Math MCA 2 8 American Indian NA NA NA NA NA NA Park Rapids Math MCA 2 11 All 28 24 10 15 18 5 Park Rapids Math MCA 2 11 American Indian NA NA NA NA NA NA Park Rapids Reading MCA 2 All All 27 29 18 10 8 8 Park Rapids Reading MCA 2 All American Indian 32 15 27 12 7 7 Park Rapids Reading MCA 2 4 All 22 41 27 4 5 2 Park Rapids Reading MCA 2 4 American Indian NA NA NA NA NA NA Park Rapids Reading MCA 2 5 All 49 28 9 11 3 1 Park Rapids Reading MCA 2 5 American Indian NA NA NA NA NA NA Park Rapids Reading MCA 2 6 All 19 29 27 7 10 9 Park Rapids Reading MCA 2 6 American Indian NA NA NA NA NA NA Park Rapids Reading MCA 2 7 All 21 28 16 12 10 14 Park Rapids Reading MCA 2 7 American Indian NA NA NA NA NA NA Park Rapids Reading MCA 2 8 All 19 25 19 14 11 13 Park Rapids Reading MCA 2 8 American Indian NA NA NA NA NA NA P a g e | 132

Park Rapids Reading MCA 2 10 All 33 25 10 11 10 10 Park Rapids Reading MCA 2 10 American Indian NA NA NA NA NA NA Naytahwaush Math MCA 2 All All 33 14 5 24 14 10 Naytahwaush Math MCA 2 All American Indian 35 15 5 20 15 10 Naytahwaush Math MCA 2 4 All 27 18 9 9 18 18 Naytahwaush Math MCA 2 4 American Indian 27 18 9 9 18 18 Naytahwaush Math MCA 2 5 All NA NA NA NA NA NA Naytahwaush Math MCA 2 5 American Indian NA NA NA NA NA NA Naytahwaush Math MCA 2 6 All NA NA NA NA NA NA Naytahwaush Math MCA 2 6 American Indian NA NA NA NA NA NA Naytahwaush Reading MCA 2 All All 62 14 5 10 5 5 Naytahwaush Reading MCA 2 All American Indian 60 15 5 10 5 5 Naytahwaush Reading MCA 2 4 All 55 27 9 0 0 9 Naytahwaush Reading MCA 2 4 American Indian 55 27 9 0 0 9 Naytahwaush Reading MCA 2 5 All NA NA NA NA NA NA Naytahwaush Reading MCA 2 5 American Indian NA NA NA NA NA NA Naytahwaush Reading MCA 2 6 All NA NA NA NA NA NA Naytahwaush Reading MCA 2 6 American Indian NA NA NA NA NA NA Pine Point Math MCA 2 All All 32 23 5 9 23 9 Pine Point Math MCA 2 All American Indian 32 23 5 9 23 9 Pine Point Reading MCA 2 All All 43 14 5 24 5 10 Pine Point Reading MCA 2 All American Indian 43 14 5 24 5 10 Waubun Math MCA 2 All All 14 21 10 22 18 12 Waubun Math MCA 2 All American Indian 16 18 9 23 19 15 Waubun Math MCA 2 4 All 8 35 22 0 22 14 Waubun Math MCA 2 4 American Indian 12 31 19 0 19 19 Waubun Math MCA 2 5 All 37 19 4 27 8 6 Waubun Math MCA 2 5 American Indian 28 20 5 33 8 8 Waubun Math MCA 2 6 All 14 23 2 27 14 21 Waubun Math MCA 2 6 American Indian 16 10 3 26 19 26 Waubun Math MCA 2 7 All 21 12 12 30 21 5 Waubun Math MCA 2 7 American Indian 20 7 10 37 20 7 Waubun Math MCA 2 8 All 6 23 11 26 26 9 Waubun Math MCA 2 8 American Indian 4 28 4 24 28 12 Waubun Math MCA 2 11 All 6 16 16 16 25 22 Waubun Math MCA 2 11 American Indian 9 13 13 13 30 22 Waubun Reading MCA 2 All All 23 18 14 12 19 14 Waubun Reading MCA 2 All American Indian 21 18 11 13 22 15 P a g e | 133

Waubun Reading MCA 2 4 All 27 24 22 3 22 3 Waubun Reading MCA 2 4 American Indian 27 31 12 0 27 4 Waubun Reading MCA 2 5 All 38 19 4 25 13 2 Waubun Reading MCA 2 5 American Indian 32 20 5 27 15 2 Waubun Reading MCA 2 6 All 18 18 25 0 23 16 Waubun Reading MCA 2 6 American Indian 13 16 26 0 26 19 Waubun Reading MCA 2 7 All 17 19 7 14 19 24 Waubun Reading MCA 2 7 American Indian 14 14 0 14 24 35 Waubun Reading MCA 2 8 All 20 20 11 11 11 26 Waubun Reading MCA 2 8 American Indian 28 16 12 12 8 24 Waubun Reading MCA 2 10 All 9 9 18 12 30 21 Waubun Reading MCA 2 10 American Indian 5 11 11 21 42 11

Comparison Among Districts

Table 1: Passing rates on state exams by grade level and ethnicity (reading, 2008-09) Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 10 District %P %P G %P %P G %P %P G %P %P G %P %P G %P %P G %P %P G AI CN AI CN AI CN AI CN AI CN AI CN AI CN Detroit Lakes 87.5 83.6 -3.86 66.7 85.7 19.1 66.7 81.8 15.1 69 79.5 10.6 47.6 70.7 23.1 45.8 67.3 21.4 61.5 78 16.4 Fosston NA 80.4 NA NA 84.8 NA NA 74.5 NA NA 79.2 NA NA 78.8 NA NA 75.5 NA NA 72.9 NA Bagley 62.5 89.5 27 56.3 70.9 14.7 50 79.5 29.5 NA 80.7 NA 38.9 68.9 30 45.5 62.5 17.1 40 77.5 37.5 Mahnomen 73.3 86.7 13.3 57.6 NA NA 56 87.5 31.5 58.6 93.3 34.7 34.2 72.7 38.5 62.2 76.5 14.3 58.1 82.4 24.3 Naytahwaush NA NA NA 46.7 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Park Rapids NA 83.6 NA NA 84.2 NA NA 65.5 NA NA 74.1 NA NA 59.2 NA 40 53.9 13.9 NA 74.5 NA Pine Point NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Waubun 58.6 75 16.4 57.1 63.6 6.49 38.1 66.7 28.6 47.1 64.3 17.2 38.7 42.9 4.15 57.1 45.5 -11.7 23.1 80 56.9

%P = Percent Proficient AI = American Indian CN = Caucasian G = gap (CN – AI)

Table 2: District rank, passing rates by grade level and ethnicity (reading, 2008-09) Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 10 District AI CN G AI CN G AI CN G AI CN G AI CN G AI CN G AI CN G Detroit Lakes 1 3 1 1 1 3 1 2 1 1 3 1 1 3 2 3 3 5 1 3 1 Fosston NA 5 NA NA 2 NA NA 4 NA NA 4 NA NA 1 NA NA 2 NA NA 5 NA Bagley 3 1 4 4 4 2 3 3 3 NA 2 NA 2 4 3 4 4 4 3 4 3 Mahnomen 2 2 2 2 NA NA 2 1 4 3 1 3 4 2 4 1 1 3 2 1 2 Naytahwaush NA NA NA 5 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Park Rapids NA 3 NA NA 3 NA NA 6 NA NA 5 NA NA 5 NA 5 5 2 NA 6 NA Pine Point NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Waubun 4 6 3 3 5 1 4 5 2 2 6 2 3 6 1 2 6 1 4 2 4

Note: for this table, just include the ranking for AI proficiency (highest is #1), CN proficiency (highest is #1), and gap (lowest is #1). P a g e | 134

Table 3: Passing rates on state exams by grade level and ethnicity (math, 2008-09) Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 11 District %P %P G %P %P G %P %P G %P %P G %P %P G %P %P G %P %P G AI CN AI CN AI CN AI CN AI CN AI CN AI CN Detroit Lakes 91.7 93.7 2.05 58.3 82.1 23.8 48.1 73 24.8 41.4 63.6 22.3 38.1 66.9 28.8 16.7 58.2 41.5 24 45.6 21.6 Fosston NA 94.1 NA NA 94.1 NA NA 75.5 NA NA 76 NA NA 59.6 NA NA 53.1 NA NA 25 NA Bagley 68.8 86 17.2 62.5 61.8 -0.69 30 59.1 29.1 NA 56.1 NA 16.7 62.3 45.6 18.2 39.6 21.4 0 18.8 18.8 Mahnomen 70 86.7 16.7 39.4 NA NA 36 68.8 32.8 28.6 73.3 44.8 37.8 86.4 48.5 50 88.2 38.2 17.6 45.5 27.8 Naytahwaush NA NA NA 35.7 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Park Rapids NA 88.4 NA NA 90.3 NA NA 60.5 NA NA 54.1 NA NA 44.3 NA 20 46.6 26.6 NA 37.4 NA Pine Point NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Waubun 69 83.3 14.4 64.3 72.7 8.44 31.7 50 18.3 20.6 50 29.4 25 35.7 10.7 25 36.4 11.4 16.7 NA NA

%P = Percent Proficient AI = American Indian CN = Caucasian G = gap (CN – AI)

Table 4: District rank, passing rates by grade level and ethnicity (math, 2008-09) Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 11 District AI CN G AI CN G AI CN G AI CN G AI CN G AI CN G AI CN G Detroit Lakes 1 2 1 3 3 3 1 2 2 1 3 1 1 2 2 5 2 5 1 1 2 Fosston NA 1 NA NA 1 NA NA 1 NA NA 1 NA NA 4 NA NA 3 NA NA 4 NA Bagley 4 5 4 2 5 1 4 5 3 NA 4 NA 4 3 3 4 5 2 4 5 1 Mahnomen 2 4 3 4 NA NA 2 3 4 2 2 3 2 1 4 1 1 4 2 2 3 Naytahwaush NA NA NA 5 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Park Rapids NA 3 NA NA 2 NA NA 4 NA NA 5 NA NA 5 NA 3 4 3 NA 3 NA Pine Point NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Waubun 3 6 2 1 4 2 3 6 1 3 6 2 3 6 1 2 6 1 3 NA NA

Note: for this table, just include the ranking for AI proficiency (highest is #1), CN proficiency (highest is #1), and gap (lowest is #1).

Table 5: Passing rates on state exams by grade level and ethnicity (reading, 2007-08) Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 10 District %P %P G %P %P G %P %P G %P %P G %P %P G %P %P G %P %P G AI CN AI CN AI CN AI CN AI CN AI CN AI CN Detroit Lakes 79.4 88.5 9.07 65 84.5 19.5 91.7 87.7 -3.95 45 76.9 31.9 40.9 65 24.1 51.6 77.7 26.1 63.3 75 11.7 Fosston NA 75.9 NA NA 87.8 NA NA 70.6 NA NA 70.8 NA NA 63.5 NA NA 51.4 NA NA 72.7 NA Bagley 70.6 81.1 10.6 42.1 84.1 42 NA 70.4 NA 61.9 68.3 6.35 52.4 55.4 2.97 53.3 48.1 -5.19 8.33 54 45.7 Mahnomen 73.3 86.7 13.3 57.6 NA NA 56 87.5 31.5 58.6 93.3 34.7 34.2 72.7 38.5 62.2 76.5 14.3 58.1 82.4 24.3 Naytahwaush 92.3 NA NA NA NA NA NA NA NA 36.4 NA NA NA NA NA NA NA NA NA NA NA Park Rapids NA 91.4 NA NA 83 NA 70 74.7 4.72 NA 64 NA NA 62.9 NA NA 80.9 NA NA 72.5 NA Pine Point NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Waubun 68.8 81.8 13.1 55.1 71.4 16.3 51.6 84.6 33 25.8 66.7 40.9 50 54.5 4.54 28.6 73.7 45.1 71.4 54.5 -16.9

%P = Percent Proficient AI = American Indian CN = Caucasian G = gap (CN – AI) P a g e | 135

Table 6: District rank, passing rates by grade level and ethnicity (reading, 2007-08) Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 10 District AI CN G AI CN G AI CN G AI CN G AI CN G AI CN G AI CN G Detroit Lakes 2 2 1 1 2 2 1 1 1 3 2 2 3 2 3 3 2 3 2 2 2 Fosston NA 6 NA NA 1 NA NA 5 NA NA 3 NA NA 3 NA NA 5 NA NA 3 NA Bagley 4 5 2 4 3 1 NA 6 NA 1 4 1 1 4 1 2 6 1 4 6 4 Mahnomen 3 3 4 2 NA NA 3 2 3 2 1 3 4 1 4 1 3 2 3 1 3 Naytahwaush 1 NA NA NA NA NA NA NA NA 4 NA NA NA NA NA NA NA NA NA NA NA Park Rapids NA 1 NA NA 4 NA 2 4 2 NA 6 NA NA 4 NA NA 1 NA NA 4 NA Pine Point NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Waubun 5 4 3 3 5 3 4 3 4 5 5 4 2 6 2 4 4 4 1 5 1

Note: for this table, just include the ranking for AI proficiency (highest is #1), CN proficiency (highest is #1), and gap (lowest is #1).

Table 7: Passing rates on state exams by grade level and ethnicity (math, 2007-08) Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 11 District %P %P G %P %P G %P %P G %P %P G %P %P G %P %P G %P %P G AI CN AI CN AI CN AI CN AI CN AI CN AI CN Detroit Lakes 82.4 90.6 8.29 71.4 79.5 8.06 83.3 76 -7.31 30 66.5 36.5 18.2 47.5 29.3 22.6 60.3 37.7 19.2 28.7 9.49 Fosston NA 96.6 NA NA 89.8 NA NA 73.1 NA NA 62.5 NA NA 56.9 NA NA 36.1 NA NA 34.2 NA Bagley 58.8 86.8 28 21.1 77.3 56.2 NA 47.2 NA 23.8 44.4 20.6 23.8 32.1 8.34 26.7 44.2 17.6 5.26 31 25.8 Mahnomen 70 86.7 16.7 39.4 NA NA 36 68.8 32.8 28.6 73.3 44.8 37.8 86.4 48.5 50 88.2 38.2 17.6 45.5 27.8 Naytahwaush 61.5 NA NA NA NA NA NA NA NA 45.5 NA NA NA NA NA NA NA NA NA NA NA Park Rapids NA 82.5 NA NA 81.8 NA 20 54 34 NA 61.2 NA NA 42.2 NA NA 61.4 NA NA 28.4 NA Pine Point NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Waubun 56.3 72.7 16.5 55.1 78.6 23.5 25.8 61.5 35.7 32.3 58.3 26.1 34.4 45.5 11.1 0 36.8 36.8 10.3 25 14.7

%P = Percent Proficient AI = American Indian CN = Caucasian G = gap (CN – AI)

Table 7: District rank, passing rates by grade level and ethnicity (math, 2007-08) Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 11 District AI CN G AI CN G AI CN G AI CN G AI CN G AI CN G AI CN G Detroit Lakes 1 2 1 1 3 1 1 1 1 3 2 3 4 3 3 3 3 3 1 4 1 Fosston NA 1 NA NA 1 NA NA 2 NA NA 3 NA NA 2 NA NA 6 NA NA 2 NA Bagley 4 3 4 4 5 3 NA 6 NA 5 6 1 3 6 1 2 4 1 4 3 3 Mahnomen 2 4 3 3 NA NA 2 3 2 4 1 4 1 1 4 1 1 4 2 1 4 Naytahwaush 3 NA NA NA NA NA NA NA NA 1 NA NA NA NA NA NA NA NA NA NA NA Park Rapids NA 5 NA NA 2 NA 4 5 3 NA 4 NA NA 5 NA NA 2 NA NA 5 NA Pine Point NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Waubun 5 6 2 2 4 2 3 4 4 2 5 2 2 4 2 4 5 2 3 6 2

Note: for this table, just include the ranking for AI proficiency (highest is #1), CN proficiency (highest is #1), and gap (lowest is #1). P a g e | 136

Table 9: Passing rates on state exams by grade level and ethnicity (reading, 2006-07) Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 10 District %P %P G %P %P G %P %P G %P %P G %P %P G %P %P G %P %P G AI CN AI CN AI CN AI CN AI CN AI CN AI CN Detroit Lakes 88.5 96.6 8.09 80 88.3 8.34 40 81.4 41.4 40 58.3 18.3 41.4 69.3 28 31 67.3 36.3 37 60.8 23.8 Fosston NA 85.4 NA NA 69.2 NA NA 81.5 NA NA 68 NA NA 45.9 NA NA 61.2 NA NA 53.7 NA Bagley 52.9 87.5 34.6 NA 70.4 NA 55.6 68.8 13.2 57.9 71.9 14 52.9 52.9 0 31.3 61 29.8 18.2 56.6 38.4 Mahnomen 52.4 78.3 25.9 39.1 83.3 44.2 51.6 72.2 20.6 62.1 72.2 10.2 28 63.6 35.6 45.7 47.4 1.65 32.4 56.3 23.8 Naytahwaush NA NA NA 20 NA NA 37.5 NA NA 20 NA NA NA NA NA NA NA NA NA NA NA Park Rapids 80 87.6 7.64 NA 87.4 NA NA 73.5 NA NA 67.3 NA NA 66.9 NA NA 63.4 NA NA 59 NA Pine Point NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Waubun 72.3 80 7.66 64.7 85.7 21 48.4 50 1.62 54.8 NA NA 20.7 72.2 51.5 22.7 53.3 30.6 37.5 56.3 18.8

%P = Percent Proficient AI = American Indian CN = Caucasian G = gap (CN – AI)

Table 10: District rank, passing rates by grade level and ethnicity (reading, 2006-07) Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 10 District AI CN G AI CN G AI CN G AI CN G AI CN G AI CN G AI CN G Detroit Lakes 1 1 3 1 1 1 4 2 4 4 5 3 2 2 2 3 1 4 2 1 2 Fosston NA 4 NA NA 6 NA NA 1 NA NA 3 NA NA 6 NA NA 3 NA NA 5 NA Bagley 4 3 5 NA 5 NA 1 5 2 2 2 2 1 5 1 2 4 3 4 3 4 Mahnomen 5 6 4 3 4 3 2 4 3 1 1 1 3 4 3 1 6 1 3 4 3 Naytahwaush NA NA NA 4 NA NA 5 NA NA 5 NA NA NA NA NA NA NA NA NA NA NA Park Rapids 2 2 1 NA 2 NA NA 3 NA NA 4 NA NA 3 NA NA 2 NA NA 2 NA Pine Point NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Waubun 3 5 2 2 3 2 3 6 1 3 NA NA 4 1 4 4 5 2 1 4 1

Note: for this table, just include the ranking for AI proficiency (highest is #1), CN proficiency (highest is #1), and gap (lowest is #1).

Table 11: Passing rates on state exams by grade level and ethnicity (math, 2006-07) Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 11 District %P %P G %P %P G %P %P G %P %P G %P %P G %P %P G %P %P G AI CN AI CN AI CN AI CN AI CN AI CN AI CN Detroit Lakes 65.4 94.5 29.1 80.8 82.2 1.44 65 75.2 10.2 25 65 40 37.9 60.1 22.2 31 56.8 25.8 22.7 35.4 12.7 Fosston NA 91.7 NA NA 69.2 NA NA 68.8 NA NA 68 NA NA 35.1 NA NA 44.9 NA NA 14.3 NA Bagley 70.6 91.7 21.1 NA 51.9 NA 31.6 59.4 27.8 15.8 43.9 28.1 17.6 51 33.3 12.5 45.5 33 20 21.5 1.53 Mahnomen 38.1 73.9 35.8 36.4 70.8 34.5 25.8 58.8 33 44.8 55.6 10.7 33.3 27.3 -6.06 29.7 52.6 22.9 0 24.1 24.1 Naytahwaush NA NA NA 50 NA NA 18.8 NA NA 10 NA NA NA NA NA NA NA NA NA NA NA Park Rapids 70 78.4 8.4 NA 88.5 NA NA 48.5 NA NA 63.4 NA NA 58.3 NA NA 49 NA NA 28.7 NA Pine Point NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Waubun 68.8 86.7 17.9 58.8 78.6 19.8 29 33.3 4.3 38.7 NA NA 13.8 77.8 64 18.2 40 21.8 7.69 5.26 -2.43

%P = Percent Proficient AI = American Indian CN = Caucasian G = gap (CN – AI) P a g e | 137

Table 12: District rank, passing rates by grade level and ethnicity (math, 2006-07) Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 11 District AI CN G AI CN G AI CN G AI CN G AI CN G AI CN G AI CN G Detroit Lakes 4 3 4 1 2 1 1 1 2 3 2 3 1 2 2 1 1 3 1 1 3 Fosston NA 1 NA NA 5 NA NA 2 NA NA 1 NA NA 5 NA NA 5 NA NA 5 NA Bagley 1 1 3 NA 6 NA 2 3 3 4 5 2 3 4 3 4 4 4 2 4 2 Mahnomen 5 6 5 4 4 3 4 4 4 1 4 1 2 6 1 2 2 2 4 3 4 Naytahwaush NA NA NA 3 NA NA 5 NA NA 10 NA NA NA NA NA NA NA NA NA NA NA Park Rapids 2 5 1 NA 1 NA NA 5 NA NA 3 NA NA 3 NA NA 3 NA NA 2 NA Pine Point NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA Waubun 3 4 2 2 3 2 3 6 1 2 NA NA 4 1 4 3 6 1 3 6 1

Note: for this table, just include the ranking for AI proficiency (highest is #1), CN proficiency (highest is #1), and gap (lowest is #1).

School District Achievement Data Analysis

Introduction

In the first round of our research, we examined state testing data from 9 school districts in

and around the White Earth Reservation in which American Indian students are enrolled. Our

review focused on three areas.

First, we analyzed trends in overall district passing rates for Caucasian and American

Indian students. Our analysis identified districts that seemed to be more successful in educating

one or both groups of students, as well as others that appeared less successful. Further analysis is

required to determine whether these differences are statistically significant, and this should be

undertaken during the second round of research. Pending this determination, differences in

district policy, resource allocation, teaching practices, and school culture should be investigated

to see if these are associated with gains or losses in achievement.

The second area of focus was environmental factors. School size, resources, and student

demographics have been shown to influence achievement patterns. There does appear to be a

potential connection between socioeconomic percentages of students and achievement. For P a g e | 138

example, Detroit Lakes has the lowest percentage of free and reduced lunch students and the highest levels of achievement. However, this issue needs further study to reach conclusions.

Comparison with statewide performance data was a third area of focus. Average passing rates for American Indian and Caucasian students, as well as the gap between passing rates for the two groups, were compared to statewide averages. While there is considerable variation among districts, overall Caucasian students performed more poorly in comparison to their statewide reference groups. Hence, the smaller gaps in achievement rates in some districts reflect convergence of the two groups toward lower standards rather than toward higher standards.

In addition to overall district passing rates, we also examined grade level passing rates for the districts. With data disaggregated by grade level, differences in district performance were more difficult to evaluate, in part because smaller numbers allow for more variability, and in part because two districts, Fosston and Park Rapids, did not report passing rates for American Indian students for most grade levels because of small cell size. Analysis of the available data, however, did suggest wider gaps and poorer performance at higher grade levels and in math when compared to reading. Further analysis in the second phase of the study will determine the level of significance of these patterns as well as the reasons behind them.

Overview of differences in district passing rate

State testing data from the 9 participating school districts generally confirmed that

American Indian achievement followed state and national patterns, with a large percentage of students not meeting standards and a significant gap in passing rates between American Indian and Caucasian students. The relevant percentages of passing rates for the past 3 years range from

6% (Fosston, reading, 2008-09) to 36% (Fosston, reading, 2007-08). The majority of gap P a g e | 139

percentages were in the high teens and low twenties. The full array of gap percentages for the three academic years 2006-2009 is shown in Table A*.

Table A*: The Achievement Gap, 2006-09* Differences in Passing Rates on State Exams, American Indian and Caucasian Students (%)† District 06-07 06-07 07-08 07-08 07-08 08-09 08-09 08-09 math reading math reading science math reading science Detroit Lakes 19 17 15 15 22 22 14 19 Fosston 19 15 28 36 34 6 28 26 Mahnomen 23 25 24 19 24 31 23 21 Naytahwaush NA NA NA NA NA NA NA NA Park Rapids 18 11 15 8 32 21 18 23 Pine Point NA NA NA NA NA NA NA NA Bagley 22 22 26 18 23 17 28 27 Waubun 13 16 19 20 12 16 18 21 Circle of Life NA NA NA NA NA NA NA NA

*There was no state test for science in 2006-07. Gaps are not listed for Pine Point, Naytahwaush, and Circle of Life since there were no Caucasian students enrolled in those schools. † Yellow-shaded cells have lower gaps (≤ 15%), cross-hatched cells higher gaps (≥ 25%).

Table A*: The Achievement Gap, 2006-09 Rankings of School Districts (#1 = lowest gap) ‡

District 06-07 06-07 07-08 07-08 07-08 08-09 08-09 08-09 math reading math reading science math reading science Detroit Lakes 3 4 1 2 2 5 1 1 Fosston 3 2 6 6 6 1 5 5 Mahnomen 6 6 4 4 4 6 4 2 Naytahwaush NA NA NA NA NA NA NA NA Park Rapids 2 1 1 1 5 4 3 4 Pine Point NA NA NA NA NA NA NA NA Bagley 5 5 5 3 3 3 5 6 Waubun 1 3 3 5 1 2 2 2 Circle of Life NA NA NA NA NA NA NA NA P a g e | 140

‡Yellow-shaded cells rank have lowest-ranking gaps (#1); cross-hatched cells have highest ranking gaps (#5 & #6).

Despite the persistence of achievement gaps between Caucasian and American Indian students, some districts did better than others in education for both groups, as is evident from the rankings in Tables B*, C*, and D*. Detroit Lakes scored consistently at or near the top of the rankings for all three years, while Circle of Life and Bagley ranked consistently in the lower half.

Waubun ranked in the lower half in all categories except American Indian scores for reading in

2006-07, when it ranked fourth of the nine districts. One district, Mahnomen, consistently improved its performance relative to other districts throughout the time period. Fosston, Park

Rapids, Pine Point, and Naytahwaush fluctuated, doing well in some years and subject areas and poorly in others.

These rankings suggest that further study is needed in several areas. What factors contribute to the relatively low performance of Waubun and Bagley, and conversely what factors explain the high performance of Detroit Lakes? In this preliminary report we consider such factors as demographics and district resources, but these turn out not to be clearly correlated with differences in achievement. From this analysis we conclude that a more fine-grained analysis of school operations is needed. Factors that might be investigated include curriculum (whether or not it is culturally relevant and whether or not it is aligned or not aligned with state standards); teacher professional development (whether it is sustained, focused, and integrated with school- wide efforts to improve student achievement); teacher evaluation; and administrator selection. In the case of Pine Point, Mahnomen, and Fosston, similar questions might be asked about the disparities in performance across subject areas.

District performance rankings for Caucasian students were generally similar to performance rankings for American Indian students. Detroit Lakes ranked high across subject P a g e | 141

areas for both groups; Waubun and Bagley ranked low across subject areas. This pattern suggests that the factors accounting for quality in these districts affected American Indian and Caucasian student performance in similar ways. The pattern is generally confirmed in gap percentages and rankings: gaps in Waubun and Detroit Lakes tended to be lower than some of the other districts.

Bagley, however, showed relatively high gaps, despite the low performance for both groups, as did Fosston and, to a lesser extent, Mahnomen, indicating that American Indian and Caucasian groups were differentially affected by whatever strategies were being employed in those districts.

Mahnomen, however, was distinguished by the fact that passing percentages for both groups improved each year in all subject areas, indicating that a relatively high and persistent gap should not necessarily lead us to conclude that the district is not making progress across populations.

Factors contributing to improvement in Mahnomen should be investigated in Phase 2 of the study.

No clear contrast emerged from comparison of district performance across subject areas.

In general, reading scores were higher than those for mathematics, but there is no way to compare the difficulty level of the two testing programs, and hence we cannot determine whether districts are more effective in teaching reading or the mathematics tests themselves are more challenging. Science scores were the lowest of all, ranging from 19-37 points below math scores in 2007-08; since this was the first year the test was given, however, it is reasonable to assume that teachers will adjust curriculum to expectations on the test, and that the gap between the subject areas will gradually decrease in future years. Achievement of American Indian students in science is particularly low, with fewer than one in 11 students passing the initial test administration in Bagley (6%), Park Rapids (6%), Mahnomen (7%) and Park Rapids (9%), and fewer than one in 9 students passing in 2008-09 in Park Rapids (10%), Bagley (11%), and P a g e | 142

Waubun (11%). The highest percentage passing in any district in these two years was 25%

(Fosston, 2008-09). Clearly this science is an area in which improvement in instruction for

American Indian students is urgently needed.

Table B*: School District Rankings, % Proficient on State Exams, 2006-09 Mathematics

District 06-07 06-07 07-08 07-08 08-0\9 08-09 American Caucasian American Caucasian American Caucasian Indian Indian Indian Detroit Lakes 1 1 2 2 2 2 Fosston 4 2 6 1 1 2 Mahnomen 7 4 5 3 3 1 Naytahwaush 9 NA 1 NA 5 NA Park Rapids 3 3 4 4 6 4 Pine Point 2 NA 3 NA 4 NA Bagley 8 6 8 6 8 5 Waubun 5 5 7 5 7 6 Circle of Life 6 NA 9 NA 9 NA

P a g e | 143

Table C*: School District Rankings, % Proficient on State Exams, 2006-09 Reading

District 06-07 06-07 07-08 07-08 08-0\9 08-09 American Caucasian American Caucasian American Caucasian Indian Indian Indian Detroit Lakes 3 1 3 1 1 2 Fosston 2 4 9 4 4 2 Mahnomen 5 3 4 3 2 1 Naytahwaush 9 NA 1 NA 6 NA Park Rapids 1 2 1 2 3 5 Pine Point 7 NA 6 NA 8 NA Bagley 5 5 7 6 5 4 Waubun 4 6 5 5 7 6 Circle of Life 8 NA 8 NA 9 NA

Table D*: School District Rankings, % Proficient on State Exams, 2006-09 Science*

District 06-07 06-07 07-08 07-08 08-0\9 08-09 American Caucasian American Caucasian American Caucasian Indian Indian Indian Detroit Lakes NA NA 1 1 3 2 Fosston NA NA 3 2 1 1 Mahnomen NA NA 5 4 2 3 Naytahwaush NA NA NA NA NA NA Park Rapids NA NA 6 3 6 5 Pine Point NA NA 3 NA NA NA Bagley NA NA 6 5 4 4 Waubun NA NA 2 6 4 6 Circle of Life NA NA NA NA NA NA

*The state science test was not administered in 2006-07. P a g e | 144

Environmental factors affecting student achievement

One set of factors that can affect student achievement are the size and demographic composition of the district, but as shown in Table E, there seems to be no consistent pattern linking demographic data and achievement for these districts. The proportion of American Indian students ranged from 6% (Fosston and Park Rapids) to 100% (Pine Point and Circle of Life). The concentration of these students potentially impacts academic achievement. The proportion of students from low socioeconomic status (SES) also varied widely, from 37% (Detroit Lakes) to

100% (Circle of Life). SES appeared to have a potential impact on academic achievement. The highest-achieving district (Detroit Lakes) had the lowest % of low-SES students, and districts with the highest low-SES representation (COL, WOWE, Naytahwaush, and Pine Point) tended to show lower achievement. The only clear correlation was between American Indian ethnicity and poverty. A high percentage of families living in poverty predicted a high percentage of American

Indian students. Only for Park Rapids did these two factors diverge dramatically: despite a very low (6%) proportion of American Indian families, a relatively high percentage of families (46%) qualified for free and reduced lunches.

P a g e | 145

Table E: District Size and Demographic Composition

District ranking ranking total # % % low % IEP American Caucasian of American SES Indian achievement students Indian achievement Detroit Lakes high high 2697 13 34 18 Fosston mixed mixed 658 6 13 13 Mahnomen improving improving 609 68 71 19 Pine Point mixed N/A 78 100 95 30 Naytahwaush mixed N/A 86 99 94 26 Park Rapids medium mixed 1502 6 46 21 Bagley low low 976 22 50 17 Waubun low low 611 71 60 16 Circle of Life low N/A 129 100 100 28*

* Circle of Life data are for 2007-08; for the other districts, 2008-09 data are reported.

A second set of factors known to affect student achievement is the district‘s level of resources, including per-pupil expenditure, teacher salary, and teachers‘ experience and educational background. Here again, there is no clear correlation between these factors and student achievement. The wide disparity in per-pupil expenditure (see Table E), ranging from

$6500 (Circle of Life) to $21,465 (Pine Point), does not appear to be related to student achievement. Detroit Lakes, the highest-performing district, has the second-lowest level of expenditure ($8331), while one of the lowest-performing districts, Waubun, has the second- highest per-pupil expenditure ($11,445). Differences in expenditure are more likely to reflect economies of scale, since administrative overhead is spread out over a larger student population: the two largest districts have among the lowest per-pupil expenditure (Detroit Lakes, 2697 students, $8331; Park Rapids, 1502 students, $9070), while the smallest school spends the most P a g e | 146

per pupil (Pine Point, 78 students, $21,465). Between these extremes, however, the pattern is less evident; so there is at best a modest correlation between size and per-pupil expenditure.

There were also no clear correlations between student achievement, on the one hand, and teacher salary, educational level, or experience on the other (see Table F). The proportion of teachers with master‘s degrees ranged from 0% (Naytahwaush and Waubun) and 49% (Park

Rapids). Both Naytahwaush and Park Rapids had mixed records student achievement.

Meanwhile, the top-achieving district (Detroit Lakes) and the district with the strongest record of improvement (Mahnomen) both reported proportions of master‘s-prepared teachers midway between these extremes or lower (26% and 14% respectively). Similarly, the top-performing districts (Detroit Lakes) reported an average teacher salary below the median of $43,522, while two of the three lowest-performing districts (Bagley and Waubun) reported average salaries above the median. The same was true for teacher experience. All but two of the districts reported fewer than 10% of their teaching staff had three years‘ experience or less. Two of the three lowest-performing districts (Bagley and Waubun) reported some of the lowest proportions of inexperienced teachers (2% and 0% respectively). These data show that the causes of disparate achievement rates among the 9 districts must be sought elsewhere.

P a g e | 147

Table F: District Resources as related to student achievement

District ranking ranking per-pupil % of avg. % of American Caucasian expenditure teachers teacher teachers, 0- Indian achievement with salary 3 yr. achievement master‘s experience Detroit Lakes high high 8331 26 43,336 3 Fosston mixed mixed 9253 26 40,516 5 Mahnomen improving improving 11,083 14 47,161 7 Pine Point mixed N/A 21,465 7 43,522 0 Naytahwaush mixed N/A 10,246 0 36, 161 59 Park Rapids medium mixed 9070 49 44,758 4 Bagley low low 9531 33 46,952 2 Waubun low low 11,445 0 45,144 0 Circle of Life low N/A 6500 10 37,000 25

One common concern related to educational equity is overrepresentation of minority or low-SES students in Special Education programs. State report card data do not allow us to identify which students are given individualized education plans (IEP‘s), and hence we cannot determine whether American Indian students within the district are disproportionately labeled as having a disability. However, between districts, there is a moderate correlation between the proportion of American Indian students and the proportion of students on IEP‘s. Pine Point,

Circle of Life, and Naytahwaush have the highest proportion of American Indian students

(100%, 100%, and 99%) and the highest rate of Special Education referrals (30%, 28%, and

26%); Fosston has the lowest in each category (6% American Indian students, 13% IEP referrals). The correlation is not as clear, however, in the remaining districts. Furthermore, there is no observable correlation between IEP rates and achievement. The two of three districts with P a g e | 148

the lowest achievement, Waubun and Bagley, have the slightly lower rates of IEP referrals (16% and 17% respectively) and higher-achieving districts, such as Detroit Lakes (18%) and

Mahnomen (19%). Clearly, more investigation is needed to determine whether American Indian students are overrepresented in special education within districts, and if so whether this has an impact on achievement rates.

Comparison with statewide averages

As shown in Table F, students in these districts did better in reading than in mathematics compared to similar students statewide. In reading, American Indian students in only one district fell significantly below the statewide average (> 10%); Caucasian students also did so in only one district. By contrast, in mathematics (see Table G), American Indian students in two districts fell significantly below the state average, while Caucasian students in three districts did so.

Achievement gaps tended to be smaller for these districts than for the state: in math, only

Mahnomen had a slightly larger achievement gap, while in reading, Fosston and Bagley showed a discrepancy in passing rates larger than the statewide averages. For all other districts, the gap was smaller. It appears, then, that the relative disadvantage of American Indian students in these districts is smaller in part because the overall achievement in these districts is lower.

This is not an encouraging picture, but there are some bright spots. Detroit Lakes,

Fosston, and Mahnomen have approached or exceeded statewide achievement averages for both groups of students in 2008-09. Waubun, Bagley, and Circle of Life, however, performed poorly, in comparison with the state, and Pine Point fell significantly below the statewide average for

American Indian students in math. Clearly, these four districts face significant challenges in improving the achievement of all students in the coming years, and it is hoped that the next phase of research can identify promising initiatives in this area. P a g e | 149

Table G: Comparison with Statewide Averages, 2006-07 Math and Reading District math math math reading reading reading (American (Caucasian) gap (American (Caucasian) gap Indian) Indian) Statewide 36.35 64.7 28.35 46.49 74.71 28.22 Detroit 47.09 66.04 18.95 51.13 73.62 22.49 Lakes Fosston 39.28 57.66 18.38 51.72 67.38 15.66 Mahnomen 28.71 52.48 23.77 44.27 68.99 24.72 Naytahwaush 22.91 NA ####### 25 NA ####### Park Rapids 40 57.55 17.55 60.41 71.38 10.97 Pine Point 40.62 NA ####### 36.66 NA ####### Bagley 28.15 50.48 22.33 43.85 66.34 22.49 Waubun 38 50.98 12.98 48.71 64.64 15.93 Circle of Life

Table G: Comparison with Statewide Averages, 2007-08 Math and Reading District math math math reading reading reading (American (Caucasian) (American (Caucasian) Indian) gap Indian) gap Statewide 38 66.82 28.82 50.71 77.41 26.7 Detroit 47.75 62.84 15.09 63.53 79.18 15.65 Lakes Fosston 36 64.35 28.35 34.78 70.68 35.9 Mahnomen 37.43 61.53 24.1 53.5 72.8 19.3 Naytahwaush 57.57 NA ####### 66.66 NA ####### Park Rapids 42.85 58.42 15.57 67.3 75.45 8.15 Pine Point 44.44 NA ####### 48.57 NA ####### Bagley 25.21 50.65 25.44 48.21 65.5 17.29 Waubun 33.18 52.08 18.9 50 70.32 20.32 Circle of Life

P a g e | 150

Table G: Comparison with Statewide Averages, 2008-09 Math and Reading

District math math math reading reading reading (American (Caucasian) gap (American (Caucasian) gap Indian) Indian) Statewide 44 73 29 53 78 25 Detroit Lakes 46 68 22 64 78 14 Fosston 54 68 14 50 78 28 Mahnomen 42 73 31 57 80 23 Naytahwaush 41 N/A N/A 47 N/A N/A Park Rapids 40 61 21 53 71 18 Pine Point 41 N/A N/A 36 N/A N/A Bagley 33 56 23 48 76 28 Waubun 36 52 15 45 63 18 Circle of Life 12 N/A N/A 28 N/A N/A

Comparisons of grade-level passing rates

Passing rates were disaggregated by grade level in reading and mathematics for the

three years of available data (2006-07, 2007-08, and 2008-09). The results are summarized in

Table A. Unfortunately, passing rates for American Indian students were not reported by

Fosston and Park Rapids, most likely because of small cell size. This complicated the

comparison of performance among districts. Thus our preliminary analysis of grade level

data focuses on comparisons of performance by subject area and by grade level.

Three trends emerge from our preliminary analysis. First, passing rates on reading

have tended to increase over the three years of data, both for Caucasian and for American

Indian students. The total number of instances in which a grade level group passing rate fell

below 40% in the reporting districts declined from 14 to 5 for reading and from 30 to 23 in P a g e | 151

mathematics over this period, while the number of instances in which grade-level group assign rates equaled or exceeded 70% rose from 22 to 32 in reading and from 15 to 17 in mathematics. This trend, however, must be approached with caution, since the absolute numbers of students tested vary among districts, grade levels, and ethnic groups. Statistical tests will be required to confirm the trend. Based on the initial analysis, however, it appears that teachers have been more successful in teaching the skills tested on state assessments over this period.

The second trend observed was that students were more likely to meet standards in lower grades than in higher grades. Grade-level group passing rates equaled or exceeded 70%

57 times in grades 3, 4, and 5, and only 21 times in grades 7, 8 and 10; comparable figures for mathematics were 50 in lower grades versus only 4 in upper grades. Conversely, grade- level group passing rates in reading equaled or fell below 40% only 3 times in grades 3, 4, and 5, compared to 17 times in upper grades; for mathematics, the comparable figures were

19 in lower grades versus 50 in higher grades. This trend is consistent with statewide data, showing a steady decline in pass rates with advancing grade levels, a pattern reflected in all three years of data and both subject areas.

Another trend emerging from this data involved differential passing rates for the two subject areas. Passing rates rose more for reading than they did for math; overall passing rates were higher for reading than for math; and student success was more evenly apportioned across grade levels in reading than in mathematics, though the negative correlation between passing rate and grade level was discernible in both areas. This trend, too, was reflected in state data; it may reflect the relative perceived difficulty of mathematics as a subject area, the greater difficulty in attracting qualified teachers to the profession, or P a g e | 152

greater lag time in adjustment of curriculum, textbooks, and teaching methods to state

standards.

Finally, larger gaps appeared to be concentrated between grades 5-8, with narrower

gaps observed in grades 3, 4, 10, and 11. This is consistent with statewide data, which shows

gaps in average passing rates gradually increasing over grades 3 through 8, then dropping off

slightly in grades 10 and 11. The increase may be due to the accumulation and compounding

of educational disadvantage as students get older, followed by a selection effect as more

Native American students are held back or leave school early by grades 10 and 11. Further

research in Phase II of the project will be needed to investigate the significance of this trend.

Table H: Trends in Gap Size vs. Grade Level, reading (≥ 25%)*

Grade 3 4 5 6 7 8 10

2006-07 2 1 1 0 3 3 1

2007-08 0 1 2 3 1 2 1

2008-09 1 0 3 1 1 0 2

*Tables H-I report the number of instances in which the gap between passing rates for American Indian and Caucasian

students equals or exceeds 25% at the listed grade level for districts included in the survey.

Table I: Trends in Gap Size vs. Grade Level, mathematics (≥ 25%)

Grade 3 4 5 6 7 8 11

2006-07 2 1 2 2 1 2 0

2007-08 0 1 2 3 2 3 2

2008-09 0 0 2 2 3 3 1

P a g e | 153

Table J: Trends in Passing Rates vs. Grade Level, reading (≥ 70%)*

Grade 3 4 5 6 7 8 10

2006-07 9 6 4 2 1 0 0

2007-08 10 5 8 4 1 3 5

2008-09 8 4 3 6 3 2 6

*Tables J-M report the number of instances the passing rate for American Indian students or for Caucasian students at a specific grade level fall within the listed range for districts included in the survey.

Table K: Trends in Passing Rates vs. Grade Level, math (≥ 70%)

Grade 3 4 5 6 7 8 11

2006-07 8 5 1 0 1 0 0

2007-08 9 7 4 1 1 0 0

2008-09 8 4 3 1 0 1 0

Table L: Trends in Passing Rates vs. Grade Level, reading (≤ 40%)

Grade 3 4 5 6 7 8 11

2006-07 0 2 1 2 2 3 4

2007-08 0 0 0 2 1 1 1

2008-09 0 0 0 0 2 1 2

Table M: Trends in Passing Rates vs. Grade Level, math (≤ 40%)

Grade 3 4 5 6 7 8 10

2006-07 1 1 5 4 6 5 8

2007-08 0 0 2 3 4 2 9

2008-09 0 2 3 2 4 6 6 P a g e | 154

Individual School District Statistics

Bagley

Attendance.

Bagley Elementary Indian Attendance 2006-09 100.0 95.0 90.0 85.0 80.0 75.0 M F M F M F M F M F M F M F KG 1 2 3 4 5 6 2006-07 90.7 81.4 89.8 90.7 91.6 89.3 93.9 90.3 86.5 92.2 89.1 93.1 92.8 94.0 2007-08 93.4 87.5 93.3 92.7 90.5 94.0 91.8 92.0 96.1 93.6 89.2 91.2 90.1 94.4 2008-09 91.7 96.7 93.0 93.2 94.1 93.0 93.7 93.3 92.3 93.3 92.9 93.1 89.8 92.5

Bagley Elementary White Attendance 2006-09 100.0 95.0 90.0 85.0 80.0 75.0 M F M F M F M F M F M F M F KG 1 2 3 4 5 6 2006-07 95.2 95.0 95.2 94.5 94.8 94.5 95.7 95.3 95.7 95.4 93.2 94.8 94.2 95.8 2007-08 95.7 93.9 94.7 96.1 95.8 95.5 95.3 91.8 96.0 97.1 96.3 95.9 95.0 94.2 2008-09 95.0 94.5 93.6 94.0 95.5 95.0 96.2 94.8 95.5 93.3 96.2 95.8 95.4 95.4

P a g e | 155

Bagley High School White Attendance 2005-09 100.0

95.0

90.0

85.0

80.0

75.0 M F M F M F M F M F M F 7 8 9 10 11 12 % 05-06 95.8 95.2 95.1 94.8 95.9 94.6 93.9 94.7 92.2 92.4 90.6 91.1 % 06-07 95.3 96.1 95.4 94.4 94.1 94.3 92.2 94.2 94.5 93.0 93.0 94.2 % 07-08 93.9 95.5 94.1 94.7 92.6 94.3 95.2 94.5 92.0 91.2 93.1 93.1 % 08-09 94.8 94.8 93.6 93.6 94.3 93.0 94.7 94.0 93.5 92.1 91.4 92.4

Bagley High School Indian Attendance 2005-09 100.0

95.0

90.0

85.0

80.0

75.0 M F M F M F M F M F M F 7 8 9 10 11 12 % 05-06 91.1 92.5 85.0 93.4 90.3 92.4 89.8 88.1 91.0 90.5 88.5 87.0 % 06-07 94.2 88.9 91.4 85.9 84.2 87.0 91.1 91.4 83.7 88.7 94.8 87.3 % 07-08 93.2 96.0 92.6 88.2 88.9 84.9 87.6 84.8 92.3 90.9 87.5 91.8 % 08-09 89.1 94.3 92.0 95.1 88.7 83.9 85.3 77.1 85.1 84.7 92.3 90.0

P a g e | 156

Behavior.

Bagley Elementary Discipline 2006-07 120 100 80 60 40 20

# ofincidents # 0 Fighting Disruptive/ Swearing/ Bullying/ Theft/ Physical Disorderly Verbal Harassment Total Vandalism Assault Conduct Abuse / Threats 2006-07 Caucasian M 30 12 3 6 0 51 2006-07 Caucasian F 3 1 1 0 2 7 2006-07 Indian M 14 7 3 6 1 31 2006-07 Indian F 2 5 0 1 0 8 2006-07 Total All 49 25 7 13 3 97

Bagley Elementary Discipline 2007-08 90 80 70 60 50 40 30 20 10 0 # ofincidents # Fighting Disruptive/ Swearing/ Bullying/ Theft/ Physical Disorderly Verbal Harassment Total Vandalism Assault Conduct Abuse / Threats 2007-08 Caucasian M 23 13 3 2 1 42 2007-08 Caucasian F 6 0 0 0 1 7 2007-08 Indian M 13 8 6 4 2 33 2007-08 Indian F 0 1 0 0 0 1 2007-08 Total All 42 22 9 6 4 83

P a g e | 157

Bagley Elementary Discipline 2008-09 60 50 40 30 20 10 # ofincidents # 0 Fighting Disruptive/ Swearing/ Bullying/ Theft/ Physical Disorderly Verbal Harassment Total Vandalism Assault Conduct Abuse / Threats 2008-09 Caucasian M 22 6 3 2 0 33 2008-09 Caucasian F 2 0 1 0 0 3 2008-09 Indian M 12 4 2 0 0 18 2008-09 Indian F 1 0 0 0 0 1 2008-09 Total All 37 10 6 2 0 55

Bagley High Discipline 2006-2007 140 120 100 80 60 40 20

# ofincidents # 0 Bullying/ Drug/ Fighting Disruptive Swearing/ Insubordi Harassme Theft/ Alcohol/ Physical /Disorderl Verbal Weapon nation nt/Threat Vandalism Tobacco Assult y Conduct Abuse s Caucasian M 6 5 92 116 4 0 8 0 Caucasian F 5 1 28 20 3 2 0 0 Indian M 4 7 72 82 1 3 3 0 Indian F 5 4 39 22 4 1 3 0

P a g e | 158

Bagley High Discipline 2007-2008 40 35 30 25 20 15

10 #of incidents #of 5 0 Drug/ Fighting Disruptive Swearing/ Bullying/ Insubordi Theft/ Alcohol/ Physical /Disorderl Verbal Harassme Weapon nation Vandalism Tobacco Assult y Conduct Abuse nt/Threats Caucasian M 3 7 7 36 4 0 0 0 Caucasian F 0 3 3 7 3 0 0 0 Indian M 1 5 1 15 0 0 0 0 Indian F 0 5 3 5 3 0 0 0

Bagley High Discipline 2008-2009 60 50 40 30 20 10 # ofincidents # 0 Drug/ Fighting Disruptive Swearing/ Bullying/ Insubordin Theft/ Alcohol/ Physical /Disorderl Verbal Harassme Weapon ation Vandalism Tobacco Assult y Conduct Abuse nt/Threats Caucasian M 2 6 0 51 10 1 4 1 Caucasian F 1 2 0 12 0 0 0 0 Indian M 6 5 4 22 8 0 0 1 Indian F 0 6 3 7 2 0 8 0

Attendance—high school

Over four years, attendance in all groups seems to fluctuate to some degree, but the average pattern indicates that attendance for white children is higher than it is for American

Indian children. Moreover, there seems to be a decline in attendance at the secondary level. Of particular concern is the attendance for American Indian females at the secondary level. P a g e | 159

American Indian female attendance is lower than Caucasian female attendance in all grades. For example, in 2008-09, American Indian female attendance in grade 7 was 94.3 percent in Grade 7,

95.1 percent in grade 8, 83.9 percent in grade 9, 77.1 percent in grade 10, 84.7 percent in grade

11, and 90 percent in grade 12. During the same year, attendance for Caucasian females was 94.8 percent in grade 7, 93.6 percent in grade 8, 93 percent in grade 9, 94 percent in grade 10, 92.1 percent in grade 11, and 92.4 percent in grade 12. Since there is reasonable likelihood that missing school compromises academic achievement, there should be effort to increase American

Indian female attendance. In Phase II of the study, this area will be examined to ascertain the reasons why attendance is lower for American Indian females in the secondary than for

Caucasian females.

Attendance—elementary school

The attendance rates seem to fluctuate depending on grade and gender. However, the average difference between attendance rates of White and Indian students decreased from 2006-

07 to 2008-09. In 2006-07 the difference is 4.6%, in 2007-08 it is 3.1%, and in 2008-09 it is

2.0%.

The average differences between the attendance of male and female students in the same grade and of the same race shows an interesting pattern. From 2006-07 to 2008-09 male

American Indian students attended 0.5% more, then 0.2% less, and then 1.1% less than their female American Indian counterparts. From 2006-07 to 2008-09 White male students attended

0.2% less, then 0.6% more, and then 0.7% more than their White female counterparts.

Discipline

At the high school, there was a general decrease in overall discipline categories from 439 in

04-05 to 162 in 08-09 (439, 695, 540, 111, and 162, respectively). Offenses were as follows: P a g e | 160

Drug/Alcohol/Tobacco offenses went from 4 in 04-05 to 26 in 05-06, 20 in 06-07, back

to 4 in 07-08, and then up again to 9 in 08-09. Overall males had a higher proportion of

drug/tobacco/alcohol offenses than females, but there was no significant pattern that

emerged relating to Caucasian and American Indian students.

Fighting/physical assault offenses went from 26 in 04-05 to 36 in 05-06, 17 in 06-07, 20

in 07-08, and then to 19 in 08-09. There was no significant pattern regarding race or

gender in this category.

Insubordination decreased significantly from 172 in 04-05 to 7 in 08-09. There was no

significant pattern involving race or gender in this category.

Disruptive/disorderly conduct went from 202 in 04-05 to 319 in 05-06, 240 in 06-07,

down to 63 in 07-08, and then up to 92 in 08-09. There was no significant pattern in

regard to ethnicity and gender.

Bullying/Harassment/Threats also decreased from 10 in 04-05 to 1 in 08-09. There was

no significant pattern in regard to ethnicity and gender.

Theft/Vandalism offenses went from 8 in 04-05 to 16 in 05-06, 14 in 06-07, 0 in 07-08,

and then to 12 in 08-09. American Indian females had a disproportionate percentage of

violations in this category.

At the elementary school, there has been a general decrease in offenses from 97 in 2006-

07 to 83 in 2007-08 to 55 in 2008-09. This includes fighting/physical assault (totals of 49,

42, 37 offenses in each group over these 3 years) as well as disruptive/disorderly conduct

(totals of 25, 22, and 10 offenses in each group over these 3 years) and bullying/harassment

(totals of 13, 6, and 2 offenses in each group over these 3 years). P a g e | 161

One area of concern regarding discipline involves the disproportionate percentage of

American Indian children who are tagged with disciplinary violations. Although only 22

percent of the total student population is American Indian, 39 percent of the violations at the

elementary school and 38 percent of the violations at the high school are committed by

American Indian children. Since disciplinary violations can lead to suspensions and other

missed class time, there is a possible connection to the underachievement of American

Indian children. In Phase II of this study, researchers will examine the underlying causes of

the disciplinary violations, whether the violations are contributing to underachievement, and

possible remedies.

Bagley Minnesota student survey data

6th grade 9th grade 12th grade Male Female Male Female Male Female Frequent Binge Drinking Last Year 0 0 9 4 38 21 Used only alcohol in the past year 15 30 27 52 45 33 Used both alcohol and marijuana in the last year 3 0 18 16 35 29 0 days 100 100 87 93 76 88 1 or 2 days 0 0 4 3 10 4 During the last 30 days, 3 to 5 days 0 0 0 0 14 4 how many days did you use marijuana or hashish? 6 to 9 days 0 0 0 3 0 4 10 to 19 days 0 0 4 0 0 0 All 30 days 0 0 4 0 0 0 0 100 100 83 90 67 76 During the last year, on 1-2 0 0 9 3 10 12 how many occasions have 3-5 0 0 0 3 14 4 you used marijuana or 6-9 0 0 0 0 5 4 hashish? 10-39 0 0 0 3 5 4 40+ 0 0 9 0 0 0 During the last year, on 0 100 100 87 95 95 96 how many occasions have 1-2 0 0 4 0 0 4 you sniffed glue or used 3-5 0 0 9 0 5 0 P a g e | 162

other solvents to get high? 6-9 0 0 0 5 0 0 During the last year, on 0 86 100 95 96 how many occasions have 1-2 9 0 0 0 you used LSD or other 3-5 0 0 5 0 psychadelics? 6-9 5 0 0 0 During the last year, on how 0 91 100 95 100 many occasions have you used "crack"? 1-2 9 0 5 0

An analysis of the student survey data would indicate concern regarding drug and alcohol usage. Binge drinking among twelfth grade students is of particular concern, as 38 percent of males and 21 percent of females report frequent binge drinking. In phase II of this study, researchers will attempt to determine whether school attendance and academic achievement are impacted by drug and alcohol usage and whether usage is more prevalent among the American

Indian population.

Bagley elementary percentiles by year, grade, and subject

Spring 2006

Grade 2 Bagley Language Percentiles Spring 2006 (N = 62) 1-10 11-30 31-50 51-75 76-100 number 9 8 11 17 17 percent 15% 13% 18% 27% 27%

Grade 2 Bagley Math Percentiles Spring 2006 (N = 64) 1-10 11-30 31-50 51-75 76-100 number 15 10 12 13 14 percent 23% 16% 19% 20% 22%

Grade 2 Bagley Reading Percentiles Spring 2006 (N = 63) 1-10 11-30 31-50 51-75 76-100 number 11 6 10 14 22 percent 17% 10% 16% 22% 35% P a g e | 163

Grade 3 Bagley Language Percentiles Spring 2006 (N = 65) 1-10 11-30 31-50 51-75 76-100 number 15 17 13 10 10 percent 23% 26% 20% 15% 15%

Grade 3 Bagley Math Percentiles Spring 2006 (N = 65) 1-10 11-30 31-50 51-75 76-100 number 9 12 13 14 17 percent 14% 18% 20% 22% 26%

Grade 3 Bagley Reading Percentiles Spring 2006 (N = 65) 1-10 11-30 31-50 51-75 76-100 number 11 11 13 15 15 percent 17% 17% 20% 23% 23%

Grade 4 Bagley Language Percentiles Spring 2006 (N = 85) 1-10 11-30 31-50 51-75 76-100 number 8 20 13 29 15 percent 9% 24% 15% 34% 18%

Grade 4 Bagley Math Percentiles Spring 2006 (N = 85) 1-10 11-30 31-50 51-75 76-100 number 5 15 16 23 26 percent 6% 18% 19% 27% 31%

Grade 4 Bagley Reading Percentiles Spring 2006 (N = 85) 1-10 11-30 31-50 51-75 76-100 number 5 11 24 20 15 percent 6% 13% 28% 24% 18%

Grade 5 Bagley Language Percentiles Spring 2006 (N = 76) 1-10 11-30 31-50 51-75 76-100 number 9 23 19 14 11 percent 12% 30% 25% 18% 14%

P a g e | 164

Grade 5 Bagley Math Percentiles Spring 2006 (N = 77) 1-10 11-30 31-50 51-75 76-100 number 7 19 21 11 19 percent 9% 25% 27% 14% 25%

Grade 5 Bagley Reading Percentiles Spring 2006 (N = 77) 1-10 11-30 31-50 51-75 76-100 number 8 18 12 25 14 percent 10% 23% 16% 32% 18%

Grade 6 Bagley Language Percentiles Spring 2006 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 10 14 14 21 11 percent 14% 20% 20% 30% 16%

Grade 6 Bagley Math Percentiles Spring 2006 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 8 6 13 22 21 percent 11% 9% 19% 31% 30%

Grade 6 Bagley Reading Percentiles Spring 2006 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 8 14 16 23 9 percent 11% 20% 23% 33% 13%

Fall 2006

Grade 2 Bagley Language Percentiles Fall 2006 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 26 15 9 14 7 percent 37% 21% 13% 20% 10%

Grade 3 Bagley Math Percentiles Fall 2006 (N = 62) 1-10 11-30 31-50 51-75 76-100 number 8 14 13 11 15 percent 13% 23% 21% 18% 24%

P a g e | 165

Grade 3 Bagley Reading Percentiles Fall 2006 (N = 61) 1-10 11-30 31-50 51-75 76-100 number 8 14 13 11 15 percent 13% 23% 21% 18% 25%

Grade 4 Bagley Language Percentiles Fall 2006 (N = 64) 1-10 11-30 31-50 51-75 76-100 number 12 19 15 8 10 percent 19% 30% 23% 13% 16%

Grade 4 Bagley Math Percentiles Fall 2006 (N = 64) 1-10 11-30 31-50 51-75 76-100 number 13 16 14 12 9 percent 20% 25% 22% 19% 14%

Grade 4 Bagley Reading Percentiles Fall 2006 (N = 64) 1-10 11-30 31-50 51-75 76-100 number 10 16 11 18 9 percent 16% 25% 17% 28% 14%

Grade 5 Bagley Language Percentiles Fall 2006 (N = 86) 1-10 11-30 31-50 51-75 76-100 number 9 21 18 25 13 percent 10% 24% 21% 29% 15%

Grade 5 Bagley Math Percentiles Fall 2006 (N = 86) 1-10 11-30 31-50 51-75 76-100 number 3 18 21 27 17 percent 3% 21% 24% 31% 20%

Grade 5 Bagley Reading Percentiles Fall 2006 (N = 86) 1-10 11-30 31-50 51-75 76-100 number 11 12 16 27 20 percent 13% 14% 19% 31% 23%

P a g e | 166

Grade 6 Bagley Language Percentiles Fall 2006 (N = 79) 1-10 11-30 31-50 51-75 76-100 number 10 17 22 22 8 percent 13% 22% 28% 28% 10%

Grade 6 Bagley Math Percentiles Fall 2006 (N = 78) 1-10 11-30 31-50 51-75 76-100 number 6 20 22 16 14 percent 8% 26% 28% 21% 18%

Grade 6 Bagley Reading Percentiles Fall 2006 (N = 80) 1-10 11-30 31-50 51-75 76-100 number 8 17 21 26 8 percent 10% 22% 27% 33% 10%

Spring 2007

Grade 6 Bagley Math Percentiles Spring 2007 (N = 78) 1-10 11-30 31-50 51-75 76-100 number 8 13 22 20 15 percent 10% 17% 28% 26% 19%

Grade 6 Bagley Reading Percentiles Spring 2007 (N = 75) 1-10 11-30 31-50 51-75 76-100 number 6 27 24 11 7 percent 8% 36% 32% 15% 9%

Spring 2008

Grade 6 Bagley Math Percentiles Spring 2008 (N = 89) 1-10 11-30 31-50 51-75 76-100 number 7 16 21 34 11 percent 8% 18% 24% 38% 12%

Grade 6 Bagley Reading Percentiles Spring 2008 (N = 89) 1-10 11-30 31-50 51-75 76-100 number 7 19 19 25 19 percent 8% 21% 21% 28% 21% P a g e | 167

Spring 2009

Grade 6 Bagley Language Percentiles Spring 2009 (N = 66) 1-10 11-30 31-50 51-75 76-100 number 6 20 17 15 8 percent 9% 30% 26% 23% 12%

Grade 6 Bagley Math Percentiles Spring 2009 (N = 66) 1-10 11-30 31-50 51-75 76-100 number 3 17 13 16 15 percent 5% 26% 20% 24% 23%

Bagley elementary percentile progressions by cohort and subject

Grade 2 spring 2006 Grade 2 Bagley Language Percentiles Spring 2006 (N = 62) 1-10 11-30 31-50 51-75 76-100 number 9 8 11 17 17 percent 15% 13% 18% 27% 27%

Grade 3 Bagley Language Percentiles Fall 2006 (N = 61) 1-10 11-30 31-50 51-75 76-100 number 12 14 9 10 16 percent 20% 23% 15% 16% 26%

Grade 2 Bagley Math Percentiles Spring 2006 (N = 64) 1-10 11-30 31-50 51-75 76-100 number 15 10 12 13 14 percent 23% 16% 19% 20% 22%

Grade 3 Bagley Math Percentiles Fall 2006 (N = 62) 1-10 11-30 31-50 51-75 76-100 number 8 14 13 11 15 percent 13% 23% 21% 18% 24%

P a g e | 168

Grade 2 Bagley Reading Percentiles Spring 2006 (N = 63) 1-10 11-30 31-50 51-75 76-100 number 11 6 10 14 22 percent 17% 10% 16% 22% 35%

Grade 3 Bagley Reading Percentiles Fall 2006 (N = 61) 1-10 11-30 31-50 51-75 76-100 number 8 14 13 11 15 percent 13% 23% 21% 18% 25%

Grade 3 spring 2006

Grade 3 Bagley Language Percentiles Spring 2006 (N = 65) 1-10 11-30 31-50 51-75 76-100 Number 15 17 13 10 10 Percent 23% 26% 20% 15% 15%

Grade 4 Bagley Language Percentiles Fall 2006 (N = 64) 1-10 11-30 31-50 51-75 76-100 number 12 19 15 8 10 percent 19% 30% 23% 13% 16%

Grade 6 Bagley Language Percentiles Spring 2009 (N = 66) 1-10 11-30 31-50 51-75 76-100 number 6 20 17 15 8 percent 9% 30% 26% 23% 12%

Grade 3 Bagley Math Percentiles Spring 2006 (N = 65) 1-10 11-30 31-50 51-75 76-100 number 9 12 13 14 17 percent 14% 18% 20% 22% 26%

Grade 4 Bagley Math Percentiles Fall 2006 (N = 64) 1-10 11-30 31-50 51-75 76-100 number 13 16 14 12 9 percent 20% 25% 22% 19% 14%

P a g e | 169

Grade 6 Bagley Math Percentiles Spring 2009 (N = 66) 1-10 11-30 31-50 51-75 76-100 number 3 17 13 16 15 percent 5% 26% 20% 24% 23%

Grade 3 Bagley Reading Percentiles Spring 2006 (N = 65) 1-10 11-30 31-50 51-75 76-100 number 11 11 13 15 15 percent 17% 17% 20% 23% 23%

Grade 4 Bagley Reading Percentiles Fall 2006 (N = 64) 1-10 11-30 31-50 51-75 76-100 number 10 16 11 18 9 percent 16% 25% 17% 28% 14%

Grade 4 spring 2006

Grade 4 Bagley Language Percentiles Spring 2006 (N = 85) 1-10 11-30 31-50 51-75 76-100 number 8 20 13 29 15 percent 9% 24% 15% 34% 18%

Grade 5 Bagley Language Percentiles Fall 2006 (N = 86) 1-10 11-30 31-50 51-75 76-100 number 9 21 18 25 13 percent 10% 24% 21% 29% 15%

Grade 4 Bagley Math Percentiles Spring 2006 (N = 85) 1-10 11-30 31-50 51-75 76-100 number 5 15 16 23 26 percent 6% 18% 19% 27% 31%

Grade 5 Bagley Math Percentiles Fall 2006 (N = 86) 1-10 11-30 31-50 51-75 76-100 number 3 18 21 27 17 percent 3% 21% 24% 31% 20%

P a g e | 170

Grade 6 Bagley Math Percentiles Spring 2008 (N = 89) 1-10 11-30 31-50 51-75 76-100 number 7 16 21 34 11 percent 8% 18% 24% 38% 12%

Grade 4 Bagley Reading Percentiles Spring 2006 (N = 85) 1-10 11-30 31-50 51-75 76-100 number 5 11 24 20 15 percent 6% 13% 28% 24% 18%

Grade 5 Bagley Reading Percentiles Fall 2006 (N = 86) 1-10 11-30 31-50 51-75 76-100 number 11 12 16 27 20 percent 13% 14% 19% 31% 23%

Grade 6 Bagley Reading Percentiles Spring 2008 (N = 89) 1-10 11-30 31-50 51-75 76-100 number 7 19 19 25 19 percent 8% 21% 21% 28% 21%

Grade 5 spring 2006

Grade 5 Bagley Language Percentiles Spring 2006 (N = 76) 1-10 11-30 31-50 51-75 76-100 number 9 23 19 14 11 percent 12% 30% 25% 18% 14%

Grade 6 Bagley Language Percentiles Fall 2006 (N = 79) 1-10 11-30 31-50 51-75 76-100 number 10 17 22 22 8 percent 13% 22% 28% 28% 10%

Grade 5 Bagley Math Percentiles Spring 2006 (N = 77) 1-10 11-30 31-50 51-75 76-100 number 7 19 21 11 19 percent 9% 25% 27% 14% 25% P a g e | 171

Grade 6 Bagley Math Percentiles Fall 2006 (N = 78) 1-10 11-30 31-50 51-75 76-100 number 6 20 22 16 14 percent 8% 26% 28% 21% 18%

Grade 6 Bagley Math Percentiles Spring 2007 (N = 78) 1-10 11-30 31-50 51-75 76-100 number 8 13 22 20 15 percent 10% 17% 28% 26% 19%

Grade 5 Bagley Reading Percentiles Spring 2006 (N = 77) 1-10 11-30 31-50 51-75 76-100 number 8 18 12 25 14 percent 10% 23% 16% 32% 18%

Grade 6 Bagley Reading Percentiles Fall 2006 (N = 80) 1-10 11-30 31-50 51-75 76-100 number 8 17 21 26 8 percent 10% 22% 27% 33% 10%

Grade 6 Bagley Reading Percentiles Spring 2007 (N = 75) 1-10 11-30 31-50 51-75 76-100 number 6 27 24 11 7 percent 8% 36% 32% 15% 9%

Grade 6 spring 2006

Grade 6 Bagley Language Percentiles Spring 2006 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 10 14 14 21 11 percent 14% 20% 20% 30% 16%

Grade 6 Bagley Math Percentiles Spring 2006 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 8 6 13 22 21 percent 11% 9% 19% 31% 30% P a g e | 172

Grade 6 Bagley Reading Percentiles Spring 2006 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 8 14 16 23 9 percent 11% 20% 23% 33% 13%

Grade 2 fall 2006

Grade 2 Bagley Language Percentiles Fall 2006 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 26 15 9 14 7 percent 37% 21% 13% 20% 10%

Bagley high school percentiles by year, grade, and subject

Fall 2005 Grade 7 Bagley Language Percentiles Fall 2005 (N = 97) 1-10 11-30 31-50 51-75 76-100 number 19 15 28 17 18 percent 20% 15% 29% 18% 19%

Grade 7 Bagley Math Percentiles Fall 2005 (N = 97) 1-10 11-30 31-50 51-75 76-100 number 9 23 22 23 20 percent 9% 24% 23% 24% 21%

Grade 7 Bagley Reading Percentiles Fall 2005 (N = 97) 1-10 11-30 31-50 51-75 76-100 number 10 16 17 29 25 percent 10% 16% 18% 30% 26%

Grade 8 Bagley Language Percentiles Fall 2005 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 14 19 22 10 6 percent 20% 27% 31% 14% 8%

Grade 8 Bagley Math Percentiles Fall 2005 (N = 73) 1-10 11-30 31-50 51-75 76-100 number 11 24 16 16 6 percent 15% 33% 22% 22% 8% P a g e | 173

Grade 9 Bagley Reading Percentiles Fall 2005 (N = 91) 1-10 11-30 31-50 51-75 76-100 number 7 16 23 14 13 percent 10% 22% 32% 19% 18%

Grade 9 Bagley Language Percentiles Fall 2005 (N = 92) 1-10 11-30 31-50 51-75 76-100 number 15 27 20 11 19 percent 16% 29% 22% 12% 21%

Grade 9 Bagley Math Percentiles Fall 2005 (N = 95) 1-10 11-30 31-50 51-75 76-100 number 16 26 17 20 16 percent 17% 27% 18% 21% 17%

Grade 9 Bagley Reading Percentiles Fall 2005 (N = 96) 1-10 11-30 31-50 51-75 76-100 number 12 23 17 21 23 percent 13% 24% 18% 22% 24%

Grade 10 Bagley Language Percentiles Fall 2005 (N = 99) 1-10 11-30 31-50 51-75 76-100 number 12 38 20 19 10 percent 12% 38% 20% 19% 10%

Grade 10 Bagley Math Percentiles Fall 2005 (N = 101) 1-10 11-30 31-50 51-75 76-100 number 10 26 27 20 18 percent 10% 26% 27% 20% 18%

Grade 10 Bagley Reading Percentiles Fall 2005 (N = 100) 1-10 11-30 31-50 51-75 76-100 number 6 30 25 18 21 percent 6% 30% 25% 18% 21%

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Grade 11 Bagley Language Percentiles Fall 2005 (N = 62) 1-10 11-30 31-50 51-75 76-100 number 3 17 13 16 13 percent 5% 27% 21% 26% 21%

Grade 11 Bagley Math Percentiles Fall 2005 (N = 63) 1-10 11-30 31-50 51-75 76-100 number 5 7 14 15 22 percent 8% 11% 22% 24% 35%

Grade 11 Bagley Reading Percentiles Fall 2005 (N = 63) 1-10 11-30 31-50 51-75 76-100 number 3 9 15 15 21 percent 5% 14% 24% 24% 33%

Grade 7 Bagley Language Percentiles Spring 2006 (N = 93) 1-10 11-30 31-50 51-75 76-100 number 6 20 19 25 23 percent 6% 22% 20% 27% 25%

Spring 2006

Grade 7 Bagley Math Percentiles Spring 2006 (N = 94) 1-10 11-30 31-50 51-75 76-100 number 8 23 14 25 24 percent 9% 24% 15% 27% 26%

Grade 7 Bagley Reading Percentiles Spring 2006 (N = 94) 1-10 11-30 31-50 51-75 76-100 number 10 15 19 21 29 percent 11% 16% 20% 22% 31%

Grade 8 Bagley Language Percentiles Spring 2006 (N = 69) 1-10 11-30 31-50 51-75 76-100 number 7 19 24 11 8 percent 10% 28% 35% 16% 12%

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Grade 8 Bagley Math Percentiles Spring 2006 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 10 9 24 19 8 percent 14% 13% 34% 27% 11%

Grade 8 Bagley Reading Percentiles Spring 2006 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 5 8 29 17 11 percent 7% 11% 41% 24% 16%

Grade 9 Bagley Language Percentiles Spring 2006 (N = 89) 1-10 11-30 31-50 51-75 76-100 number 13 17 24 18 17 percent 15% 19% 27% 20% 19%

Grade 9 Bagley Math Percentiles Spring 2006 (N = 92) 1-10 11-30 31-50 51-75 76-100 number 9 29 21 20 13 percent 10% 32% 23% 22% 14%

Grade 9 Bagley Reading Percentiles Spring 2006 (N = 92) 1-10 11-30 31-50 51-75 76-100 number 5 23 23 21 20 percent 5% 25% 25% 23% 22%

Grade 10 Bagley Language Percentiles Spring 2006 (N = 88) 1-10 11-30 31-50 51-75 76-100 number 9 21 24 24 10 percent 10% 24% 27% 27% 11%

Grade 10 Bagley Math Percentiles Spring 2006 (N = 88) 1-10 11-30 31-50 51-75 76-100 number 5 28 25 14 16 percent 6% 32% 28% 16% 18%

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Grade 10 Bagley Reading Percentiles Spring 2006 (N = 88) 1-10 11-30 31-50 51-75 76-100 number 6 16 29 20 17 percent 7% 18% 33% 23% 19%

Grade 11 Bagley Language Percentiles Spring 2006 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 1 11 19 18 8 percent 2% 19% 33% 32% 14%

Grade 11 Bagley Math Percentiles Spring 2006 (N = 58) 1-10 11-30 31-50 51-75 76-100 number 5 7 13 13 20 percent 9% 12% 22% 22% 34%

Grade 11 Bagley Reading Percentiles Spring 2006 (N = 58) 1-10 11-30 31-50 51-75 76-100 number 1 5 18 20 14 percent 2% 9% 31% 34% 24%

Fall 2006

Grade 7 Bagley Language Percentiles Fall 2006 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 7 20 17 17 9 percent 10% 29% 24% 24% 13%

Grade 7 Bagley Math Percentiles Fall 2006 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 5 22 6 17 20 percent 7% 31% 9% 24% 29%

Grade 7 Bagley Reading Percentiles Fall 2006 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 6 11 16 26 12 percent 8% 15% 23% 37% 17%

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Grade 8 Bagley Language Percentiles Fall 2006 (N = 96) 1-10 11-30 31-50 51-75 76-100 number 13 20 22 21 20 percent 14% 21% 23% 22% 21%

Grade 8 Bagley Math Percentiles Fall 2006 (N = 95) 1-10 11-30 31-50 51-75 76-100 number 8 17 21 24 25 percent 8% 18% 22% 25% 26%

Grade 8 Bagley Reading Percentiles Fall 2006 (N = 97) 1-10 11-30 31-50 51-75 76-100 number 12 17 24 22 22 percent 12% 18% 25% 23% 23%

Grade 9 Bagley Language Percentiles Fall 2006 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 8 17 27 8 11 percent 11% 24% 38% 11% 15%

Grade 9 Bagley Math Percentiles Fall 2006 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 6 14 22 19 9 percent 9% 20% 31% 27% 13%

Grade 9 Bagley Reading Percentiles Fall 2006 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 8 16 18 21 8 percent 11% 23% 25% 30% 11%

Grade 10 Bagley Language Percentiles Fall 2006 (N = 92) 1-10 11-30 31-50 51-75 76-100 number 12 30 17 16 17 percent 13% 33% 18% 17% 18%

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Grade 10 Bagley Math Percentiles Fall 2006 (N = 87) 1-10 11-30 31-50 51-75 76-100 number 12 19 26 13 17 percent 13% 21% 28% 14% 18%

Grade 10 Bagley Reading Percentiles Fall 2006 (N = 92) 1-10 11-30 31-50 51-75 76-100 number 12 23 21 13 23 percent 13% 25% 23% 14% 25%

Grade 11 Bagley Reading Percentiles Fall 2006 (N = 80) 1-10 11-30 31-50 51-75 76-100 number 5 21 21 20 13 percent 6% 26% 26% 25% 16%

Grade 11 Bagley Math Percentiles Fall 2006 (N = 84) 1-10 11-30 31-50 51-75 76-100 number 4 14 21 22 23 percent 5% 17% 25% 26% 27%

Grade 11 Bagley Reading Percentiles Fall 2006 (N = 78) 1-10 11-30 31-50 51-75 76-100 number 2 16 15 17 28 percent 3% 21% 19% 22% 36%

Spring 2007

Grade 7 Bagley Math Percentiles Spring 2007 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 5 15 12 21 18 percent 7% 21% 17% 30% 25%

Grade 7 Bagley Reading Percentiles Spring 2007 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 7 11 16 24 12 percent 10% 16% 23% 34% 17%

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Grade 8 Bagley Math Percentiles Spring 2007 (N = 94) 1-10 11-30 31-50 51-75 76-100 number 7 19 23 26 19 percent 7% 20% 24% 28% 20%

Grade 8 Bagley Reading Percentiles Spring 2007 (N = 93) 1-10 11-30 31-50 51-75 76-100 number 11 15 24 19 24 percent 12% 16% 26% 20% 26%

Grade 9 Bagley Math Percentiles Spring 2007 (N = 62) 1-10 11-30 31-50 51-75 76-100 number 6 17 17 15 7 percent 10% 27% 27% 24% 11%

Grade 9 Bagley Reading Percentiles Spring 2007 (N = 63) 1-10 11-30 31-50 51-75 76-100 number 4 24 10 12 13 percent 6% 38% 16% 19% 21%

Grade 10 Bagley Math Percentiles Spring 2007 (N = 84) 1-10 11-30 31-50 51-75 76-100 number 12 24 19 16 13 percent 14% 29% 23% 19% 15%

Grade 10 Bagley Reading Percentiles Spring 2007 (N = 85) 1-10 11-30 31-50 51-75 76-100 number 9 21 16 22 17 percent 11% 25% 19% 26% 20%

Grade 11 Bagley Math Percentiles Spring 2007 (N = 74) 1-10 11-30 31-50 51-75 76-100 number 6 14 15 16 23 percent 8% 19% 20% 22% 31%

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Grade 11 Bagley Reading Percentiles Spring 2007 (N = 74) 1-10 11-30 31-50 51-75 76-100 number 4 18 16 23 13 percent 5% 24% 22% 31% 18%

Fall 2007

Grade 7 Bagley Math Percentiles Fall 2007 (N = 78) 1-10 11-30 31-50 51-75 76-100 number 4 22 21 18 13 percent 5% 28% 27% 23% 17%

Grade 7 Bagley Reading Percentiles Fall 2007 (N = 79) 1-10 11-30 31-50 51-75 76-100 number 3 22 19 20 15 percent 4% 28% 24% 25% 19%

Grade 8 Bagley Math Percentiles Fall 2007 (N = 72) 1-10 11-30 31-50 51-75 76-100 number 7 16 13 15 21 percent 10% 22% 18% 21% 29%

Grade 8 Bagley Math Percentiles Fall 2007 (N = 73) 1-10 11-30 31-50 51-75 76-100 number 9 8 24 17 15 percent 12% 11% 33% 23% 21%

Grade 9 Bagley Reading Percentiles Fall 2007 (N = 95) 1-10 11-30 31-50 51-75 76-100 number 7 21 20 23 24 percent 7% 22% 21% 24% 25%

Grade 9 Bagley Reading Percentiles Fall 2007 (N = 95) 1-10 11-30 31-50 51-75 76-100 number 11 15 21 22 26 percent 12% 16% 22% 23% 27%

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Grade 10 Bagley Math Percentiles Fall 2007 (N = 66) 1-10 11-30 31-50 51-75 76-100 number 11 14 21 14 6 percent 17% 21% 32% 21% 9%

Grade 10 Bagley Reading Percentiles Fall 2007 (N = 67) 1-10 11-30 31-50 51-75 76-100 number 9 24 14 9 11 percent 13% 36% 21% 13% 16%

Grade 11 Bagley Math Percentiles Fall 2007 (N = 84) 1-10 11-30 31-50 51-75 76-100 number 8 21 18 15 22 percent 10% 25% 21% 18% 26%

Grade 11 Bagley Reading Percentiles Fall 2007 (N = 83) 1-10 11-30 31-50 51-75 76-100 number 8 13 20 18 24 percent 10% 16% 24% 22% 29%

Spring 2008

Grade 7 Bagley Math Percentiles Spring 2008 (N = 79) 1-10 11-30 31-50 51-75 76-100 number 2 19 11 30 17 percent 3% 24% 14% 38% 22%

Grade 7 Bagley Reading Percentiles Spring 2008 (N = 79) 1-10 11-30 31-50 51-75 76-100 number 4 18 24 20 13 percent 5% 23% 30% 25% 16%

Grade 8 Bagley Math Percentiles Spring 2008 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 8 10 12 20 20 percent 11% 14% 17% 29% 29%

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Grade 8 Bagley Reading Percentiles Spring 2008 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 6 11 25 18 10 percent 9% 16% 36% 26% 14%

Grade 9 Bagley Math Percentiles Spring 2008 (N = 92) 1-10 11-30 31-50 51-75 76-100 number 7 19 24 22 20 percent 8% 21% 26% 24% 22%

Grade 9 Bagley Reading Percentiles Spring 2008 (N = 89) 1-10 11-30 31-50 51-75 76-100 number 7 13 25 20 24 percent 8% 15% 28% 22% 27%

Grade 10 Bagley Math Percentiles Spring 2008 (N = 58) 1-10 11-30 31-50 51-75 76-100 number 5 12 24 9 8 percent 9% 21% 41% 16% 14%

Grade 10 Bagley Reading Percentiles Spring 2008 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 6 17 16 7 11 percent 11% 30% 28% 12% 19%

Grade 11 Bagley Math Percentiles Spring 2008 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 7 13 20 17 14 percent 10% 18% 28% 24% 20%

Grade 11 Bagley Reading Percentiles Spring 2008 (N = 75) 1-10 11-30 31-50 51-75 76-100 number 8 12 15 14 26 percent 11% 16% 20% 19% 35% P a g e | 183

Fall 2008

Grade 7 Bagley Math Percentiles Fall 2008 (N = 84) 1-10 11-30 31-50 51-75 76-100 number 8 11 22 31 12 percent 10% 13% 26% 37% 14%

Grade 7 Bagley Reading Percentiles Fall 2008 (N = 83) 1-10 11-30 31-50 51-75 76-100 number 7 18 16 30 12 percent 8% 22% 19% 36% 14%

Grade 8 Bagley Math Percentiles Fall 2008 (N = 76) 1-10 11-30 31-50 51-75 76-100 number 4 19 16 23 14 percent 5% 25% 21% 30% 18%

Grade 8 Bagley Reading Percentiles Fall 2008 (N = 76) 1-10 11-30 31-50 51-75 76-100 number 7 15 21 24 9 percent 9% 20% 28% 32% 12%

Grade 9 Bagley Math Percentiles Fall 2008 (N = 68) 1-10 11-30 31-50 51-75 76-100 number 4 10 14 20 20 percent 6% 15% 21% 29% 29%

Grade 9 Bagley Reading Percentiles Fall 2008 (N = 65) 1-10 11-30 31-50 51-75 76-100 number 5 13 20 18 9 percent 8% 20% 31% 28% 14%

Grade 10 Bagley Math Percentiles Fall 2008 (N = 91) 1-10 11-30 31-50 51-75 76-100 number 3 19 20 26 23 percent 3% 21% 22% 29% 25%

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Grade 10 Bagley Reading Percentiles Fall 2008 (N = 91) 1-10 11-30 31-50 51-75 76-100 number 10 18 19 24 20 percent 11% 20% 21% 26% 22%

Grade 11 Bagley Math Percentiles Fall 2008 (N = 60) 1-10 11-30 31-50 51-75 76-100 number 7 8 14 23 8 percent 12% 13% 23% 38% 13%

Grade 11 Bagley Reading Percentiles Fall 2008 (N = 61) 1-10 11-30 31-50 51-75 76-100 number 7 16 14 13 11 percent 11% 26% 23% 21% 18%

Spring 2009

Grade 7 Bagley Math Percentiles Spring 2009 (N = 83) 1-10 11-30 31-50 51-75 76-100 number 3 14 15 32 19 percent 4% 17% 18% 39% 23%

Grade 7 Bagley Reading Percentiles Spring 2009 (N = 83) 1-10 11-30 31-50 51-75 76-100 number 9 8 13 29 24 percent 11% 10% 16% 35% 29%

Grade 8 Bagley Math Percentiles Spring 2009 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 2 15 17 24 13 percent 3% 21% 24% 34% 18%

Grade 8 Bagley Reading Percentiles Spring 2009 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 3 12 17 27 12 percent 4% 17% 24% 38% 17%

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Grade 9 Bagley Math Percentiles Spring 2009 (N = 66) 1-10 11-30 31-50 51-75 76-100 number 4 8 18 12 24 percent 6% 12% 27% 18% 36%

Grade 9 Bagley Reading Percentiles Spring 2009 (N = 66) 1-10 11-30 31-50 51-75 76-100 number 5 11 16 23 11 percent 8% 17% 24% 35% 17%

Grade 10 Bagley Reading Percentiles Spring 2009 (N = 81) 1-10 11-30 31-50 51-75 76-100 number 3 13 19 19 27 percent 4% 16% 23% 23% 33%

Grade 10 Bagley Reading Percentiles Spring 2009 (N = 81) 1-10 11-30 31-50 51-75 76-100 number 4 11 22 16 28 percent 5% 14% 27% 20% 35%

Grade 11 Bagley Math Percentiles Spring 2009 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 5 13 14 17 8 percent 9% 23% 25% 30% 14%

Grade 11 Bagley Reading Percentiles Spring 2009 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 3 13 18 11 12 percent 5% 23% 32% 19% 21%

Fall 2009

Grade 7 Bagley Math Percentiles Fall 2009 (N = 72) 1-10 11-30 31-50 51-75 76-100 number 4 21 18 20 9 percent 6% 29% 25% 28% 13% P a g e | 186

Grade 7 Bagley Reading Percentiles Fall 2009 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 7 20 25 11 7 percent 10% 29% 36% 16% 10%

Grade 8 Bagley Math Percentiles Fall 2009 (N = 83) 1-10 11-30 31-50 51-75 76-100 number 5 25 9 25 19 percent 6% 30% 11% 30% 23%

Grade 8 Bagley Reading Percentiles Fall 2009 (N = 83) 1-10 11-30 31-50 51-75 76-100 number 7 17 15 27 17 percent 8% 20% 18% 33% 20%

Grade 9 Bagley Math Percentiles Fall 2009 (N = 76) 1-10 11-30 31-50 51-75 76-100 number 2 20 14 23 17 percent 3% 26% 18% 30% 22%

Grade 9 Bagley Reading Percentiles Fall 2009 (N = 72) 1-10 11-30 31-50 51-75 76-100 number 2 13 26 18 13 percent 3% 18% 36% 25% 18%

Grade 10 Bagley Math Percentiles Fall 2009 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 6 9 18 19 19 percent 8% 13% 25% 27% 27%

Grade 10 Bagley Reading Percentiles Fall 2009 (N = 72) 1-10 11-30 31-50 51-75 76-100 number 6 15 18 22 11 percent 8% 21% 25% 31% 15%

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Grade 11 Bagley Math Percentiles Fall 2009 (N = 81) 1-10 11-30 31-50 51-75 76-100 number 5 10 26 17 23 percent 6% 12% 32% 21% 28%

Grade 11 Bagley Reading Percentiles Fall 2009 (N = 81) 1-10 11-30 31-50 51-75 76-100 number 7 7 15 23 29 percent 9% 9% 19% 28% 36%

Grade 12 Bagley Math Percentiles Fall 2009 (N = 21) 1-10 11-30 31-50 51-75 76-100 number 1 5 8 6 1 percent 5% 24% 38% 29% 5%

Grade 12 Bagley Reading Percentiles Fall 2009 (N = 2) 1-10 11-30 31-50 51-75 76-100 number 1 1 percent 50% 50% 0% 0% 0%

Bagley high school percentile progressions by year, grade, and subject

Grade 7 fall 2005

Grade 7 Bagley Language Percentiles Fall 2005 (N = 97) 1-10 11-30 31-50 51-75 76-100 number 19 15 28 17 18 percent 20% 15% 29% 18% 19%

Grade 7 Bagley Language Percentiles Spring 2006 (N = 93) 1-10 11-30 31-50 51-75 76-100 number 6 20 19 25 23 percent 6% 22% 20% 27% 25%

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Grade 8 Bagley Language Percentiles Fall 2006 (N = 96) 1-10 11-30 31-50 51-75 76-100 number 13 20 22 21 20 percent 14% 21% 23% 22% 21%

Grade 7 Bagley Math Percentiles Fall 2005 (N = 97) 1-10 11-30 31-50 51-75 76-100 number 9 23 22 23 20 percent 9% 24% 23% 24% 21%

Grade 7 Bagley Math Percentiles Spring 2006 (N = 94) 1-10 11-30 31-50 51-75 76-100 number 8 23 14 25 24 percent 9% 24% 15% 27% 26%

Grade 8 Bagley Math Percentiles Fall 2006 (N = 95) 1-10 11-30 31-50 51-75 76-100 number 8 17 21 24 25 percent 8% 18% 22% 25% 26%

Grade 8 Bagley Math Percentiles Spring 2007 (N = 94) 1-10 11-30 31-50 51-75 76-100 number 7 19 23 26 19 percent 7% 20% 24% 28% 20%

Grade 9 Bagley Math Percentiles Fall 2007 (N = 95) 1-10 11-30 31-50 51-75 76-100 number 7 21 20 23 24 percent 7% 22% 21% 24% 25%

Grade 9 Bagley Math Percentiles Spring 2008 (N = 92) 1-10 11-30 31-50 51-75 76-100 number 7 19 24 22 20 percent 8% 21% 26% 24% 22%

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Grade 10 Bagley Math Percentiles Fall 2008 (N = 91) 1-10 11-30 31-50 51-75 76-100 number 3 19 20 26 23 percent 3% 21% 22% 29% 25%

Grade 10 Bagley Math Percentiles Spring 2009 (N = 81) 1-10 11-30 31-50 51-75 76-100 number 3 13 19 19 27 percent 4% 16% 23% 23% 33%

Grade 11 Bagley Math Percentiles Fall 2009 (N = 81) 1-10 11-30 31-50 51-75 76-100 number 5 10 26 17 23 percent 6% 12% 32% 21% 28%

Grade 7 Bagley Reading Percentiles Fall 2005 (N = 97) 1-10 11-30 31-50 51-75 76-100 number 10 16 17 29 25 percent 10% 16% 18% 30% 26%

Grade 7 Bagley Reading Percentiles Spring 2006 (N = 94) 1-10 11-30 31-50 51-75 76-100 number 10 15 19 21 29 percent 11% 16% 20% 22% 31%

Grade 8 Bagley Reading Percentiles Fall 2006 (N = 97) 1-10 11-30 31-50 51-75 76-100 number 12 17 24 22 22 percent 12% 18% 25% 23% 23%

Grade 8 Bagley Reading Percentiles Spring 2007 (N = 93) 1-10 11-30 31-50 51-75 76-100 number 11 15 24 19 24 percent 12% 16% 26% 20% 26%

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Grade 9 Bagley Reading Percentiles Fall 2007 (N = 95) 1-10 11-30 31-50 51-75 76-100 number 11 15 21 22 26 percent 12% 16% 22% 23% 27%

Grade 9 Bagley Reading Percentiles Spring 2008 (N = 89) 1-10 11-30 31-50 51-75 76-100 number 7 13 25 20 24 percent 8% 15% 28% 22% 27%

Grade 10 Bagley Reading Percentiles Fall 2008 (N = 91) 1-10 11-30 31-50 51-75 76-100 number 10 18 19 24 20 percent 11% 20% 21% 26% 22%

Grade 10 Bagley Reading Percentiles Spring 2009 (N = 81) 1-10 11-30 31-50 51-75 76-100 number 4 11 22 16 28 percent 5% 14% 27% 20% 35%

Grade 11 Bagley Reading Percentiles Fall 2009 (N = 81) 1-10 11-30 31-50 51-75 76-100 number 7 7 15 23 29 percent 9% 9% 19% 28% 36%

Grade 8 fall 2005

Grade 8 Bagley Language Percentiles Fall 2005 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 14 19 22 10 6 percent 20% 27% 31% 14% 8%

Grade 8 Bagley Language Percentiles Spring 2006 (N = 69) 1-10 11-30 31-50 51-75 76-100 number 7 19 24 11 8 percent 10% 28% 35% 16% 12%

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Grade 9 Bagley Language Percentiles Fall 2006 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 8 17 27 8 11 percent 11% 24% 38% 11% 15%

Grade 8 Bagley Math Percentiles Fall 2005 (N = 73) 1-10 11-30 31-50 51-75 76-100 number 11 24 16 16 6 percent 15% 33% 22% 22% 8%

Grade 8 Bagley Math Percentiles Spring 2006 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 10 9 24 19 8 percent 14% 13% 34% 27% 11%

Grade 9 Bagley Math Percentiles Fall 2006 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 6 14 22 19 9 percent 9% 20% 31% 27% 13%

Grade 9 Bagley Math Percentiles Spring 2007 (N = 62) 1-10 11-30 31-50 51-75 76-100 number 6 17 17 15 7 percent 10% 27% 27% 24% 11%

Grade 10 Bagley Math Percentiles Fall 2007 (N = 66) 1-10 11-30 31-50 51-75 76-100 number 11 14 21 14 6 percent 17% 21% 32% 21% 9%

Grade 10 Bagley Math Percentiles Spring 2008 (N = 58) 1-10 11-30 31-50 51-75 76-100 number 5 12 24 9 8 percent 9% 21% 41% 16% 14%

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Grade 11 Bagley Math Percentiles Fall 2008 (N = 60) 1-10 11-30 31-50 51-75 76-100 number 7 8 14 23 8 percent 12% 13% 23% 38% 13%

Grade 11 Bagley Math Percentiles Spring 2009 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 5 13 14 17 8 percent 9% 23% 25% 30% 14%

Grade 12 Bagley Math Percentiles Fall 2009 (N = 21) 1-10 11-30 31-50 51-75 76-100 number 1 5 8 6 1 percent 5% 24% 38% 29% 5%

Grade 8 Bagley Reading Percentiles Fall 2005 (N = 91) 1-10 11-30 31-50 51-75 76-100 number 7 16 23 14 13 percent 10% 22% 32% 19% 18%

Grade 8 Bagley Reading Percentiles Spring 2006 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 5 8 29 17 11 percent 7% 11% 41% 24% 16%

Grade 9 Bagley Reading Percentiles Fall 2006 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 8 16 18 21 8 percent 11% 23% 25% 30% 11%

Grade 9 Bagley Reading Percentiles Spring 2007 (N = 63) 1-10 11-30 31-50 51-75 76-100 number 4 24 10 12 13 percent 6% 38% 16% 19% 21%

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Grade 10 Bagley Reading Percentiles Fall 2007 (N = 67) 1-10 11-30 31-50 51-75 76-100 number 9 24 14 9 11 percent 13% 36% 21% 13% 16%

Grade 10 Bagley Reading Percentiles Spring 2008 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 6 17 16 7 11 percent 11% 30% 28% 12% 19%

Grade 11 Bagley Reading Percentiles Fall 2008 (N = 61) 1-10 11-30 31-50 51-75 76-100 number 7 16 14 13 11 percent 11% 26% 23% 21% 18%

Grade 11 Bagley Reading Percentiles Spring 2009 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 3 13 18 11 12 percent 5% 23% 32% 19% 21%

Grade 12 Bagley Reading Percentiles Fall 2009 (N = 2) 1-10 11-30 31-50 51-75 76-100 number 1 1 percent 50% 50% 0% 0% 0%

Grade 9 fall 2005

Grade 9 Bagley Language Percentiles Fall 2005 (N = 92) 1-10 11-30 31-50 51-75 76-100 number 15 27 20 11 19 percent 16% 29% 22% 12% 21%

Grade 9 Bagley Language Percentiles Spring 2006 (N = 89) 1-10 11-30 31-50 51-75 76-100 number 13 17 24 18 17 percent 15% 19% 27% 20% 19%

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Grade 10 Bagley Language Percentiles Fall 2006 (N = 92) 1-10 11-30 31-50 51-75 76-100 number 12 30 17 16 17 percent 13% 33% 18% 17% 18%

Grade 9 Bagley Math Percentiles Fall 2005 (N = 95) 1-10 11-30 31-50 51-75 76-100 number 16 26 17 20 16 percent 17% 27% 18% 21% 17%

Grade 9 Bagley Math Percentiles Spring 2006 (N = 92) 1-10 11-30 31-50 51-75 76-100 number 9 29 21 20 13 percent 10% 32% 23% 22% 14%

Grade 10 Bagley Math Percentiles Fall 2006 (N = 87) 1-10 11-30 31-50 51-75 76-100 number 12 19 26 13 17 percent 13% 21% 28% 14% 18%

Grade 10 Bagley Math Percentiles Spring 2007 (N = 84) 1-10 11-30 31-50 51-75 76-100 number 12 24 19 16 13 percent 14% 29% 23% 19% 15%

Grade 11 Bagley Math Percentiles Fall 2007 (N = 84) 1-10 11-30 31-50 51-75 76-100 number 8 21 18 15 22 percent 10% 25% 21% 18% 26%

Grade 11 Bagley Math Percentiles Spring 2008 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 7 13 20 17 14 percent 10% 18% 28% 24% 20%

P a g e | 195

Grade 9 Bagley Reading Percentiles Fall 2005 (N = 96) 1-10 11-30 31-50 51-75 76-100 number 12 23 17 21 23 percent 13% 24% 18% 22% 24%

Grade 9 Bagley Reading Percentiles Spring 2006 (N = 92) 1-10 11-30 31-50 51-75 76-100 number 5 23 23 21 20 percent 5% 25% 25% 23% 22%

Grade 10 Bagley Reading Percentiles Fall 2006 (N = 92) 1-10 11-30 31-50 51-75 76-100 number 12 23 21 13 23 percent 13% 25% 23% 14% 25%

Grade 10 Bagley Reading Percentiles Spring 2007 (N = 85) 1-10 11-30 31-50 51-75 76-100 number 9 21 16 22 17 percent 11% 25% 19% 26% 20%

Grade 11 Bagley Reading Percentiles Fall 2007 (N = 83) 1-10 11-30 31-50 51-75 76-100 number 8 13 20 18 24 percent 10% 16% 24% 22% 29%

Grade 11 Bagley Reading Percentiles Spring 2008 (N = 75) 1-10 11-30 31-50 51-75 76-100 number 8 12 15 14 26 percent 11% 16% 20% 19% 35%

Grade 10 fall 2005

Grade 10 Bagley Language Percentiles Fall 2005 (N = 99) 1-10 11-30 31-50 51-75 76-100 number 12 38 20 19 10 percent 12% 38% 20% 19% 10%

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Grade 10 Bagley Language Percentiles Spring 2006 (N = 88) 1-10 11-30 31-50 51-75 76-100 number 9 21 24 24 10 percent 10% 24% 27% 27% 11%

Grade 11 Bagley Reading Percentiles Fall 2006 (N = 80) 1-10 11-30 31-50 51-75 76-100 number 5 21 21 20 13 percent 6% 26% 26% 25% 16%

Grade 10 Bagley Math Percentiles Fall 2005 (N = 101) 1-10 11-30 31-50 51-75 76-100 number 10 26 27 20 18 percent 10% 26% 27% 20% 18%

Grade 10 Bagley Math Percentiles Spring 2006 (N = 88) 1-10 11-30 31-50 51-75 76-100 number 5 28 25 14 16 percent 6% 32% 28% 16% 18%

Grade 11 Bagley Math Percentiles Fall 2006 (N = 84) 1-10 11-30 31-50 51-75 76-100 number 4 14 21 22 23 percent 5% 17% 25% 26% 27%

Grade 11 Bagley Math Percentiles Spring 2007 (N = 74) 1-10 11-30 31-50 51-75 76-100 number 6 14 15 16 23 percent 8% 19% 20% 22% 31%

Grade 10 Bagley Reading Percentiles Fall 2005 (N = 100) 1-10 11-30 31-50 51-75 76-100 number 6 30 25 18 21 percent 6% 30% 25% 18% 21%

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Grade 10 Bagley Reading Percentiles Spring 2006 (N = 88) 1-10 11-30 31-50 51-75 76-100 number 6 16 29 20 17 percent 7% 18% 33% 23% 19%

Grade 11 Bagley Reading Percentiles Fall 2006 (N = 78) 1-10 11-30 31-50 51-75 76-100 number 2 16 15 17 28 percent 3% 21% 19% 22% 36%

Grade 11 fall 2005.

Grade 11 Bagley Reading Percentiles Spring 2007 (N = 74) 1-10 11-30 31-50 51-75 76-100 number 4 18 16 23 13 percent 5% 24% 22% 31% 18%

Grade 11 Bagley Language Percentiles Fall 2005 (N = 62) 1-10 11-30 31-50 51-75 76-100 number 3 17 13 16 13 percent 5% 27% 21% 26% 21%

Grade 11 Bagley Language Percentiles Spring 2006 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 1 11 19 18 8 percent 2% 19% 33% 32% 14%

Grade 11 Bagley Math Percentiles Fall 2005 (N = 63) 1-10 11-30 31-50 51-75 76-100 number 5 7 14 15 22 percent 8% 11% 22% 24% 35%

Grade 11 Bagley Language Percentiles Spring 2006 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 1 11 19 18 8 percent 2% 19% 33% 32% 14%

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Grade 11 Bagley Reading Percentiles Fall 2005 (N = 63) 1-10 11-30 31-50 51-75 76-100 number 3 9 15 15 21 percent 5% 14% 24% 24% 33%

Grade 11 Bagley Reading Percentiles Spring 2006 (N = 58) 1-10 11-30 31-50 51-75 76-100 number 1 5 18 20 14 percent 2% 9% 31% 34% 24%

Grade 7 fall 2006.

Grade 7 Bagley Language Percentiles Fall 2006 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 7 20 17 17 9 percent 10% 29% 24% 24% 13%

Grade 7 Bagley Math Percentiles Fall 2006 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 5 22 6 17 20 percent 7% 31% 9% 24% 29%

Grade 7 Bagley Math Percentiles Spring 2007 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 5 15 12 21 18 percent 7% 21% 17% 30% 25%

Grade 8 Bagley Math Percentiles Fall 2007 (N = 72) 1-10 11-30 31-50 51-75 76-100 number 7 16 13 15 21 percent 10% 22% 18% 21% 29%

Grade 8 Bagley Math Percentiles Spring 2008 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 8 10 12 20 20 percent 11% 14% 17% 29% 29%

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Grade 9 Bagley Math Percentiles Fall 2008 (N = 68) 1-10 11-30 31-50 51-75 76-100 number 4 10 14 20 20 percent 6% 15% 21% 29% 29%

Grade 9 Bagley Math Percentiles Spring 2009 (N = 66) 1-10 11-30 31-50 51-75 76-100 number 4 8 18 12 24 percent 6% 12% 27% 18% 36%

Grade 10 Bagley Math Percentiles Fall 2009 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 6 9 18 19 19 percent 8% 13% 25% 27% 27%

Grade 7 Bagley Reading Percentiles Fall 2006 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 6 11 16 26 12 percent 8% 15% 23% 37% 17%

Grade 7 Bagley Reading Percentiles Spring 2007 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 7 11 16 24 12 percent 10% 16% 23% 34% 17%

Grade 8 Bagley Reading Percentiles Fall 2007 (N = 73) 1-10 11-30 31-50 51-75 76-100 number 9 8 24 17 15 percent 12% 11% 33% 23% 21%

Grade 8 Bagley Reading Percentiles Spring 2008 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 6 11 25 18 10 percent 9% 16% 36% 26% 14%

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Grade 9 Bagley Reading Percentiles Fall 2008 (N = 65) 1-10 11-30 31-50 51-75 76-100 number 5 13 20 18 9 percent 8% 20% 31% 28% 14%

Grade 9 Bagley Reading Percentiles Spring 2009 (N = 66) 1-10 11-30 31-50 51-75 76-100 number 5 11 16 23 11 percent 8% 17% 24% 35% 17%

Grade 10 Bagley Reading Percentiles Fall 2009 (N = 72) 1-10 11-30 31-50 51-75 76-100 number 6 15 18 22 11 percent 8% 21% 25% 31% 15%

Grade 7 fall 2007

Grade 7 Bagley Math Percentiles Fall 2007 (N = 78) 1-10 11-30 31-50 51-75 76-100 number 4 22 21 18 13 percent 5% 28% 27% 23% 17%

Grade 7 Bagley Math Percentiles Spring 2008 (N = 79) 1-10 11-30 31-50 51-75 76-100 number 2 19 11 30 17 percent 3% 24% 14% 38% 22%

Grade 8 Bagley Math Percentiles Fall 2008 (N = 76) 1-10 11-30 31-50 51-75 76-100 number 4 19 16 23 14 percent 5% 25% 21% 30% 18%

Grade 8 Bagley Math Percentiles Spring 2009 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 2 15 17 24 13 percent 3% 21% 24% 34% 18%

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Grade 9 Bagley Math Percentiles Fall 2009 (N = 76) 1-10 11-30 31-50 51-75 76-100 number 2 20 14 23 17 percent 3% 26% 18% 30% 22%

Grade 7 Bagley Reading Percentiles Fall 2007 (N = 79) 1-10 11-30 31-50 51-75 76-100 number 3 22 19 20 15 percent 4% 28% 24% 25% 19%

Grade 7 Bagley Reading Percentiles Spring 2008 (N = 79) 1-10 11-30 31-50 51-75 76-100 number 4 18 24 20 13 percent 5% 23% 30% 25% 16%

Grade 8 Bagley Reading Percentiles Fall 2008 (N = 76) 1-10 11-30 31-50 51-75 76-100 number 7 15 21 24 9 percent 9% 20% 28% 32% 12%

Grade 8 Bagley Reading Percentiles Spring 2009 (N = 71) 1-10 11-30 31-50 51-75 76-100 number 3 12 17 27 12 percent 4% 17% 24% 38% 17%

Grade 9 Bagley Reading Percentiles Fall 2009 (N = 72) 1-10 11-30 31-50 51-75 76-100 number 2 13 26 18 13 percent 3% 18% 36% 25% 18%

Grade 7 fall 2008

Grade 7 Bagley Math Percentiles Fall 2008 (N = 84) 1-10 11-30 31-50 51-75 76-100 number 8 11 22 31 12 percent 10% 13% 26% 37% 14%

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Grade 7 Bagley Math Percentiles Spring 2009 (N = 83) 1-10 11-30 31-50 51-75 76-100 number 3 14 15 32 19 percent 4% 17% 18% 39% 23%

Grade 8 Bagley Math Percentiles Fall 2009 (N = 83) 1-10 11-30 31-50 51-75 76-100 number 5 25 9 25 19 percent 6% 30% 11% 30% 23%

Grade 7 Bagley Reading Percentiles Fall 2008 (N = 83) 1-10 11-30 31-50 51-75 76-100 number 7 18 16 30 12 percent 8% 22% 19% 36% 14%

Grade 7 Bagley Reading Percentiles Spring 2009 (N = 83) 1-10 11-30 31-50 51-75 76-100 number 9 8 13 29 24 percent 11% 10% 16% 35% 29%

Grade 8 Bagley Reading Percentiles Fall 2009 (N = 83) 1-10 11-30 31-50 51-75 76-100 number 7 17 15 27 17 percent 8% 20% 18% 33% 20%

Grade 7 fall 2009

Grade 7 Bagley Math Percentiles Fall 2009 (N = 72) 1-10 11-30 31-50 51-75 76-100 number 4 21 18 20 9 percent 6% 29% 25% 28% 13%

Grade 7 Bagley Reading Percentiles Fall 2009 (N = 70) 1-10 11-30 31-50 51-75 76-100 number 7 20 25 11 7 percent 10% 29% 36% 16% 10%

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Bagley MAP Data Bagley Grade 7 Survey with Goals Fall 2005

250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American Indian White American Indian White American Indian White y NWEA Language Math Reading area Average RIT 204 204 211 218 210 210 224 225 205 206 217 221 GoalRIT1 0 203 207 212 217 207 207 222 226 206 201 216 219 GoalRIT2 0 204 207 213 202 215 216 235 236 203 210 211 210 GoalRIT3 0 202 208 208 203 205 218 235 243 200 209 204 203 GoalRIT4 0 206 209 205 198 211 216 231 227 208 209 210 215 GoalRIT5 0 207 210 215 192 213 222 233 241 208 209 215 213 GoalRIT6 0 215 215 230 231 GoalRIT7 0 207 221 235 231

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 GoalRIT5 GoalRIT6 GoalRIT7

Language Comp. Process Comp. Structure Grammar usage Punctuation Capitalization Spatial sense/ Math Mathematical reasoning Number sense Computation/Operations Patterns/ Functions/ Algebra Data analysis/Stats/Probabilities geometry Measurement

Reading Word recognition Literal Comp. Interpretive Comp. Evaluative Comp. Literature

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Bagley Grade 7 Survey with Goals Spring 2006

240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American American American White White White y Indian Indian Indian NWEA Language Math Reading area Average RIT 211 213 218 223 215 220 230 231 206 211 222 224 GoalRIT1 0 208 215 219 223 212 222 229 231 204 215 221 223 GoalRIT2 0 210 216 219 224 225 220 231 235 201 208 224 224 GoalRIT3 0 211 208 217 224 213 223 230 231 207 212 223 227 GoalRIT4 0 211 210 220 221 213 221 229 233 208 207 222 225 GoalRIT5 0 214 214 217 225 213 220 231 234 208 213 223 222 GoalRIT6 0 219 222 230 231 GoalRIT7 0 214 214 231 226

Spring 2006 GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 GoalRIT5 GoalRIT6 GoalRIT7 Comp. Comp. Language Process Structure Grammar usage Punctuation Capitalization Patterns/ Mathematical Computation/ Functions/ Data analysis/ Spatial sense/ Math reasoning Number sense Operations Algebra Stats/Probability geometry Measurement Word Literal Interpretive Evaluative Reading recognition Comprehension Comprehension Comprehension Literature

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Bagley Grade 8 Survey with Goals Fall 2006 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American Indian White American Indian White American Indian White y NWEA Language Math Reading area Average RIT 204 213 216 222 219 223 232 231 201 210 217 224 GoalRIT1 0 202 205 216 223 219 222 233 231 201 207 220 221 GoalRIT2 0 201 209 216 221 217 223 234 233 202 214 216 225 GoalRIT3 0 205 207 215 220 221 217 232 232 202 210 216 224 GoalRIT4 0 201 206 213 220 221 217 228 228 198 208 216 225

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Writing Types / Elements of Spelling / Punctuation / Language Research Composition Grammar & Usage Capitalization Statistics & Geometry & Math Number Sense Functions & Algebra Probability measurement Informational Narrative Reading Word recognition Comprehension Comprehension Literature

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Bagley Grade 8 Survey with Goals Spring 2007 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA area Math Reading Average RIT 216 218 235 235 208 211 220 226 GoalRIT1 0 215 215 232 236 207 209 221 226 GoalRIT2 0 216 218 237 237 210 212 221 227 GoalRIT3 0 219 225 236 237 207 213 219 226 GoalRIT4 0 214 213 235 232 208 211 219 226

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Writing Types / Elements of Spelling / Punctuation / Language Research Composition Grammar & Usage Capitalization Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

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Bagley Grade 9 Survey with Goals Fall 2007 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 222 224 234 237 205 219 222 228 GoalRIT1 0 221 223 232 237 206 220 220 228 GoalRIT2 0 221 228 234 240 206 220 221 227 GoalRIT3 0 225 223 235 238 205 217 223 228 GoalRIT4 0 223 222 234 235 204 217 225 228

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Writing Types / Elements of Spelling / Punctuation / Language Research Composition Grammar & Usage Capitalization Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

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Bagley Grade 9 Survey with Goals Spring 2008

240250 230 210220 200 180190 170 150160 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 224 230 237 241 209 222 226 229 GoalRIT1 0 224 229 237 239 208 214 226 231 GoalRIT2 0 222 232 238 244 210 228 228 230 GoalRIT3 0 226 235 238 242 211 222 226 230 GoalRIT4 0 224 222 236 238 206 223 224 228

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Writing Types / Elements of Spelling / Punctuation / Language Research Composition Grammar & Usage Capitalization Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

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Bagley Grade 10 Survey with Goals Fall 2008 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 221 225 239 240 198 218 224 229 GoalRIT1 0 222 236 240 242 201 217 226 228 GoalRIT2 0 223 237 242 243 200 220 225 231 GoalRIT3 0 222 240 240 245 189 222 223 229 GoalRIT4 0 221 237 239 241 197 215 221 230

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Writing Types / Elements of Spelling / Punctuation / Language Research Composition Grammar & Usage Capitalization Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

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Bagley Grade 10 Survey with Goals Spring 2009 270 250 230 210 190 170 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA area Math Reading Average RIT 227 242 240 243 209 236 228 232 GoalRIT1 0 232 246 240 242 217 238 229 232 GoalRIT2 0 223 244 240 245 213 237 231 233 GoalRIT3 0 228 243 241 245 202 237 228 233 GoalRIT4 0 226 234 241 241 201 235 227 230

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Writing Types / Elements of Spelling / Punctuation / Language Research Composition Grammar & Usage Capitalization Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

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Bagley Grade 11 Survey with Goals Fall 2009 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 216 236 239 242 209 233 226 234 GoalRIT1 0 219 237 234 240 209 237 228 235 GoalRIT2 0 213 239 239 245 208 227 227 235 GoalRIT3 0 213 230 241 239 209 232 227 233 GoalRIT4 0 218 237 241 244 208 237 225 234

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number & Geometry & Data analysis and Math Operation Algebra measurement probability Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

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Bagley Grade 8 Survey with Goals Fall 2005 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American Indian White American Indian White American Indian White y NWEA Language Math Reading area Average RIT 207 209 211 218 216 214 224 227 209 209 220 219 GoalRIT1 0 206 214 213 219 211 213 222 227 211 205 217 216 GoalRIT2 0 204 210 211 218 223 214 226 228 208 208 218 218 GoalRIT3 0 207 208 213 217 215 217 222 231 209 212 221 219 GoalRIT4 0 205 208 209 218 214 216 224 228 209 207 222 221 GoalRIT5 0 210 206 210 219 220 217 226 230 209 214 220 224 GoalRIT6 0 215 214 222 226 GoalRIT7 0 212 208 224 220

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 GoalRIT5 GoalRIT6 GoalRIT7

Language Comp. Process Comp. Structure Grammar usage Punctuation Capitalization Spatial sense/ Math Mathematical reasoning Number sense Computation/Operations Patterns/ Functions/ Algebra Data analysis/Stats/Probabilities geometry Measurement

Reading Word recognition Literal Comp. Interpretive Comp. Evaluative Comp. Literature

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Bagley Grade 8 Survey with Goals Spring 2006 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American Indian White American Indian White American Indian White y NWEA Language Math Reading area Average RIT 210 217 216 220 221 224 230 234 215 221 222 224 GoalRIT1 0 206 216 219 223 218 228 230 233 213 223 221 223 GoalRIT2 0 215 217 218 221 219 230 232 234 212 215 223 225 GoalRIT3 0 206 217 215 220 225 219 231 237 216 224 225 224 GoalRIT4 0 211 219 214 219 221 223 230 236 216 222 221 226 GoalRIT5 0 213 218 215 219 226 223 232 233 216 220 219 224 GoalRIT6 0 219 225 230 229 GoalRIT7 0 219 220 229 234

Spring 2006 GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 GoalRIT5 GoalRIT6 GoalRIT7 Comp. Comp. Language Process Structure Grammar usage Punctuation Capitalization Patterns/ Mathematical Computation/ Functions/ Data analysis/ Spatial sense/ Math reasoning Number sense Operations Algebra Stats/Probability geometry Measurement Word Literal Interpretive Evaluative Reading recognition Comprehension Comprehension Comprehension Literature

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Bagley Grade 9 Survey with Goals Fall 2006 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American Indian White American Indian White American Indian White y NWEA Language Math Reading area Average RIT 211 218 217 221 226 220 230 233 208 224 220 221 GoalRIT1 0 209 218 218 221 229 221 227 233 213 225 219 221 GoalRIT2 0 207 222 218 220 223 223 229 238 207 219 219 221 GoalRIT3 0 213 218 216 221 226 217 233 233 204 221 220 222 GoalRIT4 0 213 214 216 224 226 220 230 229 207 230 219 221

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Writing Types / Elements of Spelling / Punctuation / Language Research Composition Grammar & Usage Capitalization Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

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Bagley Grade 9 Survey with Goals Spring 2007 250 230240 210220 190200 170180 150160 Gender Male Female Male Female Male Female Male Female Ethnicit American Indian White American Indian White y NWEA Math Reading area Average RIT 225 230 231 238 214 229 221 224 GoalRIT1 0 226 225 228 238 215 228 223 222 GoalRIT2 0 230 239 231 243 217 228 220 225 GoalRIT3 0 221 234 232 235 208 230 219 223 GoalRIT4 0 223 222 231 235 213 230 221 224

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Writing Types / Elements of Spelling / Punctuation / Language Research Composition Grammar & Usage Capitalization Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

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Bagley Grade 10 Survey with Goals Fall 2007 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 227 222 233 233 213 213 220 224 GoalRIT1 0 227 217 232 232 215 215 223 226 GoalRIT2 0 228 224 233 236 213 215 220 223 GoalRIT3 0 226 224 232 232 214 212 219 224 GoalRIT4 0 228 223 234 233 208 211 219 223

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Writing Types / Elements of Spelling / Punctuation / Language Research Composition Grammar & Usage Capitalization Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

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Bagley Grade 10 Survey with Goals Spring 2008 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 232 228 238 238 216 222 224 225 GoalRIT1 0 227 228 225 236 219 164 225 227 GoalRIT2 0 233 230 229 242 217 172 225 225 GoalRIT3 0 233 226 230 237 212 161 221 225 GoalRIT4 0 236 227 227 237 215 168 224 224

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Writing Types / Elements of Spelling / Punctuation / Language Research Composition Grammar & Usage Capitalization Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

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Bagley Grade 11 Survey with Goals Fall 2008 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 228 232 238 237 214 219 225 226 GoalRIT1 0 228 232 238 217 216 221 228 229 GoalRIT2 0 226 230 243 217 215 220 228 225 GoalRIT3 0 231 230 240 214 208 218 224 224 GoalRIT4 0 230 230 239 216 215 218 221 227

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Writing Types / Elements of Spelling / Punctuation / Language Research Composition Grammar & Usage Capitalization Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

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Bagley Grade 11 Survey with Goals Spring 2009 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA area Math Reading Average RIT 235 231 241 238 224 219 229 227 GoalRIT1 0 234 226 241 237 229 217 233 228 GoalRIT2 0 233 231 241 240 217 223 231 228 GoalRIT3 0 238 235 242 238 226 217 228 225 GoalRIT4 0 235 229 242 238 223 218 226 226

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

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Bagley Grade 9 Survey with Goals Fall 2005 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American Indian White American Indian White American Indian White y NWEA Language Math Reading area Average RIT 211 212 216 221 224 220 229 231 211 210 220 227 GoalRIT1 0 212 213 218 222 224 215 227 230 216 208 221 226 GoalRIT2 0 213 213 215 222 225 219 229 228 211 210 217 223 GoalRIT3 0 212 211 217 222 221 219 225 229 208 217 219 229 GoalRIT4 0 208 209 216 220 226 222 230 236 212 208 221 227 GoalRIT5 0 212 215 216 220 228 225 228 233 210 209 222 229 GoalRIT6 0 223 218 230 234

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 GoalRIT5 GoalRIT6

Language Comp. Process Comp. Structure Grammar usage Punctuation Capitalization Spatial sense/ Math Mathematical reasoning Number sense Computation/Operations Patterns/ Functions/ Algebra Data analysis/Stats/Probabilities geometry

Reading Word recognition Literal Comp. Interpretive Comp. Evaluative Comp. Literature

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Bagley Grade 9 Survey with Goals Spring 2006 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American Indian White American Indian White American Indian White y NWEA Language Math Reading area Average RIT 210 219 219 225 225 224 236 236 219 218 225 228 GoalRIT1 0 211 221 221 226 224 224 235 235 217 218 224 227 GoalRIT2 0 211 218 222 225 230 224 235 236 220 217 227 228 GoalRIT3 0 207 217 219 225 223 226 235 235 220 221 227 229 GoalRIT4 0 210 221 218 225 226 225 238 237 218 218 226 231 GoalRIT5 0 209 220 218 223 226 224 241 236 220 217 224 228 GoalRIT6 0 225 227 234 237 GoalRIT7 0 222 222 236 234

Spring 2006 GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 GoalRIT5 GoalRIT6 GoalRIT7 Comp. Comp. Language Process Structure Grammar usage Punctuation Capitalization Patterns/ Mathematical Computation/ Functions/ Data analysis/ Spatial sense/ Math reasoning Number sense Operations Algebra Stats/Probability geometry Measurement Word Literal Interpretive Evaluative Reading recognition Comprehension Comprehension Comprehension Literature

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Bagley Grade 10 Survey with Goals Fall 2006 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American Indian White American Indian White American Indian White y NWEA Language Math Reading area Average RIT 213 216 220 226 221 225 237 237 211 218 224 227 GoalRIT1 0 209 217 221 226 219 223 233 233 210 216 222 226 GoalRIT2 0 213 219 221 228 221 227 239 241 211 218 225 229 GoalRIT3 0 215 214 218 225 223 226 238 238 210 221 225 227 GoalRIT4 0 214 215 219 226 220 221 238 238 212 218 224 227

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Writing Types / Elements of Spelling / Punctuation / Language Research Composition Grammar & Usage Capitalization Statistics & Geometry & Math Number Sense Functions & Algebra Probability measurement Informational Narrative Reading Word recognition Comprehension Comprehension Literature

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Bagley Grade 10 Survey with Goals Spring 2007 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA area Math Reading Average RIT 231 227 239 237 219 216 225 229 GoalRIT1 0 229 224 236 233 223 215 229 230 GoalRIT2 0 229 226 241 237 215 214 226 228 GoalRIT3 0 233 233 239 241 217 217 222 230 GoalRIT4 0 234 226 240 236 222 218 225 229

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Writing Types / Elements of Spelling / Punctuation / Language Research Composition Grammar & Usage Capitalization Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

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Bagley Grade 11 Survey with Goals Fall 2007 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 222 232 239 239 219 219 228 231 GoalRIT1 0 218 229 235 234 220 220 229 231 GoalRIT2 0 222 235 238 242 217 217 227 232 GoalRIT3 0 222 235 240 240 221 217 225 230 GoalRIT4 0 225 231 241 239 218 220 230 231

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Writing Types / Elements of Spelling / Punctuation / Language Research Composition Grammar & Usage Capitalization Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

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Bagley Grade 11 Survey with Goals Spring 2008

250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 231 230 242 244 224 217 227 234 GoalRIT1 0 228 228 241 243 228 217 228 232 GoalRIT2 0 228 234 241 244 225 219 226 234 GoalRIT3 0 236 230 244 245 220 220 226 234 GoalRIT4 0 233 226 242 245 223 214 228 236

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Writing Types / Elements of Spelling / Punctuation / Language Research Composition Grammar & Usage Capitalization Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

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Bagley Grade 10 Survey with Goals Fall 2005 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American Indian White American Indian White American Indian White y NWEA Language Math Reading area Average RIT 212 220 218 222 228 231 236 234 214 227 223 225 GoalRIT1 0 207 223 219 224 229 234 237 236 212 229 225 225 GoalRIT2 0 209 220 221 223 237 232 237 233 218 220 222 227 GoalRIT3 0 213 217 217 219 222 228 235 232 213 231 225 228 GoalRIT4 0 216 221 218 222 227 233 237 236 215 229 222 226 GoalRIT5 0 215 217 218 221 226 231 236 237 210 224 223 220 GoalRIT6 0 225 230 233 236 GoalRIT7 0 233 230 239 231

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 GoalRIT5 GoalRIT6 GoalRIT7

Language Comp. Process Comp. Structure Grammar usage Punctuation Capitalization Spatial sense/ Math Mathematical reasoning Number sense Computation/Operations Patterns/ Functions/ Algebra Data analysis/Stats/Probabilities geometry Measurement

Reading Word recognition Literal Comp. Interpretive Comp. Evaluative Comp. Literature

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Bagley Grade 10 Survey with Goals Spring 2006 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American Indian White American Indian White American Indian White y NWEA Language Math Reading area Average RIT 214 223 221 224 234 234 241 237 223 208 222 229 GoalRIT1 0 220 225 223 225 236 232 242 236 225 210 223 231 GoalRIT2 0 210 224 223 226 232 230 243 235 224 207 224 230 GoalRIT3 0 214 224 220 222 235 231 241 236 224 213 221 227 GoalRIT4 0 214 227 221 224 236 239 242 241 227 203 223 229 GoalRIT5 0 213 214 219 223 233 235 240 237 214 205 221 228 GoalRIT6 0 232 238 242 238 GoalRIT7 0 236 235 241 234

Spring 2006 GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 GoalRIT5 GoalRIT6 GoalRIT7 Comp. Comp. Language Process Structure Grammar usage Punctuation Capitalization Patterns/ Mathematical Computation/ Functions/ Data analysis/ Spatial sense/ Math reasoning Number sense Operations Algebra Stats/Probability geometry Measurement Word Literal Interpretive Evaluative Reading recognition Comprehension Comprehension Comprehension Literature

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Bagley Grade 11 Survey with Goals Fall 2006 270 250 230 210 190 170 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American Indian White American Indian White American Indian White y NWEA Language Math Reading area Average RIT 214 224 222 224 227 238 245 238 222 228 230 227 GoalRIT1 0 215 223 223 224 228 232 241 234 221 232 230 227 GoalRIT2 0 212 228 224 225 224 242 246 242 226 230 229 230 GoalRIT3 0 213 221 222 222 225 239 244 239 224 227 230 228 GoalRIT4 0 218 224 221 226 232 238 247 239 217 225 230 226

Spring 2006 GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 GoalRIT5 GoalRIT6 GoalRIT7 Comp. Comp. Language Process Structure Grammar usage Punctuation Capitalization Patterns/ Mathematical Computation/ Functions/ Data analysis/ Spatial sense/ Math reasoning Number sense Operations Algebra Stats/Probability geometry Measurement Word Literal Interpretive Evaluative Reading recognition Comprehension Comprehension Comprehension Literature

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Bagley Grade 11 Survey with Goals Spring 2007 270 250 230 210 190 170 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 242 238 245 242 223 226 226 227 GoalRIT1 0 239 241 241 240 227 224 228 227 GoalRIT2 0 248 239 246 244 221 230 225 226 GoalRIT3 0 240 235 246 244 222 221 224 227 GoalRIT4 0 239 238 247 240 220 230 226 227

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

P a g e | 230

Bagley Grade 11 Survey with Goals Fall 2005

270 250 230 210 190 170 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American Indian White American Indian White American Indian White y NWEA Language Math Reading area Average RIT 221 221 222 227 244 235 241 243 221 218 225 233 GoalRIT1 0 231 220 221 230 240 230 239 243 216 218 228 233 GoalRIT2 0 217 221 225 228 243 237 246 240 222 218 228 233 GoalRIT3 0 225 223 221 224 242 230 237 243 221 218 224 229 GoalRIT4 0 215 219 222 227 248 243 242 244 220 219 225 236 GoalRIT5 0 218 224 220 226 242 238 242 244 228 219 221 233 GoalRIT6 0 248 238 240 243 GoalRIT7 0 245 227 242 244

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 GoalRIT5 GoalRIT6 GoalRIT7

Language Comp. Process Comp. Structure Grammar usage Punctuation Capitalization Spatial sense/ Math Mathematical reasoning Number sense Computation/Operations Patterns/ Functions/ Algebra Data analysis/Stats/Probabilities geometry Measurement

Reading Word recognition Literal Comp. Interpretive Comp. Evaluative Comp. Literature

P a g e | 231

Bagley Grade 11 Survey with Goals Spring 2006 270 250 230 210 190 170 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American Indian White American Indian White American Indian White y NWEA Language Math Reading area Average RIT 224 226 221 228 244 244 244 244 226 229 229 232 GoalRIT1 0 228 230 221 230 247 242 245 242 229 230 231 234 GoalRIT2 0 229 229 220 233 242 242 246 242 228 230 234 234 GoalRIT3 0 223 223 219 226 240 239 242 244 230 232 229 234 GoalRIT4 0 217 227 222 227 244 245 243 246 225 227 226 232 GoalRIT5 0 224 222 222 228 234 250 242 243 221 228 227 231 GoalRIT6 0 250 248 245 245 GoalRIT7 0 250 244 246 245

Spring 2006 GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 GoalRIT5 GoalRIT6 GoalRIT7 Comp. Comp. Language Process Structure Grammar usage Punctuation Capitalization Patterns/ Mathematical Computation/ Functions/ Data analysis/ Spatial sense/ Math reasoning Number sense Operations Algebra Stats/Probability geometry Measurement Word Literal Interpretive Evaluative Reading recognition Comprehension Comprehension Comprehension Literature

P a g e | 232

Bagley Grade 7 Survey with Goals Fall 2006 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American Indian White American Indian White American Indian White y NWEA Language Math Reading area Average RIT 207 214 212 216 219 220 225 224 208 216 213 217 GoalRIT1 0 208 214 212 214 221 218 222 224 203 217 210 214 GoalRIT2 0 213 214 215 217 221 225 225 223 204 218 213 219 GoalRIT3 0 205 213 211 213 219 222 229 225 217 215 214 218 GoalRIT4 0 203 216 209 219 215 217 224 226 208 215 215 216

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Writing Types / Elements of Spelling / Punctuation / Language Research Composition Grammar & Usage Capitalization Statistics & Geometry & Math Number Sense Functions & Algebra Probability measurement Informational Narrative Reading Word recognition Comprehension Comprehension Literature

P a g e | 233

Bagley Grade 7 Survey with Goals Spring 2007 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA area Language Reading Average RIT 220 224 231 232 210 220 218 220 GoalRIT1 0 217 225 230 232 212 218 219 218 GoalRIT2 0 220 227 232 232 207 219 219 219 GoalRIT3 0 224 227 233 236 208 221 215 222 GoalRIT4 0 220 218 230 229 213 221 218 222

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

P a g e | 234

Bagley Grade 8 Survey with Goals Fall 2007 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 217 232 232 231 206 221 215 221 GoalRIT1 0 216 228 231 231 205 217 216 220 GoalRIT2 0 220 236 232 231 203 224 214 53 GoalRIT3 0 219 232 232 233 207 223 215 221 GoalRIT4 0 213 229 232 227 206 222 217 223

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

P a g e | 235

Bagley Grade 8 Survey with Goals Spring 2008 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 229 235 236 237 213 221 219 223 GoalRIT1 0 228 237 234 238 217 224 221 222 GoalRIT2 0 227 237 236 237 211 221 219 224 GoalRIT3 0 231 234 237 237 211 222 216 224 GoalRIT4 0 228 230 236 235 216 219 220 224

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

P a g e | 236

Bagley Grade 9 Survey with Goals Fall 2008 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA area Math Reading Average RIT 228 232 236 235 214 222 220 219 GoalRIT1 0 231 231 238 226 214 222 219 217 GoalRIT2 0 227 238 238 227 214 221 223 221 GoalRIT3 0 227 236 237 225 213 221 220 220 GoalRIT4 0 225 232 237 224 213 224 219 220

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

P a g e | 237

Bagley Grade 9 Survey with Goals Spring 2009 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 236 235 238 237 216 223 222 224 GoalRIT1 0 230 234 238 238 219 218 226 223 GoalRIT2 0 241 236 237 239 216 227 222 224 GoalRIT3 0 234 237 239 236 211 226 220 225 GoalRIT4 0 238 233 239 236 218 222 221 225

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

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Bagley Grade 10 Survey with Goals Fall 2009

250

240

230

220

210

200

190

180

170

160

150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA area Math Reading Average RIT 235 234 237 237 214 225 222 226 GoalRIT1 0 233 233 236 236 215 223 222 224 GoalRIT2 0 234 237 238 240 214 226 221 225 GoalRIT3 0 235 234 237 235 212 226 223 225 GoalRIT4 0 238 233 236 239 216 223 223 229

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

P a g e | 239

Bagley Grade 7 Survey with Goals Fall 2007 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 219 220 224 223 216 215 215 215 GoalRIT1 0 215 217 222 219 216 215 214 215 GoalRIT2 0 219 219 221 223 213 215 217 214 GoalRIT3 0 220 220 226 227 220 215 214 216 GoalRIT4 0 221 222 228 223 217 215 216 217

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

P a g e | 240

Bagley Grade 7 Survey with Goals Spring 2008

240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 229 227 232 230 216 217 218 219 GoalRIT1 0 231 227 231 229 218 220 216 217 GoalRIT2 0 226 227 233 231 215 215 219 218 GoalRIT3 0 228 228 234 231 215 218 216 220 GoalRIT4 0 230 226 232 229 216 217 221 220

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

P a g e | 241

Bagley Grade 8 Survey with Goals Fall 2008 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA area Math Reading Average RIT 224.8 225.2 232.6 229.7 216.1 217.0 218.8 217.7 GoalRIT1 0 222.5 226.2 233.0 229.3 217.3 215.0 218.4 216.9 GoalRIT2 0 221.8 226.4 231.1 229.6 217.4 217.8 220.2 220.1 GoalRIT3 0 228.0 224.9 235.0 233.3 215.6 218.2 217.6 218.2 GoalRIT4 0 226.6 223.1 231.4 226.9 215.4 217.1 219.2 215.5

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

P a g e | 242

Bagley Grade 8 Survey with Goals Spring 2009 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA area Math Reading Average RIT 229 230 237 237 223 218 224 225 GoalRIT1 0 230 229 239 236 224 219 221 225 GoalRIT2 0 226 232 239 237 225 219 224 226 GoalRIT3 0 233 231 237 237 222 216 224 225 GoalRIT4 0 230 227 235 237 222 217 225 226

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

P a g e | 243

Bagley Grade 9 Survey with Goals Fall 2009 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 233 227 236 232 221 218 223 221 GoalRIT1 0 231 228 237 232 221 217 224 219 GoalRIT2 0 232 228 237 233 219 220 224 223 GoalRIT3 0 234 223 235 230 222 215 221 223 GoalRIT4 0 234 229 237 234 222 221 225 221

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

P a g e | 244

Bagley Grade 7 Survey with Goals Fall 2008 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA area Math Reading Average RIT 217 224 222 223 208 212 210 217 GoalRIT1 0 214 223 221 220 206 213 210 216 GoalRIT2 0 214 222 220 222 211 211 211 218 GoalRIT3 0 223 225 225 226 209 210 209 217 GoalRIT4 0 220 225 222 225 205 213 210 216

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

P a g e | 245

Bagley Grade 7 Survey with Goals Spring 2009 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA area Math Reading Average RIT 222 228 236 231 207 221 220 222 GoalRIT1 0 223 231 237 230 206 217 220 219 GoalRIT2 0 221 225 231 231 207 223 220 224 GoalRIT3 0 222 231 239 233 202 221 219 220 GoalRIT4 0 222 225 234 229 210 223 222 224

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

P a g e | 246

Bagley Grade 8 Survey with Goals Fall 2009 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 218 221 234 231 208 217 218 223 GoalRIT1 0 216 217 232 229 207 213 219 221 GoalRIT2 0 221 223 233 234 205 216 217 223 GoalRIT3 0 217 221 232 229 209 219 218 222 GoalRIT4 0 217 224 237 234 208 220 218 225

GoalRIT1 GoalRIT2 GoalRIT3 GoalRIT4 Number Sense & Statistics & Geometry & Math Computation Functions & Algebra Probability measurement Word recognition / Informational Narrative Reading Vocabulary Comprehension Comprehension Literature

P a g e | 247

Bagley Grade 7 Survey with Goals Fall 2009 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 207 226 219 227 196 212 208 216 GoalRIT1 0 209 223 219 227 196 213 209 216 GoalRIT2 0 205 224 217 224 195 208 209 216 GoalRIT3 0 210 226 219 226 197 209 207 216 GoalRIT4 0 206 229 221 229 196 216 206 217

Bagley NWEA Analysis

In reviewing NWEA (MAP) testing, it is evident that American Indian children tend to achieve at a lower level than do Caucasian children. However, there are some exceptions to this trend. The MAP test data indicate a trend similar to the MCAs; that is, American Indian children succeed at a lower rate than do their Caucasian counterparts. Since the MAP test scores in the fall are the most reliable predictor of MCA II test scores in the spring, this finding is not surprising. Unfortunately, however, aggregate achievement is low for both American Indian and

Caucasian students.

Another concern that is present through an analysis of existing MAP data involves growth during the school year. Aggregate growth over the academic year is not as strong as it should be. In many cases, MAP scores increased very little or decreased. The following examples illustrate this point. P a g e | 248

In Grade 6 Reading, 32% of students scored at or below the 30th percentile on the MAP test in the Fall of 2006, and 44% scored at or below the 30th percentile in the Spring of 2007. During this same time, 43% of the students scored at or above the 51st percentile in the Fall and 24% scored at or above the 51st percentile in the spring. In Grade 7 Math, 33% of the students scored at or below the 30th percentile on the MAP test in the Fall of 2005, and 33% of the students scored at or below the 30th percentile in the Spring of 2006. During this same time, 45% of the students scored at the 51st percentile or above in the Fall of 2005 and 53% of the students scored at or above the 51st percentile in the spring of 2006. In Grade 11 Reading, 27% of the students scored at or below the 30th percentile on the MAP test in the Fall of 2008, and 28% of the students scored at or below the 30th percentile in the Spring of 2009. During this same time, 39% of the students scored at or above the 51st percentile in the Fall of 2008 and 40% scored at or above the 51st percentile in the Spring of 2009.

In Phase II of this study, researchers will seek to determine which factors influence the low growth throughout the school year and the overall low achievement in aggregate of both

American Indian and Caucasian students.

P a g e | 249

Circle of Life

Attendance

Circle of Life Proficiency, Attendance, and Graduation Rate 2005-09 100 80 60 40 20 05-06 0 Math Reading Attendance Grad Rate 06-07 Proficiency Proficiency Rate 07-08 05-06 52 58 86 90 08-09 06-07 44 53 89 85 07-08 44 61 91 73 08-09 37 57 90 86

In terms of proficiency, there are concerns in mathematics. The proficiency rate in mathematics has declined from 52 percent in 2005-06 to 37 percent in 2008-09. Reading proficiency has remained relatively stable during this time frame. During Phase II of this study, researchers will endeavor to discover why math proficiency has declined. In addition, researchers will examine the static nature of reading proficiency to see whether increases could occur.

The attendance rate has increased slightly since 2005-06. An attendance rate of 90 percent is respectable. Researchers will look for possible ways to increase attendance in Phase II of the study.

The graduation rate at Circle of Life has declined slightly since 2005-06, but does show an increase from the lowest levels in 2007-08. Researcher will examine factors that impact the graduation rate in Phase II of this study.

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Discipline

Circle of Life Discipline 2005-09 70 60 50 40 30 20 10 0 K-6 7-8 9-12 K-6 7-8 9-12 K-6 7-8 9-12 K-6 7-8 9-12 2005-2006 2006-2007 2007-2008 2008-2009 Number of Incidents 3 20 40 2 24 58 0 2 23 0 0 9 Student Offenders 3 7 22 2 7 29 0 2 15 0 0 5 (unduplicated) Alcohol-related suspensions 0 0 3 0 1 0 0 0 0 0 0 0 Drug-related suspensions 0 0 0 0 0 6 0 0 2 0 0 0

K-6

The number of incidents declined from 3 in 2005-06 to 2 in 2006-07, and then was 0 in

2007-08 and 2008-09.

7-8

The number of incidents increased from 20 in 2005-06 to 24 in 2006-07, and then 2 in

2007-08 and 0 in 2008-09. There was only 1 alcohol offense by 7th and 8th grade students in 2006-07

9-12

The number of incidents increased from 40 in 2005-06 to 58 in 2006-07, and then declined to 23 in 2007-08 and 9 in 2008-09. There were only 3 alcohol offenses by 9th P a g e | 251

and 12th grade students in 2005-06. There were 6 drug offenses in 2006-07 and 2 in

2007-08.

As is generally the case, more disciplinary violations occur at the secondary level than at the elementary level. Violations of disciplinary policies have decreased significantly since 2005-

06. On the surface, this decrease would appear to be a positive trend. However, there is no way to ascertain whether disciplinary issues have truly decreased or if the reporting and enforcement of disciplinary issues have declined. It is somewhat curious that one in two students, on average, uses alcohol and/or marijuana. However, there were only 12 violations related to drugs and alcohol over a four-year period of discipline reports, and none in 2008-09. In Phase II of this study, researchers will examine the school climate, enforcement of drug and alcohol policies, and whether disciplinary items play a role in the achievement picture.

Circle of Life Drug and Alcohol Use

2003 2008 Circle of Life All BIE Circle of Life All BIE Survival School schools Survival School schools Percentage of students who had 5 drinks in a row 1 or more times in the past 30 days. 67 36 51 28 Percentage of students who used marijuana in the past 30 days 54 48 58 39 Percentage of students who used cocaine in the past 30 days 0 11 0 5

Alcohol and drug use is of significant concern for Circle of Life students. The rates are alarming. Binge drinking has decreased since 2003, but one in two students participated in binge drinking in 2008. Marijuana used increased slightly from 2003 to 2008. Rates of binge drinking P a g e | 252

and marijuana use are higher at Circle of Life than the average rate of BIE schools. Since there is a good chance that alcohol and drug usage impacts student achievement, researchers will examine this issue in Phase II of the study to ascertain whether and at what level alcohol and drug usage impacts student achievement.

Detroit Lakes

Grade 1 Average RIT 2007 170 165 160 155 150 145 140 135 130 125 Male Female Male Female Male Female Male Female Male Female Male Female Male Female Male Female American American American American White White White White Indian Indian Indian Indian Math 1 Math 2 Reading 1 Reading 2 1 1 Average RIT 140 146 163 164 147 149 162 165 154 160 162 167 143 149 158 160

Grade 2 Average RIT 2007 190 185 180 175 170 165 160 155 Male Female Male Female Male Female Male Female Male Female Male Female American American American White White White Indian Indian Indian Language Math Reading 2 Average RIT 171 179 175 184 175 178 179 182 165 180 173 180

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Grade 3 Average RIT 2007 200 195 190 185 180 175 Male Female Male Female Male Female Male Female Male Female Male Female American American American White White White Indian Indian Indian Language Math Reading 3 Average RIT 186 185 193 192 193 190 197 194 183 187 193 193

Grade 4 Average RIT 2007 210 205 200 195 190 185 Male Female Male Female Male Female Male Female Male Female Male Female American American American White White White Indian Indian Indian Language Math Reading 4 Average RIT 194 197 199 203 203 197 206 208 193 201 200 204

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Grade 5 Average RIT 2007 220 215 210 205 200 195 Male Female Male Female Male Female Male Female Male Female Male Female American American American White White White Indian Indian Indian Language Math Reading 5 Average RIT 205 207 206 211 217 217 218 216 204 204 207 209

Grade 6 Average RIT 2007

225230 215220 205210 195200 185190 Male Female Male Female Male Female Male Female Male Female Male Female American American American White White White Indian Indian Indian Language Math Reading 6 Average RIT 204 210 209 215 215 217 220 224 200 208 207 212

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Grade 7 Average RIT 2007 230 225 220 215 210 205 200 195 190 185 Male Female Male Female Male Female Male Female Male Female Male Female American American American White White White Indian Indian Indian Language Math Reading 7 Average RIT 203 212 212 219 217 213 224 226 202 200 211 217

Grade 8 Average RIT 2007

230240 210220 190200 170180 Male Female Male Female Male Female Male Female Male Female Male American American American White White White Indian Indian Indian Language Math Reading 8 Average RIT 208 213 218 220 219 223 233 234 197 212 217

Grade 9 Average RIT 2007 250 240 230 220 210 200 190 Male Female Male Female Male Female Male Female Male Female Male Female American American American White White White Indian Indian Indian Language Math Reading 9 Average RIT 210 214 217 223 233 224 238 239 218 213 222 227

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Grade 10 Average RIT 2007 250 200 150 100 50 0 Male Female Male Female Male Female Male Female Male Female Male Female American American American White White White Indian Indian Indian Language Math Reading 10 Average RIT 214 0 206 205 214 221 229 220 222 223 215 210

Grade 11 Average RIT 2007 250 200 150 100 50 0 Male Female Male Female Male Female Male Female Male Female Male Female American American American White White White Indian Indian Indian Language Math Reading 11 Series1 215 0 206 214 231 220 233 220 195 226 206 219

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Grade 1 Average RIT Fall 2009 166 164 162 160 158 156 154 152 150 148 Male Female Male Female Male Female Male Female American American White White Indian Indian Math Reading 1 Average RIT 158 160 161 163 155 157 160 164

Grade 1 Average RIT Spring 2009 190 188 186 184 182 180 178 176 174 172 Male Female Male Female Male Female Male Female American Indian White American Indian White Math Reading 1 Average RIT 179 184 185 187 178 187 179 183

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Grade 2 Average RIT Fall 2009 182 180 178 176 174 172 170 168 166 164 Male Female Male Female Male Female Male Female Male Female Male Female American American American White White White Indian Indian Indian Language Math Reading 2 Average RIT 170 174 172 173 178 180 179 178 170 172 170 172

Grade 2 Average RIT Spring 2009 200 195 190 185 180 175 Male Female Male Female Male Female Male Female Male Female Male Female American American American White White White Indian Indian Indian Language Math Reading 2 Average RIT 184 183 191 191 190 193 196 195 184 188 189 190

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Grade 3 Average RIT Fall 2009 195 190 185 180 175 170 Male Female Male Female Male Female Male Female Male Female Male Female American American American White White White Indian Indian Indian Language Math Reading 3 Average RIT 179 183 185 188 185 188 193 191 178 185 187 189

Grade 3 Average RIT Spring 2009 212 210 208 206 204 202 200 198 196 194 192 Male Female Male Female Male Female Male Female Male Female Male Female American Indian White American Indian White American Indian White Language Math Reading 3 Average RIT 200 201 200 207 204 204 208 210 199 203 200 206

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Grade 4 Average RIT Fall 2009 210 205 200 195 190 185 Male Female Male Female Male Female Male Female Male Female Male Female American Indian White American Indian White American Indian White Language Math Reading 4 Average RIT 193 201 195 204 201 204 203 206 194 202 196 203

Grade 4 Average RIT Spring 2009 225 220 215 210 205 200 195 190 185 Male Female Male Female Male Female Male Female Male Female Male Female American Indian White American Indian White American Indian White Language Math Reading 4 Average RIT 200 203 208 208 212 208 220 216 199 202 208 208

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Grade 5 Average RIT Fall 2009 220 215 210 205 200 195 190 185 Male Female Male Female Male Female Male Female Male Female Male Female American Indian White American Indian White American Indian White Language Math Reading 5 Average RIT 199 204 204 208 213 206 214 211 195 201 204 205

Grade 5 Average RIT Spring 2009 230 225 220 215 210 205 200 195 Male Female Male Female Male Female Male Female Male Female Male Female American Indian White American Indian White American Indian White Language Math Reading 5 Average RIT 206 209 210 216 221 219 223 227 208 208 212 216

P a g e | 262

Grade 6 Average RIT Fall 2009 220 215 210 205 200 195 190 185 180 Male Female Male Female Male Female Male Female Male Female Male Female American Indian White American Indian White American Indian White Language Math Reading 6 Average RIT 204 207 207 214 215 210 218 218 195 203 203 213

Grade 6 Average RIT Spring 2009 235 230 225 220 215 210 205 Male Female Male Female Male Female Male Female Male Female Male Female American Indian White American Indian White American Indian White Language Math Reading 6 Average RIT 216 218 216 220 227 227 230 230 213 218 216 220

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Grade 7 Average RIT Fall 2009 230 225 220 215 210 205 200 195 Male Female Male Female Male Female Male Female Male Female Male Female American Indian White American Indian White American Indian White Language Math Reading 7 Average RIT 213 216 215 221 225 227 228 228 207 214 214 220

Grade 7 Average RIT Spring 2009 240 230 220 210 200 190 Male Female Male Female Male Female Male Female Male Female Male Female American American American White White White Indian Indian Indian Language Math Reading 7 Average RIT 206 215 213 221 225 229 230 234 207 213 210 220

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Grade 8 Average RIT Fall 2009 240 230 220 210 200 190 180 Male Female Male Female Male Female Male Female Male Female Male Female American American American White White White Indian Indian Indian Language Math Reading 8 Average RIT 208 218 213 221 217 227 228 234 200 218 213 222

Grade 8 Average RIT Spring 2009 245 240 235 230 225 220 215 210 205 200 195 190 Male Female Male Female Male Female Male Female Male Female Male Female American Indian White American Indian White American Indian White Language Math Reading 8 Average RIT 209 219 219 225 219 226 236 239 215 216 220 226

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Grade 9 Average RIT Fall 2009 250 240 230 220 210 200 190 180 Male Female Male Female Male Female Male Female Male Female Male Female American Indian White American Indian White American Indian White Language Math Reading 9 Average RIT 201 215 217 224 221 223 235 238 201 219 221 226

Grade 9 Average RIT Spring 2009 250 240 230 220 210 200 190 180 Male Female Male Female Male Female Male Female Male Female Male Female American American American White White White Indian Indian Indian Language Math Reading 9 Average RIT 206 214 220 225 223 227 240 240 215 218 225 227

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Grade 10 Average RIT Fall 2009 240 230 220 210 200 190 180 Male Female Male Female Male Female Male Female Male Female Male Female American Indian White American Indian White American Indian White Language Math Reading 10 Average RIT 208 201 203 208 226 230 237 236 211 214 223 226

Grade 10 Average RIT Spring 2009 260 250 240 230 220 210 200 190 180 Male Female Male Female Male Female Male Female Male Female Male Female American Indian White American Indian White American Indian White Language Math Reading 10 Average RIT 227 217 208 206 246 228 246 248 238 208 205 195

P a g e | 267

Grade 11 Average RIT Fall 2009 250 240 230 220 210 200 190 180 Male Female Male Female Male Female Male Female Male Female Male Female American Indian White American Indian White American Indian White Language Math Reading 11 Average RIT 201 227 211 225 236 231 244 241 216 234 210 222

Grade 11 Average RIT Spring 2009 300 250 200 150 100 50 0 Male Female Male Female Male Female Male Female Male Female Male Female American Indian White American Indian White American Indian White Language Math Reading 11 Average RIT 215 0 211 214 240 0 226 225 198 0 214 213

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Grade 12 Average RIT Fall 2009 250 200 150 100 50 0 Male Female Male Female Male Female Male Female Male Female Male Female American Indian White American Indian White American Indian White Language Math Reading 12 Average RIT 0 0 213 212 0 0 227 234 0 0 218 226

Detroit Lakes analysis of MAP testing

In reviewing RIT scores for the MAP tests, there are some clear trends that emerge. First, for the majority of grades (2-10), Caucasian children achieve in aggregate at a higher rate than do American Indian children. However, by the end of tenth grade and in grades eleven and twelve, this disparity disappears. In some cases, American Indian children achieve at a higher rate than do Caucasian children. While the first phase of this study cannot provide conclusive evidence as to why this is the case, researchers suspect that American Indian children who do not succeed academically have dropped out by this point. As a result, test data would seem to indicate comparable educational opportunities for American Indian and Caucasian children alike.

Unfortunately, however, it is quite possible that the data simply reflect the success of American

Indian children who successfully navigated the educational setting. With that said, American

Indian success at higher grades does not preclude programming and instructional successes. The second phase of this study will need to examine in greater detail whether dropout rates or other factors are responsible for upper grade success among American Indian children. P a g e | 269

Another very interesting trend that appears to manifest itself throughout the grades, with the notable exception of the last couple of high school years, is aggregate underachievement with boys. Whether Caucasian or American Indian, a significant disparity exists between male and female achievement. This appears to be more pronounced in the Detroit Lakes School District than in other schools that are part of this study. Although the primary focus of this research involves the achievement disparity between American Indian and Caucasian children, this trend is too visible to ignore. The second phase of this study will try to glean reasons as to why boys do not succeed at the same level in aggregate than do girls. Dropout rates and other factors will be examined to see whether common explanations exist between ethnic and gender achievement disparities.

Since MAP test data are the most reliable means by which to predict student success on

MCA IIs, it is critical to fully understand trend successes and failures within this assessment

system. Phase II of the research with involve continued analysis of test data.

Attendance and discipline data

No data were provided within this area. Therefore, no analysis occurred.

P a g e | 270

Fosston

Fosston High School Discipline 35 30 25 20 15 10 5 0 Disruptive/ Swearing/ Bullying/ Fighting/ Insubordina Alcohol/ Violation disrespectf Offensive Harassment Physical Weapons tion Drugs ul Language / Threats Assault Indian M 1 0 1 0 0 1 0 0 Indian F 2 0 0 0 1 0 0 0 White M 31 0 23 2 2 5 0 1 White F 9 0 2 0 0 0 0 0

Fosston Minnesota student survey data

Fosston Minnesota Student Survey Data 2007 6th 9th 12th grade grade grade Frequent Binge Drinking Last Year 12 18 Used only alcohol in the past year 11 29 29 Used both alcohol and other drugs in the last year 14 29 0 days 100 91 82 1 or 2 days 0 9 3 During the last 30 days, how 3 to 5 days 0 0 3 many days did you use marijuana or hashish? 6 to 9 days 0 0 3 10 to 19 days 0 0 3 20 to 29 days 0 0 6 0 100 89 68 1-2 0 4 39 During the last year, on how 3-5 0 2 3 many occasions have you used marijuana or hashish? 6-9 0 0 6 10-39 0 2 3 40+ 0 2 12 P a g e | 271

During the last year, on how 0 100 95 97 many occasions have you sniffed 1-2 0 2 3 glue or used other solvents to get high? 3-5 0 2 0 During the last year, on how 0 98 94 many occasions have you used 1-2 0 6 LSD or other psychadelics? 3-5 2 0

0 98 9 During the last year, on how many occasions have you used 1-2 0 3 "crack"? 3-5 2 0 During the last year, on how 0 98 97 many occasions have you used meth? 1-2 2 3

Analysis of Fosston data

Test score data are analyzed in other sections of this report. In regard to substance abuse and disciplinary data, no unusual red flags are noted. Drug and alcohol usage is present, especially among older students. Phase II of the study will examine factors, including drugs and alcohol, that impact the academic success of American Indian children who attend Fosston.

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Mahnomen

Attendance

Mahnomen Attendance 2008-09 0.96

0.94

0.92

0.90

0.88

0.86

0.84

0.82 KG 1 2 3 4 5 6 7 8 9 10 11 12 Attendance 0.93 0.94 0.95 0.94 0.93 0.94 0.92 0.90 0.90 0.86 0.90 0.89 0.87

I=Indian W=White

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Mahnomen Attendance 2008-09 % 98% 96% 94% 92% 90% 88% 86% 84% 82% 80% I W I W I W I W I W I W I W KG 1 2 3 4 5 6 Attendance 93% 95% 93% 96% 94% 96% 93% 96% 92% 96% 93% 96% 90% 97%

Mahnomen Attendance 2008-09 % 98% 96% 94% 92% 90% 88% 86% 84% 82% 80% I W I W I W I W I W I W 7 8 9 10 11 12 Attendance 88% 95% 88% 95% 83% 94% 87% 95% 83% 94% 83% 94%

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Mahnomen Attendance 2008-2009 98.0% 96.0% 94.0% 92.0% 90.0% 88.0% 86.0% 84.0% 82.0% 80.0% M F M F M F M F M F M F M F M F M F M F M F M F M F 1 2 3 4 5 6 7 8 9 10 11 12 KG Attendance 93. 94. 95. 93. 93. 95. 93. 92. 92. 95. 94. 90. 91. 89. 89. 91. 87. 85. 90. 89. 90. 88. 87. 87. 91. 94.

Mahnomen Attendance 2008-09 % Gender 96% 95% 94% 93% 92% 91% 90% 89% 88% 87% M F M F M F M F M F M F M F KG 1 2 3 4 5 6 Attendance 92% 95% 94% 95% 96% 94% 93% 95% 94% 92% 93% 95% 94% 90%

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Mahnomen Attendance 2008-09 % Gender 94% 92% 90% 88% 86% 84% 82% M F M F M F M F M F M F 7 8 9 10 11 12 Attendance 92% 89% 89% 91% 87% 86% 91% 90% 90% 88% 88% 87%

Attendance analysis

Despite some attendance deficiencies, Mahnomen should be credited with increasing test scores over the last two years. Increasing academic achievement success has been noted elsewhere in this report.

In terms of attendance, Mahnomen does well at the elementary level, for the most part.

However, at the secondary level, attendance declines in upper grades, and in particular, among

American Indian females. The discrepancy between Caucasian and American Indian student attendance increased from 1.7% in Kindergarten to 11.0% in 11th grade at a relatively steady rate. In all likelihood, academic achievement both individually and in aggregate would increase if attendance were improved at the secondary level.

In Phase II of this study researchers will examine the factors that impact attendance, and whether there are strategies to improve the attendance rate of American Indian children (i.e. females). Attendance is a critical factor in regard to academic achievement.

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NWEA Scores

Mahnomen Reading 2009 250.00

200.00

150.00

100.00

50.00

0.00 1 2 3 4 5 6 7 8 9 10 11 12 READ 1/09 166.10 179.92 187.77 195.37 206.14 212.57 213.85 222.31 220.00 223.99 221.74 READ 5/09 172.50 186.19 193.70 198.38 205.66 212.24 215.32 222.69 220.08 227.21 225.74

Ethnicity

I=American Indian W=White

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Mahnomen Reading NWEA 2008-2009 250 200 150 100 50 0 I W I W I W I W I W I W I W I W I W I W I W I W I W 1 2 3 4 5 6 7 8 9 10 11 12 KG READ 1/09 166 164 180 180 188 188 192 198 204 208 213 212 210 218 222 222 216 225 221 228 214 229 0 0 145 150 READ 5/09 171 175 186 186 194 194 195 202 204 210 210 214 212 220 221 225 217 227 225 230 217 232 0 0 153 158

Mahnomen MAP Reading 2009 Gender 240 220 200 180 160 140 120 100 M F M F M F M F M F M F M F KG 1 2 3 4 5 6 READ 1/09 147 149 0 168 178 182 183 193 195 195 205 207 209 216 READ 5/09 156 157 0 174 184 189 189 198 199 198 209 203 209 215

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Mahnomen MAP Reading 2009 Gender 240 220 200 180 160 140 120 100 M F M F M F M F M F M F 7 8 9 10 11 12 READ 1/09 212 216 219 225 218 222 222 226 217 227 0 0 READ 5/09 214 217 221 224 221 219 226 229 221 230 0 0

Mahnomen MAP Reading 2009 Race 240 220 200 180 160 140 120 100 I W I W I W I W I W I W I W KG 1 2 3 4 5 6 READ 1/09 145 150 166 164 180 180 188 188 192 198 204 208 213 212 READ 5/09 153 158 171 175 186 186 194 194 195 202 204 210 210 214

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Mahnomen MAP Reading 2009 Race 240 220 200 180 160 140 120 100 I W I W I W I W I W I W 7 8 9 10 11 12 READ 1/09 210 218 222 222 216 225 221 228 214 229 0 0 READ 5/09 212 220 221 225 217 227 225 230 217 232 0 0

Mahnomen Math 2009

300.00

250.00

200.00

150.00

100.00

50.00

0.00 1 2 3 4 5 6 7 8 9 10 11 12 MATH 1/09 165.64 182.65 191.03 198.25 208.44 215.74 223.57 233.39 230.31 238.99 235.05 MATH 5/09 172.98 187.21 198.90 203.29 214.21 220.16 228.91 237.36 231.52 239.58 238.29

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Math NWEA 2008-2009 260.00 240.00 220.00 200.00 180.00 160.00 140.00 120.00 100.00 1 2 3 4 5 6 7 8 9 10 11 12 KG MATH 1/09 162 168 182 182 188 193 196 199 208 208 213 217 221 226 233 233 231 228 237 240 228 241 152 151 MATH 5/09 170 175 185 189 196 201 203 203 215 213 220 219 225 231 237 237 231 231 238 240 229 246 162 159

Mahnomen MAP Math 2009 Race 260 240 220 200 180 160 140 120 100 I W I W I W I W I W I W I W KG 1 2 3 4 5 6 MATH 1/09 148 153 165 162 180 184 192 191 196 200 206 213 214 218 MATH 5/09 156 163 172 172 186 188 199 199 200 206 212 218 217 224

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Mahnomen MAP Math 2009 Race 260 240 220 200 180 160 140 120 100 I W I W I W I W I W I W 7 8 9 10 11 12 MATH 1/09 219 229 230 238 226 240 236 243 231 239 0 0 MATH 5/09 224 234 236 239 228 238 236 245 232 244 0 0

Math NWEA Percentile Scores 2008-2009 70.00 60.00 50.00 40.00 30.00 20.00 10.00 0.00 1 2 3 4 5 6 7 8 9 10 11 12 KG 1/09 %ile 34. 47. 39. 40. 29. 40. 35. 30. 34. 34. 36. 41. 41. 52. 55. 53. 49. 42. 51. 56. 35. 54. 48. 47. 5/09 %ile 35. 52. 40. 46. 39. 49. 34. 31. 42. 40. 44. 39. 47. 58. 59. 57. 45. 46. 57. 52. 36. 61. 58. 54.

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Mahnomen MAP Math 2009 Gender 260 240 220 200 180 160 140 120 100 M F M F M F M F M F M F M F KG 1 2 3 4 5 6 MATH 1/09 152 151 0 168 182 183 188 194 197 200 209 208 214 218 MATH 5/09 162 160 0 176 185 189 197 201 203 203 215 213 221 219

Mahnomen MAP Math 2009 Gender 260 240 220 200 180 160 140 120 100 M F M F M F M F M F M F 7 8 9 10 11 12 MATH 1/09 221 226 233 233 232 229 237 241 229 241 0.00 0.00 MATH 5/09 226 232 238 237 232 231 239 240 230 247 0.00 0.00

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Mahnomen Math NWEA 2008-2009 260 240 220 200 180 160 140 120 100 M F M F M F M F M F M F M F M F M F M F M F M F M F 1 2 3 4 5 6 7 8 9 10 11 12 KG MATH 1/09 163168182183188194197200209208214218221226233233232229237241229241 0 0 152151 MATH 5/09 170176185189197201203203215213221219226232238237232231239240230247 0 0 162160

Reading

Kindergarten Mahnomen Reading Percentiles Winter 2009 (N = 28) 1-10 11-30 31-50 51-75 76-100 number 10 2 4 5 7 percent 36% 7% 14% 18% 25%

Kindergarten Mahnomen Reading Percentiles Spring 2009 (N = 29) 1-10 11-30 31-50 51-75 76-100 number 3 4 9 4 9 percent 10% 14% 31% 14% 31%

Grade 1 Mahnomen Reading Percentiles Winter 2009 (N = 31) 1-10 11-30 31-50 51-75 76-100 number 4 8 7 6 6 percent 13% 26% 23% 19% 19%

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Grade 1 Mahnomen Reading Percentiles Spring 2009 (N = 32) 1-10 11-30 31-50 51-75 76-100 number 5 5 7 7 8 percent 16% 16% 22% 22% 25%

Grade 2 Mahnomen Reading Percentiles Winter 2009 (N = 40) 1-10 11-30 31-50 51-75 76-100 number 7 13 7 9 4 percent 18% 33% 18% 23% 10%

Grade 2 Mahnomen Reading Percentiles Spring 2009 (N = 44) 1-10 11-30 31-50 51-75 76-100 number 4 13 13 6 8 percent 9% 30% 30% 14% 18%

Grade 3 Mahnomen Reading Percentiles Winter 2009 (N = 43) 1-10 11-30 31-50 51-75 76-100 number 10 12 8 9 4 percent 23% 28% 19% 21% 9%

Grade 3 Mahnomen Reading Percentiles Spring 2009 (N = 43) 1-10 11-30 31-50 51-75 76-100 number 8 9 10 10 6 percent 19% 21% 23% 23% 14%

Grade 4 Mahnomen Reading Percentiles Winter 2009 (N = 36) 1-10 11-30 31-50 51-75 76-100 number 7 13 7 5 4 percent 19% 36% 19% 14% 11%

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Grade 4 Mahnomen Reading Percentiles Spring 2009 (N = 38) 1-10 11-30 31-50 51-75 76-100 number 7 13 9 7 2 percent 18% 34% 24% 18% 5%

Grade 5 Mahnomen Reading Percentiles Winter 2009 (N = 38) 1-10 11-30 31-50 51-75 76-100 number 5 10 8 10 5 percent 13% 26% 21% 26% 13%

Grade 5 Mahnomen Reading Percentiles Spring 2009 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 7 9 9 11 5 percent 17% 22% 22% 27% 12%

Grade 6 Mahnomen Reading Percentiles Winter 2009 (N = 40) 1-10 11-30 31-50 51-75 76-100 number 3 9 10 10 8 percent 8% 23% 25% 25% 20%

Grade 6 Mahnomen Reading Percentiles Spring 2009 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 4 8 11 13 5 percent 10% 20% 27% 32% 12%

Grade 7 Mahnomen Reading Percentiles Winter 2009 (N = 60) 1-10 11-30 31-50 51-75 76-100 number 10 13 10 20 7 percent 17% 22% 17% 33% 12%

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Grade 7 Mahnomen Reading Percentiles Spring 2009 (N = 61) 1-10 11-30 31-50 51-75 76-100 number 11 11 11 17 11 percent 18% 18% 18% 28% 18%

Grade 8 Mahnomen Reading Percentiles Winter 2009 (N = 59) 1-10 11-30 31-50 51-75 76-100 number 4 9 14 20 12 percent 7% 15% 24% 34% 20%

Grade 8 Mahnomen Reading Percentiles Spring 2009 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 4 11 10 19 13 percent 7% 19% 18% 33% 23%

Grade 9 Mahnomen Reading Percentiles Winter 2009 (N = 33) 1-10 11-30 31-50 51-75 76-100 number 5 6 6 11 5 percent 15% 18% 18% 33% 15%

Grade 9 Mahnomen Reading Percentiles Spring 2009 (N = 35) 1-10 11-30 31-50 51-75 76-100 number 7 4 11 8 5 percent 20% 11% 31% 23% 14%

Grade 10 Mahnomen Reading Percentiles Winter 2009 (N = 44) 1-10 11-30 31-50 51-75 76-100 number 4 14 7 10 9 percent 9% 32% 16% 23% 20%

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Grade 10 Mahnomen Reading Percentiles Spring 2009 (N = 44) 1-10 11-30 31-50 51-75 76-100 number 1 10 15 7 11 percent 2% 23% 34% 16% 25%

Grade 11 Mahnomen Reading Percentiles Winter 2009 (N = 38) 1-10 11-30 31-50 51-75 76-100 number 6 13 4 6 9 percent 16% 34% 11% 16% 24%

Grade 11 Mahnomen Reading Percentiles Spring 2009 (N = 35) 1-10 11-30 31-50 51-75 76-100 number 4 6 6 8 11 percent 11% 17% 17% 23% 31%

Math

Kindergarten Mahnomen Math Percentiles Winter 2009 (N = 28) 1-10 11-30 31-50 51-75 76-100 number 3 5 6 11 3 percent 11% 18% 21% 39% 11%

Kindergarten Mahnomen Math Percentiles Spring 2009 (N = 26) 1-10 11-30 31-50 51-75 76-100 number 0 5 6 9 6 percent 0% 19% 23% 35% 23%

Grade 1 Mahnomen Math Percentiles Winter 2009 (N = 32) 1-10 11-30 31-50 51-75 76-100 number 5 14 3 4 6 percent 16% 44% 9% 13% 19%

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Grade 1 Mahnomen Math Percentiles Spring 2009 (N = 31) 1-10 11-30 31-50 51-75 76-100 number 4 11 5 7 4 percent 13% 35% 16% 23% 13%

Grade 2 Mahnomen Math Percentiles Winter 2009 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 7 10 8 11 5 percent 17% 24% 20% 27% 12%

Grade 2 Mahnomen Math Percentiles Spring 2009 (N = 43) 1-10 11-30 31-50 51-75 76-100 number 5 10 15 4 9 percent 12% 23% 35% 9% 21%

Grade 3 Mahnomen Math Percentiles Winter 2009 (N = 43) 1-10 11-30 31-50 51-75 76-100 number 7 13 10 11 2 percent 16% 30% 23% 26% 5%

Grade 3 Mahnomen Math Percentiles Spring 2009 (N = 44) 1-10 11-30 31-50 51-75 76-100 number 8 10 5 13 8 percent 18% 23% 11% 30% 18%

Grade 4 Mahnomen Math Percentiles Winter 2009 (N = 35) 1-10 11-30 31-50 51-75 76-100 number 7 12 6 9 1 percent 20% 34% 17% 26% 3%

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Grade 4 Mahnomen Math Percentiles Spring 2009 (N = 38) 1-10 11-30 31-50 51-75 76-100 number 7 14 7 8 2 percent 18% 37% 18% 21% 5%

Grade 5 Mahnomen Math Percentiles Winter 2009 (N = 38) 1-10 11-30 31-50 51-75 76-100 number 6 9 15 6 2 percent 16% 24% 39% 16% 5%

Grade 5 Mahnomen Math Percentiles Spring 2009 (N = 40) 1-10 11-30 31-50 51-75 76-100 number 4 10 12 11 3 percent 10% 25% 30% 28% 8%

Grade 6 Mahnomen Math Percentiles Winter 2009 (N = 39) 1-10 11-30 31-50 51-75 76-100 number 5 9 13 10 2 percent 13% 23% 33% 26% 5%

Grade 6 Mahnomen Math Percentiles Spring 2009 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 4 9 11 14 3 percent 10% 22% 27% 34% 7%

Grade 7 Mahnomen Math Percentiles Winter 2009 (N = 60) 1-10 11-30 31-50 51-75 76-100 number 11 10 10 15 14 percent 18% 17% 17% 25% 23%

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Grade 7 Mahnomen Math Percentiles Spring 2009 (N = 61) 1-10 11-30 31-50 51-75 76-100 number 8 13 7 15 18 percent 13% 21% 11% 25% 30%

Grade 8 Mahnomen Math Percentiles Winter 2009 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 3 5 18 19 12 percent 5% 9% 32% 33% 21%

Grade 8 Mahnomen Math Percentiles Spring 2009 (N = 54) 1-10 11-30 31-50 51-75 76-100 number 2 5 15 17 15 percent 4% 9% 28% 31% 28%

Grade 9 Mahnomen Math Percentiles Winter 2009 (N = 32) 1-10 11-30 31-50 51-75 76-100 number 4 5 8 9 6 percent 13% 16% 25% 28% 19%

Grade 9 Mahnomen Math Percentiles Spring 2009 (N = 32) 1-10 11-30 31-50 51-75 76-100 number 5 4 9 10 4 percent 16% 13% 28% 31% 13%

Grade 10 Mahnomen Math Percentiles Winter 2009 (N = 43) 1-10 11-30 31-50 51-75 76-100 number 3 7 8 12 13 percent 7% 16% 19% 28% 30%

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Grade 10 Mahnomen Math Percentiles Spring 2009 (N = 42) 1-10 11-30 31-50 51-75 76-100 number 1 7 11 14 9 percent 2% 17% 26% 33% 21%

Grade 11 Mahnomen Math Percentiles Winter 2009 (N = 39) 1-10 11-30 31-50 51-75 76-100 number 8 6 6 11 8 percent 21% 15% 15% 28% 21%

Grade 11 Mahnomen Math Percentiles Spring 2009 (N = 34) 1-10 11-30 31-50 51-75 76-100 number 7 4 5 8 10 percent 21% 12% 15% 24% 29%

MAP test score data

In terms of MAP test score data, data sets are limited. However, a couple of trends appear to be present. First, teachers seem to have the most impact at the primary and upper high school levels of increasing student success on test scores from winter to spring. More data sets would need to be analyzed to see whether these trends continue. This sort of trend tends to get at the value added by teachers and curriculum. A second trend is that there does not appear to be a decline in student success from winter to spring, which is marginally positive. However, a large percentage of students‘ scores reside in lower percentiles, and in many cases, increased test scores are not evident over the course of the academic year. This fact calls into question how much value is added by curriculum and/or teachers. The value added portion of teachers and curriculum should be studied in Phase II of this research. Test scores on both NWEA P a g e | 292

assessments and MCA IIs would likely increase in the value added by teachers and curriculum would increase as well.

NWEA Data 08-09 Reading

Caucasian students outperformed American Indian students in all but 4 grade levels in

January 2009 (1st, 3rd, 6th, and 8th), and this increased to all but 2 grade levels (2nd and 3rd) in May of 2009. The average discrepancy increased from 4.2 in January to 5.6 in May. Females outperformed males at every grade level in January 2009 and in all but 3 (4th, 5th, and 9th) in May

2009. The average discrepancy decreases from 4.8 in January 2009 to 2.8 in May 2009.

NWEA Data 08-09 Math

Caucasian students outperformed American Indian students in all but 2 grade levels in

January 2009 (1st and 3rd). The average discrepancy increased from 5.9 in January to 6.0 in May.

Females outperformed males in all but 3 grade levels (K, 5th, and 9th) in January 2009 and in all but 4 (K, 5th, 8th, and 9th) in May 09. P a g e | 293

Behavior

Mahnomen Discipline 06-07 Gender 250 200 150 100 50 0 F M F M F M F M F M F M 7 8 9 10 11 12 Violation 54 209 40 215 82 196 84 98 29 33 3 20 Insubordination 41 95 30 109 58 145 64 71 25 23 3 16 Disruptive/ disrespectful 11 101 8 93 10 40 15 23 3 8 0 4 Swearing/Offensive Language 0 6 1 7 12 7 3 1 0 1 0 0 Bullying/ Harassment/ Threats 1 5 1 2 2 2 1 3 1 0 0 0 Fighting/ Physical Assault 1 2 0 4 0 2 0 0 0 0 0 0 Alcohol/ Drugs 0 0 0 0 0 0 1 0 0 1 0 0

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Mahnomen Discipline 06-07 Race 300 250 200 150 100 50 0 I W I W I W I W I W I W 7 8 9 10 11 12 Violation 252 10 224 29 235 32 178 4 57 5 20 3 Insubordination 133 3 124 13 175 28 131 4 44 4 16 3 Disruptive/ disrespectful 106 6 87 14 46 4 38 0 10 1 4 0 Swearing/Offensive Language 5 1 6 2 8 0 4 0 1 0 0 0 Bullying/ Harassment/ Threats 5 0 3 0 4 0 4 0 1 0 0 0 Fighting/ Physical Assault 3 0 4 0 2 0 0 0 0 0 0 0 Alcohol/ Drugs 0 0 0 0 0 0 1 0 1 0 0 0

Mahnomen Discipline 07-08 Gender 200 180 160 140 120 100 80 60 40 20 0 F M F M F M F M F M F M 7 8 9 10 11 12 Violation 71 179 54 171 18 92 14 78 18 20 1 22 Insubordination 41 92 31 90 9 35 10 44 12 13 1 7 Disruptive/ disrespectful 20 65 8 53 4 42 4 24 0 3 0 6 Swearing/Offensive Language 5 11 10 16 2 3 0 2 2 2 0 3 Bullying/ Harassment/ Threats 5 5 2 3 0 3 0 3 2 2 0 0 Fighting/ Physical Assault 0 6 3 8 3 8 0 2 2 0 0 4 Alcohol/ Drugs 0 0 0 0 0 1 0 3 0 0 0 2 Weapons 0 0 0 1 0 0 0 0 0 0 0 0

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Mahnomen Discipline 07-08 Race 250 200 150 100 50 0 I W I W I W I W I W I W 7 8 9 10 11 12 Violation 194 53 199 26 102 8 78 75 38 0 20 3 Insubordination 107 24 113 8 42 2 45 42 25 0 7 1 Disruptive/ disrespectful 61 23 47 14 40 6 24 13 3 0 6 0 Swearing/Offensive Language 13 3 22 4 5 0 2 7 4 0 3 0 Bullying/ Harassment/ Threats 8 2 5 0 3 0 2 5 4 0 0 0 Fighting/ Physical Assault 5 1 11 0 11 0 2 6 2 0 3 1 Alcohol/ Drugs 0 0 0 0 1 0 3 2 0 0 1 1 Weapons 0 0 1 0 0 0 0 0 0 0 0 0

Mahnomen Discipline 08-09 Gender 250 200 150 100 50 0 F M F M F M F M F M F M 7 8 9 10 11 12 Violation 30 202 112 210 17 146 8 110 28 39 6 14 Insubordination 18 124 66 103 14 67 5 59 19 29 4 9 Disruptive/ disrespectful 1 64 29 71 0 40 0 43 2 4 0 4 Swearing/Offensive Language 5 5 14 18 1 19 2 5 1 3 0 0 Bullying/ Harassment/ Threats 2 7 2 6 0 11 0 0 2 0 0 0 Fighting/ Physical Assault 0 2 1 7 2 6 1 2 2 2 0 1 Alcohol/ Drugs 4 0 0 5 0 3 0 1 2 0 2 0 Weapons 0 0 0 0 0 0 0 0 0 1 0 0

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Mahnomen Discipline 08-09 Race 250 200 150 100 50 0 I W I W I W I W I W I W 7 8 9 10 11 12 Violation 199 33 238 80 185 163 107 11 33 34 20 0 Insubordination 125 17 134 33 115 81 59 5 22 26 13 0 Disruptive/ disrespectful 52 13 62 37 51 40 37 6 1 5 4 0 Swearing/Offensive Language 10 0 24 8 9 20 7 0 1 3 0 0 Bullying/ Harassment/ Threats 6 3 5 2 5 11 0 0 2 0 0 0 Fighting/ Physical Assault 2 0 8 0 2 8 3 0 4 0 1 0 Alcohol/ Drugs 4 0 5 0 3 3 1 0 2 0 2 0 Weapons 0 0 0 0 0 0 0 0 1 0 0 0

Analysis of Disciplinary Data

There are two trends that appear present in the data provided. First, a disproportionate percentage of disciplinary referrals are attributed to males. Second, a disproportionate percentage of violations are attributed to American Indian students. Since the likelihood of disciplinary referrals negatively impacting academic success is high, Phase II of this study will examine why these disparities exist and whether the violations negatively impact academic success. Strategies that would reduce disciplinary incidences among males and/or American Indian children could result in both individual and aggregate increased academic success among American Indian children.

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Mahnomen Minnesota Student Survey Data

2004 2007 6th grade Frequent Binge Drinking Last Year 4 Used only alcohol in the past year 4 Used both alcohol and other drugs in the last 6th 9th 12th year 7 grade grade grade 0 days 93 93 85 77 1 or 2 days 4 7 11 10 During the last 30 days, 3 to 5 days 0 0 2 0 how many days did you 6 to 9 days 0 0 0 3 use marijuana or hashish? 10 to 19 days 0 0 0 3 20 to 29 days 0 0 2 0 All 30 days 4 0 0 7 0 89 91 74 67 During the last year, on 1-2 7 4 17 10 how many occasions 3-5 0 2 2 7 have you used marijuana 6-9 0 2 2 3 or hashish? 10-39 0 0 0 7 40+ 4 0 4 7 During the last year, on 0 97 100 100 100 how many occasions 1-2 3 0 0 0 have you sniffed glue or 3-5 0 0 0 0 used other solvents to get high? 6-9 0 0 0 0 During the last year, on 0 100 97 how many occasions 1-2 0 3 have you used LSD or 3-5 0 0 other psychadelics? 6-9 0 0 During the last year, on how many occasions 0 100 100 have you used "crack"? 1-2 0 0 During the last year, on 0 100 93 how many occasions have you used meth? 1-2 0 7

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Analysis

Drug and alcohol usage is concern for a percentage of the population. For example, one in ten students uses marijuana on a daily basis. Drug and alcohol usage rates should be considered as potential factors that impact student achievement in Phase II of this study.

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Naytahwaush

Attendance

Naytahwaush Attendance 2006-2010 100.0

95.0

90.0

85.0

80.0

75.0 M F M F M F M F M F M F M F M F KG 1 2 3 4 5 6 7 % 06-07 89.1 92.6 96.4 93.7 95.6 94.7 88.0 91.9 85.5 93.5 87.9 89.4 84.3 96.7 84.4 87.4 % 07-08 94.4 99.5 98.8 95.7 96.8 94.8 96.1 96.9 88.2 100.0 91.7 93.5 80.7 91.6 0.0 0.0 % 08-09 93.6 94.9 95.8 93.5 94.2 89.3 96.8 94.0 96.6 94.8 91.9 100.0 91.2 93.5 0.0 0.0 % 09-10 95.3 97.4 98.6 98.0 98.6 99.5 97.1 96.8 97.9 98.6 96.9 97.1 96.1 98.1 0.0 0.0

The general trend has been an increase in attendance from 2006-07 to 2008-09. Looking at the average attendance of students ages Kindergarten to 6th grade, attendance rates have risen from 91.4% in 2006-07 to 94.2% in 2007-08, a gain of 2.8%. From 2007-08 to 2008-09 a more modest gain of 0.1% was observed (94.2% to 94.3%). No significant attendance differences appear to occur as the result of gender or grade level.

Phase II of this study will examine further attendance trends. Researchers will attempt to discover factors that would increase attendance and achievement.

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NWEA testing

RIT Naytahwaush 2007-09 225.0 215.0 205.0 195.0 185.0 175.0 165.0 155.0 145.0 135.0 125.0 2007 Read 2007 Math 2008 Read 2008 Math 2009 Read 2009 Math 2 M 154.0 162.0 154.9 157.9 152.2 161.6 2 F 160.7 163.3 154.5 158.8 156.8 159.0 3 M 168.0 170.3 169.0 171.0 171.1 176.9 3 F 165.5 173.3 171.3 172.7 173.8 183.0 4 M 180.3 189.3 173.5 182.3 181.3 188.3 4 F 188.0 211.0 180.2 182.0 180.8 186.2 5 M 0.0 0.0 178.7 193.7 180.8 191.0 5 F 0.0 0.0 196.0 204.0 185.1 196.6 6 M 0.0 0.0 0.0 0.0 191.0 209.7 6 F 0.0 0.0 0.0 0.0 203.0 215.0

NWEA Data

The general trends of the NWEA data indicate an overall drop in RIT scores from 2007 to

2008. The average decrease was 2.2 points in Reading, and 7.4 points in Math. While both male and female students had a decrease in both subjects during this time period, the female students had a greater average decrease. From 2007-2008, Math RIT scores decreased 5 points for males, and 8.2 points for females and Reading RIT scores decreased 10.5 points for males, and 34.5 points for females.

While these scores are concerning both groups saw very similar gains in RIT scores over the next year (from 2008-2009). The Reading RIT scores increased 7.2 points for males and 5.4 P a g e | 302

points for females, and the Math RIT scores increased 15.6 points for males, and 15.8 points for females.

It is a bit curious that scores have fluctuated in the aforementioned manner. In Phase II of this study, researchers will attempt to ascertain factors that have influenced this variation.

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Pine Point

Attendance.

Percent Attendance 2006-2009 100 95 90 85 80 75 M F M F M F M F M F M F M F M F M F KG 1 2 3 4 5 6 7 8 % 06-07 97.7 93.5 95.6 92.6 93.5 93.6 99.4 90.8 89.9 94.3 89.3 92 89.8 93.7 80.1 89.7 90.1 90.6 % 07-08 96.6 90.2 92.7 95 96 90.1 96.2 97.5 96.9 90.9 87.3 92.7 93.3 88.7 95.6 90.3 84.1 93.8 % 08-09 93.8 92.2 95.9 89.8 93.1 94.5 95.5 94.5 94.9 98 95.1 85.8 96.4 86.3 92.8 81.7 92.8 95.9

Percent Attendance 2006-07 100 95 90 85 80 75 M F M F M F M F M F M F M F M F M F KG 1 2 3 4 5 6 7 8 %Attend. 97.7 93.5 95.6 92.6 93.5 93.6 99.4 90.8 89.9 94.3 89.3 92 89.8 93.7 80.1 89.7 90.1 90.6

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Percent Attendance 2007-08 100 95 90 85 80 75 M F M F M F M F M F M F M F M F M F KG 1 2 3 4 5 6 7 8 %Attend. 96.6 90.2 92.7 95 96 90.1 96.2 97.5 96.9 90.9 87.3 92.7 93.3 88.7 95.6 90.3 84.1 93.8

Percent Attendance 2008-09 100

95

90

85

80

75 M F M F M F M F M F M F M F M F M F KG 1 2 3 4 5 6 7 8 %Attend. 93.8 92.2 95.9 89.8 93.1 94.5 95.5 94.5 94.9 98 95.1 85.8 96.4 86.3 92.8 81.7 92.8 95.9

Attendance

While attendance rates have been on the average increasing for all students from 2006-

2009 (92.0% in 2006-07, 92.6% in 2007-08, 92.7% in 2008-09) there are differences between the averages for males and females. The attendance rates for males has been increasing from 2006-

2009 (91.7% in 2006-07, 93.2% in 2007-08, 94.5% in 2008-09). The attendance rate for females has been decreasing from 2006-2009 (92.3% in 2006-07, 92.1 in 2007-08, 91% in 2008-09). P a g e | 305

In Phase II of this study, researchers will examine attendance trends. In particular, researchers will seek factors that impact attendance rates between genders.

MCA-II proficiency scores

Pine Point Percent Proficient MCA -II scores 120 100 80 60 40 20 0 M F M F M F M F M F M F 3 4 5 6 7 8 2006 Math 50 100 40 0 100 0 100 0 100 33.3 100 0 2006 Reading 50 80 20 0 33.3 50 100 100 0 33.3 100 0 2007 Math 100 100 100 80 50 100 100 66.7 100 100 100 100 2007 Reading 100 50 100 80 33.3 0 100 33.3 66.7 100 50 100 2008 Math 100 100 100 100 66.7 100 33.3 100 66.7 50 66.7 0 2008 Reading 75 75 100 100 66.7 100 100 100 25 100 100 0 2009 Math 100 100 100 100 50 80 100 66.7 50 100 50 0 2009 Reading 100 100 66.7 100 100 80 100 66.7 33.3 50 50 0

Math

The average trend of MCA-II Math scores has increased in proficiency (from 62.3% to

81.5%), although the percentages have fluctuated from year to year. In 2006, math proficiency scores were 62.3%. They then increased in 2007 to 91.4%, then decreased in 2008 to 73.6%, and then increased in 2009 to 81.5%. While the difference in scores has been similar between males and females (within 3 points) in 2007 and 2008, the difference between males and females was large in both 2006 (81.7% for males, and 33.3% for females) and 2009 (75% for males, and

89.3% for females). There are no obvious explanations for these variations. P a g e | 306

Reading

The average trend of MCA-II Reading scores shows an increase in proficiency (from

51.5% to 70.6%) although the percentages have fluctuated from year to year. In 2006, reading proficiency scores were 51.5%. They then increased in 2007 to 67.8%, and then in 2008 to

78.5%, and they decreased in 2009 to 70.6%. While the difference in scores has been similar between males and females (within 3 points) in 2006 and 2008, the difference between males and females was large in both 2007 (75.0% for males, and 60.6% for females) and 2009 (75% for males, and 66.1% for females). As with math, there is no clear explanation as to why these variations exist.

In Phase II of the study, researchers will examine these variations in more detail. In addition, researchers will attempt to discover factors that impact the success of students in regard to MCA II proficiency.

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NWEA Scores

Pine Point Reading RIT 2006-09 250 200 150 100 50 0 Spring 2006 Fall 2006 Spring 2007 Fall 2007 Spring 2008 Fall 2008 Fall 2009 1M 0 0 0 0 160 159 143 1F 0 0 0 0 168 170 149 2M 199 164 174 165 174 164 158 2F 166 157 180 153 159 117 151 3M 175 183 204 178 178 183 177 3F 190 160 178 183 191 174 183 4M 179 183 170 0 198 187 173 4F 0 189 191 187 184 194 181 5M 190 178 184 178 181 0 207 5F 189 188 0 192 193 178 188 6M 220 182 201 189 197 196 207 6F 223 195 194 181 197 199 188 7M 209 226 208 209 201 197 201 7F 208 216 214 197 195 190 210 8M 201 207 207 218 217 204 183 8F 0 204 204 0 211 195 189

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Pine Point Math RIT 2006-09 300 250 200 150 100 50 0 Spring 2006 Fall 2006 Spring 2007 Fall 2007 Spring 2008 Fall 2008 Fall 2009 1M 0 0 0 0 157 160 150 1F 0 0 0 0 166 163 145 2M 196 0 177 162 179 173 162 2F 181 0 178 163 170 184 151 3M 176 205 203 178 193 185 180 3F 197 180 189 185 190 182 182 4M 189 165 185 0 202 193 193 4F 0 196 201 191 198 198 191 5M 204 188 195 187 201 202 202 5F 189 199 0 202 203 180 191 6M 219 201 227 203 206 189 202 6F 221 198 196 204 213 212 191 7M 222 232 225 221 223 197 217 7F 205 221 0 196 202 212 205 8M 223 226 242 232 229 233 208 8F 0 202 218 0 218 209 220

NWEA RIT data

Math

The average Math RIT score has been fluctuating, yet decreasing from 202 in 2006 to

187 in 2009 (202 in Spring 2006, 201 in Fall 2006, 203 in Spring 2007, 194 in Fall 2007, 197 in

Spring 2008, 192 in Fall in 2008, and 187 in Fall 2009). This trend has been the same for both males and females. Males Math RIT scores were 204 in Spring 2006, 203 in Fall 2006, 208 in P a g e | 309

Spring 2007, 197 in Fall 2007, 199 in Spring 2008, 191 in Fall in 2008, and 189 in Fall 2009.

Females RIT scores were 199 in Spring 2006, 199 in Fall 2006, 196 in Spring 2007, 190 in Fall

2007, 195 in Spring 2008, 192 in Fall in 2008, and 184 in Fall 2009.

Reading

The average Reading RIT score has been fluctuating, yet decreasing from 196 in 2006 to

180 in 2009 (196 in Spring 2006, 188 in Fall 2006, 193 in Spring 2007, 186 in Fall 2007, 188 in

Spring 2008, 180 in Fall in 2008, and 180 in Fall 2009). This trend has been the same for both males and females. Males Reading RIT scores were 196 in Spring 2006, 189 in Fall 2006, 193 in

Spring 2007, 186 in Fall 2007, 188 in Spring 2008, 180 in Fall in 2008, and 180 in Fall 2009.

Females RIT scores were 195 in Spring 2006, 187 in Fall 2006, 193 in Spring 2007, 182 in Fall

2007, 187 in Spring 2008, 177 in Fall in 2008, and 180 in Fall 2009.

This decrease does concern researchers. In Phase II of this study, researchers will attempt to discover factors that have contributed to the trend of decreasing scores.

Behavior

Fighting/ Disruptive/ Physical Insubordi- Disorderly Bullying/ Theft/ Year Ethnicity Gender Assault nation Conduct Harassment/Threats Vandalism Weapon 2007- M 8 N/A 10 N/A N/A 1 08 Indian F N/A N/A 1 N/A N/A N/A 2008- M 33 25 45 N/A 1 2 09 Indian F 9 19 24 2 N/A N/A 2009- M 6 6 2 1 N/A N/A 10 Indian F N/A N/A N/A N/A N/A N/A

Behavior

From 2007-08 to 2008-09, there has been an increase in all of the categories of behavioral offenses. Although the categories of insubordination, bullying/harassment/threats, and P a g e | 310

theft/vandalism had no offenses in 2007-08, the increase in these and other categories is indicative of an overall rise in behavioral offenses. While there were no fighting/physical assaults for females in 2007-08, they increased to 9 in 2008-09. For males fighting/physical assaults were at 8 in 2007-08 and increased to 33 in 2008-09. Disruptive/disorderly conduct increased from 10 for males and 1 for females in 2007-08 to 45 for males and 24 for females.

Weapon offenses for males increased from 1 in 2007-08 to 2 in 2008-09.

There is a possibility that increased behavioral offenses are tied to the decreasing proficiency scores on exams. In Phase II of this study, researchers will seek to determine whether there is a direct connection between increased behavioral offenses and decreased test scores.

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WOWE

NWEA scores Ogema and Waubun elementary schools

Language

Grade 2 Language Percentiles Fall 2007 (N = 34) 1-10 11-30 31-50 51-75 76-100 number 15 7 10 12 2 percent 44% 21% 29% 35% 6%

Grade 2 Language Percentiles Spring 2008 (N = 47) 1-10 11-30 31-50 51-75 76-100 number 5 14 9 16 3 percent 11% 30% 19% 34% 6%

Grade 3 Language Percentiles Fall 2008 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 9 5 11 11 5 percent 22% 12% 27% 27% 12%

Grade 3 Language Percentiles Spring 2009 (N = 40) 1-10 11-30 31-50 51-75 76-100 number 6 9 9 13 3 percent 15% 23% 23% 33% 8%

Grade 4 Language Percentiles Fall 2009 (N = 42) 1-10 11-30 31-50 51-75 76-100 number 11 3 7 15 6 percent 26% 7% 17% 36% 14%

Grade 4 Language Percentiles winter 2010 (N = 36) 1-10 11-30 31-50 51-75 76-100 number 2 9 8 12 5 percent 6% 25% 22% 33% 14%

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Math

Grade 2 Math Percentiles Fall 2007 (N = 46) 1-10 11-30 31-50 51-75 76-100 number 15 9 8 11 3 percent 33% 20% 17% 24% 7%

Grade 2 Math Percentiles Spring 2008 (N = 47) 1-10 11-30 31-50 51-75 76-100 number 6 7 13 14 7 percent 13% 15% 28% 30% 15%

Grade 3 Math Percentiles Fall 2008 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 3 9 9 8 12 percent 7% 22% 22% 20% 29%

Grade 3 Math Percentiles Spring 2009 (N = 40) 1-10 11-30 31-50 51-75 76-100 number 2 4 11 10 13 percent 5% 10% 28% 25% 33%

Grade 4 Math Percentiles Fall 2009 (N = 43) 1-10 11-30 31-50 51-75 76-100 number 4 13 10 9 7 percent 9% 30% 23% 21% 16%

Grade 4 Math Percentiles winter 2010 (N = 38) 1-10 11-30 31-50 51-75 76-100 number 1 7 7 19 4 percent 3% 18% 18% 50% 11%

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Reading

Grade 2 Reading Percentiles Fall 2007 (N = 46) 1-10 11-30 31-50 51-75 76-100 number 12 13 10 10 1 percent 26% 28% 22% 22% 2%

Grade 2 Reading Percentiles Spring 2008 (N = 47) 1-10 11-30 31-50 51-75 76-100 number 6 9 11 10 11 percent 13% 19% 23% 21% 23%

Grade 3 Reading Percentiles Fall 2008 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 9 5 5 16 8 percent 22% 12% 12% 39% 20%

Grade 3 Reading Percentiles Spring 2009 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 4 8 11 11 7 percent 10% 20% 27% 27% 17%

Grade 4 Reading Percentiles Fall 2009 (N = 43) 1-10 11-30 31-50 51-75 76-100 number 9 12 9 10 3 percent 21% 28% 21% 23% 7%

Grade 4 Reading Percentiles winter 2010 (N = 38) 1-10 11-30 31-50 51-75 76-100 number 3 11 7 8 7 percent 8% 29% 18% 21% 18%

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Language

Grade 3 Language Percentiles Fall 2007 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 19 9 5 3 5 percent 46% 22% 12% 7% 12%

Grade 3 Language Percentiles Spring 2008 (N = 43) 1-10 11-30 31-50 51-75 76-100 number 16 7 4 10 6 percent 37% 16% 9% 23% 14%

Grade 4 Language Percentiles Fall 2008 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 13 10 3 12 3 percent 32% 24% 7% 29% 7%

Grade 4 Language Percentiles Spring 2009 (N = 39) 1-10 11-30 31-50 51-75 76-100 number 10 6 7 9 6 percent 26% 15% 18% 23% 15%

Grade 5 Language Percentiles Fall 2009 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 15 11 3 10 2 percent 37% 27% 7% 24% 5%

Grade 5 Language Percentiles Winter 2010 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 11 10 10 4 6 percent 27% 24% 24% 10% 15%

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Math

Grade 3 Math Percentiles Fall 2007 (N = 42) 1-10 11-30 31-50 51-75 76-100 number 15 4 9 3 9 percent 36% 10% 21% 7% 21%

Grade 3 Math Percentiles Spring 2008 (N = 43) 1-10 11-30 31-50 51-75 76-100 number 7 8 8 9 11 percent 16% 19% 19% 21% 26%

Grade 4 Math Percentiles Fall 2008 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 11 4 8 9 9 percent 27% 10% 20% 22% 22%

Grade 4 Math Percentiles Spring 2009 (N = 39) 1-10 11-30 31-50 51-75 76-100 number 6 4 10 5 14 percent 15% 10% 26% 13% 36%

Grade 5 Math Percentiles Fall 2009 (N = 40) 1-10 11-30 31-50 51-75 76-100 number 11 7 10 9 3 percent 28% 18% 25% 23% 8%

Grade 5 Math Percentiles Winter 2010 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 6 10 10 6 9 percent 15% 24% 24% 15% 22%

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Reading

Grade 3 Reading Percentiles Fall 2007 (N = 42) 1-10 11-30 31-50 51-75 76-100 number 13 15 3 9 2 percent 31% 36% 7% 21% 5%

Grade 3 Reading Percentiles Spring 2008 (N = 43) 1-10 11-30 31-50 51-75 76-100 number 11 11 6 9 6 percent 26% 26% 14% 21% 14%

Grade 4 Reading Percentiles Fall 2008 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 14 9 4 8 6 percent 34% 22% 10% 20% 15%

Grade 4 Reading Percentiles Spring 2009 (N = 38) 1-10 11-30 31-50 51-75 76-100 number 8 9 4 11 6 percent 21% 24% 11% 29% 16%

Grade 5 Reading Percentiles Fall 2009 (N = 40) 1-10 11-30 31-50 51-75 76-100 number 11 9 5 12 3 percent 28% 23% 13% 30% 8%

Grade 5 Reading Percentiles Winter 2010 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 12 6 8 8 7 percent 29% 15% 20% 20% 17%

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Language

Grade 4 Language Percentiles Fall 2007 (N = 64) 1-10 11-30 31-50 51-75 76-100 number 15 18 10 12 9 percent 23% 28% 16% 19% 14%

Grade 4 Language Percentiles Spring 2008 (N = 63) 1-10 11-30 31-50 51-75 76-100 number 10 19 9 19 6 percent 16% 30% 14% 30% 10%

Grade 5 Language Percentiles Fall 2008 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 17 8 9 16 7 percent 30% 14% 16% 28% 12%

Grade 5 Language Percentiles Spring 2009 (N = 56) 1-10 11-30 31-50 51-75 76-100 number 17 13 7 14 5 percent 30% 23% 13% 25% 9%

Grade 6 Language Percentiles Fall 2009 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 24 13 8 10 2 percent 42% 23% 14% 18% 4%

Grade 6 Language Percentiles Winter 2010 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 7 15 11 16 8 percent 12% 26% 19% 28% 14%

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Math

Grade 4 Math Percentiles Fall 2007 (N = 64) 1-10 11-30 31-50 51-75 76-100 number 8 14 15 15 12 percent 13% 22% 23% 23% 19%

Grade 4 Math Percentiles Spring 2008 (N = 64) 1-10 11-30 31-50 51-75 76-100 number 6 17 8 16 17 percent 9% 27% 13% 25% 27%

Grade 5 Math Percentiles Fall 2008 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 12 11 8 13 13 percent 21% 19% 14% 23% 23%

Grade 5 Math Percentiles Spring 2009 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 14 9 8 15 11 percent 25% 16% 14% 26% 19%

Grade 6 Math Percentiles Fall 2009 (N = 58) 1-10 11-30 31-50 51-75 76-100 number 20 10 8 11 9 percent 34% 17% 14% 19% 16%

Grade 6 Math Percentiles Winter 2010 (N = 58) 1-10 11-30 31-50 51-75 76-100 number 10 16 7 8 17 percent 17% 28% 12% 14% 29% Reading

Grade 4 Reading Percentiles Fall 2007 (N = 64) 1-10 11-30 31-50 51-75 76-100 number 12 24 3 17 8 percent 19% 38% 5% 27% 13% P a g e | 319

Grade 4 Reading Percentiles Spring 2008 (N = 64) 1-10 11-30 31-50 51-75 76-100 number 6 19 14 17 8 percent 9% 30% 22% 27% 13%

Grade 5 Reading Percentiles Fall 2008 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 12 13 8 18 6 percent 21% 23% 14% 32% 11%

Grade 5 Reading Percentiles Spring 2009 (N = 56) 1-10 11-30 31-50 51-75 76-100 number 15 9 14 8 10 percent 27% 16% 25% 14% 18%

Grade 6 Reading Percentiles Fall 2009 (N = 58) 1-10 11-30 31-50 51-75 76-100 number 23 13 9 11 2 percent 40% 22% 16% 19% 3%

Grade 6 Reading Percentiles Winter 2010 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 12 16 9 13 7 percent 21% 28% 16% 23% 12% Language

Grade 5 Language Percentiles Fall 2007 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 8 14 6 12 5 percent 18% 31% 13% 27% 11%

Grade 5 Language Percentiles Spring 2008 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 3 14 12 7 9 percent 7% 31% 27% 16% 20%

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Grade 6 Language Percentiles Fall 2008 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 9 12 7 13 4 percent 20% 27% 16% 29% 9%

Grade 6 Language Percentiles Spring 2009 (N = 42) 1-10 11-30 31-50 51-75 76-100 number 8 5 10 11 8 percent 19% 12% 24% 26% 19%

Math

Grade 5 Math Percentiles Fall 2007 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 8 8 10 13 6 percent 18% 18% 22% 29% 13%

Grade 5 Math Percentiles Spring 2008 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 6 10 11 13 5 percent 13% 22% 24% 29% 11%

Grade 6 Math Percentiles Fall 2008 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 5 10 7 15 8 percent 11% 22% 16% 33% 18%

Grade 6 Math Percentiles Spring 2009 (N = 46) 1-10 11-30 31-50 51-75 76-100 number 11 5 8 17 5 percent 24% 11% 17% 37% 11% Reading

Grade 5 Reading Percentiles Fall 2007 (N = 43) 1-10 11-30 31-50 51-75 76-100 number 8 7 12 9 7 percent 19% 16% 28% 21% 16% P a g e | 321

Grade 5 Reading Percentiles Spring 2008 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 5 12 4 13 11 percent 11% 27% 9% 29% 24%

Grade 6 Reading Percentiles Fall 2008 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 6 10 6 12 11 percent 13% 22% 13% 27% 24%

Grade 6 Reading Percentiles Spring 2009 (N = 46) 1-10 11-30 31-50 51-75 76-100 number 8 11 6 14 7 percent 17% 24% 13% 30% 15%

Language

Grade 6 Language Percentiles Fall 2008 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 9 12 7 13 4 percent 20% 27% 16% 29% 9%

Grade 6 Language Percentiles Spring 2009 (N = 42) 1-10 11-30 31-50 51-75 76-100 number 8 5 10 11 8 percent 19% 12% 24% 26% 19%

Math

Grade 6 Math Percentiles Fall 2008 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 5 10 7 15 8 percent 11% 22% 16% 33% 18%

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Grade 6 Math Percentiles Spring 2009 (N = 46) 1-10 11-30 31-50 51-75 76-100 number 11 5 8 17 5 percent 24% 11% 17% 37% 11%

Reading

Grade 6 Reading Percentiles Fall 2008 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 6 10 6 12 11 percent 13% 22% 13% 27% 24%

Grade 6 Reading Percentiles Spring 2009 (N = 46) 1-10 11-30 31-50 51-75 76-100 number 8 11 6 14 7 percent 17% 24% 13% 30% 15%

Language

Grade 2 Language Percentiles Fall 2008 (N = 52) 1-10 11-30 31-50 51-75 76-100 number 19 7 6 11 9 percent 37% 13% 12% 21% 17%

Grade 2 Language Percentiles Spring 2009 (N = 49) 1-10 11-30 31-50 51-75 76-100 number 5 9 7 15 13 percent 10% 18% 14% 31% 27%

Grade 3 Language Percentiles Fall 2009 (N = 47) 1-10 11-30 31-50 51-75 76-100 number 6 12 10 10 9 percent 13% 26% 21% 21% 19%

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Grade 3 Language Percentiles winter 2010 (N = 48) 1-10 11-30 31-50 51-75 76-100 number 3 10 14 13 8 percent 6% 21% 29% 27% 17%

Math

Grade 2 Math Percentiles Fall 2008 (N = 52) 1-10 11-30 31-50 51-75 76-100 number 6 13 11 9 1 percent 12% 25% 21% 17% 2%

Grade 2 Math Percentiles Spring 2009 (N = 50) 1-10 11-30 31-50 51-75 76-100 number 3 8 6 14 19 percent 6% 16% 12% 28% 38%

Grade 3 Math Percentiles Fall 2009 (N = 47) 1-10 11-30 31-50 51-75 76-100 number 7 6 7 15 12 percent 15% 13% 15% 32% 26%

Grade 3 Math Percentiles winter 2010 (N = 49) 1-10 11-30 31-50 51-75 76-100 number 3 9 7 13 17 percent 6% 18% 14% 27% 35% Reading

Grade 2 Reading Percentiles Fall 2008 (N = 52) 1-10 11-30 31-50 51-75 76-100 number 17 10 10 4 11 percent 33% 19% 19% 8% 21%

Grade 2 Reading Percentiles Spring 2009 (N = 48) 1-10 11-30 31-50 51-75 76-100 number 5 6 12 11 14 percent 10% 12% 24% 22% 28% P a g e | 324

Grade 3 Reading Percentiles Fall 2009 (N = 46) 1-10 11-30 31-50 51-75 76-100 number 8 11 6 12 9 percent 17% 24% 13% 26% 20%

Grade 3 Reading Percentiles winter 2010 (N = 49) 1-10 11-30 31-50 51-75 76-100 number 1 17 11 14 6 percent 2% 35% 22% 29% 12%

Grade 5 Language Percentiles Fall 2007 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 8 14 6 12 5 percent 18% 31% 13% 27% 11%

Grade 5 Language Percentiles Spring 2008 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 3 14 12 7 9 percent 7% 31% 27% 16% 20%

Grade 5 Math Percentiles Fall 2007 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 8 8 10 13 6 percent 18% 18% 22% 29% 13%

Grade 5 Math Percentiles Spring 2008 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 6 10 11 13 5 percent 13% 22% 24% 29% 11%

Grade 5 Reading Percentiles Fall 2007 (N = 43) 1-10 11-30 31-50 51-75 76-100 number 8 7 12 9 7 percent 19% 16% 28% 21% 16%

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Grade 5 Reading Percentiles Spring 2008 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 5 12 4 13 11 percent 11% 27% 9% 29% 24%

Grade 5 Survey with Goals Fall 2007 230 220 210 200 190 180 170 160 150 Gende Male Female Male Female Male Female Male Female Male Female Male Female r Ethnici American American American White White White ty Indian Indian Indian NWEA Language Math Reading area Average RIT 191.27 205.65 214.60 204.63 201.20 209.35 218.40 207.75 197.92 201.29 202.17 203.50 GoalRIT1 0 194.33 205.88 212.40 199.88 200.33 207.47 214.60 203.25 195.17 204.12 201.17 203.13 GoalRIT2 0 189.93 204.47 212.00 205.88 199.20 211.94 218.20 209.88 198.17 200.88 202.00 204.63 GoalRIT3 0 190.47 205.29 217.00 205.75 202.47 209.06 220.00 210.25 199.08 199.18 201.50 202.75 GoalRIT4 0 189.87 207.06 216.60 206.63 202.87 208.82 220.60 208.00 199.75 200.53 204.00 203.38

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Grade 5 Survey with Goals Spring 2008 240 230 220 210 200 190 180 170 160 150 Gende Male Female Male Female Male Female Male Female Male Female Male Female r Ethnici American American American White White White ty Indian Indian Indian NWEA Language Math Reading area Average RIT 204.77 209.32 220.20 213.75 212.46 213.79 225.00 213.75 204.00 210.63 218.80 212.13 GoalRIT1 0 204.77 206.47 221.80 215.00 209.23 215.37 223.20 213.88 204.69 210.00 215.40 206.38 GoalRIT2 0 203.85 207.42 218.80 218.00 212.62 212.68 221.20 211.13 201.85 208.95 225.00 209.88 GoalRIT3 0 206.92 211.21 218.80 211.38 213.15 216.47 227.20 216.63 201.31 210.89 215.60 215.50 GoalRIT4 0 203.62 212.05 221.40 210.63 213.85 210.47 228.60 214.50 207.85 212.79 219.40 216.38

Grade 6 Language Percentiles Fall 2007 (N = 42) 1-10 11-30 31-50 51-75 76-100 number 11 12 8 8 3 percent 26% 29% 19% 19% 7%

Grade 6 Language Percentiles Spring 2008 (N = 43) 1-10 11-30 31-50 51-75 76-100 number 5 9 14 10 5 percent 12% 21% 33% 23% 12%

Grade 6 Math Percentiles Fall 2007 (N = 43) 1-10 11-30 31-50 51-75 76-100 number 5 18 7 7 6 percent 12% 42% 16% 16% 14% P a g e | 327

Grade 6 Math Percentiles Spring 2008 (N = 43) 1-10 11-30 31-50 51-75 76-100 number 3 11 13 9 7 percent 7% 26% 30% 21% 16%

Grade 6 Reading Percentiles Fall 2007 (N = 44) 1-10 11-30 31-50 51-75 76-100 number 14 12 11 5 2 percent 32% 27% 25% 11% 5%

Grade 6 Reading Percentiles Spring 2008 (N = 43) 1-10 11-30 31-50 51-75 76-100 number 5 13 5 15 5 percent 12% 30% 12% 35% 12%

Grade 6 Survey with Goals Fall 2007 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American American American White White White y Indian Indian Indian NWEA Language Math Reading area Average RIT 200.29 205.36 212.40 212.33 210.67 206.64 224.20 219.50 195.61 202.21 199.17 208.50 GoalRIT1 0 200.65 207.29 208.00 215.83 209.44 201.43 225.00 221.50 196.83 199.71 200.17 207.17 GoalRIT2 0 201.29 204.64 212.80 207.50 207.67 207.00 222.40 218.33 194.89 200.57 195.17 211.00 GoalRIT3 0 200.35 204.07 211.40 210.50 210.94 208.29 227.60 219.00 194.22 202.43 199.83 208.50 GoalRIT4 0 198.24 206.00 217.60 215.67 214.83 210.21 222.80 219.33 196.22 206.36 200.50 207.17

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Grade 6 Survey with Goals Spring 2008 250 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American American American White White White y Indian Indian Indian NWEA Language Math Reading area Average RIT 211.00 212.36 223.40 214.29 220.35 217.79 235.80 224.00 208.06 211.64 216.60 215.57 GoalRIT1 0 211.76 213.93 224.40 212.14 219.76 217.93 238.00 226.29 208.59 212.29 215.80 220.29 GoalRIT2 0 210.12 210.57 219.60 214.86 219.76 216.14 229.60 220.86 208.00 213.00 215.40 213.86 GoalRIT3 0 213.12 213.14 221.00 214.86 221.24 218.36 238.00 223.00 204.88 211.57 218.80 217.29 GoalRIT4 0 209.71 211.79 227.80 216.29 221.35 218.71 236.60 224.86 210.76 209.93 216.40 210.29

Grade 5 Language Percentiles Fall 2008 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 17 8 9 16 7 percent 30% 14% 16% 28% 12%

Grade 5 Language Percentiles Spring 2009 (N = 56) 1-10 11-30 31-50 51-75 76-100 number 17 13 7 14 5 percent 30% 23% 13% 25% 9%

Grade 5 Math Percentiles Fall 2008 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 12 11 8 13 13 percent 21% 19% 14% 23% 23%

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Grade 5 Math Percentiles Spring 2009 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 14 9 8 15 11 percent 25% 16% 14% 26% 19%

Grade 5 Reading Percentiles Fall 2008 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 12 13 8 18 6 percent 21% 23% 14% 32% 11%

Grade 5 Reading Percentiles Spring 2009 (N = 56) 1-10 11-30 31-50 51-75 76-100 number 15 9 14 8 10 percent 27% 16% 25% 14% 18%

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Grade 5 Survey with Goals Fall 2008 230 220 210 200 190 180 170 160 150 Gende Male Female Male Female Male Female Male Female Male Female Male Female r Ethnici American American American White White White ty Indian Indian Indian NWEA Language Math Reading area Average RIT 193.73 203.76 207.14 200.86 202.09 208.90 216.43 210.86 196.82 202.29 208.71 197.86 GoalRIT1 0 194.73 203.05 203.71 196.43 200.91 209.90 215.57 211.71 197.73 202.00 208.43 196.43 GoalRIT2 0 191.09 202.19 207.86 204.57 199.50 206.75 214.14 210.29 193.73 200.71 210.00 194.29 GoalRIT3 0 195.23 205.00 208.29 202.57 203.55 212.70 217.00 210.71 195.18 203.86 205.86 198.86 GoalRIT4 0 194.05 204.33 207.29 199.86 204.00 204.05 218.86 209.14 199.45 202.10 211.43 201.86

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Grade 5 Survey with Goals Spring 2009 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American American American White White White y Indian Indian Indian NWEA Language Math Reading area Average RIT 198.81 204.83 212.33 207.00 210.05 212.96 222.17 223.50 203.18 201.61 219.17 206.17 GoalRIT1 0 197.33 203.70 212.17 204.17 213.82 214.00 220.83 226.17 203.82 204.39 221.50 202.50 GoalRIT2 0 198.19 201.61 210.00 207.67 207.09 211.30 219.67 221.67 200.45 200.17 216.67 204.83 GoalRIT3 0 199.76 204.87 212.83 210.50 208.82 216.00 223.17 222.83 203.64 201.43 219.83 210.33 GoalRIT4 0 199.90 208.78 215.00 205.17 210.09 210.78 224.67 222.83 204.50 201.04 218.67 206.33

Grade 6 Language Percentiles Fall 2008 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 9 12 7 13 4 percent 20% 27% 16% 29% 9%

Grade 6 Language Percentiles Spring 2009 (N = 42) 1-10 11-30 31-50 51-75 76-100 number 8 5 10 11 8 percent 19% 12% 24% 26% 19%

Grade 6 Math Percentiles Fall 2008 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 5 10 7 15 8 percent 11% 22% 16% 33% 18%

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Grade 6 Math Percentiles Spring 2009 (N = 46) 1-10 11-30 31-50 51-75 76-100 number 11 5 8 17 5 percent 24% 11% 17% 37% 11%

Grade 6 Reading Percentiles Fall 2008 (N = 45) 1-10 11-30 31-50 51-75 76-100 number 6 10 6 12 11 percent 13% 22% 13% 27% 24%

Grade 6 Reading Percentiles Spring 2009 (N = 46) 1-10 11-30 31-50 51-75 76-100 number 8 11 6 14 7 percent 17% 24% 13% 30% 15%

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Grade 6 Survey with Goals Fall 2008 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American American American White White White y Indian Indian Indian NWEA Language Math Reading area Average RIT 201.38 208.39 210.33 205.88 213.46 215.50 223.50 209.50 205.31 211.67 215.33 206.38 GoalRIT1 0 200.85 208.22 216.50 204.38 212.08 215.94 220.17 208.75 204.00 211.89 215.67 201.88 GoalRIT2 0 201.08 205.78 207.50 203.88 209.69 219.72 222.83 209.50 204.54 211.78 214.83 207.00 GoalRIT3 0 202.54 209.61 205.83 207.00 216.85 212.89 224.17 212.13 208.31 209.83 211.17 209.25 GoalRIT4 0 200.08 210.78 211.67 207.00 215.46 214.00 225.17 207.38 204.85 213.06 219.67 206.88

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Grade 6 Survey with Goals Spring 2009 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American American American White White White y Indian Indian Indian NWEA Language Math Reading area Average RIT 209.42 214.13 216.33 211.00 213.50 219.61 227.00 220.25 205.77 211.00 217.17 205.75 GoalRIT1 0 208.83 216.13 219.33 211.88 213.64 220.56 227.33 221.25 206.77 212.68 221.17 209.63 GoalRIT2 0 210.50 212.31 210.67 207.88 211.00 216.67 222.50 219.50 204.69 209.74 214.33 206.25 GoalRIT3 0 210.50 214.19 216.67 212.75 215.29 222.17 228.17 223.00 204.62 209.05 217.83 206.00 GoalRIT4 0 208.17 213.94 218.17 212.00 213.50 218.50 228.17 215.75 207.23 212.42 215.50 200.50

Grade 5 Language Percentiles Fall 2009 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 15 11 3 10 2 percent 37% 27% 7% 24% 5%

Grade 5 Language Percentiles Winter 2010 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 11 10 10 4 6 percent 27% 24% 24% 10% 15%

Grade 5 Math Percentiles Fall 2009 (N = 40) 1-10 11-30 31-50 51-75 76-100 number 11 7 10 9 3 percent 28% 18% 25% 23% 8%

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Grade 5 Math Percentiles Winter 2010 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 6 10 10 6 9 percent 15% 24% 24% 15% 22%

Grade 5 Reading Percentiles Fall 2009 (N = 40) 1-10 11-30 31-50 51-75 76-100 number 11 9 5 12 3 percent 28% 23% 13% 30% 8%

Grade 5 Reading Percentiles Winter 2010 (N = 41) 1-10 11-30 31-50 51-75 76-100 number 12 6 8 8 7 percent 29% 15% 20% 20% 17%

Grade 5 Survey with Goals Fall 2009 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American American American White White White y Indian Indian Indian NWEA Language Math Reading area Average RIT 183.20 195.83 204.71 201.83 199.87 207.54 211.17 205.50 189.38 198.80 205.29 200.33 GoalRIT1 0 180.87 196.00 205.71 200.67 197.33 208.85 207.67 202.50 191.06 199.60 206.71 198.33 GoalRIT2 0 182.00 196.75 201.29 200.17 199.53 209.00 211.83 207.17 186.44 199.10 206.86 200.33 GoalRIT3 0 183.13 193.67 206.14 202.50 201.60 204.00 212.00 204.50 189.88 198.70 206.86 202.17 GoalRIT4 0 185.67 197.33 205.29 203.50 200.60 208.46 213.83 207.50 189.75 197.80 202.43 200.83

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Grade 5 Survey with Goals Winter 2010 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American American American White White White y Indian Indian Indian NWEA Language Math Reading area Average RIT 193.81 205.58 206.17 209.67 208.00 215.50 215.67 214.33 194.88 205.58 209.67 208.83 GoalRIT1 0 195.81 204.33 207.00 211.00 207.06 216.00 214.17 214.17 193.81 205.25 209.17 202.67 GoalRIT2 0 191.69 207.00 205.83 206.67 208.38 215.08 217.67 213.83 194.75 204.50 211.17 209.67 GoalRIT3 0 196.38 205.50 206.50 209.67 207.50 211.58 215.00 212.67 195.50 205.50 207.67 211.00 GoalRIT4 0 192.50 205.58 205.00 212.00 209.00 219.67 215.83 217.17 195.81 208.17 209.67 213.33

Grade 6 Language Percentiles Fall 2009 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 24 13 8 10 2 percent 42% 23% 14% 18% 4%

Grade 6 Language Percentiles Winter 2010 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 7 15 11 16 8 percent 12% 26% 19% 28% 14%

Grade 6 Math Percentiles Fall 2009 (N = 58) 1-10 11-30 31-50 51-75 76-100 number 20 10 8 11 9 percent 34% 17% 14% 19% 16%

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Grade 6 Math Percentiles Winter 2010 (N = 58) 1-10 11-30 31-50 51-75 76-100 number 10 16 7 8 17 percent 17% 28% 12% 14% 29%

Grade 6 Reading Percentiles Fall 2009 (N = 58) 1-10 11-30 31-50 51-75 76-100 number 23 13 9 11 2 percent 40% 22% 16% 19% 3%

Grade 6 Reading Percentiles Winter 2010 (N = 57) 1-10 11-30 31-50 51-75 76-100 number 12 16 9 13 7 percent 21% 28% 16% 23% 12%

Grade 6 Survey with Goals Fall 2009 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American American American White White White y Indian Indian Indian NWEA Language Math Reading area Average RIT 189.86 197.87 204.67 202.00 201.73 206.63 219.33 216.00 191.82 200.38 204.67 199.83 GoalRIT1 0 188.19 195.70 205.83 199.83 201.57 205.71 216.83 214.00 192.36 200.63 205.33 200.50 GoalRIT2 0 188.00 193.74 202.17 198.67 200.76 204.29 218.33 215.50 190.18 199.75 207.17 199.83 GoalRIT3 0 191.19 201.22 204.50 206.17 204.10 206.50 218.83 219.67 192.05 201.92 205.33 199.83 GoalRIT4 0 193.10 200.91 206.00 202.67 201.67 208.92 222.17 214.33 192.64 199.00 200.50 199.50

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Grade 6 Survey with Goals Winter 2010 240 230 220 210 200 190 180 170 160 150 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American American American White White White y Indian Indian Indian NWEA Language Math Reading area Average RIT 205.95 212.50 217.83 213.67 213.09 219.13 232.50 224.50 202.68 208.17 220.17 207.17 GoalRIT1 0 207.29 213.04 217.17 216.67 215.45 220.17 235.33 223.33 202.14 209.04 219.83 205.67 GoalRIT2 0 205.52 211.50 218.83 210.17 212.59 217.13 231.00 224.33 201.55 204.78 221.33 204.17 GoalRIT3 0 204.52 210.33 219.50 214.83 213.00 218.75 230.50 224.50 203.64 208.57 219.00 211.83 GoalRIT4 0 206.76 215.38 216.67 214.17 211.59 220.50 233.50 225.33 203.73 209.83 221.50 207.00

NWEA scores WOWE high school.

Language

Grade 9 Language Percentiles Fall 2007 (N = 40) 1-10 11-30 31-50 51-75 76-100 number 6 12 9 7 6 percent 15% 30% 23% 18% 15%

Grade 10 Language Percentiles Fall 2008 (N = 35) 1-10 11-30 31-50 51-75 76-100 number 5 10 10 5 5 percent 14% 29% 29% 14% 14%

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Math

Grade 9 Math Percentiles Fall 2007 (N = 42) 1-10 11-30 31-50 51-75 76-100 number 6 10 9 11 5 percent 14% 24% 21% 26% 12%

Grade 10 Math Percentiles Fall 2008 (N = 35) 1-10 11-30 31-50 51-75 76-100 number 5 10 10 5 5 percent 14% 29% 29% 14% 14%

Grade 11 Math Percentiles Fall 2009 (N = 39) 1-10 11-30 31-50 51-75 76-100 number 5 9 12 9 4 percent 13% 23% 31% 23% 10%

Reading

Grade 9 Reading Percentiles Fall 2007 (N = 42) 1-10 11-30 31-50 51-75 76-100 number 8 14 10 5 5 percent 19% 33% 24% 12% 12%

Grade 10 Reading Percentiles Fall 2008 (N = 38) 1-10 11-30 31-50 51-75 76-100 number 4 17 5 5 7 percent 11% 45% 13% 13% 18%

Language

Grade 10 Language Percentiles Fall 2007 (N = 33) 1-10 11-30 31-50 51-75 76-100 number 5 12 6 7 3 P a g e | 340

percent 15% 36% 18% 21% 9%

Math

Grade 10 Math Percentiles Fall 2007 (N = 34) 1-10 11-30 31-50 51-75 76-100 number 4 8 7 10 5 percent 12% 24% 21% 29% 15%

Grade 11 Math Percentiles Fall 2008 (N = 30) 1-10 11-30 31-50 51-75 76-100 number 3 3 7 9 8 percent 10% 10% 23% 30% 27%

Reading

Grade 10 Reading Percentiles Fall 2007 (N = 34) 1-10 11-30 31-50 51-75 76-100 number 3 13 8 3 7 percent 9% 38% 24% 9% 21%

Language

Grade 11 Language Percentiles Fall 2007 (N = 51) 1-10 11-30 31-50 51-75 76-100 number 6 17 11 12 5 percent 12% 33% 22% 24% 10%

Math

Grade 11 Math Percentiles Fall 2007 (N = 49) 1-10 11-30 31-50 51-75 76-100 number 3 13 10 12 11 percent 6% 27% 20% 24% 22%

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Reading

Grade 11 Reading Percentiles Fall 2007 (N = 49) 1-10 11-30 31-50 51-75 76-100 number 3 13 12 8 13 percent 6% 27% 24% 16% 27%

Grade 9 NWEA Survey Fall 2007 245 240 235 230 225 220 215 210 205 200 195 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American American American White White White y Indian Indian Indian NWEA Language Math Reading area Average RIT 212.91 213.54 219.13 221.00 228.73 218.73 234.88 234.13 213.82 213.07 218.38 215.88 GoalRIT1 212.18 211.54 220.88 222.88 228.82 218.43 232.75 230.00 214.27 210.79 215.75 212.63 GoalRIT2 212.45 214.92 219.50 218.63 227.36 227.73 241.13 238.63 214.27 227.88 221.00 224.00 GoalRIT3 215.64 214.69 215.88 222.50 227.64 220.43 235.25 236.00 213.09 215.36 217.50 215.00 GoalRIT4 211.18 213.00 219.88 219.25 232.64 219.29 231.38 231.50 213.00 213.21 218.88 214.25

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Grade 10 Survey with Goals Fall 2007 250 245 240 235 230 225 220 215 210 205 200 195 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American American American White White White y Indian Indian Indian NWEA Language Math Reading area Average RIT 220.25 217.80 217.25 226.33 237.92 227.60 231.50 232.67 221.38 213.80 221.25 224.33 GoalRIT1 222.18 215.78 215.33 231.67 236.83 228.56 225.13 229.00 224.50 217.78 222.33 224.00 GoalRIT2 219.36 229.68 216.50 228.67 239.75 230.01 234.63 234.67 222.17 230.02 225.17 226.33 GoalRIT3 223.18 221.44 216.50 221.33 244.42 231.56 230.38 240.33 222.75 215.89 219.33 223.33 GoalRIT4 218.82 219.44 220.67 223.00 234.92 229.89 230.50 229.00 220.17 213.00 215.33 224.00

Grade 11 Survey with Goals Fall 2007 250 245 240 235 230 225 220 215 210 205 200 195 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnicit American American American White White White y Indian Indian Indian NWEA Language Math Reading area Average RIT 217.06 222.22 219.09 225.20 236.06 230.47 242.45 240.60 220.33 224.67 225.00 228.80 GoalRIT1 222.70 223.20 217.67 0.00 233.67 228.13 243.45 243.40 230.00 222.50 223.00 0.00 GoalRIT2 218.60 232.16 219.00 0.00 242.73 231.53 241.82 238.00 232.40 227.79 230.25 0.00 GoalRIT3 218.50 223.00 215.33 0.00 241.20 230.44 243.45 243.40 223.40 221.50 219.00 0.00 GoalRIT4 221.30 221.60 217.33 0.00 236.47 228.64 241.80 236.00 222.80 222.75 223.75 0.00

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Grade 12 Survey with Goals Fall 2007 245 240 235 230 225 220 215 210 205 200 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Language Reading area Average RIT 218.91 225.33 219.90 217.00 225.00 228.42 228.90 227.80 GoalRIT1 221.00 230.00 218.00 222.67 232.60 229.00 235.00 229.00 GoalRIT2 227.00 233.67 221.14 222.33 226.00 235.00 229.67 241.33 GoalRIT3 226.50 228.00 223.29 218.67 230.60 226.67 231.67 238.67 GoalRIT4 228.50 233.67 218.29 219.67 222.60 231.67 223.00 227.33

Grade 9 Survey with Goals Fall 2008 250

240

230

220

210

200

190 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnici American American American White White White ty Indian Indian Indian NWEA Language Math Reading area Average RIT 210.00 217.36 219.80 226.63 224.15 221.38 239.90 237.40 219.77 217.25 221.70 224.00 GoalRIT1 220.54 216.00 222.70 225.38 221.69 218.88 239.10 236.50 225.38 212.44 225.30 225.00 GoalRIT2 219.92 215.79 218.70 227.25 225.08 232.19 240.30 239.10 220.23 219.19 225.70 225.11 GoalRIT3 210.54 219.64 222.10 226.50 229.00 232.13 243.60 242.30 220.23 218.50 219.50 225.11 GoalRIT4 210.38 216.50 219.00 229.88 224.23 218.88 236.50 234.20 214.23 215.75 219.50 223.89

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Grade 10 NWEA Survey with Goals Fall 2008 250 240 230 220 210 200 190 Gender Male Female Male Female Male Female Male Female Ethnicity American Indian White American Indian White NWEA Math Reading area Average RIT 227.25 227.67 231.14 237.25 216.56 224.85 224.14 227.78 GoalRIT1 229.50 221.83 232.29 240.71 219.11 212.54 217.29 230.25 GoalRIT2 222.50 229.50 230.86 243.00 219.33 217.54 226.29 230.25 GoalRIT3 231.63 227.75 232.00 246.57 212.56 213.54 225.00 231.38 GoalRIT4 224.88 229.83 229.00 235.71 233.11 222.62 222.71 226.25

Grade 11 NWEA Survey with Goals Fall 2008 260 255 250 245 240 235 230 225 220 Gender Male Female Male Female Ethnicity American Indian White NWEA area Math Average RIT 242.31 238.89 236.60 256.50 GoalRIT1 241.62 237.89 235.80 256.50 GoalRIT2 241.62 237.89 235.80 256.50 GoalRIT3 242.85 237.78 233.60 254.00 GoalRIT4 241.08 236.78 236.80 253.00

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Grade 9 Survey with Goals Fall 2009 240 235 230 225 220 215 210 205 200 195 190 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnici American American American White White White ty Indian Indian Indian NWEA Language Math Reading area Average RIT 215.56 221.13 214.67 223.67 229.23 228.69 234.83 233.00 217.27 221.06 208.20 221.67 GoalRIT1 0 214.11 223.93 211.33 224.67 225.15 229.80 234.00 230.33 216.30 222.13 211.20 219.00 GoalRIT2 0 213.44 221.29 213.50 223.67 227.46 230.13 233.50 236.33 219.30 222.38 205.20 225.67 GoalRIT3 0 219.44 218.71 214.83 227.00 232.69 231.93 235.17 228.33 215.60 222.56 208.20 222.00 GoalRIT4 0 215.00 222.93 219.00 219.67 231.77 232.00 236.00 236.33 215.80 220.44 210.20 220.00

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Grade 10 Survey with Goals Fall 2009 250 240 230 220 210 200 190 Gender Male Female Male Female Male Female Male Female Male Female Male Female Ethnici American American American White White White ty Indian Indian Indian NWEA Language Math Reading area Average RIT 212.40 218.70 217.50 222.60 224.45 229.30 234.88 236.00 216.82 217.70 217.50 218.50 GoalRIT1 0 214.00 219.50 215.50 218.80 221.09 226.20 229.88 231.90 216.00 217.50 215.75 222.33 GoalRIT2 0 210.90 216.00 215.88 223.00 222.73 231.60 234.00 236.20 214.00 215.40 220.50 220.22 GoalRIT3 0 215.80 216.80 217.38 222.30 227.00 230.90 238.63 237.60 214.40 219.10 215.38 218.00 GoalRIT4 0 209.10 223.10 221.38 225.70 227.36 229.00 237.00 237.90 214.20 219.30 218.88 218.44

Grade 11 Survey with Goals Fall 2009 245 240 235 230 225 220 215 210 205 200 195 Gender Male Female Male Female Ethnicity American Indian White NWEA area Math Average RIT 235.88 229.09 234.00 235.78 GoalRIT1 0 234.50 228.09 231.67 233.22 GoalRIT2 0 230.88 227.55 235.89 238.33 GoalRIT3 0 241.50 229.27 232.00 232.89 GoalRIT4 0 236.50 232.00 236.33 239.56

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NWEA Analysis

Although NWEA (MAP) test score data could be analyzed in many ways, there are some general trends that seem to be present at WOWE. First, the percentage of students who score in the lower percentiles is extremely high. Since the starting point is so low for so many students, there is only so much growth that could be expected over the course of the academic year.

Unfortunately, modest to strong growth, while positive, would likely not result in proficiency on the MCA IIs for many students. As a side note, it should be remembered that scores on MAP tests in the fall are the most reliable predictor of success on MCA IIs the following spring.

A second factor that does not bode well for WOWE is that aggregate growth over the academic year is not strong. In many cases, MAP scores increase very little. The following examples illustrate this point.

In Grade 3, in the Fall of 2008, 34% of students scores at or below the 30th percentile on the Language MAP tests and 39% of students scored at or above the 51st percentile. In the Spring of 2009, 37% of students scored at or below the 30th percentile on the Language MAP tests, and 41% of students scored at 51st percentile. In Grade 5, in the Fall of 2008, 44% of students scored at or below the 30th percentile on the Reading MAP tests and 24% of the students scored at or above the 51st percentile. In the Spring of 2009, 43% of students scored at or below the 30th percentile on the Reading MAP tests and 41% of the students scored at or above the 51st percentile. In Grade 6, in the Fall of 2008, 33% of students scored at or below the 30th percentile on the Math MAP tests and 51% of the students scored at the 51st percentile. In the Spring of 2009, 35% of the students scored at or below the 30th percentile on the Math MAP tests and 48% of the students scored at or above the 51st percentile.

A third factor that likely provides a negative impact on students is the prolonged period

(summer) of little to no academic exposure. This contributes potentially to the low starting

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The neighboring school, Mahnomen, has similar demographics. Moreover, a similar trend in MAP scores has been observed by researchers. The difference in the last two years, however, is that Mahnomen has demonstrated increasing proficiency with the MCA II scores, while WOWE has witnessed a decrease. It is uncertain as to why this is.

In Phase II of this study, researchers will examine factors that prevent growth of the academic year in language, reading, and math, as well as the impact of summer on student academic success. In addition, researchers will compare similarities and differences between

Mahnomen and WOWE school districts to ascertain factors that impact student success both positively and negatively.

WOWE behavior comparison.

Copy of WOWE Behavior Comparison 197 200 180 162 160 140 105 120 91 98 100 83 80 60 36 44 24 33 40 11 11 12 14 20 19 14 2 6 3 2 1 0 1 Number ofViolations Number 20 0

2004-05 2005-06 2006-07

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Violation 2004-05 2005-06 2006-07 Insubordination 83 36 44 Disruptive/Disrespectful 197 105 91 Swearing/Offensive Lang. 11 162 98 Verbal Abuse 11 12 2 Harassment/Threatening/Intimidation 24 14 20 Fighting/Assault/Disorderly 33 19 14 Under Influence Drugs/Alcohol 6 3 2 Weapons 1 0 1

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2005 2006 2007 2005 2006 2007

2005 2006 2007 2005 2006 2007 2005 2006 2007 2005 2006 2007 2005 2006 2007

2005 2006 2007

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2004 2005 2006

2004 2005 2006

- - -

- - -

Oct. 2004 Oct. 2005 Oct. 2006 Oct.

Jan. Jan. 2004 Jan. 2005 Jan. 2006 May May May

Feb. 2004 Feb. 2005 Feb. 2006

Mar. Mar. Mar.

April 2004 April 2005 April 2006 April

Sept. 2004 Sept. 2005 Sept. 2006

Nov./Dec. 2005 Nov./Dec. 2006 Nov./Dec. Violations 2004 Nov./Dec. Disruptive Behavior 30 0 5 15 2 6 20 10 24 7 1 1 8 2 0 6 9 6 1 15 1 12 10 6 Insubordination 11 5 6 11 4 7 29 8 11 5 7 3 3 0 2 7 2 1 4 8 7 3 4 4 Swearing/Bad Language 4 26 3 2 17 2 1 33 4 0 16 0 0 12 0 0 13 5 0 13 4 0 12 4 Scuffling/Horse play 0 0 0 0 0 3 1 0 0 0 0 0 0 5 0 1 1 2 0 0 0 0 0 0 Aggressive Behavior 3 0 1 1 1 0 0 0 2 1 0 0 1 0 0 5 0 0 0 0 0 3 1 1 Smoking 7 3 0 4 3 0 1 1 0 0 0 0 0 1 0 0 3 0 1 0 0 0 1 0 Harassment 2 1 2 1 2 2 0 5 1 0 0 0 0 1 10 0 0 0 5 2 0 0 1 0 Threatening Students/Staff 2 0 0 1 0 2 5 2 0 2 0 0 5 0 0 0 1 1 3 0 1 4 1 1 Fighting 5 2 2 2 0 0 1 2 0 0 0 0 5 0 4 0 0 0 0 0 2 0 0 0 Physical Assault 3 0 0 1 2 3 1 3 1 0 2 1 3 0 0 3 3 0 1 0 0 1 0 0

Waubun Elementary Discipline 60 50 40 30 20 10 0 Indian White Indian White 2008-2009 2007-2008 Violation 56 5 30 7 Insubordination 26 2 12 2 Disruptive/ disrespectful 4 6 7 2 Swearing/Offensive Language 10 3 10 2 Bullying/ Harassment/ Threats 17 4 15 2 Fighting/ Physical Assault 10 3 11 4 Alcohol/ Drugs 0 0 0 0 Weapons 0 0 0 0

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Waubun Junior High Discipline 16 14 12 10 8 6 4 2 0 Indian White Indian White 2007-2008 2008-2009 Violation 1 7 12 Insubordination 7 0 12 1 Disruptive/ disrespectful 1 2 5 0 Swearing/Offensive Language 15 0 3 2 Bullying/ Harassment/ Threats 13 0 6 1 Fighting/ Physical Assault 14 0 3 0 Alcohol/ Drugs 0 0 0 0 Weapons 0 0 0 0

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Waubun High School Discipline 250 200 150 100 50 0 Indian White Indian White 2008-2009 2007-2008 Violation 63 23 212 127 Insubordination 37 6 40 5 Disruptive/ disrespectful 46 36 48 0 Swearing/Offensive Language 3 12 55 7 Bullying/ Harassment/ Threats 5 0 12 10 Fighting/ Physical Assault 7 1 3 0 Alcohol/ Drugs 1 0 4 1 Weapons 0 0 0 0

Behavior Analysis

It would appear that disciplinary referrals have stayed stable over the last few years.

Behavioral (student management) changes that were implemented in the fall of the 2005-06 school year appear to have been effective and sustainable, based on disciplinary referral numbers.

There is a long-term trend in terms of disparity between disciplinary referrals for

American Indian students and those of Caucasian students. American Indian disciplinary referral rates are disproportionately high.

In Phase II of this study, researchers will examine whether the student management changes implemented in 2005 have produced a positive, long-term impact on the climate of the school buildings. In addition, researchers will examine the ethnic disparity in terms of disciplinary referral rates in an attempt to explain why this disparity exists.

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References

Ah-nen-la-de-ni. (1903, July). An Indian boy‘s story. The Independent, 55, 1780-1787. Retrieved

April 13, 2005 from http://etext.lib.virginia.edu/toc/modeng/public/AhnIndi.html

Beaulieu, D. L. (2000). Comprehensive reform and American Indian education. Journal of

American Indian Education, 39(2), 29-38.

Bureau of the Census. (1995, April). Housing of American Indians on reservations—plumbing.

United States Department of Commerce: Washington, DC . Cahape Hammer, & Demmert, Jr., W. G. (2003, December). American Indian and Alaska

Native early childhood health development, and education research. (ERIC Document

Reproduction Service No. EDORC03012)

Caine, R. N., & Caine, G. (1997). Unleashing the power of perceptual change: The

potential of brain-based teaching. Alexandria, Virginia: Association for Supervision and

Curriculum Development.

Demmert, Jr., W. G. (2001). Improving academic performance among Native American

students. Charleston, WV: Clearinghouse on Rural Education and Small Schools. (ERIC

Document Reproduction Service No. ED99CO0027)

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From assimilation to self-determination. In M. W. Apple (Ed.), Review of Research in

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from http: //www.anhb.org/documents/hill%20visits/IHS%20Fact%20Sheet.pdf

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from http://education.state.mn.us/ReportCard2005/index.do. P a g e | 355

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programming improve educational outcomes for American Indian youth? Journal of

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census. Baltimore, MD: The Annie E. Casey Foundation.

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success among American Indian children in the upper Midwest. Journal of

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P a g e | 357

Dr. Rebecca Williams

Assistant Professor of Education

Minnesota State University, Moorhead

Literature Review for Native American Curriculum Studies White Earth Consortium

Study

Schaffer made the statement, ―an area of potential conflict in teaching Native American children in the classroom, is the clash between the learning styles they have been exposed to at home and those used in the classroom‖ (Gilliland, 1995, p. 70).

In Bergstrom, Cleary, Peacock‘s (2003) book, The Seventh Generation, the authors emphasized that the teachers need to use encouragement, explanation, examples, and analogies with the students. Teachers need to have the bar set realistically high and students need to be challenged in order to grow in their learning experiences. Teachers need to be insightful in all aspects. They must be interested in all of their students, assisting them when needed, being fair, flexible, and modeling respect, as well as requesting respect. The authors also maintain that teachers need to use multiple approaches in their instruction. Students learn best by a variety of teaching approaches. Bergstrom, Cleary, and Peacock (2003) stated that ―students, who live in relatively tight-knit communities, as many Native American students do, learn to work together at an early age, and most of the students prefer ---to learn together.‖(p.167). These help build social skills and learning to work with one another. (Bergstrom, Cleary & Peacock, 2003)).

Culture has an impact on learning styles, because the experiences are significant and learned from people that play an important role in one‘s life ( Williams, 2000). P a g e | 358

A key concept of learning evident among many Native American students is that, ―the whole is more important than the parts---a Gestalt idea‖ (Rhodes, 1988, p. 23). This may go back to the traditional and still present beliefs that everything is still related---that is the holistic viewpoint of the Native American people (B. Todd-Bozemore, personal communication in R.

Williams‘ dissertation).

There are some key features to educational programming for elementary and secondary children. According to Demmert (2001, p. 9), ―A school curriculum that promotes the language and culture of the community or tribe served—adopted in partnership with that community— holds significant promise for improving academic performance of Native children.‖ Since a majority of research shows a positive association between academic performance and the presence of Native language and cultural programs, schools should give serious consideration to including American Indian language and culture in their curricula. As Whitbeck, Hoyt, Stubben, and LaFromboise (2001, p. 57) noted, ―enculturation is a resiliency factor in the development of their (American Indian) children.‖ Powers, Potthoff, Bearinger, and Resnick (2003) added,

―Rather, effective cultural programs validate native culture at a social and psychological level.

Optimally, this validation includes redefining Native students as competent learners, negotiating cultural barriers to reach out to native parents as important partners in education, and creating a social climate that is nurturing and accepting of native students‘ cultural identity (p. 41).‖ ―What matters is the students‘ sense of connection to the school they attend: If students feel they are a part of the school, are treated fairly by teachers, and feel close to people at school, they have a better emotional health and lower levels of involvement in risky behavior‖ ( Bergstrom, Cleary,

Peacock, 2003, p.160). The authors stressed that teachers have an understanding of some basic cultural beliefs of the tribe. ―Native students think teachers should know something about the P a g e | 359

tribal people they teach.‖( Bergstrom, Cleary, Peacock, 2003,p.162). The authors also suggest

Indian education planning would be from the Native Americans‘ perspective. The vision, philosophy, mission statement, objectives, assessment, curriculum, content, pedagogy, research, and evaluation could be based upon the Native American values. The assessment could be taken from multiple perspectives, but would also include performance based assessment. The ideas and references on pedagogy could be based upon several Native American researched resources such as Karen Swisher‘s and John Tippeconnic III‘s Next Step, Sandra Fox‘s Creating Sacred

Places Curriculum, and Bergstrom, Cleary, and Peacock‘s The Seventh Generation to list just a few. In Bergstrom, Cleary, Peacock‘s (2003) book, the authors wrote that many models exist in

Native communities in Hawaii and New Zealand, in which the language is taught in an immersion setting. ―These schools operate with an Indigenous focus, having language maintenance and renewal as the central goals upon which other parts of the curriculum are built.‖( Bergstrom, Cleary, Peacock, 2003, p.174).

Bergstrom, Cleary, and Peacock (2003) described another model for Native communities.

This one is known as Gekinoo’imaagejig (American Indian Teacher Corps) as Fond du Lac

Tribal and Community College, a joint program with the University of Minnesota at Duluth

Teacher Education Program. All the components of the program have the traditional values at its base. It meets national and state standards as well. There are similar models at other tribal schools in South Dakota that base their mission statements, philosophy, objectives, and benchmarks on the tribal value system. The communities are an integral part in the ongoing planning and assessment process of the educational system. Part of this might include finding more American Indian teachers to work in these communities.

P a g e | 360

Educators must examine the way in which education is being conducted in the classrooms. Marshall (1990) stated in an article, ―If students don‘t learn the way we teach them, we must teach them the way they learn‖ (p. 62).

Additional Resources for Educators:

Resources for White Earth Study Curriculum and Professional Development:

Cognitive Strategy Instruction; Reading

University of Nebraska-Lincoln

http://www.unl.edu/csi/reading.shtml

Vaughn Gross Center for Reading and Language Arts Materials

University of Texas at Austin

http://www.texasreading.org/utcrla/materials/

The Florida Center for Reading Research

Florida State University

http://www.fcrr.org/Curriculum/curriculum.htm

Sandra Fox‘s Curriculum: ―Creating Sacred Places.‖

Hap Gilliland: Council of Indian Education

Jon Reyhner‘s studies on Native American students

R. Williams‘s doctoral dissertation: Reading Styles Relationship Among Native American

Students and Their Families(2000).

Karen Swisher: Learning Styles Study

Robert Marzano: What Works in Schools P a g e | 361

o Appendix: Snapshot Survey of School Effectiveness Factors

Marie Carbo---Reading Styles Inventory

Dr. Sherry Johnson‘s doctoral dissertation on ―Resiliency‖

Amy Bergstrom, Linda Miller, and Thomas Peacock book: Seventh Generation (2003).

P a g e | 362

References

Bergstrom, A., Cleary, Linda Miller, Peacock, Thomas. (2003). The Seventh

Generation. ERIC. Charlestown, West Virginia.

Gilliland, H. (1995). Teaching the Native American (3rd. Ed.). Dubuque, IA. Kendall/Hunt Publishing

Co.

Marshall, C. (1990, Oct.) . The Power of the Learning Styles Philosophy. Educational Leadership, 48

(2), 62.

More, A.J. (1989, August). Native American Learning Styles: A Review for Researchers and Teachers.

Journal of American Indian Education. Aug. Special Issue. 15-27.

Rhodes, R.W. (1988, January). Holistic Teaching/Learning for Native Americans. Journal of American

Indian Education, 27 (2). 72-76.

Swisher, K. (1994, Spring). American Indian Learning Style Survey: An assessment of Teacher

Knowledge. The Journal of Educational Issues of Language Minority Students, 13, 1-14.

Williams, R. (2000). Reading Styles Relationships Among Native American Students and Their

Families. Dissertation.

P a g e | 363

Dr. Donna Brown

Assistant Vice-President for Diversity

Minnesota State University, Moorhead

Adult Education

White Earth Tribal and Technical College

History of tribal colleges

Tribal Colleges and Universities (TCUs) were created in response to the higher education needs of American Indians and generally serve geographically isolated populations that have no other means accessing education beyond the high school level. TCUs have become increasingly important to educational opportunity for American Indian students and are unique institutions that combine personal attention with cultural relevance to encourage American Indians— especially those living on reservations—to overcome the barriers they face to higher education.

That said, too often ―students of color‖ are considered synonymous with ―at-risk students,‖ when a large portion of students of color, including American Indians, are highly intelligent and come from families who value education.

Indian education and tribal colleges

Throughout history in the United States, Indian people have faced many overwhelming barriers to the attainment of higher education. Poor preparation for college, excessive high school dropout rates, unaddressed cultural differences, and limited financial resources were just some of the hurdles that kept Indians from college (Boyer, 1997; Stein, 1988; Tierney & Wright,

1991). P a g e | 364

Indian students were often discouraged from attending college by their own teachers who, inspired by misguided kindness or overt racism, did not want to see Indian students enter the more rigorous life of higher education where, in their view, failure was likely. (Boyer, 1997, p. 20)

Even among the most academically prepared Indian people, the experience of leaving the reservation is generally accompanied by institutional shock of such enormity that few can persevere (Raymond, 1986).

Tribal colleges have been in existence for a relatively short period of time. These institutions were created over the last three decades to respond to the higher education needs of

American Indians, especially those living in geographically isolated areas such as reservations.

Tribal colleges were established in response to the conditions experienced by students at off- reservation institutions, such as inadequate funds and loneliness for the family. From the beginning, tribal colleges addressed the problems of financial aid limitations, cultural isolation, and family considerations. Ideally, tribal colleges combine the preservation of tribal history, culture, and traditions with academic preparation, vocational training, and basic adult education

(Belgarde, 1994; Boyer, 1997; Cunningham, 2000; Raymond, 1986; Wright & Tierney, 1991).

A major function of tribal colleges is to provide autonomy in higher education for American

Indians, however, they are dependent upon external sources for funds, personnel, and part of their legitimacy. Therefore, they must meet two sets of expectations (Belgarde, 1994). Tribal college administrators must manage unique problems experienced by their Indian clientele by adjusting institutional routines to the cultural norms of Indian society. At the same time, they must present the familiar appearance of a postsecondary educational institution to outside resource providers and accreditation agencies. ―Despite the adoption of formal structures, P a g e | 365

however, day-to-day practices at tribal colleges continue to reflect the social patterns of Indian rather than mainstream society‖ (p. 1).

Student development theory

One way to combat negative images is to help students of color construct ethnic identities that include achievement as not only a desirable characteristic, but an achievable characteristic as well (Pizzolato, et al, 2008).

American Indian student development

Tribal college students are unique as a group and do not mirror the image of the traditional American college student. For example, Martin (2005) reported, ―The average age of tribal college students is twenty-eight ; sixty-four percent are women; and a larger percentage are single parents‖ (p. 81). Moreover, many tribal college students are first-generation and low- income. They often do not have families who can support them procedurally and financially while in college.

Ultimately, identity as an American Indian is highly personal. It is a particular way one feels about oneself and one‘s experience as an American Indian or tribal person. Horse (2001) described five influences on American Indian consciousness:

The extent to which one is grounded in one‘s Native American language and culture, one‘s cultural identity

The validity of one‘s American Indian genealogy

The extent to which one holds a traditional American Indian general philosophy or worldview (emphasizing balance and harmony and drawing on Indian spirituality)

One‘s self-concept as an American Indian

One‘s enrollment (or lack of it) in a tribe P a g e | 366

Those who work with Native American students need to keep in mind that American

Indian or tribal identity is a personalized process that is influenced by legal and political considerations, psychosocial factors, proximity or access to a given culture, socialization, and one‘s own sensibility.

History of White Earth Technical and Tribal College (WETTC)

The White Earth Tribal and Community College is a Tribally chartered institution of higher education, which offers certificates, associate degrees, and other degree programs through affiliation agreements with other degree–granting institutions of higher education. The College is a member of the American Indian Higher Education Consortium and the National Association of

Land Grant Institutions.

Beginning in 1979, Tribal members began the initiative to provide local higher education services in partnership with Moorhead State University. On September 8, 1997 the White Earth

Reservation Tribal Council established the White Earth Tribal and Community College

(WETCC).

On September 8, 1997 the White Earth Reservation Tribal Council passed Resolution

#038–97–005 establishing the White Earth Tribal and Community College (WETCC). On

October 27, 1997 the college opened its doors to 40 students enrolled in several computer courses and a business communications course.

On February 23, 1998 classes for the spring semester began with nearly 70 students enrolled in a variety of classes. The college effectively scans the environment to determine areas of need and works hard to find ways to meet those needs. The college anticipates continuous growth and demand for the services of the White Earth Tribal and Community College.

Accreditation P a g e | 367

The White Earth Tribal and Community College achieved accreditation in October 2008.

Mission statement

The mission of the White Earth Tribal and Community College, an Anishinaabe controlled liberal arts institution of higher education, is dedicated to educational excellence through provision of a culturally relevant curriculum in partnership with students, staff, community, and industry.

Goal of the college

The College is home to over 136 College students and 170 Adult Basic Education students. The college also administers the White Earth Adult Basic Education Program which yearly serves approximately 170 students, with 30 graduating with their high school general equivalency diplomas each year. The overall goal of the college, through its affiliations, is to provide higher education programs appropriate for addressing the higher education needs of

Anishinaabe people and others who can benefit from studies at the White Earth Tribal and

Community College. These education programs include:

Associate of Arts degree programs

Associate of Applied Science degree programs

Certificate programs

Adult Education programs

Specialized training and awareness programs in topic areas of need

The College is involved in several outreach programs to meet the needs of the community. In support of the College‘s mission, cultural courses are made available to members of the community free of charge to those who interested in strengthening their knowledge in

Anishinaabe culture, history, or language through granting WETCC cultural waivers. P a g e | 368

Adult basic education

The Adult Basic Education Program (ABE) provides full time ABE/GED services to the community. Classes are designed for open enrollment and accommodate an average of 50-100 active students. The ABE program has six outreach sites in addition to the main site at WETCC.

It serves six surrounding counties (Mahnomen, Becker, Clearwater, Hubbard, Norman, and

Polk), and Tribal organizations as well as the business sector. Working in concert with the described entities ensures cooperation and clear communication of this service to the community.

The college is now a GED testing site. In 2006 the college graduated 36 students with their

GED‘s and 47 students in 2007. The GED program has served over numerous individuals through education and employment readiness education, service referrals, and GED and High

School preparation and testing. Sixteen of these student entered college as a result of receiving their GED. Sue Bishop was recognized for dedication and commitment at from the WE

Reservation Tribal Council at MIEA on October 12th of 2006; ABE also works in collaboration with several other entities, such as Minnesota Workforce Center, Minnesota State Services for the Blind, LIFE-learning in the family environment, and serves on a Committee for the

Minnesota Department of Education.

Student profile

Drawing from the Noel-Levitz Student Satisfaction Inventory (Student profile documents: self-study room), the typical student at the White Earth Tribal and Community

College is female, 25 to 34 years of age, predominately Native American, with a full-time

College status. She is typically enrolled in afternoon and evening classes primarily because of childcare and work issues. She is likely to be a freshman and the first person in her immediate family to attend college. P a g e | 369

Future research (phase II)

1. Explore retention and attrition at WETTC. Strategies: Exit interviews and surveys;

Interview students who are graduating or transferring to another institution.

2. Demographic data was not available to the researcher in phase I of this study. It is important to know the status of the student body at WETTC. It would be particularly helpful to know whether they are college graduates, or whether they have earned their general education diplomas. Furthermore, it is important to know why they chose WETTC and what their future plans are. Strategies: Interview individual students currently attending WETTC and hold focus groups.

3. The Higher Learning Commission recommended WETTC develop and implement a strategic plan (Advancement Section, Report of a Comprehensive Visit for Initial Accreditation,

April 2008). Strategies: Review WETTC‘s strategic plan(s) and progress on the plan(s).

4. The researcher will request to review the Noel-Levitz survey of student satisfaction and the Noel-Levitz survey of institutional priorities, including the raw data collected from these surveys.

Qualitative research

During the 2006/2007 academic year the faculty began to realize that the small size and family atmosphere of the college results in our obtaining useful feedback on a regular basis from students, community members, and other constituents. WETCC is currently exploring methods to document this data and formalizing its use in assessment. When designing a study involving minority populations, it is imperative to use qualitative methods.

P a g e | 370

References

Belgarde, L. (1994). Indian Colleges: A means to construct a viable Indian identity or a

capitulation to the dominant society? A paper presented at the Annual Meeting of the

American Educational Research Association. New Orleans, LA. (ERIC Document No.

ED 368 536).

Boyer, P. (1997). Native American Colleges: Progress and prospects. An Ernest T. Boyer

project of The Carnegie Foundation for the Advancement of Teaching. San Francisco:

Jossey-Bass Publishers.

Cunningham, A. F. (2000). Tribal College Contributions to Local Economic Development. A

report prepared by the American Indian Higher Education Consortium and the Institute

for Higher Education Policy.

Higher Learning Commission (2008). Advancement Section, Report of a Comprehensive Visit

for Initial Accreditation, April.

Horse, P. G., (2005). Native American Identity. In M. J. Tippeconnic Fox, S. C. Lowe, & G. S.

McClellan (Eds.), Serving Native American students. New Directions for Student

Services, no. 109, pp. 61-68. San Francisco: Jossey Bass.

Pizzolato, J. E., Chaudhari, P., Murrell, E. D., Podobnik, S., Schaeffer, Z. (2008). Ethnic

Identity, Epistemological Development, and Academic Achievement in Underrepresented

Students. Journal of College Student Development, 49 (4), pp. 301-318.

Martin, R. G. (2005). Serving American Indian students in tribal colleges: Lessons for

mainstream colleges. In M. J. Tippeconnic Fox, S. C. Lowe, & G. S. McClellan (Eds.),

Serving Native American students. New Directions for Student Services, no. 109, pp. 79-

86. San Francisco: Jossey-Bass. P a g e | 371

Raymond, J. H. III (1986). American Indian Education and the Reservation Community College.

Graduate Seminar paper, University of Florida. (ERIC Document No. ED 276 489).

Stein, W. J. (1988). A History of the Tribally Controlled Community Colleges: 1968-1978.

(Doctoral dissertation, Washington State University, 1988).

Tierney, W. G. & Wright, B. (1991). American Indians in higher education: a history of cultural

conflict. Change, 23(2), pp. 11-19.

P a g e | 372

Dr. Amy Phillips Department of Social Work, University of North Dakota Dr. Sue Peterson Department of Social Work, Minnesota State University, Moorhead Tracy Clark Department of Social Work Minnesota State University, Moorhead

Human/Social Services Report

Method

In Phase 1 of the White Earth Comprehensive Study of Education, the three researchers listed above sought to gather public domain data from tribal and county social service agencies about the impact of their programs on the academic success of American Indian children who reside on or near the White Earth Reservation. Researchers were particularly interested in child welfare programs and met with the following individuals to discuss their programs and to determine the availability of such data:

Jeri Jasken, Director, White Earth Indian Child Welfare

Brian Kemp, Child Protection Social Worker, White Earth Indian Child Welfare

Donna Richgels, Social Service Supervisor, Becker County Family and Children‘s

Services

Bruce Johnson, Director, Mahnomen County Human Services P a g e | 373

Malotte Backer, Director, and Sandy Comer-Moen, Child Protection Supervisor,

Clearwater County Human Services

Lori Thompson, Court Administrator, White Earth Tribal Court

Social Services Data

This section of the report has two parts: discussion of data collected by tribal and county child welfare programs through the Social Services Information System, and a review of data related to truancy and dropout intervention services of the White Earth Tribal Youth Program.

Tribal and county child welfare

As reported by the White Earth Indian Child Welfare and county social services staff listed above, no public domain data is currently available on the relationship between their respective programs (i.e., the services they provide and services to which they refer) and the educational achievement of White Earth children and youth. This is due primarily to the nature of their data collection system. County child welfare programs and White Earth Indian Child

Welfare collect, analyze, and report service activity and outcome data via the Minnesota

Department of Human Services‘ Social Services Information System (SSIS) (a statewide computerized case management and data collection system). SSIS allows staff in child, family, and adult services to record service information in computerized case files and permits county and state administrators to produce charts and reports on state and federal outcome indicators.

For child welfare programs, percentage data is reported on indicators such as safety and permanency outcomes, welfare system activity (e.g. number of children assessed, number of children placed in out-of-home care), reunification time frames, and institutional abuse.

Positive educational outcomes may be a by-product of county and non-county child welfare services but, as the county staff listed above indicated to the researchers, it would be P a g e | 374

difficult, if not impossible, to determine the relationship between academic success and child welfare services. As county staff noted, child welfare workers may or may not document referrals to non-county services in an SSIS case file and the entry may only be a service provider‘s name with no reference to the provider‘s agency or to the service outcome. In addition, although SSIS contains an educational screen, this screen allows only input of descriptive information such as name of school, grade level, and school schedule. Face-to-face interviews between child welfare workers and children/youth require discussion of the child‘s school experience, but workers record any documentation of this discussion in the case file hard copy, not in SSIS. Any determination of child welfare services‘ impact on educational outcomes would require reading through the hard copy service notes in case files, which may or may not contain such documentation.

It should also be noted here that White Earth Indian Child Welfare has only recently begun to use the SSIS program. Under the American Indian Child Welfare Initiative and through an agreement with the Minnesota Department of Human Services, Becker, Clearwater, and

Mahnomen counties transferred responsibility for responding to and managing child abuse and neglect cases to the White Earth Reservation in late 2007. White Earth Indian Child Welfare began using SSIS routinely in 2008. As with the counties, if child welfare workers document service referrals and any service outcome information, including information related to educational impact, they do so in the hand-written, hard-copy case files, not in SSIS. White Earth child welfare staff indicated that researchers would need to interview individual child welfare workers to determine service referral patterns and workers‘ perceptions of the impact of services on academic outcomes.

P a g e | 375

White earth truancy and dropout data

Although information is unavailable on the impact of county and tribal child welfare programs on academic success using SSIS data, an evaluation of the White Earth Tribal Youth

Program (TYP) contains published data on the success of that program in reducing the incidence of truancy and school dropout. The TYP, originally a federally funded grant program under the auspice of White Earth Tribal Court, now operates in the context of White Earth Indian Child

Welfare. The program was originally a collaborative of services designed to reduce juvenile chemical usage, reduce violence among youth and in the family, reduce truancy and school dropouts, and improve the juvenile disciplinary process (TYP Final Evaluation Report, 2008).

Between December 10, 2007 and February 4, 2008, The Improve Group (Mendota

Heights, MN) conducted an evaluation of the Tribal Youth Program (see Appendix A). The evaluation team examined a random sample of TYP case files (Appendix, Table 5), gathered data from organizations that provided Tribal Youth Program services, and conducted student surveys.

As can be seen in Appendix Table 6, the TYP effected statistically significant changes in students‘ beliefs about school and their expected school behaviors. The evaluation also found that program partners (child welfare service providers and school personnel) felt the TYP encouraged them to intervene earlier with struggling students and motivated them to continue intervening with older students because of the program‘s services and access to tribal court.

(This TYP report offers results consistent with an educational neglect study done by the

University of Minnesota‘s Center for Advanced Studies in Child Welfare. The original study, published in 2005, and a follow-up study published in 2009 examined the impact of child protection services on the school attendance of children who had received a determination of educational neglect. Findings from both studies suggested that child welfare involvement P a g e | 376

positively influenced school attendance in the short-term and long-term for both students of color and white students. The Center for Advanced Studies in Child Welfare offers a discussion of these studies on its website at http://www.cehd.umn.edu/ssw/cascw/attributes/PDF/ minnlink/No8.pdf).

Currently, two Child Protection/Truancy Workers at ICW provide educational neglect and truancy intervention/prevention services to students ages 5-18 in tribal and public schools.

With a per-worker caseload of anywhere between 40 and 100 students, workers monitor attendance, make school and home visits, offer school attendance incentives, make referrals to services, provide transportation, and engage in other supportive and case management activities to reduce truancy and school dropouts.

Despite the successes of the Tribal Youth Program mentioned above, the authors of this document have received informal reports that larger systemic problems continue to impede the academic success of White Earth youth. These systemic problems appear to include the lack of or ineffective truancy prevention programs in area schools, differences between state and tribal school attendance codes, schools not reporting truancies on a timely basis, and problems in communication between school and home. While this Comprehensive Study‘s educational system researchers will no doubt address these issues, non-school social services (e.g., the ICW educational neglect/truancy workers and the services to which they refer) play a role in mitigating the effects of these systemic issues. It is the intent of the authors of this Social

Services Phase 1 report to engage in interview research during Phase 2 to provide more data on the relationship between social services and academic success.

P a g e | 377

Appendix A

TRIBAL YOUTH PROGRAM

FINAL EVALUATION REPORT December 2008

Prepared by the Improve Group

Reduce truancy and school dropouts

Case files

Table 5 below shows that among the participant case files reviewed, the mean number of

absences for each youth was 24 days; some with very high numbers of consecutive

absences. Just under two-thirds had a report related to truancy within the current school

year. All had juvenile court cases related to truancy, and of these, 16 had court cases

within the current school year. Two students had dropped out of school.

Most of the youth and their families had been referred to programs, and all of the youth

participated in the programs they were referred to. A majority of families participated in

the programs to which they were referred.

Youth have been referred to external programs designed to help prevent truancy. These

include involvement with a truancy worker and individual counseling. Additional

services were offered through White Bison and the Northwest Minnesota Juvenile

Center. P a g e | 378

Although many of the cases were very recent, about half of the youth showed some

improvement related to truancy. Three youth were noted to have improvement lasting a

least several months.

Table 5: Truancy incidence, services and changes among TYP participants

High Low Mean # of absences 99 0 24 # of consecutive absences 60 0 7 Yes No Unsure Does the youth have a current (within 3 63% 37% 0% months) report on truancy? Does the youth have a truancy-related juvenile 100% 0% 0% case? Does the youth have a current (new within previous 3 months) 84% 11% 5% truancy-related juvenile case? Has the youth been referred to external programs 89% 11% 0% designed to prevent truancy? Has the youth been referred to programs designed to 89% 11% 0% reduce truancy? Has the youth's family been referred to programs 84% 16% 0% designed to reduce truancy? Did the youth participate in truancy 89% 11% 0% prevention/intervention programs? Did the youth's family participate in truancy 79% 21% 0% prevention/intervention programs? Got Better Did Not Change Got Worse Has the youth shown any changes in truancy- 47% 42% 11% related behavior?

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Surveys

Youth reported that after the program, they were more likely to believe school is important, attend school every day unless they were sick and expect that they will graduate from high school. These changes were all statistically significant at the 0.05 confidence level. Students also reported they were more likely to feel confident that they could succeed in the program, but this indicator was not statistically significant.

When asked what changes they‘ve seen in themselves since being involved in the program, youth said they now go to school more, their grades have increased, they stay out of trouble more and they get to class on time. Two students, however, noted that they have acted up more since being in the program since they are in school more.

Table 6: TYP participants’ average rating on their beliefs and behaviors before the program and after being involved in the program

Percent change after the program After being involved in Before the program (compared to the program before the program) Believe that school 2.7 3.3 21.6% is important1 Feel confident that they can 2.8 3.2 16.0% succeed in school Attend school 2.7 3.2 15.4% every day

1 The difference in participant ratings from before the program to after the program is statistically significant at the 0.05

confidence level. P a g e | 380

unless they are sick2 Expect that they will graduate 2.8 3.5 23.5% from school3 Note: Participants rated each item on a 4-point scale where 1 = never, 2 = rarely, 3 = sometimes, and 4 = always.

Interviews

Nearly all interviewees observed marked improvement among Tribal Youth Program participants related to truancy, and when they did see improvement they specifically attributed it to the program and to immediate consequences. They reported that with improved attendance, grades had also improved as had behavior in school.

One partner reported that the overall attendance rates had improved at the school when the Tribal Youth Program was implemented – the program helped stress the importance of attendance to all youth.

Adults also reported that the Tribal Youth Program made a difference in their work. They felt that the program helped them to intervene at a young age (under 16 years old) if they saw a student was having problems, and helped motivate them to intervene at an older age (16 to 18 years old) because they had stronger consequences to use with older youth. Most of the partners specifically reported that the involvement of the tribal courts was a strong incentive for youth to attend school. When non-native youth in their schools face issues with truancy, there is not a

2 The difference in participant ratings from before the program to after the program is statistically significant at the 0.05

confidence level.

3 The difference in participant ratings from before the program to after the program is statistically significant at the 0.05

confidence level. P a g e | 381

clear court system in place, so there are not immediate consequences or services offered. Those non-native youth struggle more and have less consistent improvements.

In addition to consequences, some partners reported that the circles helped youth feel more comfortable and committed to school. They felt that the circles helped youth know there are adults they can trust and who care about them at school.

Health Services Portion of the Study

Primary Author P a g e | 382

Tracy Moshier, RN, BSN; Graduate Nursing Student

Contributors

Tracy Wright, RN, PhD, CNE; Nursing, MSUM

Jane Bergland, RN, PhD; Nursing, MSUM

Terry Dobemeier, RN, MS; Nursing, MSUM

Abstract

The purpose of this sub-study was to describe the health disparities among White Earth

(WE) reservation youth ages 18 and younger. While some studies examine health disparities in

Native American (NA) children, very few analyze the link between health disparities and school achievement. This sub-study is a compilation of efforts from the health arm of Phase I within a larger study entitled Comprehensive Study Examining the Education and Related Services on the

White Earth Indian Reservation. The literature and retrospective data review of this sub-study sought to explore the specific health disparities that impact the WE youth. The process of reviewing national and state databases and professional journals assisted Minnesota State

University Moorhead (MSUM) and WE stakeholders in identifying areas for further in-depth review during Phase II of the larger study. During the literature review it was evident that multiple health disparities existed among NA youth. However, literature and data analysis focused specifically on the WE population was lacking. This lack of research information puts community leaders at a disadvantage when planning and seeking funding for programs aimed to address problems that are obvious to an observer however supported currently only by anecdotal evidence. Thus, the need for this study is timely and justified. This literature review provides the P a g e | 383

foundation for community-based participatory research and will aid in identifying and transitioning research findings into effective strategies to improve academic success for WE youth.

Chapter I – Introduction

Current Health Disparities for Youth on the White Earth Reservation: A Review of Literature

The Indian Health Service (IHS), an agency within the U.S. Department of Health and

Human Services, has identified that American Indians and Alaska Natives (AI/AN) suffer lower life expectancy and disproportionately higher disease burden compared to other populations.

This disparity is thought to exist due to ―inadequate education, disproportionate poverty, discrimination in the delivery of health services, and cultural differences‖ (IHS, 2008, para.3).

While Minnesota continues to lead the nation as one of the healthiest states, health disparities in communities of color within Minnesota show little to no improvement in rates of illness and death. The Minnesota Department of Health (MDH) (2007) Populations of Color in Minnesota:

Health Status Report (PCM) detailed how American Indian (AI) populations in Minnesota ranked worst in birth-related health risks and death rates. The PCM also found that AI‘s had the highest incidence of cancer and 21% were lacking health insurance coverage.

While much of the published statistics are related to the adult population, the health problems that develop during childhood and adolescence can have immediate and long-term impacts on health status later in life. Additionally, health problems of adults can directly impact

(genetically and environmentally) the future health of children in the home. Due to the unequal burden of health-related illnesses among children within our nation, especially minority children, and the central goal of Healthy People 2010 to eliminate health disparities between ethnic and racial groups, it is necessary to investigate age-specific disparities so that they may be reduced P a g e | 384

and/or eliminated. Chapter one will expand on the significance of health disparities on the White

Earth (WE) reservation and the implications of racial and ethnic disparities. It will describe the

Comprehensive Study Examining the Education and Related Services on the WE Indian

Reservation (CSEERSWE) purposed by MSUM and define the conceptual and operational variables. The theoretical framework by Lowe and Struthers (2001) will be outlined, giving a clear and culturally-appropriate format for gathering data in Phase I and II of the CSEERSWE study.

Background

The focus of the CSEERSWE study focuses on AI children birth to eighteen years, residing on the WE reservation. Researchers and WE community leaders determined five factors that were thought to be directly related to educational achievement. These factors included (a) education, (b) family, (c) justice system, (d) employment, and (e) services related to well-being.

Figure 1 below identifies the focus of the study population as including AI children residing on the WE reservation and identifies the five sub-study arms connecting to the central larger study.

The research committee for the CSEERSWE divided the study into three different phases. Phase

I required a review of literature and isolation of the relevant existing data for each of the five arms of the study. Phase II will include gathering data from potential sources such as interviews, focus groups, surveys, and/or review of quantitative data and generating recommendations and interventions for improvement for each respective partner in recognition of its respective sovereignty or autonomy‖ (Bradbury, 2008, p. 3). This report focuses on Phase I.

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Schools

Well Being American Family Services Indian Child Residing on the Reservation

Economic Justice Issues System

Figure 1. Factors Related to Educational Achievement for an AI Child Residing on the WE Reservation.

From ―Proposal for Comprehensive Study of Education and Related Services on the White Earth Indian

Reservation,‖ by B. Bradbury. Reprinted with permission of the author.

A study of this magnitude required each of the five contributing factors to be examined separately. The primary focus of this literature review by the well-being services branch (health arm) was on the health status of WE reservation youth and potential impacts on academic achievement. To achieve a comprehensive understanding of the factors in Phase I, a literature review was performed as a starting point for gathering published data on the health factors that impact AI children and the literature review acted as a basis for determining what type of WE specific data to review from IHS data banks.

To assess health disparities, it was necessary to first identify the determinant factors specific to youth on the WE population. It was believed that although related, health concerns of

WE youth are unique from adult health issues and deserving of individualized perspective.

According to Guthrie and Low (2006), ―Because adolescence is known as the period of P a g e | 386

transformation, it is an ideal time not only to identify and address but also prevent potential health disparities commonly found in adults. In addition, adolescents themselves must not be considered as downward extensions of the adult population with similar needs and experiences‖

(p. 6). For the purpose of this Phase I health arm WE literature review, ages were grouped into six categories, including 0-2 years, 3-4 years, 5-8 years, 9-11 years, 12-14 years, and 15-18 years. The breakdown into these groups allows for research-based health disparities to be age- focused, specific to the AI youth on the WE reservation, and of high utility to the school systems serving the WE reservation.

Significance of the Problem

Many studies, as discussed next, have illustrated the racial and ethnic disparities for AI adults, however there are very few studies specifically related to children and adolescents in general and even fewer related to AI children. Flores, Olson, and Tomany-Korman (2005) stated that, ―only 5 of 103 studies in the extensive literature review by the Institute of Medicine of health care disparities specifically addressed racial/ethnic disparities in children‘s health care‖ (p.

183). Of the limited studies that have been published, many only take into consideration one variable despite the fact that multiple areas such as race, socioeconomic status, environment, culture, and geography can all impacted health disparities. The article by Flores et al. (2005) gained national attention regarding its findings on racial and ethnic disparities in children.

However, their report analyzed only White, Hispanic, and Black youth. Berger, Wallace, and Bill

(2007), in the IHS Provider, summarized that, ―According to the 2000 Census, 33.3% of individuals who are American Indians or Alaska Natives are under the age of 18‖ (p. 206).

Considering the lack of studies focused on children, the lack of studies specific to NA, and the high proportion of NA who are under 18, the need for further investigation into the health P a g e | 387

disparities of NA youth is obvious and continues to grow. Unfortunately, NA youth become a minority within a minority and are shadowed by the increasing populations of Hispanics and

African Americans and the overwhelming needs of adult populations. This study attempted to overcome these barriers as much as possible by approaching the literature review of each NA age group in a methodical and individualized manner and seeking information/perspectives from tribal stakeholders.

The joint effort of MSUM and WE tribal leaders to explore the five factors thought to be related to educational achievement was a combined effort drawing on the expertise of all involved. MSUM has an extensive literature bank and expertise in synthesizing data. WE tribal leaders have supported the CSEERSWE by guiding the research to the specific needs of the children on the WE reservation. The vast knowledge and concern for the WE community generated talented individuals to help with gathering statistics and data not available in general literature reviews.

The effort to address childhood health disparities in the WE community needs to be viewed from multiple angles. Health disparities are unique to every minority population and it is the responsibility of healthcare professionals to individualize care to meet the needs of the population. Healthcare leaders need to motivate and mobilize current and future providers of healthcare to analyze their own cultural bias and move beyond those biases to provide culturally competent care. At the same time, healthcare research should continue producing evidence that supports culturally competent care while incorporating the concerns of the underserved communities. The goals of Healthy People 2010 must be recognized in healthcare research so that government responsibility and funding can be secured to help children experiencing health disparities. Lastly, by creating healthcare literature that demonstrates and supports the needs of P a g e | 388

individual NA communities, attention can be brought to the childhood health issues with the hope of providing evidence to address unmet needs. Strategies can be created, new public health policies can be adopted, resources can be used equitably, and community partnerships can grow through research such as undertaken in this sub-study.

Purpose Statement

The purpose of this study was to describe the health disparities among American Indian youth (< 18 years old) with specific focus on those using White Earth reservation IHS services.

Research Questions

Grounded theory served as the foundation for gathering health disparity data without injecting personal bias and experiences. ―The focus of most grounded theory studies is on the discovery of basic social psychological problem that a defined group of people experience, and on the social psychological stages or phases that characterize the process used to cope with or resolve this basic problem‖ (Polit & Beck, 2006, p. 222). Utilizing grounded theory concepts was ideal as it provided the basis to generate data and directions in an understudied population as the study progressed rather than in an a priori fashion. It allowed for the population of interest (WE leaders) to help guide the items of importance, research questions, and areas for closer review based on experience of the WE leaders and community members. The research questions were:

Nationally and within WE reservation: 1) What is the current state of the literature on health disparities among NA youth? and 2) What current data exists related to health disparities among

NA youth?

Conceptual/Scientific Definition of Variables

The three main variables in this study included WE reservation, youth, and health disparities. The WE reservation encompasses approximately 990,000 acres and includes P a g e | 389

Mahnomen, Becker and Clearwater Counties on the federal register. For the purpose of this study, the conceptual definition for WE was defined per the Contract Health Service Delivery

Area (CHSDA) as Mahnomen, Becker, Clearwater, Norman, and Polk Counties. The CHSDA definition includes a broader geographical region where IHS services must be provided to NA per federal law.

The second variable addressed the concept of youth. Terms such as adolescence, youth, and children can imply different age brackets. The review of literature for this study defined youth as people under the age of eighteen years.

The third variable, health disparities, needed to be considered from three different perspectives in order to fully encompass the health concerns of the WE population. The first definition generated from the literature review was based on nursing research which frequently defines health disparities in broad terms. Guthrie and Low (2006) stated that,

―Understanding and addressing health disparities moves the discourse beyond the medical consequences of health disparities toward a definition of health disparities that do not just happen or occur within a vacuum but rather are manifestations of the integral and complex life course tapestry that reflects differential treatment of youth because of their educational preparation, social position, biological and genetic endowment- including physical or mental abilities, race or color of skin, immigrant status, religion, or place of residence.‖ (p. 4).

Based on the review of literature and WE stakeholder concerns, the IHS statistician gathered data specific to WE youth health disparities and demographics. Demographic information was provided by Bemidji Area Indian Health Service and the U.S. Census Bureau

Fact Finder. The IHS statistician retrieved data on the following health disparities per researcher request: height, weight, body mass index (BMI), dental fluoride treatments, blood lead levels, diabetes, respiratory syncytial virus (RSV), bronchiolitis, lice, immunizations, and suicide. P a g e | 390

Although the information was requested, not all data was available in the database system. The

Bureau of Indian Affairs, Bemidji Area IHS, 2008 Government Performance Results Act Report for WE, and the 2005 Bureau of Indian Population and Labor Force Report were utilized in the data search.

The second definition of health care disparities was brought to the attention of the researchers during face-to-face meetings with the WE community stakeholders. During such meetings, health disparities among WE children were noted. This was especially helpful in filling in the gaps not identified in the literature review.

Lastly, health disparities is defined by the Centers for Disease Control (CDC) (2005) as,

―The quantity that separates a group from a specified reference point on a particular measure of health that is expressed in terms of a rate, percentage, mean, or some other quantitative measure‖

(p. 2).

Since this study examined WE youth in comparison to state and national data, the definition from the CDC provided uniformity when describing the conceptual definition. Figure

2 provides an illustration of the interconnected nature of the White Earth reservation, youth, health disparities, and the potential that each of these factors has to positively or negatively impact one another.

White Earth Reservation

Health Youth Disparites

Figure 2. Interconnection P a g e | 391

The operational definition (see Table 1) explains how the variables (WE reservation, youth, and health disparities) were measured. The term WE reservation was measured per the counties extracted from the IHS database within the Contract Health Service Delivery Area

(CHSDA) parameters. The term youth was measured through the demographic information from the IHS statistician. The operational definition for health disparities was approached from a three part explanation from the literature review, the second from the WE stakeholders, and the third from the CDC. Jason Douglas, statistician from Bemidji IHS, used a customized extract from

IHS National Data Warehouse (NDW) to gather information on the health disparities specific to

WE children. The customized extract included keywords, ICD-9 codes, and population statistics based on the concerns of the WE leaders and the results of the literature review.

Table 1. Conceptual and Operational Definition

Variable Conceptual Definition Operational Definition White Earth Reservation AI residing in Mahnomen, Becker, Per counties pulled in IHS Clearwater, Norman, and Polk database Counties Youth AI under the age of eighteen years Per demographic data pulls

Health Disparities Tri-fold Customized extract from IHS 1. Literature review guided National Data Warehouse specific disparities to the WE health center including 2. WE community definition all federal and tribal satellite 3. CDC definition faculties.

Theoretical Framework

The Conceptual Framework of Nursing in Native American Culture (Lowe & Struthers,

2001) was used as the theoretical framework to provide structure when thinking about and synthesizing data. Few published studies have been constructed using this conceptual model.

Even fewer have been created using NA people as the target population. The conceptual P a g e | 392

framework design by Lowe and Struthers was formed to, ―depict the nature of nursing in Native

American culture‖ (p. 280). Seven themes from the theory arose describing the core principles of

NA nursing including ―caring, traditions, respect, connection, holism, trust, and spirituality‖

(Lowe & Struthers, p. 282). The shape of the conceptual model (see Figure 3) forms a circle,

―indicating the circular holistic world view of Native American culture‖ (Lowe & Struthers, p.

282). The cross shape of the medicine wheel with the four directions of East, South, West, and

North and the great thunderbird placed on the outside of the circle all have scared meaning to many NA tribes in North America (Lowe & Struthers, p. 282). To deliver culturally competent care to NA populations, Lowe and Struthers concluded that each of the seven dimensions must be considered to guide nursing practice in delivering health care (see Figure 3).

Figure 3. Conceptual Model of Nursing in Native American Culture. From ―A Conceptual Framework of Nursing in

Native American Culture,‖ by J. Lowe and R. Struthers, 2001, Journal of Nursing Scholarship, 33(3), p.

282. Copyright 2001 by the Journal of Nursing Scholarship. Reprinted with permission of the author.

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The Conceptual Framework of Nursing in Native American Culture provides a basis for including beliefs, values, and customs into the foundational philosophy of this study. Based on the data identified in the literature review, this quantitative data was ―used to corroborate or refute qualitative study findings‖ (Bradbury, 2007, p. 2). Therefore, the research produced in WE

Phase I generated data on the current health disparities of youth on the WE reservation. The information provided in this report aimed to be specific to the WE population through the review of literature and WE specific data; however, when data was unavailable, state and national databases were used to fill in the gaps. Phase II will incorporate the conceptual framework of

Lowe and Struthers (2001) through surveys, interviews, focus groups, observations, ethnographies, historical documents, and/or review of quantitative data. Bringing to light the data from Phase I and Phase II will embody the vision of Lowe and Struthers by creating research that is mainstream and specific to the needs of NA communities.

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Table 2.

Relationship of Conceptual Framework to Research Questions, Variables, & Measurement Tools

Conceptual How each concept impacted the research question, process, or measurement Framework tools Core Principles a. Caring 1. Have WE scholars, leaders, and statisticians involved in Phase I and II of the study as a means of improving culturally competent care. 2. Gather data in a culturally sensitive manner, demonstrating concern for tribal communities when collecting information. b. Traditions 1. During Phase I, engage community leaders to identify the health disparities that they observe on the WE reservation with respect to their values and traditions. c. Respect 1. Demonstrate respect of WE tribal members by allowing them input to describe the health disparities they observe, not using time limits. Instead, valuing the use of oral tradition in Phase I to guide data to what WE leaders see as health disparities affecting their youth. 2. Be respectful of terminology when describing an individual or group, acknowledging that the people have the right to decide what they wished to be called in professional publications. 3. Phase II of the study will utilize interviews and focus groups which respect traditions and privacy. d. Connection 1. Researchers will learn about the WE community by getting to know WE people, attending local events, and becoming familiar with local customs. e. Holism 1. Researchers will honor traditional healing practices by inviting WE health care professionals as a bridge in exploring western medical practice and traditional healing. f. Trust 1. Assure WE tribal leaders and community members that research participants information will protected. 2. During Phase II, review and discuss research findings with the tribal elders so that published study results are not misinterpreted and misunderstood. g. Spirituality 1. Researchers need to consider the definition of health disparity in broader terms. It may encompass AI beliefs about destiny unity, and balance.

Assumptions and Limitations P a g e | 395

The research of AI health disparities lends itself to many assumptions and limitations.

The most profound limitation is the general lack of information and delineated ethnic/racial statistics in local, state, and national databases. Locating information specific to the WE population proved to be especially challenging. Even more difficult was isolating age-specific data for WE youth. Guthrie and Low (2006) found similar difficulties stating, ―Nursing literature remains devoid of information that identifies, prevents, or proposes a plan to address health disparities among adolescents‖ (p. 3). Surprisingly, the adolescent population produced the most information on health disparities in the literature review, but infant and school age children fell well below that margin. This lack of information often forced health disparity assumptions based on the only available data, that of adults.

A precursor to the lack of statistical analysis and publications was the lack of reliable data being collected in communities of color. Community leaders on the WE reservation are striving to improve data collection by updating IHS software. Within the last year, WE IHS implemented mental health and diabetes coding into their records. ―The collection of broader contextual data regarding adolescent health will lead to greater opportunities to conduct nursing research that addresses the complexity of health disparities,‖ (Guthrie & Low, 2006, p. 9).

A further limitation was the number of AI children not using IHS Health Services and not receiving preventative care. Although national and state databases synthesize data from IHS databases, they rarely detail the number of children in the AI population compared to the percentage receiving or not receiving IHS health care. Groom, Washington, Smith, and Bryan

(2008) reminded analysts that only 40% of AI/AN children use IHS services, therefore only the results of those children are being used to demonstrate increases in health preventative measures such as immunizations. P a g e | 396

Knopf, Park, Brindis, Mulye, and Irwin (2007) identified three strategies to strengthen adolescent sub-population needs: (a) create health profiles of a variety of adolescent sub- populations; (b) assure that national databases collect and report information regarding crucial objectives with more sub-population identifiers; and (c) create specialized data collection tools.

Again, the focus of the aforementioned studies analyzed only adolescent populations, emphasizing the need for research among infant and school age children. Creating tools to identify health needs is as important as educating health care providers to use the tools correctly so that data can be synthesized.

The final noteworthy limitation is that this is not an experimental design. There is no randomization, assurance of generalization to the larger population, control of variables, or complete/comprehensive data. This study proceeded without these controls and thus the limitations inherent in a descriptive retrospective design are applicable.

Chapter I Summary

Health disparities in the AI population have persisted for generations despite medical advances. The impact that health has on classroom achievement is an important aspect of the

CSEERSWE study. The purpose of this literature and data review sub-study was to examine the predominant health disparities that exist for specific age brackets of WE youth. This focused literature and data search identified national, state, and WE information needed to formulate a more comprehensive understanding of the situation and assisted in the planning for Phase II surveys, recommendations, and ultimately interventions to improve classroom achievement for youth on the WE reservation.

Chapter II- Review of Literature

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Phase I in the CSEERSWE required researchers to perform a literature review of each of the five arms of the study. Therefore, the focus of this health arm sub-study was to determine what health disparities exist for WE youth, ages 18 and under, as described in the national, state, regional literature and databases.

Literature Review Organization

For the purpose of this WE literature review, ages were grouped into six categories, including 0-2 years, 3-4 years, 5-8 years, 9-11 years, 12-14 years, and 15-18 years. The breakdown into these groups allowed for research-based health disparities to be age-focused, specific to the AI youth on the WE reservation and have high utility to the school systems serving the WE reservation.

At the beginning of the literature review, it was evident that some data was either not available for every age bracket and/or data fell outside of the 2 year limits. For example, the

CDC Pediatric Nutrition Surveillance System (PedNSS) (2007) grouped ages 2-5 years therefore skewing information breakdown established by the literature review. To maintain the integrity of the data and capture information that did not nicely fit into the pre-established age groups, summary paragraphs, for ages 9 and under and ages 10 and over were created to identify health disparities in a larger group format and to provide a more comprehensive overview.

After providing the search strategy, the two year age brackets were further broken down into national/state data, WE data, and specific areas of focus/concern. The specific areas of concern for Phase II of the study were created based on the results of the literature review, input from meetings with WE community leaders, and the researcher‘s expertise.

Search Process P a g e | 398

The introduction paragraph for each two year age bracket includes a separate search strategy with individual search engines and the keywords. This was necessary due to the changing terminology of children throughout different stages of development. For example, words such as infant, child, toddler, school-age, and teenager could all produce different journal articles or national data bank results. Instead of creating a search process that described the entire literature review, each age bracket outlines a separate search strategy as a means to provide detail and auditability to this report.

Age Group: 0-2 Years of Age

Search strategy.

The search strategy used in this age group included a review of the following databases:

(a) Native Health Database, (b) Gale Power Search, (c) ERIC, (d) PubMed, and (e) CINAHL.

Keywords used included (a) White Earth reservation, (b) infant, and (c) health disparities. This generated only one article related to otitis media. The search was expanded to include the key words (a) Native American, (b) American Indian, (c) Minnesota, (d) Mahnomen, (e) rural, (f)

Northern plains, and (g) ages 0-2 years. This broadened search revealed studies on breastfeeding practices, immunizations, and provided a comparison study on infant mortality trends in the

1990‘s. The literature search captured articles from 1980 to the present.

Due to the limited nature of the journal hits, the search data bases were expanded to include the Minnesota Department of Health, Kaiser State Health Facts, Centers for Disease

Control and Prevention, the U.S. Department of Health and Human Services Office of Minority

Health, and Indian Health Services. Still, there remained a gap between the verbal concerns expressed during meetings with WE stakeholders and published information. To bridge this gap, P a g e | 399

search engines such as Google and Yahoo were also incorporated into the following summaries as a means to explore media and community concerns.

National and state data.

The Office of Minority Health (OMH), a division of the U.S. Department of Health and

Human Services, found that the NA infant in the general population has a mortality rate 1.4 times higher than non-Hispanic whites. Some of the contributing factors to this disparity included (a) sudden infant death syndrome (SIDS), (b) congenital anomalies, (c) unintentional injury, (d) respiratory distress syndrome, and (e) low birth weight (Tomashek et al., 2006). IHS Trends in

Indian Health (2000-2001) showed a 64% decline in infant mortality rates from 1972 to 1998.

However, the rate for AI/AN infant mortality rate continued to be 24% higher than all other races in the United States. Mathews and MacDorman (2008), in the CDC National Vital Statistics

Reports (NVSR), indicated that the state of Minnesota has an infant mortality rate of 4.78 per

1,000 live births in the general population with the rate for American Indians or Alaskan Natives in the state at 8.59 per 1,000 live births.

White Earth data.

No specific data for infant mortality rates was located in the literature review for the WE reservation. The only study located related to WE was conducted by Daly, Pirie, Rhodes, Hunter, and Davey (2007) which explored the relationship between otitis media risk factors, sociodemographic characteristics, maternal knowledge, and maternal attitude . The participants in the study were adult women from Minnesota Ojibwe reservations. Findings concluded that

―infant history of upper respiratory infection and maternal otitis media history are risk factors for early otitis media in American Indian infants. Mother‘s pre-partum knowledge and attitudes regarding otitis media did not predict their postpartum avoidance of risk factors‖ (Daly et al., p. P a g e | 400

17). Some of the risk factors for otitis media (OM) in the Daly et al. study included breast- feeding, living arrangements, and smoke exposure. A separate study by Curns et al. (2002), although not specific to the WE reservation, supported Daly et al. by affirming, ―OM morbidity is greater among specific groups of American Indian/Alaskan Native (AI/AN) children than among the general population of children‖ (p. e42). While this morbidity information is important, the WE-specific literature is remiss in providing information on mortality in this age group and a comprehensive coverage of high morbidity rates within other disease categories.

Specific areas of focus/concern.

Fatal injuries.

There may be general awareness of an increased rate of fatal injuries among the most vulnerable of the NA population; however the extent of this is area of morbidity/mortality is astonishing. Benard, Paulozzi, and Wallace (2007) conducted a major study titled, Fatal injuries among children by race and ethnicity-United States, 1999-2002. The findings concluded that NA infants under l year of age had injury death rates ―two to three times those of white infants for total injury, unintentional injury, and homicide‖ (Benard et al., 2007, Results, para. 1). A major conclusion in the Benard et al. article was that AI/ANs had the highest rate of motor-vehicle

(MV)/traffic deaths for children under one year of age (Results, para. 1). Patel, Wallace, and

Paulozzi (2005) published the Atlas of injury mortality among AI and AN children and youth

(AIM) covering a ten year span from 1989-1998 for children 0-19 years old in all IHS areas in the United States. The executive summary notes a few items significant to NA youth aged 0-2 years. Patel et al. found that children under 1 year of age were most likely to die of suffocation, choking, and strangulation (p. 3). Homicide rates for infants were the second leading cause of P a g e | 401

injury death among infants and the second highest rate in all ages combined; second only to males ages 15-19 (p. 3). The PCM did not list any cause of death specific to age nor did it include AI data on SIDS for the state of Minnesota.

There was no information in the literature review which grouped WE infant statistics; however the IHS area in Bemidji was noted in the Patel et al. atlas as having one of the highest rates of suffocation deaths among the IHS areas (p. 3). Although the information from the above studies is useful when examining AI populations as a whole, it does not provide health disparities specific to the WE reservation. Overall, data was gleaned from ICD9-E-Codes limiting the needs of individual reservations. Fatal injuries are of great concern because the data suggests that many of the infant deaths are of a nature which are preventable with parent education and support.

Sudden infant death syndrome.

The American Academy of Pediatrics (AAP) indicated that SIDS rates have decreased by

50% in the general population since 1992 (AAP, 2005). However, huge disparities exist among the IHS areas. Burd et al. (2007) noted that ―All Races SIDS rate was 10.7 per 1,000 live births, the all IHS rate was 18.1‖ (p. 365). Older studies such as the one by Bulterys (1990) discussed the increased rate of SIDS in the Northern Indians linking it to the increased incidence of maternal smoking. More recent findings indicated that SIDS education has improved and the leading cause of infant mortality in the state of Minnesota is currently congenital malformations

(Mathews, 2008, p. 10). The prevention of SIDS continues to be a national movement in AI communities. No data specific to SIDS on the WE reservation was available. P a g e | 402

Prenatal care.

Access to prenatal care and follow up care of low birth weight or premature infants contributes to the increase in infant mortality. ―Although difficult to measure, the timing and quality of prenatal care by the mother during pregnancy can be important to the infant‘s subsequent health and survival‖ (Mathews & MacDorman, 2008, p. 7). Tomashek et al. (2006) cited, ―The remoteness of many AI/AN communities and difficulties in recruiting and retaining professional staff to serve in isolated Indian Health Services areas are obstacles to providing quality delivery services‖ (p. 2225).

The adequacy and use of prenatal care cannot be ignored. According to OMH (2008),

―American Indian/Alaska Native infants are 3.6 times as likely as non-Hispanic white infants to have mothers who began prenatal care in the 3rd trimester or did not receive prenatal care at all‖

(bullet 3). The Kaiser Family Foundation (2007) produced a study with similar result showing that AI/AN are at least twice as likely to receive little or no prenatal care. What makes these statistics even more concerning for the WE reservation is the increased rate of poor birth outcomes in impoverished rural populations. A study by Larson, Murowchick, and Hart (2008) found that residents of rural persistent poverty counties experienced higher risk of low birth weight and post-neonatal mortality than residents of rural non-poverty counties. The Minnesota

County Health Tables (2007) indicated that Mahnomen County had the fourth highest rating for inadequate or no prenatal care in the state of Minnesota (p. B-7). Becker and Clearwater counties, also part of the WE reservation, were comparable to other counties in the state (p. B-7). P a g e | 403

Impact of teen pregnancy.

Children ages 0-2 years old born to teenagers may also be impacted by their mother‘s young maternal age. These children have a higher incidence of unintentional injury, illnesses, hospitalizations, and emergency room visits (Koniak-Griffin & Turner-Pluta, 2001). Factors affecting adolescent mothers include poverty, social isolation, social inequality, and abuse

(Koniak-Griffin & Turner-Pluta). These factors may impact infant health and may be superimposed on the WE adolescents bearing children. A correlation between the teen pregnancy rate, prenatal care, and infant statistics was not available for WE reservation. Further information specific to teen pregnancy will be addressed later in the literature review under the adolescent age bracket.

Age Group: 3-4 Years of Age

Search strategy.

The search strategy used in this age group included a review of the following databases:

(a) Native Health Database, (b) Gale Power Search, (c) ERIC, (d) PubMed, and (e) CINAHL.

Keywords used included White Earth reservation and health disparities. No literature was located for ages 3-4 years. Expanding the search to include the key words (a) Native American, (b)

American Indian, (c) Minnesota, (d) Mahnomen, (e) rural, (f) Northern plains, (g) preschool, (h)

Head Start, and (i) children ages 3-4 years revealed studies on immunization coverage, oral health, vision and lead screening. The addition of IHS information produced an article specific to

Bemidji and child mortality rates for this age range. The CDC website provided information specific to ages 3-4 in the 2006 PedNSS. Many of the reviewed articles summarized statistics from the IHS and CDC and did not produce new findings. The literature review captured articles from 1980 to the present. P a g e | 404

Because the review of journal information was limited, the search was again expanded to include the Minnesota Department of Health, Kaiser State Health Facts, Centers for Disease

Control and Prevention, the U.S. Department of Health and Human Services Office of Minority

Health, and Indian Health Services. Still, there remained a gap between the verbal concerns expressed during meetings with WE leaders and published information. To bridge this gap, search engines such as Google and Yahoo were incorporated into the following summaries as a means to explore media and community concerns.

National and state data.

The national and state data bases grouped ages into three brackets for the majority of the literature review. The CDC findings identified children as less than one year of age, 1-9 years of age, and 10-19 years of age. The literature review was further complicated by the lack of data for

NA populations in national surveys and reports.

The IHS methods of gathering data pooled CDC statistics, National Center of Health

Statistics (NCHS), and U.S. Census Bureau in many of the articles in the IHS Provider. This allowed for much more age-specific data to be analyzed and was very useful for the purposes of the literature review. As stated earlier, the 3-4 year old age bracket in the majority of the articles was incorporated in the 1-9 age category. The best way to include these health disparities was to create a summary for 1-9 years and identifying Specific areas of focus/concern which will be analyzed later in the literature review.

One exception to available literature was found. Berger, Wallace, and Bill (2007) used

CDC information which bracketed ages 1-4 years. The best way to organize this particular set of information was for it to remain in the 3-4 year category when summarizing the health disparity of unintentional injury. P a g e | 405

White Earth data.

No literature was located with the keyword search for the WE reservation for children 3-4 years old. There was literature for the Bemidji IHS related to Head Start health indicators. Head

Start data placed children into the age bracket of 2-5 years which exceeded the limits established by this literature review age bracket; however it was most appropriate to cover these topics in the

3-4 year old category. To organize and expand upon the topics of dental caries, vision screening, lead screening, obesity, unintentional injury, and fire-related injury and death the Specific areas of focus/concern will be used.

Specific areas of focus/concern.

Dental caries.

IHS (2008) recognized dental caries as one of the health priority focus areas in the Head

Start program and Healthy People 2010, a division of the U.S. Department of Health and Human

Services (HHS), identified dental caries as the single most common chronic disease of childhood

(IHS, 2009) (HHS, Oral Health, Issues, para. 1).

American Indian and Alaska Native (AI/AN) children experience dental caries at a higher rate than the general U.S. population. Data from 2,663 children ages 2-5 years documented that 79 percent had experienced dental caries (filled or unfilled decay) and 68 percent had untreated dental caries. Over 50 percent of the children ages 2-5 years had severe Early Childhood Caries (ECC). (IHS, 2009, para.2).

Two articles were located that addressed oral health as a health disparity in AI/AN populations. Both concluded that AI/AN children are disproportionately burdened and dental caries should be treated as a priority illness (Allukian, 2008; Nash & Nagel, 2005). The Kaiser

Family Foundation (2003) concurred that oral health disparities are especially high in minority and vulnerable populations. Two other articles were very specific about the cause of dental caries P a g e | 406

in children. Weinstein, Troyer, Jacobi, and Moccasin (1999) and Bruerd and Jones (1996) both gathered data on IHS children in Head Start and found a high incidence of baby bottle tooth decay, a pattern of dental decay affecting the primary teeth due to sweetened liquids during naps or bottle feeding beyond 12 months. Allukian cited cost, lack of dental public health infrastructure, lack of dental insurance, limited providers, lack or diversity among providers as some of the barriers to oral health. One consideration in long-term risk factors associated with dental caries is the link between nutrition and diabetes. However, no studies were available on this topic for this age bracket. Nash and Nagel (2005) concluded their article by suggesting that it was a matter of social justice that AI/AN children receive adequate oral care (p. 1328).

The only specific information for AI/AN patients that reside in the WE service delivery area was provided by the 2008 Government Performance Results Act report for WE. These patients, age not identified, had at least 2 visits to an IHS or tribal provider at White Earth between 07/01/2005 and 06/30/2008, there were 936 topical fluoride and 2,266 dental sealant applications between 07/01/2007 and 06/30/2008.

Vision screening.

Vision screening disparities produced four journal articles all of which were specific to narrow NA populations, unrelated to WE, or they were published in ophthalmology journals depicting specific procedures. There was no available data on Minnesota or WE reservation regarding vision disparities for 3-4 year olds.

Lead screening.

The lead screening literature search did not produce any information for AI/AN children on the WE reservation, Mahnomen, or Northern Plains. Articles containing information related P a g e | 407

to AI/AN children were outdated, prior to 2000, or were using lead levels from children in known high level areas. Meyer et al. (2003) in the article Surveillance for elevated blood lead levels among children, indicated that approximately half of the data gathered failed to identify a specific race or ethnicity. The information that did result from the Meyer et al. study showed

AI/AN children to have a decreasing trend in the incidence of blood lead levels. This was also supported in the Bartholomew and Vanderwagen (1999) study. However, Meyer et al. found that

Minnesota was in the upper third of confirmed lead blood levels above 10 ug/dl. This information may warrant further investigation into blood lead levels on the WE reservation.

Statistical data was unavailable for lead blood levels in children residing on the WE reservation.

Obesity.

The increasing trend in obesity statistics started to become evident in the 3-4 year old age group. No keywords located literature on obesity for WE reservation, Minnesota, Mahnomen, or

Northern Plains specific to ages 3-4 years. The 2006 CDC PedNSS indicated that although only

1% of the children in the study were of AI/AN decent, they carried the highest burden of obesity.

The PedNSS (2006) found the prevalence of overweight AI/AN children ages 2-5 was 14.8% compared to 13.9% for all U.S. children. The IHS Head Start Program identified obesity and diabetes as a health priority focus area, although their data was grouped <15 years of age, that bracket has seen a 77% increase in obesity from 1990-2004. Story et al. (2003) stated,

―American-Indian children ages 24-59 months showed that 29.3% had a BMI-for-age greater than the 85th percentile and 13.7% had a BMI greater than the 95th percentile. This data indicates that obesity in American-Indian children appears to begin in early childhood‖ (p. S5). Story et al. cited three different research studies that pointed to the increasing trend in AI/AN obesity. One P a g e | 408

study in particular was performed in the Midwestern region of the U.S. implicating a closer relationship to the WE reservation.

Meager statistical data was available specific to WE in the data summary from the national repositories by Jason Douglas, Bemidji Area Indian Health Service Statistician. For 3-4 year olds, the mean BMI for children who had their height and weight measured in the same day during a visit sometime during calendar years 2005-2007 was 17.33. Further analysis revealed that the BMIs for 3-4 year old females (M = 17.22, N = 117) was not significantly different from the BMIs for 3-4 year old males (M = 17.18, N = 130) [t (245) = 0.11, p > .05]. Noticeable increases above the 50th percentile BMI were not noted in children receiving care at WE health center until after the age of 5 years.

In the Bemidji Area IHS data pull for WE between 01/01/2005 and 12/31/2007, there was one diabetes-related visit by a 4 year-old female. In this particular case, the principle diagnosis was diabetes mellitus type II, not stated as uncontrolled. Further BMI data is represented in the

13 years and under summary.

Unintentional Injury.

The IHS Provider published an article by Berger et al. (2007) summarizing the 2000-

2002 leading causes of death for AI/AN children and youth. Although the article grouped children into 1-4 years of age, making it difficult to delineate the information into two age categories, for the purpose of study it will remain in the 3-4 year section of the literature review.

Overall, the findings in Berger et al. for AI/AN children was equal to white children except for mortality rates in infants and in 1-4 year olds. Unintentional injury accounted for 35.9% of the deaths for 1-4 year olds. Motor vehicle crashes, which are consistently high for every age P a g e | 409

bracket, and homicide were responsible for the highest number of AI/AN deaths. An important consideration for WE children is the rural location of the reservation boundaries and the general underestimation of national AI child mortality rates. Berger et al. noted, ―Particularly in AI/AN communities, geographic isolation, lack of resources, an absence of tribe-specific child mortality review teams, and cultural practices can be barriers…..‖ (p. 206). The IHS Head Start Program recognizes injury prevention as one of the five focus areas and lists it as the leading cause of death for children aged 1-4 years old.

Fire-related injury and death.

The rate of fire-related injury and death for preschoolers is of great concern to the NA populations of Northern Minnesota. Kuklinski and Cully (2007) published an article that detailed the Bemidji area IHS program to increase smoke alarm usage in the region. The authors indicated that residential fire mortality rate for AIs was 1.5 times the national rate and areas specific to the north-central and Midwestern portion of the U.S. had disproportionally higher rates, 10 times the national combined rates. The data gathered by Kuklinski and Cully from several reservations during the study indicated that less than 50% of homes had at least one working smoke alarm. The study went on to further assess the fire-related mortalities of AI children in the Bemidji area where 0-4 year old children had a 10.9 per 100,000 increased chance of a fire-related death, three times higher than the national all-races rate. This information also parallels the above findings from Berger et al. on unintentional deaths. Although no data related to smoke alarm usage has been reported from the WE reservation, the proximity to Bemidji and related mortality rates to this region demonstrate the need for further evaluation.

Age Group: 5-6 Years of Age P a g e | 410

Search strategy.

The search strategy used in this age group included a review of the following databases:

(a) Native Health Database, (b) Gale Power Search, (c) ERIC, (d) PubMed, and (e) CINAHL.

Keywords used included White Earth reservation and health disparities. No articles were generated using the above combination of keywords and databases. Expanding the search to include the key words (a) Native American, (b) American Indian, (c) Minnesota, (d) Mahnomen,

(e) rural, (f) Northern plains, (g) school age, and (h) ages 5-6 years revealed no literature. The literature review targeted articles from 1980 to the present.

Because the review of journal information harvested no publications, the search was again expanded to include the Minnesota Department of Health, Kaiser State Health Facts,

Centers for Disease Control and Prevention, the U.S. Department of Health and Human Services

Office of Minority Health, and Indian Health Services. Still, there remained a gap between the verbal concerns expressed by the WE stakeholders and published information. To bridge this gap, search engines such as Google and Yahoo were incorporated into the following summaries as a means to explore media and community concerns.

National and state data.

National and state information was provided in grouped data format typically between ages 1-9 years. The more specific data on injury and death rates were also lumped into ages 1-9 years. The most feasible way to deliver this information was to create a summary for ages 1-9 years found later in the literature review.

White Earth data

One qualitative study by Aakhus and Hoover (1998) titled Rural Ojibwe Mother’s

Experiences with Early Childhood Special Education Services sampled two NA mothers from P a g e | 411

the Midwest. Although this article is useful at revealing underlying experiences, qualitative studies do not aim to provide generalizable information that would apply to general health disparities for 5-6 year olds. No data specific to the WE reservation was generated in this journal article.

At a joint meeting between MSUM researchers and WE stakeholders, a concern was raised regarding the incidence of lice in young school-age children. In most school districts when nits are found a child‘s hair, school policy mandates immediate removal from school grounds by a parent or guardian and children may not return until evidence of lice is gone. The statistician for this study attempted to locate E-codes for the bite of non-venomous arthropods but the information was not in the data set. Therefore, statistical data was not available to objectively supplement the anecdotal evidence. The incidence of lice or non-venomous arthropods needs to be investigated further to indicate a health disparity for 5-6 year olds attending school on the WE reservation as frequency of this issue or reoccurrence would directly impact school attendance and progression.

Age Group: 7-8 Years of Age

Search strategy.

The search strategy used in this age group included a review of the following databases:

(a) Native Health Database, (b) Gale Power Search, (c) ERIC, (d) PubMed, and (e) CINAHL.

Keywords used included White Earth reservation and health disparities. No articles were generated. Expanding the search to include the key words (a) Native American, (b) American

Indian, (c) Minnesota, (d) Mahnomen, (e) rural, (f) Northern plains, (g) school age, and (h) ages

7-8 years revealed no literature. The literature review targeted articles from 1980 to the present. P a g e | 412

Again, the review of journal information was limited, therefore the search was expanded to include the Minnesota Department of Health, Kaiser State Health Facts, Centers for Disease

Control and Prevention, the U.S. Department of Health and Human Services Office of Minority

Health, and Indian Health Services. Still, there remained a gap between the verbal concerns expressed by the WE stakeholders and published information. To bridge this gap, search engines such as Google and Yahoo were incorporated into the following summaries as a means to explore media and community concerns.

National and state data.

The information from the major federal and state agencies included no age-specific data for 7-8 year olds. The grouped data and specific focus areas will be addressed in the summary for ages 1 to 9 years.

An article by Story et al. (2001) was the only relevant journal article generated in the literature search titled, Weight Loss Attempts and Attitudes Toward Body Size, Eating, and

Physical Activity in American Indian Children: Relationship to Weight Status and Gender. The participants were second and third graders from Arizona, New Mexico, and South Dakota Indian reservation schools. Story et al. found that that 42% (n=1441) of second and third graders were overweight or obese and weight modification efforts were common among overweight children

(p. 362). No other literature indicated that dieting began this early for AI children.

White Earth data.

No literature was located with the previously outlined keyword search specific to the WE reservation for children aged 7-8 years old.

P a g e | 413

Age Group: 9-10 Years of Age

Search strategy.

The search strategy used in this age group included a review of the following databases:

(a) Native Health Database, (b) Gale Power Search, (c) ERIC, (d) PubMed, and (e) CINAHL.

Keywords used included White Earth reservation, and health disparities. No articles were generated. Expanding the search to include the key words (a) Native American, (b) American

Indian, (c) Minnesota, (d) Mahnomen, (e) rural, (f) Northern plains, (g) school age, and (h) ages

9-10 years revealed no literature. The literature review targeted articles from 1980 to the present.

The review of journal information was limited, therefore the search was again expanded to include the Minnesota Department of Health, Kaiser State Health Facts, Centers for Disease

Control and Prevention, the U.S. Department of Health and Human Services Office of Minority

Health, and Indian Health Services. Still, there remained a gap between the verbal concerns expressed at WE meetings and published information. To bridge this gap, search engines such as

Google and Yahoo were incorporated into the following summaries as a means to explore media and community concerns.

National and state data.

The information from the major federal and state agencies included no age specific data for 9-10 year olds. The grouped data and specific focus areas will be addressed in the summary for ages 1 to 9 years.

White Earth data.

No literature was located with the keyword search for the WE reservation for children 9-

10 years old.

P a g e | 414

Summary of Data 1-9 Years of Age

Search strategy.

The differing national and state age brackets made it difficult to clearly delineate which ages were affected by which unique health disparities. This inconsistency created a variety of problems in the literature review. In cases where the literature did not fit the 2-year age brackets of this research, the best way to disseminate information was to create a summary which included leading health disparities for ages 1-9 years. Children under one year were not included because most data bases provided concrete information specific to the health disparities of the infant age group and therefore that information was able to be captured in the 0-2 year old category previously reviewed.

For the purpose of this summary, CDC information categorizing ages 1-9 years will be included in this summary and ages 10-19 years will be included in the 10 and over summary. The format of the 1-9 year old summary will be organized into specific areas of focus/concern at the national and state level followed by data unique to the WE population, when available.

Specific areas of focus/concern.

Unintentional injury.

The leading cause of death for all children in the United States is unintentional injury.

Bernard et al. (2007) in the CDC MMWR summarized that the risk of unintentional injury for

NA youth, ages 1-9 years, is ―two times higher than whites‖ (results, para. 2). Bernard et al. described the leading mechanisms of unintentional injury as motor vehicle (MV) traffic injury, drowning, and fire/burn for all ages (Mechanisms of Unintentional Injury Death by Age Group, para. 2). Berger et al. (2007) published an article that contained much of the same CDC statistics P a g e | 415

as Bernard et al. and concluded that, ―Adjusted all-cause mortality rates for AI/AN were lower than for White rates in age groups 5-9, 10-14, and 15-19 years, but AI/AN adjusted rates remained higher among infants and 1-4 year olds‖ (p. 206). The most definable health disparity for AI/AN children was MV-traffic injury and death.

Poor compliance with seatbelt use has been a major contributing factor in the MV mortality rate in NA youth. Garcia, Patel, and Guralnik (2007) published an article specific to the seat belt use in AI/AN populations. In the article, Garcia et al. found that the National Highway

Traffic Safety Administration (NHTSA) estimated 76% of the occupants involved in fatal accidents on tribal reservations were not wearing a seat belt (p. 200). Typical seat belt use on reservations is at ―55.4%, which was substantially lower than the national prevalence of 82%‖

(Garcia et al., p. 200). The state of Minnesota compliance rate is presently 85.5% (WCCO,

2008). In July 2008, The WE Tribal Council approved a primary seat belt law (meaning offenders can be stopped for seat belt use alone) to combat the low seat belt usage rate of 61% specifically on the WE reservation (WCCO, 2008).

The second most common cause of unintentional injury is drowning for ages 1-9 years

(Bernard et.al., 2007). No literature was found indicating a higher incidence of drowning on the

WE reservation. However, increased drowning risk factors may exist for the WE reservation including proximity to lakes and streams, lack of flotation devices, alcohol use, or lack of supervision. No literature was found to support this conclusion.

The third leading cause of increased child mortality rates, fire/burns, was specifically addressed in the 3-4 year old age bracket. P a g e | 416

Immunizations.

Overall, national findings indicate that immunization compliance for AI populations has improved steadily over the last ten years. Immunization status is listed as one of the additional primary focus areas of IHS and the special attention to this topic seemed to be positively impacting immunization rates. The CDC‘s National Immunization Summary (NIS) (2006) indicated Minnesota was rated seventh from the top in the United States. The CDC MMWR publication (2008) stated that the vaccine coverage for AI/AN children ages 19-35 months showed a noticeable increase, especially in the PCV7 (7-valent pneumococcal conjugate vaccine), which exceeded the state averages for other children. This increase is attributed in part to the improved communication and reminder calls placed by local IHS providers. The MDH published Immunizations and Health Disparities (2007) concluded that,

―In Minnesota, currently, all 12 of Minnesota‘s American Indian Tribes have access to MIIC (Minnesota

Immunization Information Connection); however, only four of them input data into the system at this time.

They are Red Lake, Cass Lake, White Earth, and Prairie Island. Red Lake Indian Health Service Agency

reports that as of January 2007, 75 percent of two-year olds in the MIIC system were up to date on their

recommended vaccines. This compares to 62 percent of two-year olds in Beltrami County and 57 percent

in Cass County. These are the counties closest to the Red Lake tribe. In addition, MIIC reports that the

White Earth Tribe has higher rates than the counties closest to it‖ (p. 26).

The MDH does caution that poverty and higher concentrations of non-White children do decrease immunization rates. Keep in mind that the percentage of AI children may be higher in specific IHS counties but not all AI children receive vaccinations from IHS facilities, therefore the overall compliance rate may appear higher than is actually the case (Groom, Washington,

Smith, and Bryan, 2008). P a g e | 417

A study by Groom et al. (2008) refuted the only two AI/AN immunization studies performed since 2000, both of which indicated coverage for AI/AN was similar to that of other ethnic groups. Groom et al. suggested that more effort needed to be made to ensure the accuracy of state registries and improved strategies be put in place to help bring immunizations to AI/AN families. As previously suggested, Groom et al. reminded analysts that only 40% of AI/AN children use IHS services, therefore only the results of those children are being circulated as the reason for the increase in immunization rates. No immunization data was located in the literature review for the WE reservation. However, the authors believe the remote location of WE may prove to be a barrier for some parents in providing preventative care.

IHS tracks childhood immunizations through the Government Performance Results Act

(GPRA) report. Childhood immunization requirements in this case are the 4:3:1:3:3 vaccine combination (4 DTaP, 3 Polio, 1 MMR, 3 HiB, 3 Hepatitis B) for 19-35 month olds including contraindications and refusals. Patients included in the GPRA report are AI/AN patients who are

19-35 months old at the end of the reporting period (07/01/2007-06/30/2008) and who live in one of the communities served by the WE health program. Table 3 indicates that the 60-80% of 571 eligible children received immunization care at WE health center. However, this number also included refusals and comparing only two years does not provide a trend in immunization rates.

P a g e | 418

Table 3. GPRA Immunization Usage for WE

07/01/2007-06/30/2008 07/01/2006-6/30/2007

N % n % Active Clinical Patients 662 NA 658 NA 19-35 Months # w/ 43133 combo or 387 58.5% 422 64.1% w/ Dx/ Contraind/Refusal # w/ 4 doses DTaP or 403 60.9% 434 66% w/ Dx/Contraind/Refusal # w/ 3 doses Polio or 544 82.2% 550 83.6% w/ Dx/Contraind/Refusal # w/ 1 dose MMR or 507 76.6% 525 79.8% w/ Dx/Contraind/Refusal # w/ 3 doses HIB or 488 73.7% 504 76.6% w/Dx/Contraind/Refu sal

# w/ 3 doses Hep B or 571 86.3% 558 84.8% w/ Dx/Contraind/ Refusal

Note: Data exported by WE Health Center to national repository and evaluated by

Jason Douglas BIHS.

Bronchiolitis.

The CDC (2003) in the MMWR report titled Bronchiolitis-Associated Outpatient Visits and Hospitalizations Among American Indian and Alaska Native Children--United States 1990—

2000, indicated that the rate of AI children ages 1-4 years hospitalized for bronchiolitis was two times higher than the overall rate for children in the U.S. The Northern Plains region had the third highest rate of hospitalization and outpatient treatment of bronchiolitis. The CDC sited household crowding, under ventilation, smoke exposure, and lack of breastfeeding as possible associated risk factors to bronchiolitis. The CDC concluded that, ―Continued efforts are needed P a g e | 419

to identify and better understand host factors and environmental risk factors for bronchiolitis for targeted preventive strategies (e.g., campaigns to decrease parent smoking) to have a more immediate impact on decreasing disease burden among children, especially those in the AI/AN communities‖ (p. 709).

The only available relevant information for children on the WE reservation was calculated using the ICD-9 codes from the page 75 catalog visit from the NDW. Between

01/01/2005 and 12/31/2007, there were 103 visits with a primary, secondary, or tertiary diagnosis of ICD-P code 079.6 [respiratory syncytial virus (RSV)] or ICD-9 code 466.19 [acute bronchiolitis] due to other infectious organisms for patients ages 0-18 years. During this same time frame, there were no visits with a first, second, or third diagnosis of either ICD-9 code

466.1 (acute bronchiolitis) or ICD-9 code 466.11 (acute bronchiolitis due to RSV). Table 4 uses

ICD-9 codes 079.6 (RSV) and 466.19 (bronchiolitis) to demonstrate the number of WE Health

Service visits within a two year span for patients 0-18 years old. The majority of the visits occurred due to acute bronchiolitis with RSV not being the causative factor.

Table 4. BIHS WE Reservation Respiratory Syncytial Virus and Bronchiolitis Between

01/01/2005 and 12/31/2007.

Diagnosis Primary Secondary Tertiary (dx1) (dx2) (dx3) n n n 079.6 respiratory syncytial virus (RSV) 3 1 0 466.19 acute bronchiolitis due to other infectious 60 38 1 organism Note: Data exported by WE Health Center to national repository and evaluated by Jason Douglas

BIHS. P a g e | 420

Obesity and diabetes.

The PedNSS (2007) collected data on 7.6 million children from birth to 5 years old and of those 1% were identified as AI/AN. The PedNSS found 19.4% of NA children were overweight, the highest rate of combined populations. The PNSS did not provide information regarding diabetes. However, the correlation between obesity and diabetes has become undeniable. Story et al. (2003), a well known research team focused on obesity, diabetes, and NA children, confirmed that, ―Children who develop Type 2 diabetes are at greater risk for earlier development of microvascular (e.g., visual, neurological, and renal impairment) and macrovascular (e.g., hypertension, hyperlipidemia, and cardiovascular disease) complications than are individuals who are diagnosed as adults‖ (p. S6).

The MDH Diabetes in Minnesota report (2003) provided a very general overview of diabetes. The only data implications for the WE reservation were identified at the end of the report, indicating that AIs in the state of MN had 1.5 to more than 3 times higher death rate due to diabetes. There was no indication of age on the report. Unfortunately, no other data supported concerns of local community members.

WE statistical data was limited. There were 11 individuals under the age of 13, who had had a primary, secondary, or tertiary visit of diabetes (ICD-9 of 250.00 through 250.93) to the

WE Health Center during calendar years 2005-2007. The associated risk factor of a high BMI and diabetes can be analyzed using the CDC database to examine the patients visiting Health

Services on WE. When available, patient‘s height and weight were used to calculate BMI using the formula provided by the CDC (see Figure 4). According to the CDC Body Mass Index for

Age Percentiles for Boys 2-20 years, the 50th percentile BMI for age 2-4 years is 15.5 to 16.5, age 5-6 years is 15.5, age 7-8 is 15.5 to 16.0., and age 9-10 is 16.0 to 17.0 (CDC, 2000) ). In P a g e | 421

Table 5, height, weight, and BMI calculations are presented along with other basic descriptors.

Height is presented in inches and weight in pounds. The data sets from the WE Health Services

indicated that obesity is a significant issue on the WE reservation and the mean BMI starting at

age 5 appears to be two points above recommended 50th percentile for White males, placing AI

children on WE in the 95th percentile.

weight in pounds 703 height in inches 2

Figure 4. Centers for Disease Control Body Mass Index Calculation

Table 5. BIHS Height in Inches and Weight in pounds for Ages 0-9 years.

Age 0-2 3-4 5-6 7-8 9

N 15 119 247 356 192 374 184 376 78 185

Height Weight Height Weight Height Weight Height Weight Height Weight

Range 25.00 38.0 35.80 81.04 22.50 84.68 23.50 145.70 16.70 155.75 Mean 35.38 23.43 51.16 42.62 46.28 57.19 51.86 76.62 55.40 95.55

Median 37.00 23.33 41.30 41.50 46.00 53.80 51.50 68.95 54.80 85.75

SD 6.06 8.23 3.25 8.03 2.86 14.37 3.49 24.17 3.18 31.81

Note: Data exported by WE Health Center to national repository and evaluated by Jason Douglas

BIHS.

Red Lake Ojibwe fourth and fifth graders found a culturally significant way to

incorporate diabetes education into their curriculum using the WOLF (workout low fat) program

as a way to educate 450 families and students. Black Bear elementary school in Cloquet also

used the WOLF program incorporating drumming and Pow Wows into their exercise routine. A

similar study by Saksvig et al. (2005) in Manitoba Canada researched 4th, 5th, and 6th graders P a g e | 422

from the Cree and Ojibway [Canadian spelling] nation to illustrate how the use of ―culturally adapted diabetes program can be an effective means of reaching North American children and modifying risk factors related to diabetes and obesity‖ (p. 2397). Finding culturally appropriate methods of diabetes education was only cited in these two articles suggesting that there is limited data on these methods of reducing obesity and subsequently diabetes.

What is often overlooked by researchers is the emotional impact that obesity has on young people. Story et al. (2001) performed a research study of 1,441 third-grade children with a mean age of 8.6 years from Arizona, New Mexico, and South Dakota. Her study found that 42% were overweight or obese, of these children 70% had tried to lose weight and 63% were currently trying to lose weight. The children in the Story et al. article utilized exercise and going without food for a day as methods of weight loss. Story et al. is quick to note that dieting is linked to eating disorders and although the study did not address it, ―special care must be taken not to label or stigmatize overweight children‖ (p. 362). No articles for ages 13 and younger were located for the WE reservation regarding obesity, BMI, or diabetes.

Age Group: 11-12 Years of Age

Search strategy.

The search strategy used in this age group included a review of the following databases:

(a) Native Health Database, (b) Gale Power Search, (c) ERIC, (d) PubMed, and (e) CINAHL.

Keywords used included White Earth reservation and health disparities. No articles were generated. Expanding the search to include the key words (a) Native American, (b) American

Indian, (c) Minnesota, (d) Mahnomen, (e) rural, (f) Northern plains, (g) pre-teen, and (h) ages P a g e | 423

11-12 years revealed no literature. The literature review targeted articles from 1980 to the present.

Because the review of journal information was limited, the search was again expanded to include the Minnesota Department of Health, Kaiser State Health Facts, Centers for Disease

Control and Prevention, the U.S. Department of Health and Human Services Office of Minority

Health, and Indian Health Services. Still, there remained a gap between the verbal concerns expressed at WE meetings and published information. To bridge this gap, search engines such as

Google and Yahoo were incorporated into the following summaries as a means to explore media and community concerns.

National and state data.

The information from the major federal and state agencies included no age-specific data for 11-12 year olds. Interestingly, major research organizations such as the 2007 National Drug

Survey of Drug Use and Health, began collecting data at age 12. Whitesell et al. (2007) studied

Northern Plains and Southwest tribes and compared the data on marijuana use with a national sample. They found that the initiation rate for marijuana use in Northern Plains youth was higher. ―What is of most concern here, however, is the suggestion that cultural differences may be less apparent among younger tribal members and that overall, American Indian youths had a greater risk for early marijuana use compared with either their elders or their peers across the country‖ (Whitesell et al, p. 1316). In summary, the researchers felt that effective prevention needed to start in elementary school around age 11 or 12 and special consideration need to be made with children at high risk. The grouped data and specific focus areas will be addressed in the 13 year and under summary. Drug and alcohol use among NA youth is a specific area of concern elaborated on in the summary for ages 13 to 18 years. P a g e | 424

White Earth data.

No literature was located with the keyword search specific to the WE reservation for children 11-12 years old

Age Groups: 13-14 Years of Age, 15-16 Years of Age, and17-18 Years of Age

Rather than using the predetermine two-year age breakout, this section combines the information from 13-18 because the searches for each two-year age bracket consistently yielded no results. Therefore, this section is aggregated.

Search strategy.

The search strategy used in this age group included a review of the following databases:

(a) Native Health Database, (b) Gale Power Search, (c) ERIC, (d) PubMed, and (e) CINAHL.

Keywords used included White Earth reservation and health disparities. No articles were generated. Expanding the search to include the key words (a) Native American, (b) American

Indian, (c) Minnesota, (d) Mahnomen, (e) rural, (f) Northern plains, (g) high school (h) youth, (i) teenage, (j) adolescent, and (k) ages 13-18 years revealed no literature. The literature review targeted articles from 1980 to the present.

Because the review of journal information was limited, the search was again expanded to include the Minnesota Department of Health, Kaiser State Health Facts, Centers for Disease

Control and Prevention, the U.S. Department of Health and Human Services Office of Minority

Health, and Indian Health Services. Still, there remained a gap between the verbal concerns expressed at WE meetings and published information. To bridge this gap, search engines such as

Google and Yahoo were incorporated into the following summaries as a means to explore media and community concerns.

P a g e | 425

National and state data.

When performing the literature review in two year increments for ages 13-18 years, there was only one study specific to ages 13-15 year age bracket. The article, with a population sample from the Lumbee area of North Carolina, proved to have no relation to children on the WE reservation. The literature review for all other two year age bracket failed to produce any specific research data.

White Earth data.

No literature was located with the keyword search for the WE reservation for youth 13-18 years old.

Summary of Grouped Disparities for Youth 10-18 Years Old

Search strategy.

As stated in the summary for ages 9 and under, the differing national and state age brackets made it difficult to clearly delineate which ages were affected by which unique health disparities. This was even more profound in the adolescent population. The literature review for ages 14-16 and 17-18 consistently overlapped and often times included ages 13 as well. The best way to disseminate information was to create a summary which included leading health disparities for ages 10 years to 18 years. The CDC MMWR Fatal Injuries Among Children by

Race and Ethnicity-United States, 1999-2002, collected data by categorizing ages 10-19 years creating a guideline for researchers in this study. The format of the 10-18 year old summary will be organized into specific areas of focus/concern at the national and state level followed by data unique to the WE population, when available.

Of all the mentioned age brackets thus far, age 10 and older accumulated the greatest amount of national data. Utilizing Native Health Database, Gale Power Search, ERIC, PubMed P a g e | 426

and CINAHL data base using keywords: White Earth reservation, youth, adolescent, teen, and health disparities cited one article related gambling behavior on a Northern Plains Reservation.

Expanding the search to include Native American, American Indian, Minnesota, rural, and

Northern plains for ages 10 to 18 years and older revealed studies on suicide, diabetes, alcohol and drug use (substance abuse), smoking, high school dropout, and sexual health issues. The search was expanded to include the Minnesota Department of Health, Kaiser State Health Facts,

Centers for Disease Control and Prevention, the U.S. Department of Health and Human Services

Office of Minority Health, and Indian Health Services. The literature review captured articles from 1980 to the present.

Similar to youth throughout the U.S., AI/AN youth show an increase in many risk-taking behaviors. However, AI/AN children tended to be more likely to experience higher mortality rates and suffer more long term repercussions compared to White youth (Neumark-Sztainer et al,

1996). Some of the key areas identified in larger population groupings such as Northern Plains failed to generate articles specific to the WE reservation or Minnesota. WE community leaders identified health concerns for adolescents; however, no published material could be found in the literature review. To bridge this gap, search engines such as Google and Yahoo were incorporated into the following summaries as a means to explore media and community concerns. This was especially helpful when exploring the topic of suicide and teenage pregnancy. It should be noted that national and state statistics included data from both urban and rural AI/AN populations making it more difficult to isolate and apply to the WE population.

P a g e | 427

Specific areas of focus/concern.

Suicide.

The teen suicide rate on NA reservations has been the source of great concern for many

Indian nations. An article by Berger et al. (2007) summarized CDC data indicating that suicide was the second leading cause of death of AI/AN youth. The Native American Report (2005) indicated that ages 15-24 made up 40% of all suicides in Indian Country and the report went on to quote Surgeon General Richard Carmona as saying, ―Those numbers are just the tip of the iceberg; for each fatality, some 13 nonfatal events occur‖ (para 6 ). In the Native American

Report, Senator Bryan Dorgan, the ranking Democrat on the Indian Affairs Committee, cited the lack of mental health professionals and distance needed to travel to receive help as a major barrier to receiving mental health services. In addition, poverty rates and lack of suicide prevention programs limit accessibility on the reservations. In the Native American Report, Julie

Garreau, executive director of The Cheyenne River Youth Project in South Dakota, was most concerned about the population in the Northern Plains area where NA youth are often five to seven times more likely to commit suicide. ―Geographically isolated reservations may increase the likelihood of economic deprivation, lack of education, and limited employment opportunities, thereby contributing to a sense of hopelessness among young people‖ (Goldston et al., 2008, p.

20).

No published research articles examining the suicide rate and causes specific to the WE reservation were found. However, numerous newspaper articles and radio programs have discussed the increasing suicide concern on WE. Minnesota Public Radio, in August 2000, reported ―a cluster of teenage suicides and then a rash of attempts by other WE young people P a g e | 428

galvanized residents-they would not stand by and watch their children die‖ (Olson, 2000, para.

4). This increase in suicides prompted WE community leaders to create a volunteer dispatch system that supported the family and individuals, sadly the program shut down due to volunteer burn out according to Olson.

The increased suicide rate is noted to be higher amongst Indians in the Northern Plains.

According to Gunderson (2005), ―The rate is much higher in the Upper Midwest and Great

Plains, where it‘s five to seven times higher than the national average, according to an official with the federal Substance Abuse and Mental Health Services Administration‖ (para. 28).

Potential reason for increased suicides and attempts may include lack of positive role models, inadequate or nonexistent mental health counseling, sense of hopelessness, and poverty (Barney,

2001). Although the data is not age-specific, the MDH Suicide Prevention Plan Progress Report

(2005) listed ―the rate of suicide among American Indians in Minnesota (19.96 per 100,000, US

Census, 1997-2001) is over twice that of all other racial and ethnic groups‖ (p. 6). The MDH

Student Prevention Plan Progress Report (2005) quoted the Minnesota Student Survey (2001) as saying ―34% of 6th grade American Indian girls reported having thought about killing themselves as compared to 20% of 6th grade girls statewide. One in five 9th grade American Indian boys

(20%) report having attempted suicide as compared to 7% of 9th grade boys statewide‖ (p. 7).

Minnesota State Senator Amy Klobuchar (2008) noted the expanse of WE reservation as a barrier to mental health services stating:

―The WE reservation in Minnesota is the largest reservation in our state. It spans 200 miles and it is the home to almost 10,000 people, yet elective surgeries are not even an option in an area that spans 200 miles due to a lack of modernized health care resources and facilities‖ (para. 8).

P a g e | 429

Recently, WE reservation has procured funding from the Shakopee Mdewakanton Sioux

Community and the state of Minnesota totaling $4 million for a youth treatment center that is anticipated to be completed in 2008.

Mental health.

A paucity of data exists for the prevalence of mental health disorders among NA children and adolescents. ―Although relatively little evidence is available, the existing data suggest that

American Indian and Alaskan Native youth and adults suffer a disproportionate burden of mental health problems compared with other Americans‖ (U.S. Department of Health and Human

Services, 2001, p. 96). It is well recognized that Native people, including children, often live in stressful poverty-stricken environments and are exposed to violence and chronic substance abuse that can lead to potentially negative mental health consequences. The prevalence of suicide among Native American youth is an obvious indicator of mental health concerns. Historical trauma passed from parent to child has been identified as a contributor to mental health issues as well (Struthers & Lowe, 2003).

There are important issues to consider when reviewing the literature related to the Native

American youth population. The U.S. Department of Health and Human Services 2001 supplement to the Surgeon General’s Report on Mental Health stated ―Even when large samples are acquired, findings are constrained by the marked heterogeneity that characterizes the social and cultural ecologies of Native people‖ (p. 84). Thus, the great diversity among NA groups can lead to difficulties with comparability. The report also pointed out that Diagnostic and Statistical

Manual (DSM) diagnoses and many assessment tools used are not sensitive to cultural expression and differences in reporting of distress by NA people. P a g e | 430

Two well-recognized 1997 studies examined mental health issues in NA youth populations. The Great Smokey Mountain Study (Costello, Farmer, Angold, Burns, & Erkanli,

1997) examined the prevalence of psychiatric disorders, social and family risk factors among NA youth age 9-13 in Appalachia. The study found that substance use, with and without co-morbid psychiatric diagnoses, was more common in NA children than White children in the sample.

Beals et al. (1997) conducted a school-based psychiatric epidemiologic study involving 13-17 year old Northern Plains youth. They found that NA youth were more likely to be diagnosed with substance abuse or dependence disorders and co-morbid ADHD, as well as conduct and oppositional defiant disorders, than the non-minority youth in the study. Native children also had higher 6 month rates of simple phobia, social phobia, and overanxious disorder than non- minority children. Prevalence rates of depressive disorders were not found to be elevated for NA youth in either study.

Pointing to a specific NA adolescent population of concern, Duclos et al. (1998) evaluated psychiatric disorders among NA adolescents that were incarcerated in a Northern

Plains reservation juvenile detention center. They found in their sample of 150 youth, 49% had at least one alcohol, drug, or mental disorder, a rate exceeding that of adolescents in the community. The most common disorders found were substance abuse, conduct disorder, and depression.

In addition to concerns regarding historical trauma, there is concern related to the first hand exposure of NA children to trauma. Jones et al. (1997) reported that in a sample of

Northern Plains youth ages 8-11 years old, 61% had been exposed to a traumatic event. Though they did not show significantly higher rates of diagnosable PTSD, they showed more trauma- related symptoms than the national youth population. Christensen and Manson (2001) also P a g e | 431

identified an increased risk for domestic violence, spousal abuse, and family instability for NA families due to poverty, demoralization, and rapid culture change.

No statistical data was located regarding the prevalence of psychiatric disorders in the state of Minnesota. State statistics related to substance use in NA adolescent populations is discussed subsequently in this report.

WE data related to prevalence of psychiatric diagnoses for children and adolescents was unavailable, but the WE Health Division Chemical Dependency Program (P. Moran, personal communication, January 21, 2009) reported that in 2007, 15% of the 378 client cases reported by

WE Health Division Chemical Dependency Program were adolescents. In 2008, 9% of 473 cases were adolescents.

Findings from a report to the White Earth Band of Ojibwe People regarding the Healing

Pathways Longitudinal Study were made available to the researchers of this CSEERSWE study with the WE Tribe‘s permission (M. Fox, personal communication, Feb 24, 2009). The three year, four wave Healing Pathways study, conducted through a partnership between the WE Band and the University of Nebraska-Lincoln, provided insight into factors that affect the well-being of WE children and adolescents. The study sample was comprised of 189 families, including children who were age 10-12 years at Wave 1 and reached age 13-15 at Wave 4, and their adult caretakers. Prevalence rates for major depression, conduct disorder, and substance use disorders were found to be greater among the children sampled as compared to national prevalence rates.

The findings in regard to major depression are in contrast to those of Beals et al. (1997) and

Costello et al. (1997), who did not find rates of major depression to exceed that of the general population. In assessing the caretakers‘ attitudes regarding help-resources for childrens‘ emotional and substance use problems, it was found that a majority of respondents felt that P a g e | 432

traditional tribal and family resources would be most effective. A summary of Wave 4 findings for the WE Band is presented in figure 5.

Anishinabe Giigewin Miikana Healing Pathways

Summary

 Rates of substance use disorders, major depression, and conduct disorder higher among White Earth children are high for this age group compared to national prevalence rates.  These results suggest risk for potentially harmful behaviors including suicidal behaviors, unintentional injuries such as car accidents, fighting, risky sexual behaviors, and criminal behaviors.  Results indicate the need for identification and careful monitoring of individual high risk children by qualified mental health professionals.  Best point of intervention is around ages 10-12 before this dramatic increase in psychological and behavioral problems.

Figure 4. Healing Pathways Summary, M. Fox, personal communication, Feb 24,

2009.Reprinted with permission of the author.

Findings from the Healing Pathways Study also pointed out a number of issues that impact the mental health of the WE Band children. ―At year 2, over 56.5% of the parents/caretakers feel there is a problem with child neglect in their community, 40% report a problem with child physical abuse, and 33.2% feel there are problems with child sexual abuse‖

(p. 12). Twenty percent of families reported experiencing violence in the past year.

In regards to strategies for seeking help with children‘s emotional and substance use problems, the majority of parents and caretakers rated family members, tribal elders, and P a g e | 433

traditional healers as the most effective resources. This perspective is in harmony with that of clinicians and researchers (LaDuke, 2002; Struthers & Lowe, 2003) that seek to find ways to prevent and treat mental illness among NA children.

Diabetes.

IHS (2008) identified diabetes as a primary prevention focus for AI/AN populations having found that 6% of NA children under age 15 had been diagnosed with diabetes. The

National Diabetes Education Program (NDEP) (2008) found that after 10 years of age, Type 2 diabetes becomes increasingly common, especially in minority populations. As the obesity statistics increase with age, so do the risks for diabetes. ―Type 2 diabetes once considered rare in children is now commonly seen in AI children aged 10 and over. It may be that Type 2 diabetes among American-Indian youth is the first consequence of the epidemic of pediatric obesity‖

(Story et al., 2003, p. S5). Urruita-Rojas and Menchaca (2006) concurred, ―Throughout the world, among children and adolescents, type 2 diabetes mellitus (T2DM), historically called non- insulin-dependent diabetes mellitus or adult-onset diabetes, has increased parallel to the increase of overweight and obesity in the past 10-15 years‖ (p. 189). The NDEP indicated that diabetes among AI youth (ages 15-19) has increased 106% between 1990 and 2001 and are thought to have continued to increase since 2001. The NDEP found that diabetes among AI/AN youth increased by 68% between 1994-2004 for ages 15-19. LaDuke (2002) indicated that youth on the

WE reservation had an increase of 60% in the diagnosis of diabetes. LaDuke did not cite the source of information or dates for the 60% increase. However, because of her involvement in the community her insight is valued. P a g e | 434

The SEARCH for Diabetes in Youth Study Group (2006) compiled data from ~3.5 million youth in the United States and Canada. The highest prevalence of type 2 diabetes was found in the AI youth at 1.74 cases per 1000. They concluded that the mean age for diagnosis among AI was 12.0 years old and females had a higher incidence. Type 1 diabetes statistics were comparable to that of other ethnic backgrounds. Most of the other research statistics are formulated from the IHS and SEARCH data. For example, a study by Islam-Zwart and Cawston

(2008) examined the factors that contributed to the risk of diabetes in AI/AN youth. They used

IHS data to examine the relationship between parental diabetes, sedentary behaviors, and risk for childhood type 2 diabetes in children third grade to twelfth grade.

As mentioned in the summary for ages 1-9, the link between obesity and diabetes is undeniable. Table 6 shows the height, weight, and BMI for children ages 10-18 years who utilized WE Health Services wherein the clinic visit included a height and weight measurement.

Height is presented in inches and weight in pounds. Per CDC BMI calculations in Figure 4, youth ages 10 to 15 years were in the 95th percentile for BMI. However, the 15-18 year age group dropped very slightly into the low 90th percentile. It should be noted that 50th percentile is the goal.

P a g e | 435

Table 6. BIHS Height and Weight for ages 10 to 18 years

Age 10 11-12 13-14

N 116 206 237 379 225 387

Height Weight Height Weight Height Weight

Range 19.00 187.87 22.00 239.60 22.7 230.00

Mean 57.01 105.53 61.10 126.58 64.74 151.41

Median 57.23 96.81 61.00 115.70 64.55 139.90

SD 3.20 34.81 3.46 40.09 3.27 44.57

Age 15-16 17-18

N 289 503 249 463

Height Weight Height Weight

Range 38.50 292.73 17.00 380.77

Mean 66.72 166.45 66.57 171.35

Median 66.50 153.35 66.13 158.94

SD 3.87 48.28 3.35 46.63

Note: Data exported by WE Health Center to national repository and evaluated by Jason Douglas

BIHS.

P a g e | 436

Gambling.

A search of the national databases failed to locate any articles for gambling in the 9-18 year age bracket. Zitzow (1996) performed a study which targeted youth ages 12-19 in rural

Minnesota. According to Zitzow, Native American youth were found to be at higher risk for developing gambling problems due to early onset of gambling, greater frequency, family member gambling, lower socioeconomic status, and the cultural acceptance of fate. The link between gambling and other addictive behaviors such as alcoholism is of special concern when paired with concerns of depression and poverty.

Momper and Jackson (2007) examined the relationship between 150 Native American mothers‘ gambling habits, parenting, and child behavior issues. These mothers were located on

Great Lakes Indian reservations and had children between the ages 6-15 years. The results of the study indicated that economic strain, less than adequate parenting, and the age of the child were more indicative of behavior problems than gambling. Momper and Jackson (2007) noted that the issue of gambling is complicated by the positive aspect of bringing jobs to reservation communities and the negative aspects of loss of emotional and financial support in the home environment if gambling becomes pathological. The National Gambling Impact Study

Commission Report (NGISC) (1999) noted that ―adolescent gamblers are more likely than adults to become problem or pathological gamblers‖ (chapter 7, p. 20). The same report by NGISC indicated that, ―Several studies have shown that pathological gambling is associated with alcohol and drug use, truancy, low grades, problematic gambling in parents, and illegal activities to finance gambling‖ (chapter 7, p. 24). The only casino on the WE reservation is The Shooting

Star Casino. The number of WE band members employed is unavailable to these authors. Further P a g e | 437

study is needed with this specific NA community to examine the link between gambling and juvenile addiction and behavior problems.

Alcohol and drug use.

Alcohol and drug use for the adult AI/AN population has been documented. However, adolescent alcohol and drug rates severely lack detailed population data. For example, the U.S.

Department of Health and Human Services (USDHHS) completed an extensive study titled

Results from the 2007 National Survey on Drug Use and Health: National Findings (NSDUH)

(2007). This survey sampled ages 12 and older, however lacked data representing the AI youth.

Another study with major shortcomings was the USDHHS National Institute on Drug Abuse,

Monitoring the Future National Results on Adolescent Drug Use: Overview of Key Findings

(2007). Again, no data for AI/ANs was identified. A study by Winters, Latimer, Stinchfield, and

Egan (2004) found that the literature and the lack of assessment tools is dually complicated. ―The lack of ethnic-specific psychometrically sound adolescent assessment measures is unfortunate in light of a growing body of literature regarding ethnicity and AOD (alcohol and other drug) behaviors among adolescents. Ethnicity has shown a significant association with drug use patterns‖ (Winters et al., 2004, p. 227). The increasing body of evidence the Winter et al. authors cite is only four articles, of which only two have NA data.

The national report of alcohol-attributable deaths (AADs) among A/AN was published by the CDC (2008) in the MMWR. The MMWR showed that AI/AN ages 20 years and older were twice as likely to die from alcohol-related causes and the greatest number of these deaths occurred in the Northern Plains. However, the study was not age-specific and only indicated that

6.9% of these deaths were <20 years of age. Another report by Bernard et al. (2007) indicated P a g e | 438

that AI/AN youth had a high incidence of alcohol-impaired driving and the highest alcohol- related motor vehicle rates among any of the other populations. The NSDUH (2007) grouped ages 12-49 years and did not report any ethnic specific trends. O‘Connel et al. (2007) examined the childhood characteristics associated with substance abuse in Northern Plains and Southwest

Native America adults. They found that the Northern Plains tribes were at higher risk of substance abuse than the Southwest tribes. O‘Connell identified the contributing factors were parental substance abuse and traumatic experiences such as sexual abuse, violent trauma, and witnessing family violence.

The literature review failed to produce any data specific to the WE reservation and adolescent alcohol and drug use. The most relevant data for WE was found in Substance Use in

Minnesota: A State Epidemiological Profile (SUMN) (MDH, 2008). To break down the extensive data in the profile, it was most useful to isolate statistics for NA youth under 18 in the non-metro area when available. Consistently, the SUMN report identified AI students as scoring highest in drinking initiation, binge drinking, impaired driving, and riding with impaired friends.

The Neumark-Sztainer et al. (1996) article included the relationship of other high risk behaviors such as delinquency and precocious intercourse in relationship to alcohol consumption and marijuana use in 6th, 9th, and 12th grades in Minnesota. ―Prevalence rates of most health- compromising behaviors differed by gender, increased with age, and tended to be highest among

American Indian youth and lowest among Asian Americans‖ (Neumark-Sztainer et al., p. 1599).

The strong association between alcohol and other substances has led researchers to examine marijuana initiation amongst Northern Plains and Southwest reservations. Whitesell et al. (2007) findings indicated that AI reservation youth may be more vulnerable to drug use. P a g e | 439

Beauvais (1998) agreed that the link between alcohol and drug use exists, ―Among both Indian and non-Indian adolescents, drug and alcohol use are much more tightly coupled than they are among adults. Nearly all adolescent drug users also use alcohol, and more than one-half of adolescent alcohol users use drugs at some level‖ (p. 254). Wallace et al. (2003) combined multiple large population studies and concluded that across ethnic groups, Native American adolescent girls showed the greatest increase in drug use and that the relationship between female and male adolescent drug use may be comparable.

Tobacco use.

In the NA community, the use of tobacco has deep cultural implications. Although the role of tobacco in sacred ceremonies has been a part of the NA culture for thousands of years, other causes for tobacco use among adolescents continue to be examined. ―The risk factors include peer influences, parental influences, access to tobacco, underestimation of the negative effects of tobacco, overestimation of the perceptions of the positive effects, stressful life events, and low socioeconomic status‖ (Unger, Soto, & Thomas, 2008, p. 129). NSDUH (2007) indicated that 41.8 percent of AI/AN, ages 12 years and older, currently used tobacco products.

Kegler et al. (1999) reinforced the need for further study of the prevalence of AI teen smoking and, ―For American Indian youth, particular attention should be paid to the distinction between traditional uses of tobacco and cigarette smoking‖ (p. 41).

Recent data from the MDH in the SUMN (2008) listed NA youth as having the highest rate of use in almost every category for both smoke and smokeless tobacco. In the SUMN,

29.7% of Minnesota students reported they first smoked all or part of a cigarette at age 13 or younger. A study by Henderson, Jacobsen, Beals, and the AI-SUPERPFP Team (2005) noted P a g e | 440

that the earlier the smoking is initiated, the more difficult it is to quit, making tobacco use a major public health concern. The literature review produced one article by Hodge and Struthers

(2006) that included grouped data from seven Northern Plain reservations, specifically the

Minnesota Ojibwe reservations of Leech Lake, Mille Lacs, and WE. Although the study included a small number of participants and all were over 18 years of age, it provided further insight into the complicated issue of tobacco use in the NA population. Hodge and Struthers indicated

―lenient attitudes towards smoking, low perceived harm value and feeling of partiality toward the smoking habit and associated rituals are very important pieces of information in the puzzle to counteract persistent smoking among Northern Plains Indians‖ (p. 184). Tobacco use among 13-

18 year olds specific to the WE reservation did not produce any findings in the literature review.

School dropout.

Freudenberg and Ruglis (2007) considered education to be the ―elixir‖ for increasing life expectancy, reducing the burden of illness, delaying the consequences of aging, decreasing health behavior risks, and reducing health disparities. National Center for Education Statistics

(NCES) published two reports providing information on AI/AN students. In the Freeman and

Fox (2005) article, the term dropout is defined as,

―An individual who was enrolled in school at some time during the previous school year, but was not enrolled at the beginning of the current school year, has not graduated from high school or completed a state- or district-approved education program; and does not meet any of the following exclusionary conditions: transfer to another public school district, private school, or state- or district-approved education program; temporary absence due to suspension or school-approved illness; or death‖ (p. 6).

The first NCES article by Freeman and Fox (2005) titled, Status and Trends in the

Education of American Indians and Alaska Natives, appeared to have the most recent data set P a g e | 441

found in the literature. Unfortunately, the report did not provide dropout rates specific to the

AI/AN students in grade 9-12 in Minnesota. The bottom of the graphs indicated that ―‡

Reporting standards were not met. Data were missing for more than 20 percent of grade total membership‖ (Freeman & Fox, p. 6). The last recorded dropout rate for the entire state of

Minnesota was 3.8 for the 2002-2003 school years (Freeman & Fox). Broader NCES compiled by Devoe, Darling-Churchill, and Snyder (2008) indicated that although public school students in the Midwest were less likely to drop out of school, nationally, AI/AN public school students were more likely to drop out compared to other racial/ethnic groups.

Devoe et al. (2008) combined other statistical data such as demographics and post- secondary education to aid in the understanding of AI/AN student trends overall. Highlighted findings concluded that it was difficult to establish a trend in the dropout rate of AI /AN students due to the fluctuating data sets per year. According to Devoe et al., AI/AN students in the United

States had a dropout rate of 15% in 2003, the second highest rate surpassed only by Hispanics.

There was no literature specific to WE on the academic search engines pertaining to high school dropout and AI/AN.

Sexual health.

Adolescent sexual activity combined with existing racial disparities place AI youth at increased risk for multiple short-term and long-term health issues. Some of the disparities cited in the literature review regarding AI adolescents included teenage birth rates, poor birth outcomes, sexually transmitted infections (STIs), low birth weight, and other risk factors (Bohn,

2003; Mylant and Mann, 2008; Peterson-Hickey, Rhodes, and Garwick, 2006). Before analyzing P a g e | 442

the disparities individually, it was necessary to consider the cause of early adolescent sexual behavior.

Mylant and Mann (2008) were most concerned with the incidence of intimate partner violence and sexual trauma among high-risk teens. They cited an Ojibwe study by Bohn (2003) which stated, ―Half of the American Indian women in Bohn‘s study also experienced physical and sexual abuse as children, and over 50% experienced both forms of abuse at some time in their lifetime‖ (p. 166). This is important to note because childhood sexual abuse has been linked to substance abuse, depression, suicide, and post-traumatic stress disorder (PTSD) (Mylant &

Mann). It is difficult to isolate the relationship of childhood abuse to early onset of sexual risk- taking behavior, especially in the AI population. Hellerstedt, Peterson-Hickey, Rhodes, and

Garwick (2006) noted that the ability to analyze the AI youth is especially hard because the national surveillance and survey reports about adolescent sexual behavior has focused on White,

African American, and Hispanic youth. To illustrate this point, the only AI/AN results from the

CDC (2005) in the NVSS indicated a 4 % increase in birthrate for AI/AN girls ages 15-19 years from 1991-2005. One of the most difficult aspects of locating information specific to the WE reservation or surrounding area is the lack of information on sexual health for rural teens. An article by Garwick, Rhodes, Peterson-Hickey, and Hellerstedt (2008), separate from the above mentioned, considered pregnancy prevention in only the urban AI teens in the Twin Cities,

Minnesota.

Individual states seem to do a far better job of tracking adolescent sexual behavior.

Minnesota Organization on Adolescent Pregnancy, Prevention, and Parenting published the

Minnesota Adolescent Sexual Health Report (2008) indicating that the birth rates were disproportionately higher for populations of color. Unfortunately, the report did not specify other P a g e | 443

health indicators such as prenatal care, low birth weight, STIs, and associated risk factors for AI youth.

The MDH published the PCM (2007) to provide more precise statistical information for adolescent sexual health. In the MDH PCM, the Minnesota rate of AI teen births, ages 15-19 years, per 1000 was 93.6 compared to the U.S.AI/AN rate of 52.5 per 1000. Although this was a decline from previous years it still was three to four times higher than Whites in the state of

Minnesota. In the MDH PCM, AI women, age not specified, were six times more likely to receive inadequate or no prenatal care compared to the Whites.

The most detailed data was located in the MDH Minnesota County Health Tables

(MCHT) (2007). However, the information could only be used to make assumptions for three reasons. First, the data was not broken down into AI groupings. Second, the only data set to be divided into ages was the teen birth and pregnancy rate category. Third, due to the expanse of the

WE Health Services area which includes Mahnomen, Becker, Clearwater, Norman, and Polk counties, it was impossible to determine AI disparities. When independently analyzing the

MCHT, it is possible to conclude that the teen pregnancy rates for AI women ages 15-19 in

Mahnomen County are the highest in the state of Minnesota. This assumption can be made from

MCHT Natality Table 7 indicating Mahnomen County has the highest teen birth and pregnancy rates in Minnesota per county. Further studies documenting this data are needed to support this conclusion. Overall, data from the WE reservation is severely lacking in the regards to teen sexual behavior and outcomes of pregnancy.

Gaps in the literature.

Numerous gaps were evident in the literature review of youth health disparities on the

WE reservation. Most evident was the lack of age-specific data for each two year age bracket. P a g e | 444

Summaries of 1-9 years old and 10-18 years old needed to be created to group information that fell outside of the two year limits. This lack of age-specific information for NA children reiterates the concerns of numerous researchers who believe that without sufficient disparity determinants it is almost impossible to understand, correct, or prevent health disparities.

The second gap in literature was the lack of tribal customs, traditions, and beliefs in relationship to health disparities, especially related to children. ―The Native American population consists of over 500 federally recognized tribes, each having its own culture, life way, traditions, and beliefs, with widely varying degrees of acculturation. Each tribe is distinct‖ (Lowe &

Struthers, 2001, p. 279). As evidenced above in the literature review, few journals considered the needs of the community or the individual North American Indian tribes when discussing health disparities. Often times, articles used CDC, NIH, and MDH databases to create conclusions. The

WE reservation data was especially difficult to isolate because little to no studies were found pertaining to children receiving care at the WE IHS health facilities and data regarding WE youth receiving care outside the IHS was untraceable. The general lack of data for NA children under 18, coupled with the lack of tribe-specific research, leads to an incomplete understanding of the situation and potentially an inequitable distribution of resources to prevent health disparities.

Chapter II Summary

The literature review of health disparities in children under 18 years of age on the WE reservation established many health implications for the CSEERSWE . During Phase II of the study, researchers will consider the specific needs of youth on the WE reservation and create surveys to gather specific information, further interpretation, and a create a more comprehensive understanding. The outcome of the CSEERSWE is to, ―include findings and conclusions in P a g e | 445

regard to school attendance and achievement, evidence of rigor in relation to academic achievement, and the effectiveness of related agencies in relation to academic success‖

(Bradbury, 2008, p. 3). This chapter covered the well-being services disparities (health arm) for

WE youth, ages 18 and under, as described in the national, state, regional literature and databases.

P a g e | 446

Chapter III-Research Design, Methods, and Procedures

Chapter three of the literature review will describe the research design, methods, and procedures used when identifying health disparities on the White Earth reservation. Target population, setting and sample plan, and variables will be described for the comprehensive literature review. Measurement tools used by the IHS statistician will be identified as well as the plan for data analysis and dissemination of findings.

Purpose

The purpose of this study was to describe the health disparities among American Indian youth (0-18 years old) with specific focus on those using White Earth reservation IHS services.

Population Description

The target population for the CSEERSWE purposed by MSUM was twofold. First, the individual must have been 18 years and younger and second they must have received care from the WE IHS. National and state literature and statistical data bases were used to identify health disparities and WE-specific data was also included when available.

Target population.

WE tribal enrollment in 2005 was estimated at 19, 506 with 7, 926 living on or near the reservation according to the 2005 Bureau of Indian Affairs Indian Population and Labor Force

Report. IHS Service Population is advantageous to raw census data for AI/AN populations for two reasons: IHS Service Population considers births and deaths and adjusts populations accordingly. Raw census data provides information for respondents with ties to WE regardless of where they live. Since the current CSEERSWE project‘s primary aim is an investigation of the extent to which health status affects educational factors for children on WE reservation, IHS service population seems to be the more appropriate choice. Table 7 illustrates the current IHS P a g e | 447

Service Population for 2000 and estimates the following age breakdown (in percentages) of the

AI/AN living in the WE CHSDA.

Table 7. WE CHSDA Percentage of Population per Sex and Age.

< 1 1–4 5–9 10–14 15–19 Yr. Yrs. Yrs. Yrs. Yrs. Male 1.031 4.050% 5.478% 6.364% 5.713% % Female 1.031 4.176% 5.695% 6.021% 5.189% % Note: Data exported by WE Health Center to national repository and evaluated by Jason Douglas

BIHS.

Setting and Sampling Plan

The WE reservation was identified by researchers and community stakeholders on WE reservation to have a lower than average rate of academic success. This conclusion was supported by the WE tribal council, specifically Erma Vizenor tribal chairwoman, and the decision was made to expand the study outside of education to consider some of the variants potentially impacting academic success. The decision to create the CSEERSWE was a collaboration with the WE tribe, local school districts, and MSUM. Literature and statistical data from existing national, state, and WE sources were queried to identify services related to wellbeing (health disparities).

The sampling plan included Mahnomen, Becker, and Clearwater counties because of the federal recognition of reservation boundaries. The sample plan was expanded to include Polk and

Norman because the additional counties were included in the broader CHSDA definition.

The sampling plan also targeted individuals 18 years and younger which was the definition of ―youth‖ used in this study. Ages were grouped into two year brackets to assist the P a g e | 448

school districts in utilizing research results. There are 9 different school districts which serve the

WE reservation. Each of these districts uses different age groupings to define elementary, middle school, and high school. It was hoped that these two-year age clusters would increase the usability of data for individual school districts.

The retrospective literature review of national, state, and WE data did not require recruitment of individuals. Instead demographic information was gathered from Bemidji Area

Indian Health Service and the U.S. Census Bureau Fact Finder. The data requested for specific areas of concern by the IHS statistician was retrieved from the Bureau of Indian Affairs, Bemidji

IHS, 2008 Government Performance Results Act Report for White Earth, and the 2005 Bureau of

Indian Population and Labor Force Report. The convenience sample pooled all relevant cases between 2005-2007. The databases were analyzed by an IHS statistician prior to being inputted into this report. Inclusion criteria for the WE study population required that an individual be 18 years of age or younger and have received health care services from the WE CHSDA area. No exclusion criteria narrowed the sample population.

Research Design

The goal of this retrospective descriptive study was to gain more knowledge on the health disparities that exist for children ages 18 and younger on the WE reservation. It was necessary to first research the current health disparities in hopes of decreasing the incidence of bias in research development. When utilizing the descriptive study design to examine a single sample, it is best to create clarification, followed by measurement, description, and interpretation (Polit &

Beck, 2006, p. 266). To achieve this in the review of literature, ages were placed in bracket of every two years. This clarification of age groupings allowed health disparity research to be readily utilized in the school district format. P a g e | 449

The retrospective method of reviewing Bemidji Area Indian Health Services data, specific to WE, provided researchers with a sampling specific to the health disparities fleshed out in the literature review. This non-experimental retrospective design reduced the incidence of research assumptions and created better representation of an understudied population like WE. It was the logical place to begin the exploration of WE youth health disparities. The health disparities that occur for children in the U.S. are potentially more complex for children living on the WE reservation. The descriptive method of design allowed the researcher to investigate health disparities through literature review and retrospective data collection to create a summary of health disparities for WE youth that would have otherwise been narrowed by researcher perspective or a priori research question boundaries.

―Demographic and other data were provided by the Bemidji Area Indian Health Service

(BAIHS), the administrative body that serves the 34 federally recognized tribes in Michigan,

Minnesota, and Wisconsin including the White Earth tribe. The database used was a catalog of visits to the federal health sites (White Earth Health Center, Naytahwaush Health Location, and

Pine Point Health Location) as well as visits to the White Earth Tribal health program during the years of 2005-2007. This catalog of visits was produced by the NDW in Albuquerque, NM, the central repository for all health-related data exports for Indian Health Service and serves several purposes which include producing annual user counts for funding distribution to the twelve IHS areas and providing health data to IHS to inform policy‖ (J. Douglas, personal communication,

March 27, 2009).

Data provided by IHS is facility-level data. In other words, patients are not filtered by their community of residence on or off the White Earth Indian Reservation. All patients age 0-18 regardless of their community of residence, who had a visit to either a tribal or Federal managed P a g e | 450

health program during 2005-2007 are represented (J. Douglas, personal communication, March

27, 2009)

In order to produce demographic data for each two-year age group in question 0-2, 3-4,

5-6, 7-8, 9-10, 11-12, 13-14, 15-16, 17-18 and age at visit was calculated for each patient visit and it was these ages that were used to categorize patients into age groups. This method was used instead of aggregating the entire database in order to maintain the integrity of visit/diagnosis data for each visit and also because any given patient may have multiple ages between visits in 2005-

2007 and as a result, fall into separate age categories. Thus, the resulting duplicative number of patients falling into each age group (5,692) exceeds the actual number of patients aged 0-18 in the database (3,496). In fact, the difference between these two figures (5,692 – 3,496 = 2,196) could be interpreted loosely as the number of patients represented in multiple age categories. (J.

Douglas, personal communication, March 27, 2009). Table 8 below displays the number and relative percent of male and female patients who had a visit to the WE Health Center between calendar year 2005-2007.

Table 8. WE CHSDA Two-year Age Categories.

Age in 0-2 3-4 5-6 7-8 9-10 11-12 13-14 15-16 17-18 Total yearsN 792 643 605 557 586 584 595 682 654 5,698 % Male 52.3% 50.4% 49.9% 47.6% 50.5% 50.3% 49.7% 46.9% 43.0% 49.4%

% Female 47.7% 49.6% 50.1% 52.4% 49.5% 49.7% 50.3% 53.1% 57.0% 50.6%

Note: Data exported by WE Health Center to national repository and evaluated by Jason Douglas

BIHS.

P a g e | 451

The Conceptual Framework of Nursing in Native American Culture by Lowe and

Struthers (2001) complimented the research design well because it allowed for the unique characteristics of the NA population to be examined. When possible, every consideration was made to discover the health disparities of the youth on the WE reservation through conversations with stakeholders before examining the national or state data. The framework will be used to the fullest potential in Phase II and III of the CSEERSWE.

Research Questions

Research questions were as follows:

1) What is the current state of the literature on health disparities among NA youth? and 2)

What current data exists related to health disparities among NA youth?

Research Variables

Three research variables existed in the literature review including WE reservation, youth, and health disparities. The variables were analyzed through national and state databases. In addition, a customized extract from IHS NDW specific to the WE Health Center, including all satellite facilities, federal and tribal, were utilized to develop WE population specific information. No independent or dependent variables existed.

Demographic variables included NA children on the WE reservation age 18 years and younger. When isolating information from the customized extract from IHS NDW, the demographic variable narrowed to children 18 years and younger who received health care from

Bemidji area IHS and received direct care at the WE IHS facility. The IHS statistician retrieved data on the following health disparities per researcher request including, but not limited to: height, weight, body mass index (BMI), dental fluoride treatments, blood lead levels, diabetes, respiratory syncytial virus (RSV), bronchiolitis, lice, immunizations, and suicide. These areas of P a g e | 452

interest were isolated based on the review of literature and conversations with stakeholders.

Although the information was requested not all data was available in the database system

Treatment/Intervention

No treatment was involved.

Measurement Methods/Tools

The customized data extract from IHS NDW specific to the WE health center including all satellite faculties federal and tribal was the method used in the operational definition. The secured IHS National Data Warehouse Overview (2009):

―Contains data about all patients and their encounters, and tracks in detail the changes made in those data over time, the sheer amount of information is overwhelming and impractical for individual searching. NDW data become valuable to most end users when it can be extracted from the database and turned into information that is meaningful.‖ (A Single Historical Data Resource, para. 2)

Statistician, Jason Douglas from Bemidji IHS, lead the data recovery effort. As stated earlier, the IHS statistician retrieved data on the following health disparities per researcher request including, but not limited to: height, weight, body mass index (BMI), dental fluoride treatments, blood lead levels, diabetes, respiratory syncytial virus (RSV), bronchiolitis, lice, immunizations, and suicide. These diagnoses were isolated as ones of importance through literature review and meetings with WE stakeholders. Due to the gaps in the existing literature, the formulation of diagnoses in meetings with WE tribal stakeholders allowed researchers to consider a unique list of health disparities undiluted by national and state data.

Data Collection Process and Logistics

As previously mentioned, statistician Jason Douglas from Bemidji IHS was the primary statistician gathering data from the IHS NDW for the WE population. The process of extracting P a g e | 453

and analyzing data took approximately 3 months to complete. Tracy Moshier RN, BSN, graduate nursing student, gathered the data from the review of literature, national, and state databases. The length of literature and statistical data collection took approximately 10 months. Editing, formatting, synthesis, and further questioning of areas were contributed to by the entire health care team.

Data Analysis

The literature review isolated health disparities for WE population age 18 and younger through national and state databases and professional journals. Many of those health disparities were researched further by the statistician for Bemidji IHS. Some of the examples of disparities investigated were BMI‘s and bronchiolitis. This descriptive style of research was used to

―explore and describe phenomena in real-life situations. This approach is used to generate new knowledge about concepts or topics about which limited or no research has been conducted‖

(Burns & Grove, 2009, p. 45).

No comparative data was used, so the examination of continuous variables by the statistician was in table format listing the number, range, mean, median, and standard deviation.

These tables were imbedded into the literature review to better understand the relationship of WE health disparities to corresponding studies or national database information. These statistical results will be analyzed further during Phase II of the CSEERSWE to generate themes for focus and additional exploration with tribal community members.

Data coding and cleansing was performed during raw data examination by the statistician. Obvious erroneous data was examined and the outliners were eliminated. Some examples of these outliners included a three year old weighing 400 pounds or a five year old entered as six foot tall. The IHS statistician noted problems that appeared to be from incorrect P a g e | 454

data entry, other examples of these are pounds entered instead of kilograms or inches instead of centimeters. Data that appeared to fall outside of the standard deviation was reviewed and eliminated as deemed appropriate.

Description of Human Subject Protection

The retrospective review used human subject data during data collection. Although individuals did not give written permission or informed consent for use of their health statistics in this study all information contained no identifying markers of individuals. Additionally, Tribal

Chairwoman Vizenor gave written permission (see Appendix E) to gather and evaluate data relevant to the CSEERSWE project. WE tribal council endorsed the study and was affirmed by the chair woman Vizenor authorizing MSUM to conduct research of WE. MSUM Institutional

Review Board (IRB) approval was established for the CSEERSWE study and is included in

Appendix D. In addition, to aid in the understanding of protecting human research participants, this author successfully completed the NIH Office of Extramural Research program and the certificate of completion for the NIH Web-based training course ―Protecting Human Research

Participants‖ is included in Appendix C.

Plans for Dissemination of Findings

The health arm literature review was submitted to the CSEERSWE project committee early May, 2009. Upon review of the literature review findings from all of the arms, the committee will enter Phase II of the study. The goal of the CSEERSWE is to have the Phase I project completed and a final report in 2010. Co-authorship will be acknowledged in the final report for the contribution of the literature review and retrospective data review during Phase I by the health arm of the study. P a g e | 455

A copy of the literature review manuscript will be provided to MSUM department of nursing the fall semester 2009. If the CSEERSWE committee and WE tribal elders agree the results of the literature review could be submitted to a Minnesota nursing conference, not yet determined, for a poster presentation.

Chapter III Summary

The purpose of this study was to describe the health disparities among American Indian youth (0-18 years old) with specific focus on those using White Earth reservation IHS services.

Utilizing the resources of Bemidji IHS data bases, combined with the expertise of the IHS statistician, and the vast literature resources available at MSUM, health disparities in this population were unveiled and gaps identified. The eventual dissemination of findings of the

CSEERSWE has the potential to improve educational achievement by creating recommendations and interventions for the major partners involved in the study. Some of these include the WE nation, WE education division, WE health division, WE police, and local public school systems outside of the reservation boundaries. Overall, public and political awareness may be increased improving overall funding and cultural sensitivity to the WE nation in the hopes of improving educational achievement.

P a g e | 456

Chapter IV-Summary of Health Disparities

A significant gap exists in the overall health of the AI child compared to the health of children in the general population. The marginalization of the AI in the U.S. population has increased the morbidity, mortality, and burden of disease for children in AI communities.

The lack of statistical data for the AI youth was most alarming and often times documented data simply did not exist to support the expressed concerns on the WE reservation.

This scant amount of generalized national data was often used to identify health disparities for the children on the WE reservation.

Children‘s health status is uniquely impacted by biologic, genetic, socioeconomic, environmental, socioculutural, and behavioral factors. In addition to these, the compounding effects of poverty, stress, and access to health care for children using WE IHS can increase the incidence of health disparities (Chen, Martin & Matthews, 2006; Guthrie & Low, 2006; Hughes

& Ng, 2003)

The following list is a summary of key disparities which the authors of this Phase I health arm feel should be prioritized and addressed further in Phase II. It is important to note that none of the health disparities mentioned below occur in a vacuum and many impact or overlap the others. The literature review and retrospective data review found the following disparities to be significant for children under the age of 18 years receiving care from WE IHS.

Unintentional Injury

The IHS Provider indicated that AI/AN child mortality rates ages 1-19 years is nearly

―40% higher than that of White children in the U.S. (31.94 per 100,000)‖ (Berger et al., 2007, p.

203). Health professionals have worked diligently on campaigns educating the public about the impact of unintentional injury on children. However, the cause of unintentional injury for the AI P a g e | 457

child varies from that of the general population. The top three causes of death for children under one year old are congenital anomalies, SIDS, and short gestation (Berger et al.). In the White population SIDS is ranked third (Berger et al.). The preventative nature of prenatal care and education cannot be overstated when addressing health disparities for a population as vulnerable as infants. Further investigation is needed to identify the accessibility of prenatal care and availability and attendance of prenatal classes on the WE reservation.

The second method of preventing unintentional injury in children is education on the use of seatbelts. The Minnesota Department of Public Safety (MDPS) (2008) estimated the WE reservation seat belt usage to be 61%, well below the state average of 85.5%. Not all motor vehicle crashes end in fatality, life altering injuries can be just as devastating. Children are especially vulnerable to caregiver‘s implementation and correct use of car seats. Adolescents participate in risk taking, often combining substance abuse, high speed, and lack of seat belt use increasing the likelihood of death in a motor vehicle crash. Further explanation is needed to explore the perception as well as the facilitators and barriers to seat belt use.

Substance Abuse

There is a lack of statistical data clearly outlining the issue of substance abuse among AI adolescents. National and Minnesota reports failed to identify which adolescent age groups showed an increase or link in substance initiation. This is disturbing to health care professionals and educators because preventative programs may need to begin at a younger age than what is being currently implemented. To bridge the lack of data, it may be necessary to coordinate efforts with WE law enforcement to gather data on motor vehicle accident reports involving alcohol or arrests of minors involving the influence of drugs or alcohol. The link between alcohol, illicit drug use, delinquent behavior, and other risk factors was identified in the national P a g e | 458

literature review (Clarke, 2002; Neumark-Sztainer et al., 1996; Wallace et al., 2003); however, no literature searches produced evidence of this specifically on the WE reservation. Before initiating changes based on national and state data, school surveys should be performed to assist in providing age-specific information for the WE youth.

The National Institute on Drug Abuse produced the Overview of Key Findings 2007, listing specific results by drug and subgroup. Unfortunately, the AI population was not delineated in the findings. However, the study design and methodology was very specific, analyzing 16 total drugs for trends. This type of comprehensive school survey would be extremely helpful prior to making recommendations to the WE reservation and school districts.

At this point, it is difficult to know if youth on the WE reservation have an increased use of alcohol, methamphetamines, cocaine, ecstasy, prescription drugs, or steroids. In order to stem drug use, it is necessary to explore the accessibility and usage of adolescent drug use. The secondary impacts of drug use are equally devastating. Teen pregnancy, violence, depression, suicide, sexually transmitted diseases, and school performance are all closely linked (Neumark-

Sztainer, 1996).

Mental Health

The literature review noted the limited information regarding mental health and AI adolescents. The Healing Pathways Longitudinal Study (2009), the Native American Report

(2005), and state and local articles highlighted the impact of mental health on reservations. In summary, the predisposing factors appear to be poverty, stress, exposure to family trauma, and physical and sexual abuse. These factors can lead to depression, suicide, substance abuse, unintentional injury, and other risk taking behaviors. The Healing Pathways Study was the only research specific to youth on the WE reservation and finding supported the need for mental P a g e | 459

health intervention around ages 10-12 years old before children initiate harmful coping mechanisms.

The concerns regarding suicide on the WE reservation were not substantiated by statistics which is likely a reflection of lack of data rather than lack of an issue. However, this appeared to be one of the most significant issues surrounding mental health. The barriers to receiving care for depression and other mental health issues may be the geographic isolation and lack of mental health professionals for the WE reservation (Klobuchar, 2008, para. 8). This is compounded by the alarming trend of adolescents using suicide as a common remedy to depression after hearing of friends who have attempted suicide. Culturally-appropriate suicide prevention initiatives need to begin quickly and state and local government need to make suicide prevention a health priority (Goldston et al., 2008; Native American Report, 2005). Already, WE has begun using community members to support and counsel each other through suicide attempts and deaths

(Gunderson, 2008); however, prevention needs to occur much sooner. Funding for school-based mental health services with trained personal can only begin when accurate data and research is made available to legislators.

Obesity and Diabetes

The statistics from the Bemidji IHS for WE health services indicated that AI youth ages

5-15 years are in the 95th percentile for BMI. Ages 15-18 years had BMIs that were on the lower aspect of the 95th percentile, but still significant for obesity risk. There have been contradicting correlates between genetics, diet, lack of exercise, and poverty in the obesity epidemic in the

United States. AI children appear to be more likely to suffer long-term chronic illnesses related to obesity; these include diabetes, cardiovascular disease, and hypertension (Story et al., 2003).

ICD-9 codes indicated only 11 individuals under the age of 13 were seen in the WE Health P a g e | 460

Center from 2005-2007 for diabetes related care. Corresponding t-test with comparisons may be possible with Bemidji IHS information for WE youth, diabetes, and obesity; however Phase I time constraints limited statistical analysis and further examination may need to be considered during Phase II of the CSEERSWE. Another method to strengthen the current method of retrospective study would be to use case-control design and select ICD-9 correlates, such as family history or diet-related issues, to establish risk factors within the WE youth population.

Factors for increased risk of obesity and subsequent diabetes need to be considered in the lives of youth on the WE reservation. School lunch programs and after school activities are related preventative factors for obesity. Activities such as walking or biking to school also increase daily exercise. Other variables remain outside of a child‘s control; these include parent‘s ability to afford and community availability of healthy foods. Another method of preventing and identifying diabetes is having regular screenings by a school nurse during school hours. Not only does testing blood sugar diagnosis diabetes, but it also identifies children with high normal blood sugars at risk of developing diabetes.

Teen Pregnancy

The MDH PCM (2007) indicated that the AI girls, age 15-19 years, had a three to four times higher teen pregnancy rate than Whites in the state of Minnesota. The Bemidji IHS database for pregnancy was very large and difficult to isolate information for women under the age of 18 years. Phase II of the study may require further examination of Great Lakes

Epidemiology Center statistics or natality rates for the state of Minnesota. Another route of study may be the ICD-9 codes for prenatal care, however these numbers would not reflect the number of youth choosing to terminate a pregnancy or spontaneous abortions/miscarriages. Pregnancy prevention education needs to be expanded to address the issues surrounding early initiation of P a g e | 461

sexual behavior. Special attention needs to be paid to the impact of early sexual behavior on mental health issues and self-perception as well. In Phase II of the CSEERSWE, researchers may investigate the association between substance abuse, depression, suicide, and teen pregnancy.

Another consideration is age and amount of information school health programs are able to disseminated to children regarding sexual health. It may be necessary to begin sexual education earlier and provide birth control for younger ages in school serving the WE reservation.

Chapter IV Summary

To quote Freudenberg and Ruglis (2007), education is the ―elixir‖ for increasing life expectancy, reducing the burden of illness, delaying the consequences of aging, decreasing health behavior risks, and reducing health disparities. In order to identify health disparities for youth on the WE reservation it was necessary to first perform a literature review, retrospective data collection, and conduct meetings with tribal leaders so that WE youth can benefit from care that incorporates their cultural values, beliefs, and practices. By creating research that values diversity and respects traditions, researchers can identify the barriers to academic success and work to improve student outcomes.

P a g e | 462

Appendix A

Permission to Use Conceptual Model of Nursing in Native American Culture.

From: John Lowe [mailto:[email protected]]

Sent: Monday, April 06, 2009 10:44 PM

To: Tracy Moshier

Subject: Re: Dr. Lowe

Dear Tracy:

Yes, you may use the Conceptual Framework of Nursing in the Native American Culture and I am honored that you would consider using the framework for your study. Please send me the findings/results of the study when completed.

Thank you,

John Lowe

954-236-1275

P a g e | 463

Appendix B

Permission to Use Proposal for Comprehensive Study of Education and Related Services on the

White Earth Indian Reservation and Associated Diagrams

From: Boyd Bradbury

Date: April 15, 2009 11:36:21 PM CDT

To: Tracy Moshier

Subject: Re: permission to use proposal

Tracy,

You have my full permission to use any and all parts of the study as needed. You've done a wonderful job on this. I'm very grateful for your efforts. Just let me know if you need anything else.

Thanks, Tracy.

Boyd

P a g e | 464

Appendix C

IRB Ethical Training Certification

Certificate of Completion

The National Institutes of Health (NIH) Office of Extramural Research certifies that Tracy Moshier successfully completed the NIH Web-based training course

―Protecting Human Research Participants.‖

Date of completion: 11/25/2008

Certification Number: 121981

P a g e | 465

Appendix D

IRB Approval

P a g e | 466

Appendix E

Approval from WE Tribal Council Chairwoman Erma Vizenor P a g e | 467

P a g e | 468

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P a g e | 481

Justice Section

Mr. James Bergman, Graduate Assistant

Minnesota State University, Moorhead

Previous parts of this study brought up issues that relate to crime and justice. These issues have implications that effect many social aspects that relate to academic achievement. This section looks specifically at data relating to crime and justice, specifically in the Native

American population.

The White Earth Indian Reservation is situated within five counties. These five counties are Becker, Clearwater, Hubbard, Mahnomen, and Polk. By looking at the statistics that relate to these counties as well as the broader Indian population, a more thorough understanding of how these affect academic achievement may be gained.

The 2007 Probation Survey published by the Minnesota Department of Corrections

(2008) states that American Indians make up 4.06% of the total Minnesota probation population as of the end of 2007. This is much lower than the average of these five counties (33.71%) and lower than each individual county, which ranged from 5.34% in Polk to 80.54% in Mahnomen.

The amount of probations relating to arson were 0.14% higher on average in these 5 counties

(0.33%) than in the rest of Minnesota (0.19%) and each of the counties had a higher percent with the exception of Clearwater county which was 0%. The amount of probations relating to assault was 1.77% higher on average in these 5 counties (6.75%) than in the rest of Minnesota (4.98%).

The amount of probations relating to burglary were 3.95% higher on average (5.87%) than in the rest of Minnesota (2.27%) as well as being higher in each of these individual counties. The amount of probations relating to crimes against family were 0.58% higher on average (1.06%) P a g e | 482

than in the rest of Minnesota (0.47%) as well as being higher in each of these individual counties. The amount of probations relating to drugs was 4.51% higher on average (14.28%) than in the rest of Minnesota (9.77%) with every county except Clearwater (6.78%).

These are only some of the statistics for these five counties, but in looking at the numbers related especially to assault, crimes against family, and drugs, a trend seems to be appearing related to crime in these counties. These crimes may likely have an effect on home life and these may serve to negatively affect academic achievement in school-aged children. Statistics from the National

Criminal Justice Association (NCJA) (2003) also state that "on any given day an estimated one in 25 American Indians 18 years old or older is under the jurisdiction of the nation‘s criminal justice system. This is 2.4 times the rate for whites and 9.3 times the per capita rate for Asians."

In addition to this, "the number of American Indians per capita confined in state and federal prisons is about 38 percent above the national average."

Beyond looking at this issue from the perpetrator perspective, it is necessary to note that

American Indians are likely to experience violent crimes at more than twice the rate of all other

U.S. residents (NCJA, 2003) Between 1992 and 1996 the average annual rate of "violent victimizations among Indians (including Alaska Natives and Aleuts) was 124 per 1,000 residents ages 12 years old and older, compared to 61 violent victimizations per 1,000 blacks, 49 per 1,000 whites, and 29 per 1,000 Asians." These numbers reveal that this population is very vulnerable to especially violent crime. As stated by the Bureau of Justice Statistics (BJS) Director, Jan

Chaiken, ―the findings reveal a disturbing picture of American Indian involvement in crimes as victims and offenders. Both male and female American Indians experience violent crime at higher rates than people of other races and are more likely to experience interracial violence‖

(NCJA, 2003). The BJS also reported (as cited in NCJA, 2003) that "it is non-Indian P a g e | 483

defendants/suspects who commit 70 percent of the violent crimes perpetrated against Native

Americans. This is an appallingly higher rate of interracial violence than that experienced by either white or black victims."

Looking specifically at youth, both from the perpetrator and victim perspective can also provide insight into what is affecting academic achievement. The UIHI (2009) cites findings in the Youth Risk Behavior Survey 1997-2003 to show how rates of negative risk behaviors, often associated with illegal activity, differ in American Indian/Alaska Native (AI/AN) Youth versus

White Youth. Many of these risk behaviors were at least two-fold higher in AI/AN Youth versus

White Youth. These behaviors include having been forced to have unwanted sex, which AI/AN

Youth reported 16.4% and White Youth reported 6.6%. A similar finding was revealed regarding how many had been physically hurt by a boy/girlfriend during the past 12 months, which AI/AN

Youth reported 17% and White Youth reported 8%. These social problems may not be explicitly linked to academic achievement, but the negative impact that they have on the lives of youth, regardless of race, needs to be understood.

The United States Department of Justice (DOJ) Office of Justice Programs (OJP) released a report in 1999 entitled American Indians and Crime (DOJ, 1999). In this report, the

OJP discusses some of the findings regarding crime in the American Indian population. Figure 1 shows violent victimizations between the years of 1992 and 1996, which were discussed previously in this section. This report also goes into depth regarding the age of the victim for all races and for American Indians. As seen in Figure 2, rates of violence in every age group are higher among American Indians than that of all races. This report also stated that ―nearly a third of all American Indian victims of violence are between ages 18 and 24. This group of American

Indians experienced the highest per capita rate of violence of any racial group considered by age- P a g e | 484

-about 1 violence crime for every 4 persons of this age‖ (DOJ, 1999). When divided by sex, the statistics regarding violent victimization indicates a disproportionate amount of victimization in

American Indians of both sexes as can be seen in Figure 3. All of these statistics indicate that violence is a significant problem to American Indians who are often victims, regardless of age and sex.

Another justice matter that has a significant impact on academic achievement would be that of child abuse, neglect, and maltreatment. In the United States, between the years of 1992 and 1995 there was a significant increase in the rate of abuse/neglect of children under 15, as measured by incidents recorded by child protective service agencies (DOJ, 1999). While during the same time an increase was also seen in the Asian population, the increase in the American

Indian population was more than 3 times as large as that for Asian children and the per capita rate for American Indian children was 7 times that of Asian children. Figure 4 shows the differences in child abuse/neglect between races in the years of 1992 and 1995 and the percent change over these years.

P a g e | 485

Violent Victimizations, 1992-96: Annual Average Number of Victims per 1000 persons age 12 or older

150 124

100 61 50 49 29 50

0 All races American Black White Asian Indian

Figure 1: Violent victimizations, 1992-96

Age of victim, 1992-96: Annual Rate of Violent Vicitimizations per 1000 persons in each group

232 250 200 171 145 150 116 124 100 100 61 44 43 27 50 9 14 0 12-17 18-24 25-34 35-44 45-54 55 or older

All Races American Indians

Figure 2: Age of Victim, Violent victimizations, 1992-96

P a g e | 486

Gender of Victim, 1992-96: Rate of Violent Victimizations per 1000 persons age 12 or more in each group

200 153 150 98 60 100 42 50 0 All races American Indian

Male Female

Figure 3: Sex of Victim, Violent Victimizations, 1992-1996

Number of child abuse/neglect victims per 100,000 children, age 14 or younger

4000 3560 3,343 3323 3500 2,830 3000 2500 1866 1724 1992 2000 1,6281520 1486 1500 1254 1995 1000 Percent change 454479 500 -8% 18% -7% -7% 6% -16% 0 All American White Black Asian Hispanic Children Indian

Figure 4: Number of child abuse/neglect victims per 100,000 children, age 14 or younger

P a g e | 487

In Phase II of this study, researchers will strive to discover whether criminal activity by students or family members has a negative effect on student achievement through surveys and possibly interviews. In addition, researchers will try to discover what sorts of support mechanism are in place or could be in place to help offset any negative effects of criminal activity, assuming criminal activity negatively impacts student achievement.

P a g e | 488

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