Predicting Adolescents' Academic Achievement: the Contribution of Attention and Working Memory

Total Page:16

File Type:pdf, Size:1020Kb

Predicting Adolescents' Academic Achievement: the Contribution of Attention and Working Memory University of South Florida Scholar Commons Graduate Theses and Dissertations Graduate School 11-10-2014 Predicting Adolescents' Academic Achievement: The onC tribution of Attention and Working Memory Diane Elizabeth Napier University of South Florida, [email protected] Follow this and additional works at: https://scholarcommons.usf.edu/etd Part of the Curriculum and Instruction Commons Scholar Commons Citation Napier, Diane Elizabeth, "Predicting Adolescents' Academic Achievement: The onC tribution of Attention and Working Memory" (2014). Graduate Theses and Dissertations. https://scholarcommons.usf.edu/etd/5544 This Dissertation is brought to you for free and open access by the Graduate School at Scholar Commons. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. Predicting Adolescents’ Academic Achievement: The Contribution of Attention and Working Memory. by Diane E. Napier A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Curriculum and Instruction Psychological and Social Foundations College of Education University of South Florida Major Professor: Darlene DeMarie, Ph.D. James King, Ed.D. Jeffrey Kromney, Ph.D. Barbara Shircliffe, Ph.D. Date of Approval: November 10th, 2014. Keywords: reading achievement, math achievement, written expression Copyright © 2014, Diane E. Napier Acknowledgments I would like to thank my Chair, Dr. Darlene DeMarie, for her patience in guiding me through this process. Your high expectations and high standards encouraged me to continue working to complete the finished product. This finished product is proof of your abilities as a wonderful dissertation chair. I also thank my committee members, Dr. James King, Dr. Jeffrey Kromrey, and Dr. Barbara Shircliffe for their expertise and patience with me throughout the writing of this dissertation. I also thank retired committee members Dr. Mary Lou Morton, and Dr. Nancy Williams for their guidance and instruction in the early development of this work. All of you made the writing of the dissertation a very valuable experience Table of Contents List of Tables vi List of Figures vii Abstract viii Chapter One: Introduction 1 Background of the Problem 1 Statement of the Problem 2 Purpose of the Study 8 Proposed Study 9 Overview of the Research Method and Design 10 Research Questions 10 Verbal working memory questions 10 Visual working memory questions 11 Theoretical Framework 12 Assumptions 13 Scope and Limitations 15 Delimitations 17 Chapter Two: Review of the Literature 18 A Historical Perspective 18 The Prediction of Ability and Academic Achievement 19 Intelligence tests 19 Working Memory 21 Three Perspectives of Working Memory 22 The Developmental Model 23 Pascual-Leone’s model 23 The Neuropsychological Model 25 Cowan’s model 25 The Cognitive Model 28 Baddeley’s Model 28 The Phonological Loop 29 The Visuo-sketchpad 30 The Central Executive 31 The Episodic Buffer 31 Working Memory as a Predictor of Academic Achievement 32 Working Memory with Children aged 4-10 32 Working Memory with Children aged 7-14 34 i New Trends in the Literature 35 Long-term Memory 36 Working Memory, Executive Function, and Inhibition 36 Attention and Working Memory 38 Inattention Problems 38 Working Memory and Clinical Population 39 Rogers et al. (2010) 40 Limitations within Working Memory Research 41 Participants 42 Outcome Measures 42 Prediction Tests 43 Single Predictor Tests 43 Moderator Variables 44 Omitted Variables 45 Bias in Testing 47 Criterion Bias 47 Construct Bias 47 Confirmational Bias 48 Methodological Measurement of Bias 48 Error Bias 49 The Present Study 50 Comparison of Rogers et al. (2012) and the Present Study 52 Participants 52 Diagnostic Measures 52 Verification of ADHD 52 Teacher Interview 52 Rating Scales 53 Verbal-Auditory Memory 56 Visual-Spatial Memory 56 Academic Achievement 57 Contribution to the Field 57 Chapter Three: Method 61 Method and Design 61 The Rationale 61 The Research Design 62 Research Questions 63 Verbal Working Memory Questions 63 Visual Working Memory Questions 64 Participants 64 Participant Selection 64 Participant Delimitations 66 Sample Size 68 Sampling Frame 69 Sampling Method 69 Geographic Location 69 ii Sampling Sources 69 Sampling Procedures 70 Sampling Time Frame 71 Informed Consent 71 Confidentiality 72 Procedure 72 Data Collection Procedures 72 Instrumentation 74 Behavior Assessment System for Children – 2nd Ed.(BASC-2) 74 Wechsler Intelligence Scale for Children -4th Ed. (WISC-IV) 77 Woodcock-Johnson Tests of Achievement – 3rd Ed. (WJ3) 79 Universal Nonverbal Intelligence Test (UNIT) 82 Order of Test Administration 84 Internal Validity for the Present Study 84 Threats to Validity for the Present Study 86 Data Analysis 87 Descriptive Statistics 87 Participants 87 Variables 87 Analysis 88 Correlational Analysis 88 Multiple Regression Analysis 88 Equations 89 Procedures 89 Interaction Statement 91 Summary 91 Chapter Four: The Results 93 Descriptive Statistics 93 Population 93 ADHD 93 Gender 96 Race/Ethnicity 96 Distribution of Scores 96 Analysis 97 Pearson Product-Moment Correlation Analysis 97 Attention 98 Academic Achievement and Working Memory 98 Analysis of Variances (ANOVAs) 99 Regression Analysis 99 Reading Achievement by Verbal Working Memory 100 Math Achievement by Verbal Working Memory 102 Written Achievement by Verbal Working Memory 105 Reading Achievement by Visual Working Memory 108 Math Achievement by Visual Working Memory 110 Written Achievement by Visual Working Memory 113 iii Summary 117 Chapter Five: The Discussion 118 Goals and Research Findings 118 Goal One: The Prediction of Academic Achievement by Working Memory 118 Reading 119 Math 122 Written Expression 123 Verbal Working Memory 123 Visual Working Memory 124 Goal Two: Do Attention Problems Add to the Prediction? 124 Goal Three: Do Attention Problems Moderate the Relations? 127 Limitations of Present Study 129 Threats to Internal Validity 129 Selection of Subjects 129 Within Participant Differences 129 Age of Participants 130 Diagnosis of ADHD 130 Race/Ethnicity 130 Social-Economic Class 131 Threats to External Validity 131 Construct of Attention 132 Learning Environment 133 Academic Achievement Assessments 133 Teacher Instructional Style 135 Contributions to the Field 135 Significant Findings 135 Verbal Working Memory 135 Visual Working Memory 135 Behavioral Inattention 136 Academic Achievement 137 Racial/Ethnicity 137 Recommendations for Future Research 139 Conclusion and Implications for Educators 140 References 143 Appendices 163 Appendix A.: Minimal Risk Informed Consent Form 164 Appendix B. Child Assent Form 175 Appendix C. Demographic Form 180 Appendix D. Flyer to recruit participants 182 iv List of Tables Table 1. Order of Test Administration 83 Table 2. Key for Abbreviations in Regression Equations: Questions “a” 88 Table 3. Key for Abbreviations in Regression Equations: Questions “b” 89 Table 4. Key for Abbreviated terms in Regression Equations: Questions “c” 89 Table 5. Frequency of ADHD by Gender and Ethnicity 94 Table 6. Frequency and Percentage of ADHD by Gender and Ethnicity 95 Table 7. Mean Scores of Achievement by Gender 95 Table 8. Mean Scores by Race/Ethnicity 97 Table 9. Distribution of Scores by Variable 98 Table 10. Bi-Variate Intercorrelations of the Variables 98 Table 11. Analysis of Variance (ANOVA) Between Subjects and Gender 99 Table 12. Regression Analysis: Reading Achievement and Verbal Working Memory 103 Table 13. Regression Analysis: Math Achievement and Verbal Working Memory 105 Table 14. Regression Analysis: Written Expression and Verbal Working Memory 108 Table 15. Regression Analysis: Reading by Visual Working Memory 111 Table 16. Regression Analysis: Math by Visual Working Memory 114 Table 17. Regression Analysis: Writing by Visual Working Memory 116 v List of Figures Figure 1. Baddeley’s Model of Working Memory 3 Figure 2. Baddeley’s Model of Working Memory 28 Figure 3.1. The Relation between Working Memory and Academic Achievement 58 Figure 3.2. The Relation between Attention and Academic Achievement 59 Figure 3.3. Does Attention Moderate the Prediction of Academics by Working Memory? 60 Figure 4. Frequency of Students with ADHD by Ethnicity 94 Figure 5. Reading Achievement by Verbal Working Memory 101 Figure 6. Math Achievement by Verbal Working Memory 104 Figure 7. Written Expression by Verbal Working Memory 107 Figure 8. Reading Achievement by Visual Working Memory 109 Figure 9. Math Achievement by Visual Working Memory 112 Figure 10. Written Expression by Visual Working Memory 115 vi Abstract The present study examined the direction and strength of the relation between three different areas academic achievement and working memory with adolescent students. The data analyzed included ratings for inattention, a diagnosis of ADHD (or not), and demographic information for race/ethnicity. Fifty children aged 11 to16 years of age participated in the study. Participants were recruited from several middle schools, homeschooling networks, and churches from a southeastern state of the United States. Each participant completed a standardized achievement test, a behavioral rating scale, and visual and verbal working memory tests. The research questions investigated: 1) the relation between visual and verbal working memory with each of three areas of academic achievement; 2) whether the relation between visual and verbal working
Recommended publications
  • Big Five Predictors of Academic Achievement
    Journal of Research in Personality 35, 78±90 (2001) doi:10.1006/jrpe.2000.2309, available online at http://www.idealibrary.com on Big Five Predictors of Academic Achievement Sampo V. Paunonen University of Western Ontario, London, Ontario, Canada and Michael C. Ashton Brock University, St Catharines, Ontario, Canada A large-sample study (N ϭ 717) is described in which two broad Big Five factor measures were compared with two narrow personality trait measures in the predic- tion of ®nal grades in an undergraduate psychology course. The Big Five factors evaluated as predictors were Conscientiousness and Openness to Experience (or Intellect). The traits evaluated, which were constituents of the respective factors, were need for Achievement and need for Understanding. In each comparison, the lower level trait measure did better than its higher level factor measure in the predic- tion of course grades. We conclude that the aggregation of narrow trait measures into broad factor measures can be counterproductive from the points of view of both behavior prediction and behavior explanation. 2001 Academic Press Some researchers believe that the variation in human behavior can be ade- quately summarized in terms of ®ve broad dimensions of personality. Those dimensions, known as the Big Five personality factors, are typically labeled as Extraversion, Agreeableness, Conscientiousness, Neuroticism (vs Emo- tional Stability), and Openness to Experience (or Intellect). The Big Five have been recovered in many studies and in many cultures, with the analysis of both comprehensive lists of personality-descriptive adjectives (e.g., De Raad, Perugini, HrebõÂckovaÂ, & Szarota, 1998) and numerous questionnaires comprising diverse personality trait scales (see McCrae & John, 1992).
    [Show full text]
  • The Influence of Paying Attention in Classroom on Students' Academic Achievement in Terms of Their Comprehension and Recall Ability
    2-4 February 2015- Istanbul, Turkey 684 Proceedings of INTCESS15- 2nd International Conference on Education and Social Sciences THE INFLUENCE OF PAYING ATTENTION IN CLASSROOM ON STUDENTS’ ACADEMIC ACHIEVEMENT IN TERMS OF THEIR COMPREHENSION AND RECALL ABILITY Turkiya Al’Omairi1*, Husam Al Balushi2 1Ms. Assistant Lecturer, Sultanate of Oman, [email protected] 2Mr. English Teacher, Sultanate of Oman, [email protected]. * Corresponding Author Abstract Students' attention in classroom and their academic achievement are two related variables, and they are reflected in students' comprehension and recall ability. However, most of the studies referred to comprehension and recall ability interchangeably and mainly used recall tasks to measure working memory capacity. Adding to that, to the best of my knowledge, there are not many studies that combine the three main variables, but they relate each one of attention and working memory capacity to achievement in an indirect way. Thus, this paper was conducted to investigate whether paying attention in class affect students' academic achievement in terms of their comprehension and recall ability. In order to measure the three main variables, which are comprehension, recall ability and attention, three different tests were used, and they were applied on a sample of two hundred English Education students in counseling psychology class. The comprehension test had three questions related to the previous lesson of counselling psychology class. For the recall ability, a task had three parts, each of which included lists of pictures or letters that the participants needed to recall their order, and the attention task was mainly adapted from the Stroop colour naming task.
    [Show full text]
  • The Association Between School-Based Physical Activity, Including Physical Education, and Academic Performance
    The Association Between School-Based Physical Activity, Including Physical Education, and Academic Performance U.S. Department of Health and Human Services Centers for Disease Control and Prevention National Center for Chronic Disease Prevention and Health Promotion Division of Adolescent and School Health www.cdc.gov/HealthyYouth Revised Version — July 2010 (Replaces April 2010 Early Release) Acknowledgments: This publication was developed for the Centers for Disease Control and Prevention’s (CDC) Division of Adolescent and School Health (DASH) under contract #200 -2002-00800 with ETR Associates. Suggested Citation: Centers for Disease Control and Prevention. The association between school- based physical activity, including physical education, and academic performance. Atlanta, GA: U.S. Department of Health and Human Services; 2010. TABLE OF CONTENTS Executive Summary . 5 Introduction . 8 Methods 10 Conceptual Definitions . 10 Inclusion Criteria . 10 Identification of Studies that Met the Inclusion Criteria . 11 Classification of Studies . 11 Study Coding Process . 12 Data Analysis . 13 Results . 14 School-Based Physical Education Studies . 16 Recess Studies . 19 Classroom Physical Activity Studies . 21 Extracurricular Physical Activity Studies . 24 Summary . 28 Overall Findings . 28 Findings for Physical Activity by Context . 29 Findings by Gender, Other Demographic Characteristics, and Research Design . 30 Strengths and Limitations of Review . 30 Implications for Future Research or Evaluation . 31 Implications for Schools . 32 References . 34 Appendices . 39 Appendix A: Database Search Terms . 39 Appendix B: Coding Sheet . 41 Appendix C: Glossary of Research Design Terms . 51 Appendix D: School-Based Physical Education Summary Matrix . 52 Appendix E: Recess Summary Matrix . 62 Appendix F: Classroom Physical Activity Summary Matrix . 67 Appendix G: Extracurricular Physical Activity Summary Matrix .
    [Show full text]
  • The Impact of Executive Functions on Academic Performance
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Available online at www.sciencedirect.com Procedia Social and Behavioral Sciences 11 (2011) 240–244 Teachers for the Knowledge Society Cognitive control goes to school: The impact of executive functions on academic performance Laura Visu-Petraa,*, Lavinia Cheiea, Oana Bengaa,b, Mircea Micleab aDevelopmental Psychology Lab, Department of Psychology, Babeş-Bolyai University bApplied Cognitive Psychology Center, Department of Psychology, Babeş-Bolyai University Abstract The general aim of the present study was to investigate EF in relation to academic performance. We chose tasks evaluating three EF dimensions: working memory (WM), inhibition (resistance to interference and negative priming), and set-shifting. Subjects (N = 70) were school-aged children in the 5th and the 8th Grades. Regression models supported the contribution of individual differences in EF performance to explaining over half of total variance in school performance, revealing the main role of WM in predicting Mathematics performance. Results are discussed in terms of relevance of meaningful assessment practices and for educational interventions. © 2011 Published by Elsevier Ltd . Open access under CC BY-NC-ND license. Selection and peer-review under responsibility of Masterprof team. Keywords: cognitive control, executive functions, academic performance, predictors, school-age children 1. Problem statement and motivation Executive functions (EFs) play a central role in sustaining and calibrating the development of academic skills and in school performance in general; however, few studies have directly targeted EF as a predictor and/or correlate of school readiness and achievement. According to the EF model proposed by Miyake and collaborators (2000), which received the largest empirical support for adults and children after the age of 5 (Best, Miller, & Jones, 2009; Visu-Petra, Benga, & Miclea, 2007), there are three main EF dimensions: updating, set-shifting, and inhibition.
    [Show full text]
  • Conscientiousness and Academic Performance: a Mediational Analysis Nicole Conrad Saint Mary’S University, [email protected]
    International Journal for the Scholarship of Teaching and Learning Volume 6 | Number 1 Article 8 1-2012 Conscientiousness and Academic Performance: A Mediational Analysis Nicole Conrad Saint Mary’s University, [email protected] Marc W. Patry Saint Mary’s University, [email protected] Recommended Citation Conrad, Nicole and Patry, Marc W. (2012) "Conscientiousness and Academic Performance: A Mediational Analysis," International Journal for the Scholarship of Teaching and Learning: Vol. 6: No. 1, Article 8. Available at: https://doi.org/10.20429/ijsotl.2012.060108 Conscientiousness and Academic Performance: A Mediational Analysis Abstract Previous research has established that a relationship exists between the personality trait of conscientiousness and academic achievement. The current study extends prior research by using a path analysis model to explore various proximal traits that may mediate this relationship in a sample of two hundred and twenty three undergraduate university students. Consistent with previous research, a strong positive relationship was found between conscientiousness and academic performance as measured by final grades. Of greater importance, two factors were found to mediate this relationship: Academic Self-Efficacy and Test Anxiety. The current study illustrates the complex nature of the relation between personality traits and academic achievement and indicates that personality likely has a distal effect on academic performance through more proximal characteristics. Keywords Big five, Personality, Conscientiousness, Academic achievement;, Academic performance Creative Commons License Creative ThiCommons works is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 LAicttreinbutse.ion- Noncommercial- No Derivative Works 4.0 License IJ-SoTL, Vol. 6 [2012], No. 1, Art. 8 Conscientiousness and Academic Performance: A Mediational Analysis Nicole Conrad Saint Mary’s University Halifax, Nova Scotia, Canada [email protected] Marc W.
    [Show full text]
  • A Study of Academic Achievement and Mental Health of the Special School Students
    IOSR Journal Of Humanities And Social Science (IOSR-JHSS) Volume 21, Issue12, Ver. 7 (December. 2016) PP 49-52 e-ISSN: 2279-0837, p-ISSN: 2279-0845. www.iosrjournals.org A Study of Academic Achievement and Mental Health of the Special School Students M.Sathiyaraj1, and Dr. R.Babu2. 1. Research scholar, Department of Education, Annamalai University, India. 2. Professor of Education & Dean, Faculty of Education, Annamalai University, India. ABSTRACT:- An attempt has been made to construct and validate the academic achievement and mental health scales among the special school students. Well structured scales were administered among them. The sample consists of 750 special school student randomly selected from the schools situated in Tamilnadu state. The scales were validated using‘t’ test and ‘F’ test. The present research discusses about the level of academic achievement and mental health among the special school students. Keywords: academic achievement, mental health, special school student. I. INTRODUCTION It is known fact that the special school students dependent status and expressing the emotions in an unbalanced way participating in social process like competition, rivalry, assimilating social skill and values, participating actively in sharing problems of the family obviously the individual at this stage are confronted with problems due to emerging self. Special education (also known as special needs education, aided education, vocational education, and limb care authority education) is the practice of educating students with special educational needs in a way that addresses their differences and needs. Ideally, this process involves the individually planned and systematically monitored arrangement of teaching procedures, adapted equipment and materials and accessible settings.
    [Show full text]
  • Executive Function As a Mediator Between SES and Academic Achievement Throughout Childhood
    International Journal of Behavioral Development 2017, Vol. 41(1) 94–104 Executive function as a mediator ª The Author(s) 2015 Reprints and permissions: between SES and academic achievement sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/0165025415603489 throughout childhood journals.sagepub.com/home/ijbd Gwendolyn M. Lawson and Martha J. Farah Abstract Childhood socioeconomic status (SES), as measured by parental education and family income, is highly predictive of academic achievement, but little is known about how specific cognitive systems shape SES disparities in achievement outcomes. This study investigated the extent to which executive function (EF) mediated associations between parental education and family income and changes in reading and math achievement in a sample of 336 children between the ages of 6 and 15 years from the NIH MRI Study of Normal Brain Development. Verbal memory was simultaneously modeled as a comparison candidate mediator. SES predicted significant changes in reading and math achievement over a two-year time period. Furthermore, executive function, but not verbal memory, was found to partially mediate the relationship between SES variables and change in math achievement. Collectively, these results suggest that executive function may be an important link between childhood SES and academic achievement Keywords academic achievement, executive functions, socioeconomic status Childhood socioeconomic status (SES) is a powerful predictor of opposed to ‘hot’) EF, that is EF in emotionally neutral contexts academic achievement throughout childhood and adolescence (Zelazo & Carlson, 2002), and further subdivide EF into working (e.g., Bradley & Corwyn, 2002; Reardon, 2011). Research aimed memory, attention shifting, and response inhibition (Miyake at understanding the SES achievement gap in terms of child cogni- et al., 2000).
    [Show full text]
  • Variations on Children's Performance on the Marshmallow Test Across Age, Socioeconomic Status, Ethnicity and Body Mass Index
    Variations on cperformance on the marshmallow test across age, socioeconomic status, ethnicity and body mass index Submitted by Jeffrey P. Salik Student No: 412112 Supervised by Professors Rumen Pozharliev and Willem Verbeke In partial fulfillment of the requirements To obtain a degree in MSc in Business and Economics (Specialization in Marketing) Erasmus School of Economics, Erasmus University Rotterdam June 2016 Abstract Better self-regulatory competency in children had been closely linked with better academic performance, better adjustment, and the ability to cope with frustration and stress, among many others. Self-regulation among (N=159) preschoolers aged 41.0 to 84.9 months of various socioeconomic and ethnic backgrounds living in the Netherlands, the Philippines and United Arab Emirates were evaluated using W. Although significant difference on the performance on the marshmallow test was detected on age and income, there were no significant differences across ethnic backgrounds, income-to-needs ratio and body mass index (BMI). Correlation between performance index and ethnicity was also found to be significant. Pertinent policy implications of these findings were thoroughly presented towards the end of this paper. Keywords: Self-regulation, age, income, ethnicity, and body mass index (BMI) Acknowledgements Heartfelt thanks and appreciation are extended to Professors Rumen Pozharliev and Willem Verbeke and for their invaluable support and assistance in making this study possible. Their openness in giving advice and suggestions, and their tireless dedication to promote and advance research on this subject have greatly motivated me to work hard towards the timely completion of this paper. I also wish to extend my gratitude to the following school administrators who welcomed me to their respective schools Mr.
    [Show full text]
  • To What Extent Can the Big Five and Learning Styles Predict Academic Achievement
    Journal of Education and Practice www.iiste.org ISSN 2222-1735 (Paper) ISSN 2222-288X (Online) Vol.7, No.30, 2016 To What Extent Can the Big Five and Learning Styles Predict Academic Achievement Yaman Köseoğlu Lecturer; Faculty of Arts and Sciences, Bahçeşehir University, İstanbul, Turkey Abstract Personality traits and learning styles play defining roles in shaping academic achievement. 202 university students completed the Big Five personality traits questionnaire and the Inventory of Learning Processes Scale and self-reported their grade point averages. Conscientiousness and agreeableness, two of the Big Five personality traits, related positively with all four learning styles, namely synthesis-analysis, methodical study, fact retention and elaborative processing. On the other hand, neuroticism was found to have a negative relationship with all four learning styles. Furthermore, both extraversion and openness appeared to have positive relationships with elaborative processing. The results of the Big Five personality traits explained 17% of the variance in grade point average and learning style added 5% , indicating that both contribute to academic performance. Further, the relationship between openness and GPA was mediated by synthesis-analysis and elaborative processing, both reflective learning styles. These findings suggest that when students process information thoroughly and meticulously and combine such an approach with intellectual curiosity, their academic performance will be enhanced. The impacts of these findings on teaching techniques and curriculum design are also deliberated. Keywords: Learning styles, reflective, synthesis-analysis, Big Five, conscientiousness, openness, academic achievement, 1. Introduction The way of processing, encoding, recalling, organizing and applying the knowledge assimilated changes from student to student in universities.
    [Show full text]
  • Are Cognitive G and Academic Achievement G One and the Same G? an Exploration on the Woodcock–Johnson and Kaufman Tests
    INTELL-00687; No of Pages 16 Intelligence xxx (2012) xxx–xxx Contents lists available at SciVerse ScienceDirect Intelligence Are cognitive g and academic achievement g one and the same g? An exploration on the Woodcock–Johnson and Kaufman tests Scott Barry Kaufman a,⁎, Matthew R. Reynolds b, Xin Liu c, Alan S. Kaufman d, Kevin S. McGrew e,f a Psychology Department, New York University, USA b The University of Kansas, USA c NCS Pearson, Clinical Assessment, Bloomington, MN, USA d Yale Child Study Center, Yale University School of Medicine, New Haven, CT, USA e Woodcock-Muñoz Foundation, USA f University of Minnesota, Minneapolis, MN, USA article info abstract Article history: We examined the degree to which the conventional notion of g associated with IQ tests and Received 13 January 2011 general cognitive ability tests (COG-g) relate to the general ability that underlies tests of read- Received in revised form 14 January 2012 ing, math, and writing achievement (ACH-g). Two large, nationally representative data sets Accepted 14 January 2012 and two independent individually-administered set of test batteries were analyzed using con- Available online xxxx firmatory factor analysis procedures: (a) the Kaufman-II sample (N=2520), organized into six age groups between 4–5 and 16–19 years, tested on both the Kaufman Assessment Battery Keywords: for Children-2nd ed. (KABC-II) and the Kaufman Test of Educational Achievement-2nd ed. Intelligence (KTEA-II) Comprehensive Form; and (b) the WJ III sample (N=4969), organized into four General cognitive ability age groups between 5–6 and 14–19 years, tested on both the Cognitive and Achievement Academic achievement batteries of the Woodcock–Johnson-3rd ed.
    [Show full text]
  • COGNITIVE PREDICTORS ACADEMIC SKILLS Executive Functions and Metacognitive Monitoring Are Not Interchangeable in Educational
    COGNITIVE PREDICTORS ACADEMIC SKILLS 1 Executive Functions and Metacognitive Monitoring Are Not Interchangeable in Educational Settings: Shared and Unique Contributions to Academic Outcomes Rina Pak-ying Lai, Michelle R. Ellefson, and Claire Hughes University of Cambridge Author Notes This manuscript is under peer review. This is not the final version. Correspondence concerning this article should be addressed to Michelle R. Ellefson, University of Cambridge Faculty of Education, 184 Hills Road, Cambridge, CB2 8PQ, United Kingdom. Email: [email protected]. A joint-council award to the authors funded this research (ES/K010225/1: Economic and Social Research Council, Research Grants Council of HK). Thinking Games website development supported by the Institute of Educational Sciences, U.S. Department of Education, through Grant R305A110932 to the University of Cambridge. The opinions expressed are those of the authors and do not represent the views of the Institute or the U.S. Department of Education. Electronic access to dataset from the entire project: http://reshare.ukdataservice.ac.uk/ 852570/. The full data set for the externally funded project is available through the UK Data Service at http://reshare.ukdataservice.ac.uk/852570/. Materials used for the executive function tasks are available from http://reshare.ukdataservice.ac.uk/852658/. A preprint has been uploaded to https://psyarxiv.com/4jhnz. Initial analyses for this manuscript were conducted by Rina Pak-ying Lai in partial fulfillment of a masters degree. Thanks to (1) Geoff Martin for Thinking Games website programming; (2) Florrie Ng and Qian Wang for comments on the early research design; (3) COGNITIVE PREDICTORS ACADEMIC SKILLS 2 Annabel Amodia-Bidakowska, Emma Chatzispyridou, Yiming Han, Katherine Parkin, Annie Raff, Antonia Zachariou for data collection assistance; (4) Rosie Blunt, Hannah Bush, Claudia Chu, Shehnaz Dowlet, Ellie Frank, Anton Evans, Tanya Paes, Nelly Hu-Kwo for scoring and data entry assistance and (5) Ric Parkin for proof reading.
    [Show full text]
  • Intelligence and Verbal Short-Term Memory/Working Memory: Their Interrelationships from Childhood to Young Adulthood and Their Impact on Academic Achievement
    Journal of Intelligence Article Intelligence and Verbal Short-Term Memory/Working Memory: Their Interrelationships from Childhood to Young Adulthood and Their Impact on Academic Achievement Wolfgang Schneider * and Frank Niklas Department of Psychology, University of Würzburg, Würzburg 97070, Germany; [email protected] * Correspondence: [email protected]; Tel.: +49-931-3182352 Received: 22 February 2017; Accepted: 7 June 2017; Published: 16 June 2017 Abstract: Although recent developmental studies exploring the predictive power of intelligence and working memory (WM) for educational achievement in children have provided evidence for the importance of both variables, findings concerning the relative impact of IQ and WM on achievement have been inconsistent. Whereas IQ has been identified as the major predictor variable in a few studies, results from several other developmental investigations suggest that WM may be the stronger predictor of academic achievement. In the present study, data from the Munich Longitudinal Study on the Genesis of Individual Competencies (LOGIC) were used to explore this issue further. The secondary data analysis included data from about 200 participants whose IQ and WM was first assessed at the age of six and repeatedly measured until the ages of 18 and 23. Measures of reading, spelling, and math were also repeatedly assessed for this age range. Both regression analyses based on observed variables and latent variable structural equation modeling (SEM) were carried out to explore whether the predictive power of IQ and WM would differ as a function of time point of measurement (i.e., early vs. late assessment). As a main result of various regression analyses, IQ and WM turned out to be reliable predictors of academic achievement, both in early and later developmental stages, when previous domain knowledge was not included as additional predictor.
    [Show full text]