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Assessment and comparison of environmental knowledge and attitudes held by thirteenth grade general and technical education students in the Republic of Burundi
Ndayitwayeko, Albert, Ph.D.
The Ohio State University, 1994
UMI 300 N. Zeeb Rd. Ann Arbor. M I 48106 ASSESSMENT AND COMPARISON OF ENVIRONMENTAL KNOWLEDGE
AND ATTITUDES HELD BY THIRTEENTH GRADE GENERAL AND TECHNICAL
EDUCATION STUDENTS IN THE REPUBLIC OF BURUNDI
DISSERTATION
Presented in Partial Fulfillment of the Requirement for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University
By
Albert Ndayitwayeko, B.S., M.ED
The Ohio State University 1994
Dissertation Committee: Approved by Robert E. Roth, Advisor Rosanne W. Fortner Stanley L. Helgeson Gary W. Mullins Advisor College of Education To My Wife P6iagie, My two Daughters Annick and Erica, and My Son Landry
ii ACKNOWLEDGMENTS
Grateful acknowledgment is made to Dr. Robert E. Roth for his guidance, advice, deep understanding, and insight throughout this study and the entire Ph. D program. My sincere gratitude also go to the other members of my dissertation committee, Dr Rosanne W, Fortner, Dr. Stanley L. Helgeson, and Dr. Gary W. Mullins for their wise suggestions and comments, and their commitment to make this work a success. Thanks also go to Michelle Roberts, my program officer (AID), for her assistance and fruitful advice. Mr Charles Rutonesha and his family, Mr Frederic Ruland, Ms. Irma Cooper, and Ms. Mwajabu Possi, will always be remembered for their friendship, kindness, and moral support. Special thanks go to my wife P6lagie for her love, courage, and strong dedication to family matters during my absence. VITA
June 11.1952 ...... Born-Mugamba, Burundi
1978-197 9 ...... B.S., Department of Biology and Chemistry. University of Burundi, Bujumbura.
1979-1980 ...... Biology teacher.Teacher Training High School, Buj u m bu ra-Bu r und i.
1980-198 1...... Director, Teacher Training High School, Bujumbura-Burundi.
* Certificate in ecology. Bureau des Programmes pour I’ Enseignement Secondaire, Bujumbura-Burundi. VITA (continued) 1981 -1982...... Visiting assistant lecturer in Biology University of Burundi-Bujumbura.
1982-1984...... Assistant lecturer in Biology, University of Burundi.
1984-198 5...... Certificate of ecology and Science Teaching Methods, University of Lidge, Sartilman, Belgium.
1985-198 7 ...... Master lecturer in Biology, University of Burundi.
1987-1988 ...... Academic secretary, Teacher Training Institute, University of Burundi
1988-1989...... Dean,Teacher Training Institute University of Burundi. 1989-199 1...... M. Ed., Department of Science Education, University of Florida, Gainesville, Florida.
v PUBLICATIONS
(1984). Approche system at ique des plantes medicmales du Mugamba-Sud. Presses et Publications, University du Burundi (45 pages) Bujumbura-Burundi
(1985). Rapport de Stage en Biology et en Mythodologie de I' Enseignement des Sciences (33 pages), University de Liyge, Sartilman. Belgium.
(1986/87). Guide pour la Mythodologie de I’ Enseignement de la Biologie au Cycle Inferieure des Humanitys (50 pages), Presses et Publications, University du Burundi
(1990). Some observations on natural history museums and zoos in the Republic of Burundi. A pilot study. Visitor behavior. 5 (4), 10-11.
Major Field: Education Studies in Environmental Education Minor Field: Science Education
vi TABLE OF CONTENTS
DEDICATION...... ii ACKNOWLEDGEMENTS...... iii VITA...... iv LIST OF TABLES...... ix LIST OF FIGURES...... xiv CHAPTER...... RAGE I. INTRODUCTION...... 1 Need for the Study...... 4 Implications for the Present Research...... 8 Statement of the Problem ...... 8 Objectives and Statistical Hypotheses ...... 9 Definition of Terms ...... 11 Limitations of the Study...... 12 Basic Assumptions ...... 13 II. REVIEW OF LITERATURE...... 14 Structure of the Burundi System of Education...... 14 Environmental Knowledge, Environmental Attitudes, and Education ...... 17 Environmental Knowledge, Environmental Attitudes, and Demographic Variables...... 20 Education and Human Population ...... 23 Education and Natural Resources ...... 27 Education and Water Quality...... 32 Education and Ecological Principles ...... 34 Education and Environmental Global Concerns ...... 36
vii III. PROCEDURES...... 42 Research Design ...... 42 Validity Determination ...... 45 Reliability Determination ...... 46 Population and Sampling ...... 47 Conditions of Testing ...... 49 Data Analysis...... 50
IV. ANALYSIS OF RESULTS...... 52 Respondents’ Background Information ...... 52 Age...... 53 Gender ...... 54 M ajor...... 54 Residential Location ...... 55 School Geographic Location...... 56 Major Source of Information about the Environment ...... 57 Parents’Occupation ...... 58 Parents’ Highest Degree...... 59 Analysis of the Results by Objectives ...... 61 Data Analysis for Objective 1 ...... 61 Data Analysis for Objective 2 ...... 73 Data Analysis for Objective 3 ...... 86 Data Analysis for Objective 4...... 88 Data Analysis for Objective 5 ...... 112
V. SUMMARY, DISCUSSION, IMPLICATIONS, AND RECOMMENDATIONS...... 147 Summary of The Study ...... 147 Discussion ...... 151 Implications ...... 169 Recommendations for Practice...... 172 Recommendations for Further Study ...... 173 APPENDICES A. Instruments (English Version) ...... 175 B. Instruments (French Version) ...... 190
viii C. Panel of Experts and Field Test Report ...... 202 D. Letter to the Ministry of Education ...... 206 E. Planned Participating Schools ...... 208 F. Coding keys ...... 212 BIBLIOGRAPHY...... 217
ix LIST OF TABLES
TABLE PAGE 1. Distribution of items according to environmental issues ...... 44 2. Descriptive a id inferential statistics ...... 51 3. Frequency distribution of respondents’ age ...... 53 4. Frequency distribution of respondents' gender...... 54 5. Frequency distribution of respondents’ major ...... 55 6. Frequency distribution of respondents' residential location ...... 56 7. Frequency distribution of school geographic location ...... 57 8. Frequency distribution of major source of environmental information 58 9. Frequency distribution of parents' occupation ...... 59 10. Frequency distribution of respondents’ parents’ highest degree ...... 60 11. Summary of score statistics on environmental knowledgeitems ...... 62 12 Frequency of response (as percent) to each alternative on environmental knowledge items ...... 63 13. Frequency of respondents' correct responses (as percent) to knowledge of population issues ...... 65
14. Frequency of respondents’ correct responses (as percent) to knowledge of water quality...... 66 15. Frequency of respondents' correct responses (as percent) to knowledge of natural resources ...... 67
16. Frequency of respondents’ correct responses (as percent) to knowledge of ecological principles ...... 68 17. Frequency of respondents’ correct responses (as percent) to knowledge of global environmental concerns ...... 69 x 18. Respondents' environmental knowledge score statistics by subscales ...... 70 19. Respondents’ environmental knowledge by school category and subscales ...... 71
20. T-test of respondents’ environmental knowledge mean scores by school categories and subscales ...... 72
21. Summary of respondents’ environmental attitudes score statistics by school category...... 74
22. Frequency of respondents' responses (as percent) to each alternative on environmental attitude items ...... 75
23. Frequency of respondents’ environmental attitude scores (as percent) on human population issues ...... 77
24. Frequency of respondents’ environmental attitude scores (as percent) on natural resources issues ...... 78
25. Frequency of respondents’ environmental attitude scores (as percent) on water quality issues ...... 79
26. Frequency of respondents’ environmental attitude scores (as percent) on ecological principles...... 80
27. Frequency of respondents’ environmental attitude scores (as percent) on global issues ...... 82
28. Summary of respondents’ environmental attitude score statistics by school subscales ...... 83
29. Respondents’ environmental attitude score statistics by school category and subscales ...... 84
30. T-test of respondents’ environmental attitude mean scores by school category and subscales ...... 85
31. Relationship: respondents' environmental knowledge and attitudes by school category and subscales ...... 87
32. ANOVA of the overall environmental knowledge mean scores by independent variables ...... 91 xi 33. ANOVA ot human population knowledge mean scores by independent variables ...... 93
34. LSMeans of DE 2 and DE 4 by knowledge of human population ...... 95
35. Probability matrix of means in Table 34 ...... 97
36. LSMeans of DE 2 and DE 8 by knowledge of human population issues ...... 98
37. Probability matrix of means in Table 3 6 ...... 100
38. ANOVA of water quality knowledge mean scores by independent variables...... 101
39. ANOVA of natural resources knowledge mean scores by independent variables ...... 102
40. LSMeans of DE 1 and DE 2 by knowledge of natural resources issues ...... 103
41. Probability matrix of means in Table 40 ...... 105
42. ANOVA of ecological issues knowledge mean scores by independent variables ...... 106
43. ANOVA of global issues knowledge mean scores by independent variables...... 107
44. LSMeans of DE 1 and DE 4 by knowledge of global environmental issues ...... 108
45. Probability matrix of means in Table 44 ...... 110
46. ANOVA of the overall environmental attitude mean scores by independent variables ...... 114
47. LSMeans of DE 1 and DE 2 by the overall environmental attitude 115
48. Probability matrix of means in Table 47 ...... 117
49. ANOVA of human population attitude mean scores by independent variables...... 118
xii 50. LSMeans of DE 2 and DE 6 by attitudes toward human population issues ...... 119 51. Probability matrix of means in Table 50 ...... 121
52. ANOVA of natural resources attitude mean scores by independent variables...... 122
53. LSMeans of DE 1 and DE 9 by attitudes toward natural resources.....123
54. Probability matrix of means in Table 53 ...... 125
55. LSMeans of DE 2 and DE 8 by attitudes toward natural resources issues ...... 126
56. Probability matrix for means in Table 55 ...... 128
57. ANOVA of water quality attitude mean scores by independent variables...... 130
58. LSMeans of DE 1 and DE 8 by attitudes toward water quality issues ...... 131
59. Probability matrix ot means in Table 58 ...... 133
60. ANOVA of ecological principles attitude mean scores by independent variables ...... 135
61. LSMeans of DE 1 and DE 2 by attitudes toward ecological principles ...... 136
62. Probability matrix of means in Table 61 ...... 138
63. ANOVA of global issues attitude mean scores by independent variables...... 139
64. LSMeans of DE 1 and DE 4 by attitude toward global environmental issues ...... 140
65. Probability matrix of means in Table 64 ...... 142
66. LSMeans of DE 2 and DE 9 by attitudes toward global environmental issues ...... 144
67. Probability matrix of means in Table 66 ...... 146 xiii LIST OF FIGURES
FIGURE PAGE 1. ANOVA: Human population interaction DE 2 by DE 4 ...... 96 2. ANOVA: Human population interaction DE 2 by DE 8 ...... 99 3. ANOVA: Natural resources interaction DE 1 by DE 2 ...... 104 4. ANOVA: Global issues interaction DE 1 by DE 4 ...... 109 5. ANOVA: Overall attitude mean scores interaction DE 1 by DE 2 ...... 116 6. ANOVA: Human population interaction DE 2 by DE 6 ...... 120 7. ANOVA: Natural resources interaction DE 1 by DE 9 ...... 124 8. ANOVA: Natural resources interaction DE 2 by DE 8 ...... 127 9. ANOVA: Water quality interaction DE 1 by DE 8 ...... 132 10. ANOVA: Ecological principles interaction DE 1 by DE 2 ...... 137 11. ANOVA: Global environmental issues interaction DE 1 by DE 4 ...... 141 12. ANOVA: Global environmental issues interaction DE 2 by DE 9 ...... 145
xiv CHAPTER I INTRODUCTION In spite of the fact that more than three decades have elapsed since the Republic of Burundi became independent, its system of education still bears the old and traditional curriculum picture of colonial times. New realities and constraints have surfaced which call for greater reassessment and revision of school policies, programs, and procedures. However, the shortage of economic resources, limited school supplies, and inexperienced teachers prevented the Burundi System of Education from becoming a changing institution dedicated to meet today's country needs. At the same time, environmental degradation is continuing at an accelerating pace. The failure to include environmental education topics in school curricula as demonstrated by the (1991) Preliminary Seminar on a National Strategy for the Environment in Burundi is a specific indication of how the Burundi System of Education is slow in moving toward curricular improvement. Whereas the need for an integrated environmental education approach reached the level of national commitment as early as 1991, the above Seminar found that few environmental issues and/or problems have received adequate attention in Secondary School curricula or through assessment. In such a climate, some key environmental issues and/or problems recognized by the above Seminar as being the most compelling in Burundi need to be addressed and infused into the existing school curricula and emphasized in informal educational settings. These issues and/or problems
1 are: (1) Human population explosion; (2) Natural resources depletion; (3) Water quality; (4) Ecological principles; and (5) Global concerns such as: pesticide use and misuse; acid rain; global warming ; and desert creeping,especially in Africa. These issues seemed to be most related to environmental problems in Burundi, and have proven useful in students’ evaluation of environmental knowledge and attitudes toward the environment in the Dominican Republic Indonesia, and the United States of America {Roth and Batista, 1990; Indratmo, 1990; and Kenneth 1990). According to a Burundi Minister of the Environment’s speech (Renouveau no 3557 du Mercredi 31 Juillet 1991), overpopulation and natural resources depletion originating especially from land exhaustion, slash and burn practices, shifting cultivation, deforestation, ecological disruptions, soil erosion, flooding, and drought constitute the most compelling environmental problems facing the Republic of Burundi. In addition, Le Renouveau no3558 du 1 Aout 1991 pointed out that natural resources depletion, lack of materials and equipment, lack of food, energy supply, and water pollution seriously impact the quality of the environment in Burundi. While the above threats still challenge the environment and the quality of life in Burundi, progress is being made to include them in government policy planning and the decision-making processes (Preliminary Seminar on the National Strategy for the Environment in Burundi, 1991). However, these issues are given minimal attention in public school curricula. The Preliminary Seminar on a National Strategy for the Environment in Burundi (1991) identified a lack of emphasis on ecological and environmental issues in primary school programs. The need for more inclusion of 3 environmental topics in secondary school instruction was also highlighted. In spite of the fact that some environmental topics or issues were included in secondary school curricula, the participants in the above Seminar found that environmental concerns were dealt with very superficially through school instruction because of a lack of teacher preparation and interest in conducting environmental programs. The seminar recognized some effort devoted to environmental science instruction at the university level. The extent to which these issues and/or problems are understood by high school seniors, and their feelings and/or perceptions about related environmental problems in Burundi, constitute the basis for the present research. The Republic of Burundi is located in the heart of Central Africa along the northeastern shore of Lake Tanganyika (Burundi Post, 1987). Burundi is small in area, comprising 27,834 sq km (10,747 sq miles), but with a relatively large population of 5.5 million (1990 estimate). The capital of Burundi is Bujumbura. Burundi is bordered by Rwanda to the north, by Zaire to the west, and Tanzania to the east and south. The natural divide between Burundi and Zaire is formed by Lake Tanganyika and the Ruzizi River on the floor of the western Rift-valley system. To the east, the land rises sharply to elevations of around 1,800m above sea level in a range that stretches north into the much higher volcanic mountains of Rwanda. Away from the edge of the Rift-Valley, elevations are lower and most of Burundi consists of plateaus of 1,400-1800m. Here the average temperature is 20 degrees Celsius or 43.1 Fahrenheit, and has an annual rainfall of 1,200mm. In the Rift-Valley, the temperature averages 23 degrees Celsius, or 44.7 Fahrenheit, while rainfall is much lower at 750mm per year. Burundi has a distinct dry season and two rainy seasons. The short rainy season begins in October and ends in December The long rainy season begins in February and continues through mid-May. The rest of the year is the dry season. It also has eleven distinct natural regions characterized by their differences in relief features, temperature, soil types, and vegetation.
Need for the Study About twenty five years ago some precursors of environmental education consciousness among nations began to emerge in the developed countries, especially in the United States of America, and such interest is still growing in the rest of the World . In his message to Congress, President Nixon (1970) stated that:
We must seek nothing less than basic reform in the way our society looks at problems and makes decisions. Our educational system has a key role in bringing about this reform.... It is also vital that our entire society develop a new understanding and a new awareness of man’s relation to his environment that might be called ‘environmental literacy’. This will require the development and teaching of environmental concepts at every point in the educational process, (p. vii)
In addition. Commissioner Marland (1971) indicated: ...We now see environmental education as a new approach to learning. Even as attitudes of individual worth, free agency, democratic consent, and cooperative effort are learned subconsciously in many parts of the school curriculum, so must new attitudes of environmental concern pervade each subject, each course, and each discipline, whether mathematics, English, science, social studies, music, or whatever. Environmental education is interdisciplinary, pervading in spirit of alt levels. (55: 8)
Stapp et al. (1969) proposed that environmental education should work 5 to develop a citizenry that is knowledgeable concerning the biophysical environment and its associated problems, aware of how to help solve these problems, and motivated to work toward their solutions. It may be the landmark Intergovernmental Conference on Environmental Education .Tbilisi (USSR), 1977, that brought together many countries of the World to understand that education should play a leading role in creating an awareness and a better understanding of environmental problems. According to the Tbilisi Conference final report: A basic aim of environmental education is to succeed in making individuals and communities understand the complex nature of the natural and built environments resulting from the interaction of their biological, physical, social, economic, and cultural aspects, and acquire the knowledge, values, attitudes, and practical skills to participate in responsible and effective way in anticipating and solving environmental problems, and the management of the quality of the environment (p. 25).
When considering effectiveness of educational programs, both student attitudes and knowledge about a particular subject are often measured. It is therefore desirable to identify the extent to which students comprehend and believe in the importance of environmental issues to be cornerstones upon which environmental research, programs and materials would develop. As a result of the Tbilisi conference, Jeske (1978) advocated that education should provide every person with opportunities to acquire the knowledge, values, attitudes, commitments and skills needed to protect and improve the environment; to create new patterns of behavior of individuals, groups and society as a whole toward the environment. Hungerford, Peyton, and Wilke (1980) on the other hand, presented a superordinate goal for environmental education: “ to aid citizens in becoming environmentally 6 knowledgeable and, above all, skilled and dedicated citizens who are willing to work, individually and collectively, toward achieving and/or maintaining a dynamic equilibrium between quality of life and quality of the environment, p. 42-47" Ramsey, Hungerford and \A>lk (1989) suggested that, since education is the vehicle through which society prepares its citizens to carry out their responsibilities, education must be environmental. Graham (1987) stated that many people have understandably looked to the educational system as the principal channel for influencing the behavior of future generations. Graham added that the above expectation applies especially to schools in the Third World, where environmental problems of over-population, lack of water, fuel and food, soil erosion and deforestation are at their most acute. Graham also reported that students do not perceive school knowledge as having any relevance to their everyday lives. Moreover, where such school knowledge is explicitly related to the local environment, it often conflicts with traditional (indigenous) knowledge and felt needs. lozzi (1989) reported that several studies showed a positive relationship between environmental knowledge and attitudes; others revealed no relationship at all, while still others showed a negative relationship between environmental knowledge and attitudes, lozzi added that the relationship between these two variables whether positive, negative, or non-existent seems to depend on the specific program studied. Cohen (1973) compared environmental attitudes of two groups of high school students who had different levels of environmental knowledge, he found that groups with more knowledge had different attitudes and were more willing to express environmental attitudes than were their less knowledgeable 7 counterparts. In addition, a study on knowledge and attitudes of Ohio students about both oceans and the Great Lakes revealed that student higher knowledge scores were related to more positive attitudes ( Fortner and Mayer 1983 ). In a study aimed at assessing the problems in exporting environmental education models from the United States to the Third World, Castillo and Ham (1990) concluded that U.S. environmental education models and materials may be based on the assumptions about U.S. schools that do not hold in developing countries. They added that the practice of simply translating materials for use in these countries may not contribute to the growth of environmental education in the developing world. A better approach suggested would be to support in-country development of materials and programs. In addition, the Tbilisi (USSR), 1977 Intergovernmental Conference final report recognized that problems addressed by environmental education should be those familiar to the learners in their own home, community, and nation and should help the learners acquire the knowledge, values, and skills necessary to help solve those problems. The United Nations Educational, Scientific, and Cultural Organization (1980) also pointed out that:
There is no universal model for the incorporation of environmental education into environmental process. The approaches, procedures, and progressive stages of integration must be laid down in the light of the specific conditions, ultimate aims, educational and socio-economic structures of each country, (p. 35) 8 Implications for the Present Research With respect to the research findings, it is clear that the Burundi Educational System which has taken a back seat (see introduction) in the development and implementation of environmental programs, must be provided with baseline data on which to initiate the development of environmental programs for schools and the general public.
Statement of the Problem The aim of the present study is to assess and compare environmental knowledge and attitudes toward the environment held by thirteenth grade General and Technical Education students in the Republic of Burundi. Although environmental education has been a major concern for many countries around the World; no attempt to assess students’ environmental knowledge levels and/or their attitudes toward the environment has been made in the Republic of Burundi. In terms of school curricula, no materials or other resources are or have been allocated specifically to environmental education (Preliminary Seminar on a National Strategy for the Environment in Burundi,1991 and Burundi Ministry of Environment: Environmental Policy Guidelines,1991). The information from the study may be of use in developing a policy framework for decision-making based on current environmental concerns in Burundi. Further, the study may be of use in designing environmental education curriculum and materials for primary and secondary education instruction and may also be of use in promoting general public environmental awareness. 9 Objectives and Statistical Hypotheses With regard to the five selected environmental issues involved in the study: human population explosion, water quality, natural resources depletion, ecological principles, and global environmental concerns such as acid rain, desertification, global warming, pesticide misuse; the following objectives have been employed:
Objective # 1 To assess and compare the levels of environmental knowledge held by two selected samples of thirteenth grade General and Technical Education students in the Republic of Burundi. *H0 : There is no significant difference between General Education and Technical Education respondents’ levels of environmental knowledge.
Objective #2 To assess and compare the attitudes toward the environment held by two selected samples of thirteenth grade General and Technical Education students in the Republic of Burundi. *H0 : There is no significant difference between General Education and Technical Education respondents’ attitudes toward the the environment.
Objective #3 To investigate possible relationships between the respondents’ environmental knowledge levels and their attitudes toward the environment for 10 the two categories of schools. *H0 (Rho = 0): There is no significant relationship between the respondents’ levels of environmental knowledge and their attitudes toward the environment for the two categories of schools.
Objective # 4 To investigate any variation between the respondents' environmental knowledge levels related to their age, gender, residential location, source of environmental information, school category, parents ‘occupation and level of education. *H0 : There is no significant difference between the respondents' environmental knowledge levels based upon their: age category, gender, residential location, source of environmental information, type of school, parents’ occupation and level of education.
Objective #5 To examine any variation between the respondents’ attitudes toward the environment due to their age, gender, residential location, source of environmental information, school category, parents' occupation and level of education. *H0 : There is no significant difference between the respondents’ environmental attitudes based upon their: age category, gender, residential location, source of environmental information, type of school, parents'occupation and level of education. 11
Definition of Terms ENVIRONMENTAL EDUCATION: A process aimed at developing a world population that is aware of and concerned about the total environment and its associated problems, and which has the knowledge, attitudes, motivations, commitments, and skills to work individually and collectively toward solutions of current problems and the prevention of new ones (Stapp, 1982, p.83).
ATTITUDE (constitutive definition): An attitude describes a person’s complex set of beliefs, feelings, and behavioral tendencies about another person or thing. Every attitude has cognitive, affective, and behavioral components. It is persistent over time and produces consistent behavior, has a directional quality (like, dislike) and a strength (like very much, like very little); (Van Tilburg, 1989).
ATTITUDE TOWARDS THE ENVIRONMENT (Operational definition): In this study, attitude refers to student’s summated score on a 25 item Likert Scale instrument designed to measure their beliefs, or action toward the assumed five most compelling environmental issues in Burundi (see page 3).
KNOWLEDGE ( Constitutive definition) : “ Knowledge is a structure of concepts and relationships built by reflective thought out of information received. Any experience of participation, observation, reading, or thinking can become part of a person’s knowledge. It will become part of that knowledge if he or she thinks about it, and understands it” (Norland, 1992, p. 164).
KNOWLEDGE ABOUT ENVIRONMENTAL ISSUES /PROBLEMS (Operational definition): In this study, the knowledge represents a student's summated score 12 on a 25 item achievement test designed to measure his / her thinking and understanding of the aforementioned environmental issues in Burundi.
GENERAL EDUCATION SCHOOL: In Burundi, general secondary school studies last for seven years, with a lower school of four years and an upper school of three years. The aim is to give, over the seven years, a general literary and scientific education, preparatory to higher education (Ntawurish ira, 1988).
TECHNICAL EDUCATION SCHOOL: In Burundi, technical education school varies from one to four years, after lower-secondary school, and produces partly qualified technicians and specialized workers (Ntawurishira,1988). For the purpose of this study, technical, vocational, or teacher training schools have been considered the same and only the schools having the thirteen grade level have been included in the study samples (see Appendix E).
Limitations of the Study 1. Time, the political instability in the country, and financial constraints limited the extent to which the plan for this study could be implemented. 2. Since the study will be conducted in the Burundi social context, results wilt not be generalized beyond the target population. 3. The list of the most compelling environmental problems in Burundi is not exhaustive, but is considered to be representative. Basic Assumptions 1. The selected students will represent the populations from which they will be drawn. 2. The respondents will answer the questions to the best of their ability with respect to instructions, their knowledge levels, and their attitudes toward the environment. 3. The information collected will provide a conceptual framework aimed at helping educators, planners, decision-makers, legislators, students, and the general public to understand the need to conserve, improve and protect the environment. CHAPTER II REVIEW OF LITERATURE
The purpose of this chapter is to examine research and literature related to the present study. The review will include the following sections: * Structure of the Burundi System of Education * Environmental knowledge, environmental attitudes, and education * Environmental knowledge, environmental attitudes, and demographic variables * Education and human population * Education and natural resources * Education and water quality * Education and ecological principles * Education and environmental global concerns * Discussion
Structureof the Burundi System of Education The Burundi System of Education is organized into three levels: (1) Primary Education, (2) Secondary Education, and (3) Higher Education. Ntawurishira (1988), and Nizigiyimana (1990) described the Burundi Educational System with an emphasis on an historical overview which is not necessary for the purpose of the present study, however, their observations
14 15 about the structure of the three levels of education are useful.
1. Primary Education. Primary Education in Burundi enrolls children aged seven or eight and keeps them for six years. After six years of studies, the students take a competitive national exam, success at which is a prerequisite for continuing to the middle secondary school. A key objective at this level is to provide schooling to all children. To achieve this objective, a double shift system has been in effect in the schools since 1982-83 with one group of students attending the morning sessions and a second group attending the afternoon sessions.
2. Secondary Education. Secondary Education includes all schools to which pupils are admitted after passing the national examination at the end of their primary school career General secondary school studies last for seven years, with a lower school of four years and an upper school of three years. The aim is to give, over the seven years, a general literacy and scientific education, preparatory to higher education. Technical and professional schools award diplomas after four five, seven, or eight years depending on the nature of the program. Technical education mostly produces partly qualified technicians and specialized workers. However, those students who successfully finish the seven or eight year tracks also qualify for higher education. French is the language of instruction for the three levels of education. In addition Kirundi and English are required, the former for the Primary and Secondary Education, and the latter at the Secondary Education level only. 16 3. Higher Education. Higher Education in Burundi presently aims at achieving several objectives, most significant of which is to produce the highest level of manpower to meet the country's needs; to adapt educational programs to suit national realities with emphasis on practical training; to promote integrated and interdisciplinary programs, to develop inter-university cooperation; to promote Burundization of faculty positions; and to initiate graduate programs on an experimental basis. The University of Burundi is a public institution administered by the Ministry of Higher Education and Scientific Research. In addition to this unique university there are several other higher education institutions with emphases on technical and professional education. The program of studies offered at the University of Burundi leads to the license (first degree), engineering degree, and doctorate degree. The faculties of law, letters and humanities, economic and administrative sciences, science, and psychology offer a license after four years of studies. The Faculty of Agronomy awards the dipiome d'ing4nieur in five years. The Faculty of Medicine requires six years of studies for the degree of doctorate in medicine. The Faculty of Applied Sciences awards an engineering degree in five years. The Institute of Physical Education offers a license after four years. The Teacher Training Institute has a two year program leading to a university diploma, and the Higher Technical Institute offers a dipiome d'inggnieur in three years. Graduate programs (Master’s and Ph. D. ) are not yet available at the University of Burundi. The government awards scholarships to selected candidates for study at foreign universities for graduate degrees. 17 Environmental Knowledge, Environmental Attitudes, and Education The proposed study is based on the premise that intellectual force does not exist apart from attitudes, feelings or emotions that make us open-minded rather than close-minded, responsible rather than irresponsible (Dewey, 1933). In addition, lozzi (1989) concluded that it would seem that cognitive and affective factors should be considered holistically in the teaching and learning process. In addition, Ausubel et al. (1978) revealed that the assessment of student knowledge in a given domain should provide information useful in the design of curricula and educational materials that address students' conceptual problems and misconceptions directly and that introduce new and difficult concepts in ways that facilitate meaningful linkages to existing relevant knowledge in students’ cognitive structures. On the question of environmental knowledge and environmental attitudes, the Tbilisi Conference (USSR), 1977 final report also stressed that:
Education should promote understanding of the role of various biological, physical and socio-economic factors on whose interaction the very nature of the environment depend.. .Environmental education should also promote attitudes which would encourage individuals to discipline themselves in order not to impair the quality of the environment and to play a positive role to improve it. (p. 6)
Eiss and Harbeck (1969) stated that the common person does not deal with knowledge alone because knowledge, feelings, and emotions are, in reality, inseparable. In investigating the relationship between environmental education and the affective domain, lozzi (1989) revealed that one must first develop positive environmental attitudes before dealing with the cognitive 18 domain, lozzi also specified a series of major ideas that educators should refer to in their environmental research endeavors: Major idea 1: Environmental education is effective in teaching positive environmental attitudes and values when programs and methods are designed specifically to accomplish those objectives. Major idea 2: The relationship between environmental knowledge and positive environmental attitudes and values is unclear Major idea 3: Positive environmental attitudes and values, once acquired, appear to be long lasting. Major idea 4: Development of environmental attitudes and values should begin before kindergarten and be further developed and regularly reinforced as a student progresses through elementary, middle / junior high school and senior high school. Major idea 5: Evidence of the relationship between environmental attitudes and age, socioeconomic status, place of residence, and gender is conflicting. Major idea 6: Outdoor education is an effective way of improving environmental attitudes and values. Major idea 7: Various types of teaching methods seem to be effective in improving environmental attitudes and values. Major idea 8: The media are powerful sources for influencing environmental attitudes and values, lozzi therefore concluded that incorporating these ideas into the environmental education curricula may well improve students attitudes toward the environment. 19 Brough (1992) stated that environmental studies is often questioned and sometimes dismissed by the professional educational establishment because it does not fit the mold of a conventional academic discipline. “Connect” (March, 1991) documented that intelligent and effective citizen participation in environmental concerns requires public awareness deepened by knowledge from the sciences, social sciences and humanities. "Connect” added that citizen participation requires the development of attitudes and practical skills which aid people to live in a manner enhancing environmental quality and reducing environmental degradation. Mager (1968) documented that development of positive attitudes toward school subjects is fundamental for three reasons First, attitude seems to be related to achievement and may actually enhance cognitive development. Second, students with a positive attitude toward a subject are more likely to want to extend their learning in that field, both formally and informally, after the direct influence of the teacher has ended. Third, attitude is often communicated to peers in a variety of ways throughout life. Champagne and Klopfer (1984) advocated that before attempting to assess student knowledge in any domain, the major concepts and organizing principles of the knowledge domain should be identified. In a survey of environmental knowledge and environmental attitudes held by the top ten percent and the lowest ten percent of tenth and twelfth grade students in 199 schools of six far Western and five Great Lakes States; Perkes (1973) demonstrated that students with high scores tended to have more positive environmental attitudes than students with low scores. In addition, Eyers (1975) found that students with higher environmental attitude scores, also scored higher in their environmental knowledge. No single study 20 has been conducted in Burundi dealing with environmental knowledge and/ or attitudes toward environmental issues.
Environmental Knowledge, Environmental Attitudes, and Demographic Variables Roth and Batista (1990) found that geographic location, sex, age, place of residence, level of education, socioeconomic status, and occupation often have been important variables included in surveys and baseline research. They recommended that it is important to know how these variables can influence respondents’ attitudes, knowledge, and perceptions of environmental issues. Jacobson and Beaver's (1987) attitudinal study indicated that demographic variables, personal values, contact with the attitude object, and amount of information one has about the object correlate with the attitudes manifested by the subject(s). Kellert and Berry (1984) found that similar attitude orientations occurred within children but with less divergence between the sexes. On the other hand, Karst (1985) revealed that opinions of students were significantly different based upon sex, region of the country, and academic preparation. Karst also found that females had more positive attitudes toward resource conservation than did males. Golden and Hunter (1974) pointed out that gender might be one of the variables which affects environmental attitudes and amount of knowledge. Kellert and Westervelt (1983) demonstrated that young children, in grades two through five ( ages seven to ten ), were the least informed about animals and the most exploitive. From grades five to eight (ages ten to thirteen) 21 children gained a major increase in factual knowledge of animals. Children in the grades eight to eleven ( ages thirteen to sixteen ) became more interested in animals for ecological, moral, and naturalistic reasons. Kellert and Westervelt also found that culture, status, parental occupation and influence, ethnic background, area of residence, scholastic ability, participation in nature activities, books, TV, family, and friends all can possibly affect children’s perceptions of the natural world. Atwater, Sal wen and Anderson (1985), Bowman (1978); Dona (1969); Fortner and Lyon (1985); Ruben et al. (1974); and Sharlin (1985) found a lack of consensus in the environmental literature on the effects of media content, such as news reports concerning topics, on people’s levels of awareness, knowledge, concerns, and subsequent behaviors. Newspapers and television, however, have been found to have some impact on both specific and general environmental knowledge (Ostman and Parker, 1987). Ostman and Parker (1985) found that newspaper readers were more oriented toward print media, whereas television viewers used more radio. Educated people preferred print media as a source for environmental information, but older people preferred television. In a study on students’ knowledge and beliefs concerning environmental issues in the United States, Australia, England, and Israel; mass media, radio, television, and the press were the students’ most important sources of information on environmental issues (Blum, 1987). Hardy and Fox (1976) found a significant relationship between environmental knowledge and environmental attitudes for suburban and inner city children, but not for rural students. 22 Kostka (1976) reported that life experiences, such as environment in which a person grew up, have been found to correlate with environmental attitudes. Kostka also found that inner-city sixth-grade students scored much lower on environmental assessment than did suburban sixth-graders, probably because of a wide array of variables, such as influence of peers and family, other activities, and the physical environment. Van Liere and Dunlap (1980) demonstrated that the level of education was related to information, the greater the amount of education, the greater the amount of environmental information. Those who were active politically also knew more about the environment. On the other hand, Thompson and Gasteigner (1985) examined the environmental attitudes of Cornell University undergraduates in 1971 and 1981 and concluded that the level of education was only a minor influence on defined shifts in attitudinal response. Although the above studies demonstrate various relationships between environmental knowledge, environmental attitudes, and a number of demographic variables; Ladd (1982) reported that people seem to have positive feelings toward the environment, but often do not know much about specific topics or issues. Kernochan (1992) on the other hand, reported that educational campaigns are needed on all levels-whether it is to inform policy-makers, farmers, consumers or students in schools and universities worldwide. Therefore, there is a need to review what the literature tells us about the five issues identified for the purpose of this study ( see page 8) with regard to education, knowledge of and attitudes toward the environment. 23 Education and Human Population Brouse (1990) indicated that human population growth must be included in any meaningful discussion of ecological balance because it contributes to virtually all of the other environmental problems we face today. Air and water pollution, deforestation, acid rain, threats to biodiversity, waste disposal problems, and ozone layer depletion have their roots in human behavior, and are made worse and harder to reverse as human numbers increase. In order to strengthen students' awareness about population education, Brouse also provided three basic guidelines based on the students' hands-on activities: (1) Use hands-on activities that make the abstract concrete and get students actively involved in the learning process. Simulations, games, and group exercises involving problem solving and decision making are excellent techniques for population education. (2) Encourage the expression and consideration of different [joints of view in the classroom. Population and environmental issues are often very complex, and students can be helped to think them through and come to their own conclusions when a variety of view-points are presented. (3) Make students aware that something can be done about population and environmental problems, even when they seem like awfully big problems. Discuss concrete things every individual can do to find solutions.
Agarwal et al. (1982) supported the fact that: To feed increasing numbers of people, developing countries usually attempt to increase farm outputs. However, increased agriculture carries environmental costs. The clearing of large forest tracts and the soil erosion that accompanies intensive agriculture have led to landslides, floods, and the silting of reservoirs needed for electric power. Animal habitats are being endangered as more and more land is turned over to 24 agriculture or gathering of fuel wood. Agricultural pesticides and fertilizers have polluted waters and pose new health problems for agriculture workers. In some environmentally fragile areas, the combination of population growth and drought has turned large areas into virtual desert. Erosion, pollution, loss of species, and loss of land have all resulted from unchecked population growth... A lack of educational opportunities also contributes to high birth rates, as may certain social patterns such as the way property is distributed or inherited, (p. 79)
"Connect” ( March, 1991) maintained that one of the most urgent problems today in environmental education is how to translate and transmit in simple, understandable terms such vital concepts as interdependence, limitation of unrenewable resources, human population growth and energy flow. It was argued that out-of-school environmental education along with formal environmental education might be the solutions since the vast majority of the world's population, youth as well as adult, is outside the formal school system and educational process. Brown et al. (1989) indicated that countries that have made the shift to small families typically have four things in common: (1) an active national population education program, (2) widely available family planning services. (3) incentives for small families (and disincentives for large ones), and (4) widespread improvements in economic and social conditions. He added that any meaningful effort to slow population growth quickly will thus depend on heavy additional investments in the provision of family planning services, improvements in education and health, and financial incentives that encourage couples to have smaller families. Sikes and Kerr (1991) sought a need to change traditional content sources of population education to include population related concepts in the area of human sexuality. They identified the following focuses : respecting 25 others, developing self-esteem, postponing the first pregnancy, understanding that it is possible to plan, fostering responsibility for behavior, and withstanding social pressure. Schuyler (1983) stated that population growth, resource depletion, and environmental stress are all part of one problem. Schuyler then suggested that: ...We must stabilize and eventually reduce population if we are to preserve the carrying capacity of the earth and give ourselves and our children a reasonable quality of life. If we fail to make population stabilization an integral part of the solution, population increase becomes an insurmountable problem. Our renewable resources such as fisheries, forests, and groundwater will be stressed to meet the demands of this increasing population and will no longer be sustainable. Our non-renewable resources of energy and minerals will be so depleted that the economic and environmental costs of extending them will not be acceptable. So if you look at the firmly linked triangle of population growth, resource depletion, environmental stress-all three of which place a strain on the carrying capacity-it is clear that population stabilization is the only action that can result in a long-term sustainable future. Every decade that we delay in reaching a replacement level of fertility will raise the ultimate stable population 10 percent. Environmental educators should be among the leaders in making population policy an integral part of our thinking and planning for the future, (pp. 1-2)
While several nations in the western world and other industrialized countries are concerned with a declining or stagnating population growth due to an overall decrease in fertility per woman, nearly all countries commonly known as Third World, are still struggling with not only bad economic development, but also one of the most undermining factors of any development efforts, that is population overgrowth. No other area of the world experiences this situation with such a strain as Sub-Sahara Africa, especially the East African Sub-Region. As a reminder, the East African Sub-Region includes the following 26 countries: Burundi, Comoro Islands, Djibouti, Ethiopia, Kenya, Madagascar, Malawi, Maurice Islands, Mozambique, Reunion Island, Rwanda, Seychelle Islands, Somalia, Sudan, Tanzania, Uganda, Zambia, and Zimbabwe. It has been shown, for example, that the Burundi population will reach a frightening 8 million by the year 2,000 as a result of demographic momentum created by previous growth rates and the slow motion of family planning policies (PC Globe 1988). In Burundi, the government considers population growth to be unsatisfactory because the rate is too high (3.6 percent per year). It believes over-population has been a destructive force in the country’s development and adversely affects agriculture, employment, health, and education (United Nations Population Funds 1987/1988). The government acknowledges the necessity of integrating demographic variables into development planning and projects to review the rural economy to restructure it in a way that will be more compatible with land and population resources. The1990 Census of Burundi population did not find improvement in population control adoption after several years of implementation of a nationwide program on birth control. It may be therefore, necessary to try a more rational program other than to just expose the population to new methods without knowledge or awareness about new strategies of birth control. Education and dissemination of information may prove useful in public school communities and with the general public in encouraging them to comprehend the problem, and to understand the need and the commitment to change their behavior that will be required with regard to population control. Hungerford and \A>1k (1990 ) stressed empowerment variables as the keys in the training of responsible citizens. These variables give human beings 27 a sense that they can make changes and help resolve important environmental issues. In this regard, Burundi people need to make new techniques of population control theirs, and use them because their well-being in the future will be strongly challenged by unbalanced population growth and sluggish economic development, both highly related to the size of the population.
Education and Natural Reaourcaa In his study on curriculum for the conservation of people and their environment, Brennan (1986) contended that: We are now passing through a period of biological, environmental, and cultural evolution unmatched in the history of the earth. (1) Whole environments have been altered. Consider the destruction of the rain forests the deserts creeping over formerly productive crops, grasslands, and forests the increasing poverty of land and ocean as resources are depleted. (2) living things and societies which have evolved over millions of years stand on the threshold of extinction. (3) Human populations now place infinite demands on the limited resources of planet earth. (4) For the first time in history, people are concerned about the deteriorating quality of their lives. We hear talk of survival, nuclear disaster, of a future in which people will struggle for space in which to live, water fit to drink, food and fuel for bodies and machines-in short for an environment fit for life and living... (p. 2)
Birch and Schwab (1983) indicated that water education programs are effective in developing students' knowledge and positive attitudes concerning water conservation, as well as establishing a water use ethic that permanently improves their water-using habits as adults. Southern (1967) revealed that twelve environmental understandings could be suitable in designing a natural resources education framework: 1 Natural resources are everything man uses; they are in constant redefinition. 28 2. Man is dependent on renewable resources for his survival. 3. Our industrial civilization depends on nonrenewable resources such as metals and fossil fuels. 4. Living things are interdependent with each other and the physical environment. 5. Man, as all other living things, is subject to the laws of nature. 6. Change is a fact of the environment, it is dynamic and inevitable. 7. The pressures of population and urbanization accelerate and increase resource use. 8. The amount and the rate of resource use are determined by the economy. 9. Environmental quality cannot always be easily defined in economic terms. 10. Man has learned to use his environment wisely in a number of ways. 11 Government is active in the discovery, development, management, and protection of resources. 12. Everyone has the responsibility for conserving the resources around him. Roth (1969) conducted a study to determine concepts that are fundamental to environmental management education and natural resources management (K-16). He identified a list of 111 concepts related to 13 areas: environmental management, economics, natural resources, environmental ecology, management techniques, adaptation and evolution, socio-cultural environment, culture, politics, environmental problems, the individual, the family, and psychological aspects. With regard to Roth’s environmental management education concepts, five understandings are essential to resource management education: 1. Living things are interdependent with one another and their environment. 2. Humans have been a factor affecting plant and animal succession and 29 environmental processes. 3. The management of natural resources to meet the needs of successive generations demands long range planning. 4. Safe waste disposal, including the reduction of harmful and cumulative effects of various solids, liquids, gases, radioactive wastes, and heat is important if the well-being of man and the environment is to be preserved. 5. Environmental management involves the application of knowledge from many different disciplines. On the other hand, in their advocacy of what every 17-year old should know about Planet Earth, Mayer and Armstrong (1992) produced a list of 10 basic concepts deemed to be essential for Earth Science Education and highly related to resource management education: 1. The earth system is a small part of a solar system within the vast universe. 2. The earth system is comprised of the interacting subsystems of water, land, ice, air, life. 3. The earth’s subsystems (water, land, ice, air and life) are continuously evolving changing and interacting through natural processes and cycles. 4. The earth's natural processes take place over periods of time from billions of years to fractions of seconds. 5. Many parts of the earth s subsystems (fossil fuels, minerals, fresh water, soils, flora and fauna) are limited and vulnerable to overuse, misuse, or change resulting from human activity. 6. The better we understand the subsystems, the better we can manage our resources. Humans use Earth resources such as minerals and water. 7. Human activities, both conscious and inadvertent, impact Earth subsystems. 8. A better understanding of the subsystems stimulates greater aesthetic 30 appreciation. 9. The development of technology has increased and will continue to increase our ability to understand Earth. 10. Earth system scientists are people who study the origin, processes, and evolution of Earth’s subsystems; they use their specialized understanding to identify resources and estimate the likelihood of future events. Mayer and Armstrong concluded that science educators are challenged to incorporate an understanding of students and how they come to investigate the Earth into planning future curriculum and teaching. Walter and Reisner (1990) suggested that discussion of issues, ethics, and values in agricultural courses and curricula can help students increase their conservation knowledge and integrate it with their own values. Heslop et al. (1981) found that a given level of energy consumption was directly related to an individual's knowledge of energy conservation activities. Morrisey and Barrow s (1988 /89) synthesis of energy education literature revealed that educators generally agreed with the need for including energy education as a part of every public school student’s education and that the best vehicle for promoting energy literacy would be the existing school curriculum. Pemberton (1989) indicated that the earth’s resources that sustain people and their economic systems are fragile and limited He concluded that ensuring wise use of these resources requires an educated and informed citizenry. Schicker’s (1988) comparison of child and adult wildlife knowledge and interest in lower forms of animals showed that these attributes changed over the years, and such knowledge was found to be extremely interesting and important to children, but almost never mentioned by adults. The latter define and recognize wildlife primarily as birds and mammals. Children were also very 31 interested in the conditions of their outdoor environments. They expressed strong opinions and ideas about how their neighborhoods and school grounds should look, and they exhibited strong tendencies toward taking active roles in environmental form and change. Schicker (1986) also found that natural history courses appeared to be influential in improving knowledge, attitudes, and interest in wildlife, as well as in reducing children's fears of certain animals, mainly snakes and other reptiles. George (1966) reported a study designed to determine whether knowledge and understanding resulted in more favorable attitudes toward conservation. A Likert-type attitude scale related to conservation was used to make 1618 observations, representing three different age and educational levels: (1) high school students, (2) college students, (3) adults. He found significant differences in attitudes among the three groups as indicated by a comparison of the total mean scores. The high school students had a mean score of 185.08, while the college students had a mean score of 191.32 and the adults, 196.93. Age and education were associated with the most significant differences in attitudes of the high school students. The most significant characteristics in the college student group were age and sex, while sex and residency background were significant for the adults. He also found that attitudes toward conservation did change, that the changes were associated with interest motivation, and exposure to conservation knowledge, and that significant attitude change could be identified and associated with the special conservation education experience designed for each of the groups. Jacobson (1991) used a comprehensive approach based on an education evaluation model to develop, implement, and assess educational programs for four specific Kinabalu park audiences in Malaysia: general park 32 visitors, school groups, local villagers, and the public reached by mass media. The programs, including an interpretive natural trail, a school biology program, a mobile extension program, and a newspaper series, were implemented and assessed. The results demonstrated that all the programs were successful in increasing environmental knowledge or fostering favorable attitude shifts toward the park system and conservation. In Burundi, some efforts to cope with natural resources depletion have been observed (Le Renouveau no 3557, du Mercredi 31 Juillet 1991): (1) About 100,000 ha. of forests and natural preserves were protected, (2) 80,000 ha. of high lands was reforested, (3) agroforestry was encouraged, (4) public environmental awareness and international cooperation were suggested, and (5) a call for public involvement in the resolution of environmental problems and / or issues was formulated. However, very little effort has been devoted to environmental education in general, and to natural resources education in particular.
Education and Water Quality Miller (1988 ) defined pollution as any change in the physical, chemical, or biological characteristics of the air, water, or soil that can affect the health, survival or activities of humans or other forms of life in an undesirable way Strandberg (1972) reported that The American Medical Association has cited eight consequences of water pollution : (1) disease transmission through infection, (2) poisoning of man and animals, (3) detrimental effects on aquatic life, (4) creation of objectionable odors and unsightliness, (5) cause of unsatisfactory quality of treated water, (6) impairment of shellfish culture, (7) excess mineralization, and (8) destruction of aesthetic value. In his study on 33 aquatic education curriculum need, Rakow {1983 / 84) indicated that people have begun to realize that the oceans are not a limitless sink for the dumping of wastes. He also maintained that the role of water in living organisms as well as the plants and animals that live in water, have been topics included most often in ecology units and biology courses. As a consequence of water resources education, Rakow pointed out that attitudes about water addresses the values held toward water resources issues such as the perceived importance of protecting water supplies, and the willingness to make lifestyle changes to help solve the problems of water pollution and overuse.
In a study of understanding of pollution among 4th, 8th, and 11th grade students. Brody (1990-1991) stated that knowledge of students’ understanding of pollution can help educators construct a variety of meaningful classroom experiences concerning pollution topics, including solid and toxic waste and air, soil, and water pollution. Blum (1979) compared water pollution curriculum units from four secondary school science programs in Britain, Germany, Israel, and the United States. He found an evident dissimilarity in central topic selection, the use of laboratory, learning media, controversial issues, and teacher-student roles. Ryan (1992) reported that while Lake Tanganyika (in Burundi) has been overfished in places, its most serious problem may be sedimentation. The sedimentation results from northern portion of its watershed having been largely deforested. He added that because tropical lakes hold less oxygen than those in colder climates, oxgyen-consuming pollution is even more of a problem in warmer waters. Worse, since deep lakes like Tanganyika take centuries to flush 34 themselves out, they are easily susceptible to long-lasting damage from levels of pollution that other water bodies could handle. Ryan also reported that the Global Environmental Facility or Green Fund is about to fund ecological research, expansion of protected areas, environmental education, and development of economic alternatives to destructive fishing in Lake Tanganyika. In addition, waste disposal into Lake Tanganyika from industries, municipal and household activities constitute imminent threats to public health and challenges for aquatic life survival in Burundi. Land erosion and stream n utrient loading greatly contribute to eutrophication of the Lake and subsequent fish kills. Education and Ecological Principles Orr (1990) defined ecological literacy as a broad understanding of how people and societies relate to one another and to the natural systems, and how they might do so sustainably. It presumes both an awareness of the interrelatedness of life and the knowledge of how the world works as a physical system. In a study on the implications of attitude and behavior research for environmental conservation; Newhouse (1990) stated: ...based on the available knowledge about attitudes and behavior, how should conservationists who are interested in promoting environmentally responsible behavior design educational programs? Although there is no easy answer to this question, some general guidelines can be offered. First, the program must be appropriate for the level of knowledge, attitude, and moral development of the individual ...One of the central components must be information-information about how ecosystems naturally function and the problems that are threatening the well-being of ail life. Coupled with this should be information about action strategies, which may be best transmitted through the use of a respected role model. Such information should explain both sides of environmental issues, encourage people toward direct contact with the natural environment, and stimulate a sense of responsibility and personal control, (p. 31) 35 Using case study data, Paul and Gill (1989) determined high school pupils' and university students’ (n = 162) ability to predict possible outcomes of interactions between ecological populations. Results indicated that the majority of respondents could predict interactive outcomes within a simple food web but not when the interaction involved multiple routes. Gerri (1991) evaluated natural resource education materials for the elementary level to determine their emphasis on educational goals. The majority of materials addressed basic knowledge of ecological principles, with minimum coverage of resource management issues. Disinger and Lisowski (1991) conducted a study focussing on students' conceptions of ecological concepts clustered in eight categories: (1) plant and animal characteristics, (2) plant and animal classification, (3) plant and animal habitats, (4) food chains, (5) food webs, (6) energy transfer, (7) energy pyramids, (8) and nutrient cycles. The influence of field instruction strategies on students’ understanding of the above concepts was statistically significant and showed evidence of students’ retention of the targeted concepts. Buethe (1987), in his study on environmental literacy of Indiana teachers, found that for a period of ten years (1975-1985), these teachers, did not much improve their knowledge of environmental issues related to ecology. His findings tell us that if teachers are not intellectually equipped to deal with environmental problems and/or issues, their students will not acquire the competence and the skills they need to act responsibly in resolving environmental problems. In Leslie’s (1987) study on cultural ecology and environmental education it was revealed that resource depletion, environmental degradation, and related problems are not simply the results of technology and economy. Leslie 36 demonstrated that the underlying cause is the collective behavior of individuals in society, behavior that is predominantly cultural. Cultural ecology was found to be a potential contributor to environmental science and education as well as to the solution of environmental problems by providing concrete case studies that demonstrate the importance of the culture on human environmental interactions and environmental problems.
Education and Environmental Global C oncerns Berne (1986) recognized that when students get involved in regional issues and investigate real-life situations in surrounding areas, " learning becomes meaningful, because it is needed by them.” He added that:
... by examining their own surroundings in depth and then comparing their area to another, both teachers and students learn to understand relationships, develop historical perspectives, and begin to infer trends. They learn to use their own communities as microcosms of principles that are valid at a global level, (pp. 432-433)
Marion et al. (1988-89) reported that acid precipitation has been recognized as a hazard for many years. The European Atmospheric Network, established in the 1950s, first produced data on the acidification of Europe’s precipitation. However, wide-scale monitoring and research did not commence in the United States and Canada until the mid-1970s. Hepburn and Hepburn (1985) revealed that in the 1970s many scientists in Canada and the United States agreed that increased acidity of the lakes resulted when the quantities of sulfur and nitrogen compounds in the air become acidic when mixed with water in the wet deposits of rain, snow, or fog. The coal-burning power plants, factories, and ore smelters were 37 determined to be the main sources of the problem. The authors maintained that as acid rain increases, fish and trees are affected, and regional economies based on recreation, sport-fishing, and tourism suffer As a result of increasing public concern about acid rain deposition, the National Film Board of Canada (1982) released an educational film, “Acid Rain: Requiem or Recovery?" The purpose of the film was to increase public awareness of the threat to the North American environment posed by acid rain-destroying woods, water, and wildlife. Graphs, maps, and scientific experiments were used to examine what acid rain is, where it originates, and how it threatens natural life and man-made environments. Brody et al. (1988-89) assessed the level of scientific and natural resource knowledge that fourth, eighth, and eleventh-grade students in Maine possessed concerning acid deposition. A representative sample of public school students (N = 175 ) was interviewed on twelve concept principles considered critical to a full understanding of the acidic deposition problem. These included geological, meteorological, ecological, political, and economic concepts. The content principles used in the study were the following: 1. Geological processes include sedimentary and igneous processes that produce, among other things: sedimentary rocks, such as limestone; fossil fuel beds, such as coal and petroleum; volcanoes; and intrusive igneous rocks, such as granite. 2. Acid precipitation affects the way various rock types are weathered. Soils produced from sedimentary rocks tend to act as a buffer against the effects of acid precipitation; soils produced from igneous rocks have little buffering capacity, allowing acidic waters to leach essential plant nutrients from the soil and also to liberate metals and toxins from the soils. 38 3. The products of combustion of fossil fuels, and to some extent volcanism, contribute sulfuric and nitric oxides and dust to the atmosphere. These elements contribute to the production of acidic precipitation. 4. Chemical pollutants and water combine in the atmosphere as a result of reaction triggered by the sun. 5. Weather patterns and wind currents result from differences in heat in the atmosphere and the earth's rotation and result in the transportation of chemical pollutants. 6. Ecology is the study of aquatic and terrestrial ecosystems, including living and non living components. 7. Living components include producers, consumers, and decomposers combining to create a food web. 8. The system can be altered by increased acidity, which can affect growth, reproduction, respiration, and may indirectly cause death. 9. Industries that consumes natural resources to produce materials for profit may use processes that contribute to acid deposition. 10. Acid deposition affects natural resource utilization in recreation and agriculture. 11. Acid deposition occurs within a political system based on local, regional, and global concerns. 12. Conflicts may arise over acid deposition, possibly leading to confrontation, negotiation, and/or arbitration; treaties, regulation, and/or legislation to solve the conflicts may result. Student knowledge was rated for each concept principle as high partial, low partial, or no understanding. Common misconceptions were also noted. The findings led the authors to admit that their conclusions have implications for 39 teaching about acidic deposition and the design of environmental education curriculum materials based on student knowledge. Postel (1989), in her call for halting land degradation referred to desertification as the impoverishment of the land by human activities. The four principal causes of desertification or land degradation were reported as being: (1) overgrazing on rangelands, (2) overcultivation of croplands, (3) waterlogging and salinization of irrigated lands, and (4) deforestation. All the above stem from excessive human pressures or poor management of the land. Therefore, since today's school prepares decision-makers for tomorrow, school curricula at all levels ought to address the above problems as more and more countries around the world are being challenged by food shortages, economic disasters, and famine, all resulting from galloping deserts and land exhaustion. Jager (1986) noted that global warming is caused by an increase in greenhouse gases in the atmosphere, especially carbon dioxide and nitrous oxide, the result of increased carbon dioxide emissions from fossil fuel combustion,deforestation, and land use changes. He added that carbon dioxide levels could double due to projected increases in combustion of fossil fuels to meet increasing world energy demand. Ruben et al. (1991) maintained that the potential for man-made emissions of carbon dioxide (C02), Chlorofluorocarbons (CFCs), methane (CH4), nitrous oxide (N02), and other greenhouse gases to alter the earth’s climate have gained widespread attention in recent years. They revealed that international concern has been spurred by predictions that a doubling of atmospheric C02 concentrations could produce a
1° to 5° C increase in average global temperature by the middle of the next 40
century. The authors reported th a t: (1) the fear of significant climate change
impacts, includes rising sea levels, altered precipitation patterns, increased storm frequency, and damage to natural ecosystems, has led policy- makers in Europe and elsewhere to call for immediate action to stabilize or reduce the growing in greenhouse gas emissions; (2) the U.S. government, however, has argued that current scientific understanding of global climate change is still too crude and uncertain to warrant such programs, which it believes could severely damage the economy...( p. 148). In Burundi, le Renouveau no. 3558 pointed out that on a global scale, each country in the World contributes to ozone depletion and the greenhouse effect, and therefore to global climate change. The newspaper added that Burundi is playing a minor but a significant contribution to globa1 climate change given its dominant traditional agriculture, based mostly on slash and burn practices and forest clearing. The fire wood and charcoal production which constitute the main sources of energy in Burundi also contribute to the generation of greenhouse gases. According to Service des Presses et Publications (1985), Lake Tanganyika (in Burundi) has been overexploited for fish supply since 1946, but its other major problem, besides sedimentation, stems from its contamination by chemicals from pesticides and fertilizers improperly applied on cotton and coffee crops near its shores. The use of DDT for pest control weighs heavily on public health and aquatic life safety. All the environmental problems and / or issues included in the present study had been recognized by Dunlap, Gallup and Gallup (1992) as major challenges to the environment in many countries around the world; rich and 41 poor nations as well. On the other hand. Keating (1993) stated that to improve sustainable development education, nations should seek to: 1. Make environment and development education available to people of all ages. 2. Work environment and development concepts including of population, into all educational programs, with analyses of the causes of the major issues. There should be a special emphasis on training decision makers. 3. involve schoolchildren in local and regional studies on environmental health, including safe drinking water, sanitation, food and the environment and economic impacts of resource use. As stated in the previous sections, the present study will stress the most challenging environmental issues and/or problems in Burundi (see pagel), assess what thirteenth grade General and Technical Education students know and how they feel about environmental concerns, and thus produce baseline data on which further research and future programs can proceed. CHAPTER III PROCEDURES
With regard to the purpose and objectives of the study, this chapter is divided into the following sections: * Research design * Validity determination * Reliability determination * Population and sampling * Conditions of testing * Data analysis
Research Design Based on the information obtained from prior research studies about environmental knowledge and attitudes as reported in the previous sections of this study, this research is designed as a descriptive correlational study. To test student knowledge and student attitudes toward the environment in selected high schools in the Perimian Basin Region of Texas. Sammy (1991) used the " Environmental knowledge and Attitude Inventory" with measures of validity and reliability established by Perkes (1973). Several environmental fact and attitude items were updated. Additionally, Sammy's study is based on Hardy and Fox’s (1976) study of student environmental attitudes and knowledge. On the other hand, in a survey of environmental knowledge and 42 43 attitudes of tenth and twelfth grade students from five Great Lakes and six Far Western States, Perkes (1973) used an inventory developed by the ERIC Clearinghouse for Science, Mathematics, and Environmental Education and the Center for Science and Mathematics Education at The Ohio State University and selected consultants. As Castillo and Ham (1990) advocated (see page 5 ), U.S. environmental education models and materials may be based on assumptions about U.S. schools that do not hold in developing countries such as Burundi. As a result, the present research used three researcher developed instruments to collect the data: (1) an achievement test instrument designed to measure students’ environmental knowledge, (2) an attitudinal instrument designed to measure students’ attitudes toward the environment, and (3) a demographic instrument designed to measure students' demographic characteristics ( see Appendix A). The knowledge instrument is a 25 item self-administered multiple-choice achievement test which allowed respondents to check the answers that apply. One choice was allowed for each item and the scores were “ 1 ” for a correct answer and " 0 ” for an incorrect response. The attitudinal instrument utilized a Likert scale of 25 items that let subjects indicate their responses to selected statements on a continuum from Strongly Disagree,l 1 ” to Strongly Agree “ 5 ” for each statement. An individual’s score was determined by summing the point values for each statement. The following point values were assigned to responses on positive statements: Strongly Agree = 5; Agree = 4; Neutral = 3; Disagree = 2; Strongly Disagree = 1. For negative statements, the point values are reversed; that is SA - 1, A = 2, and so on. The demographic instrument is an eight item self-ad ministered multiple 44 choice instrument which allowed respondents to check the answers that apply to their specific and individual characteristics. Items were distributed according to environmental issues of interest as displayed in Table 1.
Table 1 Distribution of Items According to Environmental Issues
Environmental Environmental Environmental Subscales Knowledge Attitudes (Item number) { Item number)
Human Population 1 2 3 4 5 1 2 3 4 5 Water Quality 6 7 8 9 10 11 12 13 14 15 Natural Resources 11 12 13 14 15 6 7 8 9 10 Ecology 16 17 18 19 20 16 17 18 19 20 Global Issues 21 22 23 24 25 21 22 23 24 25
Data collection with students was conducted by the researcher and two trained interviewers through interviews (face-to-face) and self-administered questionnaires (respondents’ written responses). However, respondents were reluctant to participate in the interview schedules section because of the lack of confidence in the quality of their answers and the tape recording used to collect data. Since this phenomenon was observed in more than two thirds of the participating schools, the corresponding section was removed from the study. 45 Validity Determination Gay (1992) admits that the most simplistic definition of validity is that it is the degree to which a test measures what it is supposed to measure. He argues that a common misconception is that a test is, or is not, valid. A test is not valid or invalid, it is valid for a particular purpose and for a particular group. To respond to the above contention, the knowledge and the attitude instruments’ validity were determined in the United States and in Burundi. The instrument validity was reviewed using a panel of experts in the United States, and a panel of experts and a field test in Burundi. The panel of experts in the United States included four advisory committee members and three other experts: two experts in sampling and environmental content, and one expert in measurement. In Burundi, the panel of experts included five secondary school curriculum developers: one expert in Biology, two experts in Chemistry, one expert in Geography, and one expert in Agriculture Education. According to practice advocated by Norland (1992), the field test involved two samples of randomly selected students (20 for each school category) from the target population. The two panels of experts and the two groups of respondents on the field test suggested a series of changes about the content and the structure of the instruments. These changes were made based on the panel of experts and the field test results (see Appendix C). It was anticipated that if non-responses occurred during the data collection phase, they would be handled by either following up a sample of non-respondents by face-to-face interviews, or by randomly selecting a sample of non-respondents, getting their responses, and statistically comparing those answers to those of the respondents on known characteristics. Fortunately, no 46 one student failed to answer to the whole instrument. In some schools some students did not respond to one or another item. The item non-response rate ranges from 11(0.11%) to 126 (1.23 %) for the knowledge instrument and from two { 0.05% ) to 11(0.3% ) for the attitudes instrument. These item non-response rates are too low to justify any additional research activity.
Reliability Determination The instruments’ reliabilities were established with data obtained from a pilot test involving two samples of randomly selected students (20 for each school category). In addition, since summated instruments had to be used in the study, the measurement of item internal consistency using Cronbach’s Alpha was used to supplement the test-retest reliability check accomplished through the pilot test for the knowledge and attitude instruments. However, the second test was not administered because of the political instability in Burundi during the short period (about two weeks) suggested as being necessary to elapse between the administration of the two tests. Therefore, the data from the administration of one test was used. Gay (1992) and Norland (1992) admit that the method of rational equivalence reliability is not established through correlation, but rather estimates internal consistency by determining how all items on a test relate to all other items and to the total test. The rational equivalence reliability is determined through application of one of the Kuder-Richardson formulae, usually formulae 20 or 21 (KR20 or KR21). Both formulas require that each item be scored dichotomously. If items are scored such that different answers are worth different numbers of points, then Cronbach’s Alpha can be used. 47 Using KR20 for the knowledge instrument and Cronbach's Alpha for the attitudes instrument (item 20 deleted), the rational equivalence reliability was 0,63 and 0.61, respectively. However the item 20 was considered for further analysis because the information it holds could not be obtained from any of the other items on the attitude instrument. Although the reliability coefficients found are low, Kuhn et al. (1989) concluded that a score of 0.40 or greater is generally considered to be an acceptable level of reliability. On the other hand, Gay (1992) reported that when tests are developed in new areas, which was the case for the present study instruments, one usually has to settle for lower reliability, at least initially
Population and Sampling Thirteenth grade General and Technical Education students are identified as the target population for this study Their selection is based on Burundi high school curriculum guidelines (1989 /1990) in the disciplines of Biology, Chemistry, Agriculture, and Geography At the thirteenth grade level, students are about to graduate from High School and have been exposed to some environmental issues through their instruction in the aforementioned disciplines. The target population was about 2,000 students. However, because it would be very time consuming and expensive to collect data from the entire target population, data were collected using a multistage sampling technique: According to Fowler (1988): If one wanted to draw a sample of all students enrolled in the public schools of a particular city.. .since every individual in the study population can be attached to one and only one of those units, a perfectly acceptable sample of students can be selected using a two-stage strategy, first selecting schools, and then selecting students 48 from within those schools, (p. 27)
In this study, participating schools were randomly selected and all the students at grade level thirteen in selected schools participated in the data collection phase. However, if the school had an enrollment of more than 25 students at the thirteenth grade level, a random selection of students was performed in order to keep the class sample size closer to the average class size of 20 students. The Fowler s formula was used: Probability Probability Overall of selection x of selection = probability at stage I at stage II of selection There are 28 General Education schools having the thirteenth grade level and 30 technical education schools having the thirteenth grade level (Appendix E). Given the following data: about 2,000 students; fifty eight General and Technical Education schools having the thirteenth grade level; (desired sample = 1,000 =1/2 students [ The Fowler’s formula was applied] 58 /2 x 1/1 = 29 schools for both types of schools). Since the upper high school class size in Burundi averages 20 students per class, 580 students were needed to participate in the study (290 for each school category). As specified in the Chapter 1, because of the political instability in the country during the data collection period, the sample sizes for both the General and the Technical Education were not reached in the desired proportion (50 % for each school category ). Twenty eight schools ( 97 % ) participated in the data collection instead of the 29 schools planned. Of the 28 schools, 20 (71.4 % ) were General Education schools with an overall sample size of 49 411 students(73.5 %). Only eight Technical Education schools (28.6 %) participated in the data collection with an overall sample size of 148 students (26.5 % ). In order to ensure the validity and the reliability of the data, students who had participated in pilot or field testing were excluded from the data collection phase.
Conditions of Testing Prior to the data collection phase, the researcher sent a letter to the Minister of Primary and Secondary School (see Appendix D) requesting authorization to use thirteenth grade General and Technical Education students as data sources The letter was written in French because French is the official and main instructional language in Burundi. A complete list of all the participating schools is available and was obtained from the Ministry of Primary and Secondary School at Bujumbura, the capital of Burundi. In addition, in the attempt to increase the response rate and facilitate communication between researcher, interviewers, and respondents, the translation of the instrument items and directions from English to French was performed by the researcher and a panel of five language specialists in Burundi. Since the study was conducted using students who are different from other Burundi social groups in terms of academic preparation and cultural change, results are not generalized beyond the target population (all the thirteenth grade general and technical education students). The researcher spent six months (Summer and Autumn, 1993) engaged in the training of interviewers, review of literature, instrument verification, instrument validation, and data collection in Burundi 50 Data Analysts With regard to the nature of research questions, objectives and/or associated statistical hypotheses formulated, researchers have used several different descriptive and inferential statistics in order to describe and generalize their findings as in: Perkes (1973); Fortner and Mayer (1983); Ostman and Parker (1987); Roth and Perez (1989);Sammy (1991) etc. In this regard, data obtained through the use of the above mentioned instruments allowed the researcher to assign points to the various responses and compute frequencies, percentages, and measures of central tendency in order to describe the samples. Correlation coefficients were computed to show possible associations or relationships between variables. To investigate whether or not any significant difference existed between environmental knowledge levels or attitudes towards the environment held by the two categories of respondents, a t-test was performed using the scores on the knowledge and attitude items respectively. Analysis of variance (ANOVA) was computed in order to analyze the variability of the differences in knowledge or attitudes of students possessing different demographic characteristics (age, gender, residential location, source of environmental education, school category, parents’ occupation and level of education). Table 2 summarizes the descriptive and inferential statistics used in the present research. 51
Table 2 Descriptive and Inferential Statistics
Objective Descriptive Inferential Statistics Statistics
Objective #1 Mean / Median t-test Standard deviation Range Frequencies Percentages
Objective #2 Same t-test
Objective #3 Pearson r Test Rho = 0
Objectives #4 ANOVA and #5
Note: The Statistical Analysis System (SAS) at the Ohio State University was utilized for the analyses of data. CHAPTER IV ANALYSIS OF RESULTS This chapter aims at describing and interpreting data obtained from an overall sample of 559 respondents to knowledge, attitudinal, and demographic instruments used in this study. Subjects were divided into two sub-samples (411 students) for General Education and (and 148 students) for Technical Education. In addition, the knowledge and the attitude instruments were divided into five sub-categories of five items each, corresponding to each of the five environmental issues and/or problems specified in the previous chapters. Descriptive statistics were used to describe, summarize, and reduce data to manageable forms. Inferential statistics were used to make inferences from the two data subsamples to the population of thirteenth grade seniors in Burundi. The tasks performed were the description of respondents’ background information, and the analysis of the results with regard to the five objectives of the study specified in Chapter I (p 9-10).
Respondents’ Background Information All the respondents were asked to answer a series of seven questions pertaining to background information (See Appendix A). These demographics, or independent variables, referred to the subjects' age categories, gender, school category, residential location, source of environmental information, 52 53 parents’ occupation and level of education. All eight items have been answered. Age The status of age categories distribution of respondents for the two types of schools is shown in Table 3. For General Education, 27 percent of the students are 18 to 20 years old, 54.3 percent are 21 to 22 years old, and 18.7 percent are 23 to 25 years old. For Technical Education, 25 percent of the respondents are 18 to 20 years old, 53.4 percent are 21 to 22 years old, and 21.6 percent are 23 to 25 years old.
Table 3 Frequency Distribution of Respondents’ Aae
Age General Education Technical Education f % f % 18 to 20 111 27.0 37 25.0 21 to 22 223 54.3 79 53.4 23 to 25 77 18.7 32 21.6
Total 411 100.0 48 100.0
It was discovered that the age category of 21 to 22 had the highest percentage of participation for both General and Technical Education. The lowest percentage of participation was observed for the category of 23 to 25 years of age for both the General and the Technical Education samples. 54 Gender Table 4 reveals that for General Education, 62.8 percent of the students were males and 37 2 percent were females. For Technical Education, 72.3 percent of the students were males and 27.7 percent were females. There were more male respondents than female respondents for both school categories.
Table 4 Frequency Distribution of Respondents’ Gender
Gender General Education Technical Education f % f % Male 258 628 107 78.3 Female 153 37.2 41 27.7
Total 411 100.0 148 100.0
Maior Table 5 reports the frequency distribution of students by major. It was found that of the 411 students attending General Education, 63.7% majored in science, and 36.3 majored in humanities. For Technical Education, all the students majored in professional fields such as business, administration, teacher training schools, agriculture education, and medical schools. 55 Table 5 Frequency Distribution of Respondents' Maior
Major General Education Technical Education f % f %
Science 262 63.7 — —
Humanities 149 36.3 ——
Professional -- — 148 100
Total 411 100.0 148 100
Residential Location Among the 411 respondents for General Education, 16.1% resided in cities, 72% resided in rural areas, but not on a farm, 7.1% lived on a farm, and only 4.9% lived in suburbs. For Technical Education, 23.6% resided in cities, 8.1% resided in suburbs, 54.7% lived in rural areas, but not on a farm, and 13.5% lived on a farm in rural areas (See Table 6). For both school categories, more than 50% of the respondents lived in rural areas, whereas an average of 20% lived in cities. It is surprising that an average of only 7% of the respondents resided in suburbs. Since the suburban areas have more residents than city areas, they were expected to have more students enrolled in High School. 56
Table 6
Frequency Distribution of Respondents' Residential Location
Residential Location General Education Technical Education f % f % City 66 16.1 35 23.6 Suburban 20 4.9 12 8.1 Rural (not on a farm) 296 72.0 81 54.7 Rural (on a farm) 29 7.1 20 13.5
Total 411 100.0 148 100.0
School Geographic Location Five school geographic locations are represented in this study. For General Education, 24.3% of the schools are located in Bututsi, 2.7% in Buragane, 17.3% in Buyenzi, 26% in Imbo, and 29.7% of the schools are located in Mugamba. For Technical Education, 27% of the schools are located in Buragane, 12.2% in Buyenzi, and 60.8% of the schools are located in Imbo Natural Region (See Table 7). No technical school is located either in the Bututsi or Mugamba natural regions. This can be understood when one considers that Roman Catholic missionaries who were in charge of most technical schools until early in the 1960s in Burundi showed a lack of interest in those two regions. 57
Table 7
Frequency Distribution of Respondents1 School Geographic Location
School Geographic General Education Technical Education Location f % f %
Bututsi 100 24.3 — — Buragane 11 2.7 40 27.0 Buyenzi 71 17.3 18 12.2 Imbo 107 26.0 90 60.8
Mugamba 122 29.7 — --
Total 411 100.0 148 100.0
Maior Source of Information about the Environment The major sources of environmental information of General and Technical Education respondents are shown in Table 8. For General Education, 13.4% of the respondents reported books as their major sources of environmental information, 57.7% had classroom instruction as their major source of information about the environment. 22.4% reported radio and television as the best sources, 4.9% did not specify their sources of environmental information, and very few respondents (1.7%) cited their parents as major sources of environmental information. For Technical Education, 22.3%, 38.5%, 30.4%, 2.0%, and 6.8% of the respondents reported books, classroom instruction, radio or television, unspecified sources, and parents as their major sources of environmental 58 information, respectively. Classroom instruction was the most reported source of environmental information in both samples, and parents were the least mentioned sources. Radio or TV ranked higher than books.
Table 8 Frequency Distribution of Respondents' Maior Source of Environmental Information
Source General Education Technical Education f % f % Books 55 13.4 33 22 3 Classroom Instruction 237 57.7 57 38.5 Radio or Television 92 22.4 45 30.4 Parents 7 1.7 10 6.8 Other 20 4.9 3 2.0
Total 411 100.0 148 100.0
Parents1 Occupation With regard to the respondents' parents’ occupation, General Education students reported their parents as government officials (3.9%), government servants (30.2%), farmers (43.6%), and unspecified occupation (22.4%). For Technical Education, respondents' parents' occupation was reported as being 9.5% government officials. 25.7% government servants, 49 3% farmers, and 15.5% unspecified occupation. These data are summarized in Table 9. 59
Table 9
Frequency Distribution of Respondents' Parents’ Occupation
Occupation General Education Technical Education f % f % Government Officials 16 3.9 14 9.5 Government Servants 124 30.2 38 25.7 Farmers 179 43.6 73 49.3 Other 92 22.4 23 15.5
Total 411 100.0 148 100.0
Farmer subcategory included the highest percentage of respondent parents’ occupation, followed by government servants and unspecified occupation. Very few parents were found to be government officials.
Parents' Highest Degree Table 10 displays the frequency distribution of the respondents’ parents’ highest degree. For General Education, 45.5% of the parents had Elementary School as their highest degree, 22.9% had some high school experience, 13.9% had some college experience, 17.8% of the respondents did not specify their parents degrees. For Technical Education, 51.4% of the parents had some elementary school as their highest degrees, 21.6% some high school degrees, 13.5% some college degrees, and 13.5% did not report their parents’ highest degrees. 60
Table 10
Frequency Distribution of Respondents' Parents Highest Degree
Degree General Education Technical Education f % f % Elementary School 187 45.5 76 51.4 High School 94 22.9 32 21.6 College 57 13.9 20 13.5 Other 73 17.8 20 13.5
Total 411 100.0 148 100.0
Elementary School parents formed the biggest subgroup, whereas college parents and unspecified degrees constituted the smallest categories, respectively. 61 Analysis of the Results by Objectives The data gathered for this study were analyzed using the Statistical Analysis System (SAS) at the Ohio State University. The SAS System is an integrated system of software providing complete control over data access, management, analysis, and interpretation. Frequencies, percentages, measures of central tendency, measures of dispersion, measures of associations or relationships, t-tests, and analysis of variance (ANOVA) were performed with regard to each objective and associated null hypothesis. An alpha level of 0.05 was used to test for the significance of the differences between different respondent groups and for examining the level of significance of the differences between the demographic variables (independent variables) in explaining the respondents’ environmental knowledge and attitudes variables (dependent variables). The analysis targeted the overall group responses and school category responses with regard to the five environmental issues and /or problems specified in previous chapters.
Data Analysis for Objective 1
Objective 1: To assess and compare the levels of environmental knowledge held by two selected samples of thirteenth grade General and Technical Education students in the Republic of Burundi.
Table 11 summarizes respondents’ mean knowledge score on the overall sample and the the school category mean scores. Table 12 displays frequencies of responses (as percent) to each environmental knowledge alternative. 62 The total knowledge score was calculated as the average knowledge mean score of items answered correctly. One point value was awarded to each correct answer, an incorrect answer was scored zero. The average score on the overall knowledge instrument was 47% answers correct (mean = 11.65; SD =2.36). When considering respondents' environmental knowledge levels by school categories, Genera) Education participants scored higher than Technical Education respondents (see Table 11).
Table 11 Summary of Score Statistics on Environmental Knowledge Items
School category n Mean* SD Min Max
General Education 411 11.81 242 5 21 Technical Education 148 11.18 2.10 6 19 Overall 559 11.65 2.36 5 21
Note: * 25 possible points. 63
Table 12 Frequency of Responses (as Percent) to Each Alternative on
Environmental Knowledge Items
Alternative (%) Item n A B C D
1 526 14.6 17.7 34.8 32.9* 2 559 2.5 3.0 84 4* 6.1 3 559 9.9 7.9 74.6* 8.6 4 505 21.0 17.6 3 6 6 24.8* 5 559 7.2 7.5 17.5 67.8* 6 559 16.1 14.8 52.4* 16.6 7 548 24.3 22.6 29.0* 24.1 8 413 22 3 19.1 47.9 10.7* 9 520 26 0 28.8 23.3* 21.9 10 559 25 8 18.2 37.9* 18.1 11 559 2.1 85.9* 9.1 2.9 12 542 22.0 12.2 48.2* 17.7 13 559 7.9 7.7 22.9 61.5* 14 559 11.4 12.9 63.7* 12.0 15 559 7.2 6.4 80.3* 6.1 16 474 20.9 23.0 37.1 19.0* 17 559 9.7 10.7 21.6 58.0* 18 542 10.9 43.5* 32.5 13.1 19 559 17.4 14.0 37.7 30.9* 20 531 18.3 14.7 44.1 23.0* 21 511 18.8 15.9 3 68 28.6* 22 507 17.0 18.3 43.6 21.1* 23 559 1.6 2.3 7.7 84.4* 24 559 12.9 11.4 26.7 49.0* 25 559 13.1 42.4* 28.1 16.5
Note: * Correct response Missing cases are excluded from the calculation of frequencies. 64 (1) Human Population Items 1, 2. 3, 4, and 5 were used to assess respondents’ knowledge relating to human population. Of the five items provided in this environmental knowledge subcategory, three items were answered correctly by 67% or more of the respondents. Only 32.9% correctly answered the question relative to the method used to determine the size of human population in a given country, and a high percentage (88.4%) of students correctly estimated the current size of Burundi population. The most threatening environmental problem in the Republic of Burundi, which is the rapid human population growth, was identified by 74.7% of the respondents. Malthusian growth was understood by only 24.8% of the respondents. This principle specifies that populations (human and others) grow until they use up the resources available to them, and then growth is limited by catastrophes such as famines, diseases, violence, etc. A moderately high percentage (67.8%) correctly answered item 5 pertaining to the use of modern contraceptive devices as the best method of human birth control. In general, respondents' knowledge of human population issues revealed high variabilities, ranging from 24.8% to 88.4%. The same kind of variability was found among the respondents’ school categories in which General Education students scored much higher on items 1, 3, and 4 compared to Technical Education counterparts (see Table 13). 65
Table 13 Frequency of Respondents' Correct Responses fas Percent) to Knowledge of Population Issues
General Education Technical Education Item n % n %
1 128 33.9 45 30.4 2 360 87 6 134 90.5 3 308 74.9 109 73.6 4 100 26.5 25 19.5 5 268 65.2 111 75.0
(2) Water Quality Item 6 through item 10 were employed to assess students' knowledge about water quality. As summarized in Table 14, students’ scores on items pertaining to water quality were very low with General Education outseoring Technical Education respondents, except for item 10 dealing with Nitrogen and Phosphorus behavior in sewage waters. The scores ranged from 10.9 to 55.5 for General Education respondents and from 10.2% to 43.9% for Technical Education respondents. 66
Table 14
Frequency of Respondents’ Correct Responses fas Percents to
Knowledge of Water Quality
General Education Technical Education Item n % n %
6 228 55.5 65 43 9 7 117 29 9 42 28.4 8 31 10.9 13 10.2 9 95 25.5 26 19.7 10 154 37.5 58 39.2
(3) Natural Resources Items 11, 12, 13, 14, and 15 were used to measure respondents’ environmental knowledge relating to natural resources issues. For both General and Technical Education, respondents’ scores were moderately high although showing a slight variability within each school category and across the two types of schools. As summarized in Table 15, more than 80% of the respondents were able to recognize that the Tropical Jungle is the habitat where one would expect the largest amount of energy to be produced by photosynthesis. In both groups, students scored low on item 12 dealing with non-renewable resources such as oil, natural gas, and coal (50.5% for General Education and 41.9% for Technical Education). Item 13, designed to assess respondents' knowledge levels about 67 deforestation, flooding, and soil erosion, item 14, dealing with Tropical Rain Forest, and item 15 about water pollution, were correctly answered by 56% or more of the students in both groups of respondents.
Table 15 Frequency of Respondents’ Correct Responses fas Percent) to Knowledge of Natural Resources
General Education Technical Education Item n % n %
11 349 84.9 131 88.5
12 199 50.5 62 41.9 13 260 63.3 84 56.8 14 262 63.7 94 63.5 15 342 83 2 107 72.3
(4) Ecological Principles Environmental knowledge relative to ecological principles was assessed using items 16, 17, 18, 19, and 20. Of the five items utilized in this subcategory, only item 17 was answered correctly by more than 50% of the respondents in both types of schools. The remaining items showed low scores ranging from 18.5% to 47%. Item 17 dealt with vegetation climax and items 16. 18, 19, and 20 were about habitat, trophic structure, ecosystem, variation, and selection principles {see Table 16). 68
Table 16
Frequency of Respondents' Correct Responses fas Percent) to
Knowledge of Ecological Principles
General Education Technical Education Item n % n %
16 64 18.5 26 20.3 17 239 58.2 85 57.4 18 193 47.0 43 32.8 19 136 33.1 37 25.0 20 81 21.1 41 27.7
(5) Global Environmental Issues Items 21, 22, 23, 24, and 25 were employed to examine respondents’ environmental knowledge levels relative to global environmental issues such as the greenhouse effect, desertification, pesticide use and misuse, global warming and acid rain. Since DDT is extensively used in Burundi for pest control, almost all the respondents appeared to be highly knowledgeable on item 23 dealing with that insecticide. General Education students obtained 87.6% on the item and Technical Education respondents scored 90.5% on the same item. The scores on the remaining items in this subcategory revealed relatively low knowledge levels among respondents with regard to ecological principles. It was also shown that General Education respondents outscored their Technical Education counterparts except for items 21 and 23 dealing with the greenhouse effect and 69 the use of DDT, respectively (see Table 17).
Table 17 Frequency of Respondents’ Correct Responses fas Percents to Knowledge of Global Environmental Concerns
General Education Technical Education Item n % n %
21 119 31.2 27 20.8
22 74 18.8 33 29.2 23 360 87.6 134 90.5 24 213 51.8 61 41.2 25 175 42.6 62 41.9
When considering the respondents’ scores on the overall knowledge instrument by subscales, the participants seemed lo be more knowledgeable on issues relative to natural resources followed by issues pertaining to human population, global issues, ecological principles, and water quality, respectively (see Table 18). On the other hand.Table 19 displays respondents’ environmental knowledge score statistics by school category and subscales. Except for the human population issues subscale. General Education respondents outscored their Technical Education counterparts. 70
Table 18 Respondents’ Overall Environmental Knowledge Score Statistics bv Subscales
Subscale n Mean SD Min Max
Human population 559 2.84 0.98 0 5 Water quality 559 1.48 0 94 0 5 Natural resources 559 3.38 1.00 0 5 Ecology 559 1.69 1.03 0 5 Global issues 559 2.25 0.96 0 5 71 Table 19 Respondents’ Environmental Knowledge Scores Statistics bv school Category and Subscales
General Education Technical Education Subscale n Mean SD n Mean SD
Human population 411 2 83 1.00 148 2.86 0.89 Water quality 411 1.52 0.97 148 1.38 0.86 Natural resources 411 3.44 1.00 148 3 23 0.99 Ecology 411 1.73 1.05 148 1.57 0.96 Global issues 411 2.29 0 96 148 2.14 0.97
A t-test for independent groups was utilized to investigate for the difference between the levels of environmental knowledge held by the thirteenth grade General and Technical Education respondents (see Table 20). The results were analyzed by school categories and the five predetermined subscales . Table 20
T-test of Respondents’ Environmental Knowledge Mean Scores bv School
Category and Subscales
Subscale n Mean SD t-value1 df Pr**
Overall 411 11.81 2.42 2.99 (410, 147) .0030* 148 11.18 2.11
Human population 411 2.83 1.00 -0.35 (410, 147) .7265 148 2.86 0.89
Water Quality 411 1 52 0.96 1.58 (410, 147) .1153 148 1 38 0.86
Natural resources 411 3 44 1.00 2.14 (410, 147) .0329* 148 3.23 0.99
Ecology 411 1.73 1.04 1.70 (410, 147) 0897 148 1.57 0.96
Global issues 411 2.29 0.96 1.60 (410, 147) .1096 148 2.14 0.97
Note: * Significant at the 0.05 alpha level, General Education {n = 411), Technical Education (n = 148) ** Each set of t and p-values corresponds to items 1-5, 6-10, 11-15, 16-20, 21-25 respectively; except for the overall where the whole knowledge instrument (25 items) is concerned. 73 A significant difference at the 0.05 alpha level (p = 0.0030) was found between General and Technical Education respondents on the entire knowledge instrument. Table 20 summarizes the findings and reveals that General Education students scored higher {Mean = 11.81; SD = 2.42) than Technical Education respondents (Mean = 11.18, SD = 2,10). It was also established that a statistically significant difference at the 0.05 alpha level (p = 0.0329) existed between the two group mean scores pertaining to natural resources issues. No significant differences were found between group means on the issues dealing with human population, water quality, ecological principles, or global environmental concerns. The null hypothesis associated with Objective 1, assuming that the two population mean scores were equal was rejected for the overall environmental mean score (p = 0.0030), and natural resources issues (p = 0.0329). The researcher failed to reject the null hypothesis for human population issues, water quality, ecological principles, and global environmental issues for which the probability levels were greater than the predetermined alpha level of 0.05 (see Table 20). Considering that the sample mean (Warmbrod, 1993) is a good estimate of the population mean, these results may be generalized to the target populations of General and Technical Education seniors in the Republic of Burundi.
Data Analysis for Objective 2
Objective 2: To assess and compare the attitudes toward the environment held by two selected samples of thirteenth grade General and Technical Education students in the Republic of Burundi. 74 Table 21 illustrates respondents’ score statistics on the overall sample and the school category samples. An individual score was determined by summing the point values tor each statement on a 25 item Likert Scale (see Appendix A). Although the researcher and a panel of experts preferred some alternative responses for each item, each alternative response specified was considered acceptable. The mean and standard deviation values were determined for the overall instrument according to school category and environmental attitude subgroups.
Table 21 Summary of Respondents’ Environmental Attitudes Score Statistics bv School Category
School category n Mean SD Min Max
General Education 411 3.68 0.26 2.84 4.24 Technical Education 148 3.52 0 24 2.12 3.28 Overall sample 559 3.64 0.26 2 88 4.08
Note: All alternative responses were considered acceptable. 75
Table 22
Frequency of Respondents’ Responses fas Percent! to Each Alternative on
Environmental Attitude Items
Alternative (%) Item n 1 2 3 4 5
1 557 40.9* 38 6 2 2 14.2 4.1 2 557 60.0* 28.7 1.4 6 1 3.8 3 557 7.0 14.0* 7.5 59.2 12.2 4 557 21.7* 42.0 6 6 23.3 6.3 5 557 19.7 39.0* 19.4 16.0 5.9 6 559 288 46.6* 7.9 17.5 3.2 7 555 9.5 15.3* 8 6 47.9 18.6 8 557 25.1 21.5* 3.1 33.9 16.3 9 556 12 8 16.2 3.1 43.0* 25.0 10 550 39.5 50.9* 2.9 4.4 2.4 11 556 50.5* 31.1 1.8 13.8 2.7 12 553 32 4 36.7* 6.1 19.0 5.8 13 554 45.7 33.8 5.2 11.7* 3.6 14 553 40.9 31.8* 5.6 15.2 6.5 15 554 49.5 28 5* 4.7 12.6 4.7 16 552 49.5 38.9* 4.7 4.2 2.7 17 553 32.0* 47.7 9.9 7.8 2.5 18 556 8.5 7.6 5.2 49.8 29.0* 19 554 48.4* 20.8 3.1 14.6 13 2 20 555 16.6 36.2* 10.8 29.9 6.5 21 555 23.2 33.9 28 5* 10.1 4.3 22 553 53.2* 33.1 7.6 4.9 1.3 23 555 21.8 30.6* 16.8 25.8 5.0 24 555 14.8 39.3* 4.1 32.1 9.7 25 547 11.3 22 7* 9.1 42 8 14.1
Note: * Desired response 1-Strongly Disagree, 2-Disagree, 3-Neutral, 4-Agree, 5-Strongly Agree 76 Since each alternative response on the attitude instrument is deemed to be acceptable, the respondents’ answers can be trichotomized according to the levels of agreement, disagreement, or neutrality on each item and subscales.
(1) Population Items 1, 2, 3, 4, and, 5 were employed to assess respondents’ attitudes toward human population. A high percentage (79.5%) of the respondents recognized that an unbalanced population growth in Burundi contributes a major challenge for the nation, while one-fifth (18.3%) disagreed with the statement. Only 2 2% were neutral. A low percentage of neutral cases was observed in all five subscales utilized in the study. The majority of the respondents (88.7%) supported the idea that over-population is a barrier to economic growth and the quality of the environment in the Third World. Very low percentages were either neutral (1.4%) or in disagreement (9.9%) with item 2. Although it has been demonstrated that little effort has been devoted to lowering current population growth trends in Burundi, more than 70% of the respondents thought the opposite, and 21% disagreed with the statement. Respondents differed on the statement that "humans can live in harmony with the environment regardless the size of their populations." More than sixty percent (63.7%) disagreed with the statement, about thirty percent (29.6%) agreed, and only 6.6% were neutral. Item 5 states that ‘no program on population control will work in Africa if it is imported.” About the same percentage of respondents were either neutral (19.4%) or agreed (21.9%) with the statement. More than half of the respondents (58%) did not support the statement (see Table 23). 77
Table 23
Frequency of Respondents’ Environmental Attitude Scores (as Percent) on Human PoDulation Issues
Item General Education Technical Education n 1 2 3 n 1 2 3
1 409 81.9 1.0 17.1 148 73.0 5.4 21.6 2 409 88.0 1.0 11.0 148 90.5 2.7 6 8 3 409 20 5 4.6 74.8 148 22.3 15.5 62.1 4 409 63 8 6.6 296 148 63.5 6.8 29.7 5 409 59.4 18.6 22.0 148 56.8 21.6 21.6
Note: 1 - Disagree, 2 - Neutral, 3 - Agree Missing cases are excluded from the calculation of frequencies and percentages.
(2) Natural Resources Items 6 through item 10 are about issues related to natural resources depletion. High percentages of agreement were observed for item 7 (66.5%) dealing with protection of endangered wildlife in the developing nations, item 8 (50.2%) pertaining to human rights to modify the environment to fit their needs, and item 9 (68.0%) specifying that “until people s primary needs are met, they will have little enthusiasm seeking a quality environment.'1 Very high percentages of disagreement were revealed by item 6 (71 4%) “The clearing of Burundi large forest tracks and soil erosion that accompanies 78 intensive agriculture will not impact the country’s economic growth," and on item 10 (90.3%) which states that ‘‘conservation of natural resources implies that those resources cannot be utilized (see Table 24).”
Table 24 Frequency of Respondents’ Environmental Attitude Scores fas Percent) on Natural Resources Issues
Item General Education Technical Education n 1 2 3 n 1 2 3
6 411 74.9 5.8 19.2 148 61.5 13.5 25.0 7 407 25.8 6.9 67.3 148 22 3 13.5 64.2 8 409 47.7 2.0 50.4 148 43.9 6.1 50.0 9 408 26.5 1.7 71.2 148 35.8 6.8 57.4 10 402 91.3 1.7 7.0 148 87.8 6.1 6.1
Note: 1 - Disagree, 2 - Neutral, 3 - Agree Missing cases are excluded from the calculation of frequencies and percentages.
(3) Water Quality Items 11, 12, 13, 14, and 15 were used to measure respondents’ environmental attitudes toward water quality. These items dealt with water pollution, drinking water treatment, drinking water quality, irrigation with polluted water, and waste disposal in water ways, respectively. 79 Seventy percent or more agreed on item 11 (81.7%), and item 12 (81.7%), and about the same percentages of disagreement were observed on item 13 (79.4%). Given these results, we can infer that water quality is a very controversial issue in Burundi high schools (see Table 25).
Table 25 Frequency of Respondents1 Environmental Attitude Scores fas Percent) on Water Quality Issues
Item General Education Technical Education n 1 2 3 n 1 2 3
11 408 83.8 0.7 15.4 148 75.7 4.7 19.6 12 405 70.6 4.0 25.4 148 64 9 12.2 23.0 13 406 79.1 5.2 15.7 148 80.4 5 4 14.2 14 405 77.3 4 4 18.3 148 60.1 8.8 31 1 15 406 83.5 3.7 12.8 148 62.8 7.4 29.7
Note: 1 - Disagree, 2 - Neutral, 3 - Agree Missing cases are excluded from the calculation of frequencies and percentages.
(4) Ecological Principles In order to investigate the levels of respondents’ feelings on appreciation about ecological principles, item 16 through item 20 were utilized. High percentages of respondents disagreed on all items except items 18 80 and 19. More than eighty percent (88.4%) disagreed with item 16 dealing with environmental degradation and ecological problems in poor countries, 79.7% disagreed with item 17 about the controversy on biodiversity conservation in developed and developing nations, and 52.8% of the respondents disagreed with item 20 that "humans should stop harvesting trees because they harbored wildlife." Item 18 (78.8% of agreement), and item 19 (69.1% of agreement) were about interdependence of living things with one another and their physical environment, and slash and burn activities impacts on ecological relationships, respectively (see Table 26).
Table 26 Frequency of Respondents' Environmental Attitude Scores (as Percent) on Ecoloaical PrinciDles
Item General Education Technical Education n 1 2 3 n 1 2 3
16 404 90.8 3.7 5.4 148 81.8 7.4 10.9 17 405 82.7 8.4 8.9 148 71.6 14.2 14.2 18 408 14.2 4.7 81.1 148 20.9 6.8 72.3 19 406 73.2 2.7 24 2 148 58.1 4.1 37.9 20 407 52.6 8.6 38.8 148 53.4 16.9 27.7
Note: 1 - Disagree, 2 - Neutral, 3 - Agree 81 Missing cases are excluded from the calculation of frequencies and percentage
(5) Global Environmental Issues To measure respondents’ levels of concern about global environmental issues such as pesticide use and misuse, acid rain, global warming and the like, items 21 through 25 on the attitude instrument were utilized. About half of the respondents disagreed with item 21 dealing with the global warming dilemma (57.1%), with item 23 about acid rain (52.4%), and item 24 (54.1%) concerning pesticide use as the best method to increase crop production. Item 22 relative to desertification had a high rate of agreement (86.3%) and the percentages of disagreement and unspecified opinions were about the same, 7.6 % and 6.1%, respectively. Item 24 was also about pesticides and their harmful effects on pests and people. More than half of the respondents (56.9%) agreed with the statement and 34.0% disagreed. Only 9.1 % of the respondents were neutral. It may be because global issues are less visible in the Third World, and in Burundi, in particular, that students had different views about those topics (see Table 27), 82
Table 27
Frequency of Respondents' Environmental Attitude Scores fas Percent) on Global Issues
Item General Education Technical Education n 1 2 3 n 1 2 3
21 407 61.7 25.8 12.6 148 44.6 35.8 19.6 22 405 89.9 4.7 5.4 148 76.4 15.5 8.2 23 407 53.6 12.8 33.7 148 493 27.7 23.0 24 407 54.8 4.9 40.3 148 52.0 2.0 46.0 25 399 31.8 7.0 61.1 148 39.9 14.9 45.3
Note: t - Disagree, 2 - Neutral, 3 - Agree Missing cases are excluded from the calculation of frequencies and percentages.
In general, the percentage of respondents’ scores on the environmental attitude instrument were mildly variable (see Tables 21 through Table 31J. The results of this descriptive statistic analysis revealed that, on the average, General Education respondents disagreed more on different item sub-scales than did their Technical Education counterparts. The rate of neutrality and the rate of agreement on different item subscales were much higher for Technical Education participants. When interpreting these results, it is recommended to bear in mind the differential scoring procedure on positive and negative statements with regard 83 to the Likert Scale of measurement used to collect environmental attitude data. It may also be misleading to believe that one or the other group had more or less positive or negative attitudes about different environmental issues and/or problems presented in this study because the respondents were exposed to this type of assessment for the very first time during their 13 years of schooling.
Table 28 Summary of Respondents' Environmental Attitudes Score Statistics bv Subscales
Subscale n Mean SD Min Max
Human population 559 3.56 0.47 2.20 4.80 Natural Resources 559 3.40 0 54 1.80 4.80 Water Quality 556 3.96 0.54 2.40 5.00 Ecology 557 3.82 0.53 2.00 5.00 Global issues 557 3.45 0.53 2.00 4.80 84
Table 29
Respondents’ Environmental Attitude Score Statistics bv School
Category and Subscales
General Education Technical Education Subscale n Mean SD n Mean SD
Human population 411 3.56 0.47 148 3.54 0.48 Natural resources 411 3 44 0.55 148 3.29 0.51 Water quality 408 4.04 0.53 148 3.76 0.52 Ecology 409 3 89 0.51 148 3.63 0.53 Global issues 409 3.48 0.55 148 3.37 0.49
A t-test was performed to test for the significance of the difference between the levels of environmental attitudes in both school categories. Table 30 summarizes the results by school categories and environmental attitude subscales. 85
Table 30
T-test of Respondents' Environmental Attitude Mean Scores bv School
Category and Subscales
n Mean SD t-value*’ df prob”
Overall 411 3.68 0.26 7.00 (410, 147) 0.0001’ 148 3.52 0.24
Human population 411 3.56 0.47 0.48 (410, 147) 0.6304 148 3 54 0.48
Natural resources 411 3.44 0.55 2.95 (410, 147) 0.0034* 148 3 29 0.51
Water quality 411 4.04 0.53 5.57 (407, 147) 0.0001’ 148 3.76 0.52
Ecology 411 3.89 0.51 5.24 (408, 147) 0.0001’ 148 3.63 0.53
Global issues 411 348 0.55 2.28 (408, 147) 0.0234’ 148 3.37 0.49
Note: * Significant at the 0.05 alpha level, General Education (n = 411), Technical Education (n = 48) ** Each set of t and p-values for the sub-scales corresponds to item 1 -5, 6-10, 11-15, 16-20, and 21-25 respectively: except for the school category where the whole instrument (25 items) is concerned. 86 The different t-tests indicated the significance of differences among respondents’ attitude scores with respect to overall attitude mean scores, natural resources, water quality, ecology, and global issues. No significant differences were found between respondents’ mean attitude scores with regard to human population. General Education students outscored Technical Education for the overall and for the five environmental attitude subscales. The null hypothesis associated with objective 2 stating that no difference existed between General and Technical Education respondents’ environmental mean scores was rejected for the overall environmental attitude mean scores, natural resources issues, water quality, ecological principles, and global issues. The researcher failed to reject the null hypothesis associated with Objective 2 for human population issues {p = 0.6304). These results may be generalized to the target populations of thirteenth grade General and Technical Education students in Burundi.
Data Analysis for Objective 3
Objective 3: To investigate possible relationships among respondents’ environmental knowledge levels and their attitudes toward the environment.
Pearson’s Product Moment Correlation was employed to determine whether there were relationships between respondents' knowledge scores and their attitude scores The analysis was performed according to the overall respondent sample and the five environmental knowledge and attitude sub-scale samples specified earlier. Table 31 summarizes the findings. 87
Table 31
Relationship: Respondents’ Environmental Knowledge and Attitudes bv School Category and Subscales
General Education Technical Education Group n r Pr. n r Pr.
All Cases 411 0.13 0.0065* 148 0.11 0.1812 Human population 411 0.13 0.0090* 148 0.12 0.1340 Natural resources 408 0.30 0.5335 148 -0.08 0.3642 Water quality 411 0.01 0.8508 148 0.20 0.0167* Ecology 409 0.17 0.0006* 148 -0.23 0.0052* Global issues 409 0.10 0.0441* 148 0.12 0.1322
Note: * Significant at the 0.05 alpha level
As shown in Table 31, for General Education there were low and significant positive associations between respondents' environmental knowledge levels and their attitudes toward the environment for all cases (r = 0.13, p = 0.0065), human population (r = 0.13, p =0.0090), ecological principles (r = 0.17, p = 0,0006), and global environmental issues (r = 0.10, p = 0.0441). These four observations did not support the null hypothesis associated with Objective 3 (Ho: Rho = 0), therefore the hypothesis was rejected and the conclusion that associations between environmental knowledge and attitudes existed generalized to the related target population. On the other hand, significant relationships were not found for the items 88 associated with water quality and natural resources. Therefore, the researcher failed to reject the null hypothesis and concluded that significant relationships did not exist between respondents’ knowledge and attitudes for those sub scales. The results also may be generalized to the target population. For Technical Education respondents, a low and significant positive association at the .05 alpha level was observed for knowledge and attitudes toward water quality issues {r =0.20, p = 0.0167). A low, significant, and negative association was seen for the knowledge and attitudes toward ecological principles ( r = - 0.23, p = 0,0052). No significant relationships were found between respondents’ environmental knowledge and attitude scores on the overall, human population issues, and global environmental concerns. The null hypothesis was rejected for for water quality and ecological principles; and the researcher failed to reject the null hypothesis stating that Rho = 0 for all cases, human population, natural resources, and global issues (see Table 31). These results may be generalized to the corresponding target population. All the significant groups showed positive relationships except for the water quality subscale (-0.08) and the ecological issues subscale (-0.23) for Technical Education.
Data Analysis for Objective 4
Objective 4: To investigate any variation between the respondents’ environmental knowledge levels related to their age, gender, residential location, source of environmental information, type of school, parents’ occupation and level of education. 69 An analysis of variance (ANOVA) was utilized in order to examine any differences in environmental knowledge mean scores of students possessing different demographic characteristics. Tables 32, 33, 38, 39, 42. and 43 provide summaries of the findings and also reveal the effect of each individual independent variable. The analysis was performed for the overall environmental knowledge group response mean scores and the five environmental sub-group mean scores. Tables 38 and 42 provide evidence that neither respondents' type of school or other demographic variables included in the study accounted for a significant amount of the variability in the knowledge of water quality issues and ecological principles. However, significant interactions were found between gender and residential location (p < 0.0240) for human population, between gender and parents’ occupation (p < 0.0464) for human population also, respondents’ age category and gender (p < 0.0487) for the natural resources sub-scale, and the age category and residential location (p < 0.0153) for the global environmental concerns subscale. No main effects were detected in the respondents’ overall knowledge or for the five environmental subgroup mean scores. In order to visualize and interpret the interactions, graphs have been constructed and levels of significance for individual comparisons among the least square means are listed. The use of adjusted means (least square means) was required due to the fact that the mean cell sizes involved in the present study were unbalanced. Respondents’ major (DE 3), school geographic location (DE 5), and respondents’ type of school (DE 7) information were confounded with other independent variable information, therefore, the researcher excluded them from 90 the analysis of objective 4. During the process of simplifying each model (which included main effects and two-way interaction), non-significant interactions were dropped from the analysis one at a time in a backward elimination approach. The null hypothesis associated with Objective 4 was that no significant difference existed between respondents’ environmental knowledge levels based upon their age, gender, residential location, source of environmental information, school category, or parents' occupation and level of education. The task was to investigate whether the variability found in the respondents’ knowledge scores was explained by demographic variables. 91
Table 32 ANOVA of The Overall Environmental Knowledge Mean Scores
bv Independent Variable
Source df SS MS F-value Pr > F
Model 45 791.1493 17.5810 3.89 0.0001* Error 513 2316.7182 4.5160 Total 558 3107.8676 Model Breakdown: School category 1 63.9374 63.9374 2.69 0.1133 Class (EDUCA) 26 618.8968 23.8037 5.27 0.0001* Age group 2 17.2914 8.6457 1.91 0.1485 Gender 1 0.3872 0.3872 0.09 0.7698 Location 3 30.8127 10.2709 2.27 0.0791 Information source 3 18.7401 6.2467 1.38 0.2470 Parents’ occupation 3 1.8687 7.2895 1.61 0.3271 DE 2 by DE 4 3 30.5701 10.1900 2.26 0.0810 R-Square = 0.2545
Note: * Significant at .05 alpha level Class (EDUCA): Any particular thirteenth grade classroom subjects DE 2: Gender, DE 4: Residential location DE2 by DE4: Interaction of gender and residential location R-Square values were used to explain the amount of variance the significant independent variables were accounted for cumulatively 92 The model employed in the analysis of Objective 4 consisting of school category and other independent variables accounted for a significant (p < 0.0001) amount of the variability in the overall environmental knowledge scores {25%). As shown in Table 32, no significant main effects or interactions were found in the overall group response mean scores. 93 Table 33 ANOVA of Human Population Knowledge Mean Scores bv Independent Variables
Source df SS MS F-value Pr > F
Model 50 173.9319 3.4786 4.95 0.0001* Error 508 356.8980 0.7025 Total 558 530.8300 Model Breakdown: School category 1 0.2233 0.2233 0.04 0.8357 Class (EDUCA) 26 132.3391 5.0899 7.24 0.0001* Age 2 3.3020 1.6510 2.35 0.0964 Gender 1 0.0097 0.0097 0.01 0.9061 Location 3 9.2190 3.0730 4.37 0 0047* Information source 3 0.7566 0.2522 0.36 0.7826 Parent’ occupation 3 0.3635 0.1211 0.17 0.9150 Parent's degree 3 1.0859 0.3619 0.52 0.6719 DE 1 by DE 2 2 3.4397 1.7198 2.45 0.0875 DE 2 by DE 4 3 6.6853 2.2284 3.17 0.0240* DE 2 by DE 8 3 5.6459 1.8819 2.68 0.0464* R-Square = 0.3276
Note * Significant at the .05 level, DEt: Age, DE2: Gender, DE4: Location, Class (EDUCA): Any particular thirteenth grade classroom subjects DE1 by DE2: Interaction of age and gender, DE8: Parents’ occupation, DE2 by DE4: Interaction of gender and residential location DE2 by DE8: Interaction of gender and parents’ occupation 94 By breaking down the model, it appears that there were significant interactions between DE 2 (gender) and DE 4 ( residential location) (p < 0.0240), and DE 2 and DE 8 < parent’s occupation) (p < 0.0464). However, no main effects were observed for human population issues. Table 34 displays the least square or adjusted mean scores, the standard error of the least square means, and the least square mean numbers appropriate for unbalanced data. Table 35 provides the probability matrix for means in Table 34 and in the model, two-way interaction ANOVA was used like a t-test. 95 Table 34 LSMeans of DE 2 and DE 4 bv Knowledge of Human Population Issues
Level of Std. Error LSMean DE 2 DE 4 n LSMean LSMean number
1 1 62 2.87 0.13 1 1 2 24 3.06 0.21 2 1 3 250 2.64 0.10 3 1 4 29 2.84 0.19 4 2 1 39 3.36 0.17 5 2 2 8 2.51 0.32 6 2 3 127 2.84 0.12 7 2 4 20 2.61 0.23 8
Note: LSMean = Adjusted or Least Square Mean DE2: Gender DE4: Residential location Std Error LSMean: Standard error of the least square mean(s) LSMean number: Any combination of adjusted means corresponding to different levels of DE2 and DE4 KNOWLEDGE OF
FIGURE 1: INTERACTION OF GENDER AND LOCATION AND GENDER OF INTERACTION 1: FIGURE POPULATION ISSUES 3 4 3 2 LOCATION FEMALE MALE ■ ■ LOCATION 1-City 3.Rural 4. Farm 4. . Suburban 2. 96 97
Table 35
Probability Matrix for Means in Table 34
i / j 1 2 3 4 5 6 7 8 1 • 2 0.3871 « 3 0.0835 0.0476* • 4 0.9222 0.3969 0.2606 • 5 0.0221* 0.2641 0.0003* 0.0486* « 6 0.3086 0.1505 0.7080 0.3742 0.0149* • 7 0.8723 0.3631 0.2117 0.9694 0.0014* 0.3215 « 8 0.3545 0.1631 0.9221 0.4465 0.0024* 0.7990 0.3130 •
Note: * Significant at the .05 alpha level i and j represent any combination of LSMean numbers in Table 34
When considering male respondents, a significant difference (p < 0.0476) was found between suburban and rural residents. Males who lived in suburban areas scored higher on the average (LSMean - 2.78) than males who resided in rural areas (LSMean = 2.74) but not on farms. For female respondents, city residents scored higher (LSMean = 3.11) than suburban (LSMean = 2.78), rural not on a farm (LSMean = 2.73), and on farm residents (LSMean = 2.72). In general, city female respondents outscored male respondents for rural (not on a farm) and farm resident groups (see Tables 34, 35, and Fig 1). Interaction was also found between DE 2 (respondents' gender) and 98 DE 8 (respondents’ parents’ occupation). Table 36 lists the least square means, least square standard errors, and the least square numbers tor DE 2 and DE 8. Table 37 displays the probability matrix for means in Table 36.
Table 36 LSMeans of DE 2 and DE 8 bv Knowledge of Human Population issues
Level of Std. Error LSMean DE 2 DE 8 n LSMean LSMean number
1 1 11 2.76 0.29 1 1 2 96 2.95 0.13 2 1 3 177 3.04 0.12 3 1 4 81 2 66 0.13 4 2 1 19 2.82 0.25 5 2 2 66 2.81 0.17 6 2 3 75 2 73 0.16 7 2 4 34 2.97 0.18 8
Note: LSMean = Adjusted or Least Square Mean DE2: Gender, DE8: Respondents' parents’ occupation LSMean number: Any combination of adjusted means corresponding to different levels of DE2 and DE8 FIGURE INTERACTION2: OF GENDER AND PARENTS' OCCUPATION KNOWLEDGE OF POPULATION ISSUES 2 0 1 “ - 2.96 OCCUPATION 3 2 304 2.97 MALE ■ FEMALE ■ . Farmer 3. 4. Other OCCUPATION . v servant Gvt 2. 1. Govt official 99 100 Table 37
Probability Matrix for Means in Table 36
i / j 1 2 3 4 5 6 7 1 * 2 0.5356 3 0.3776 0.5622 • 4 4.7420 0.0622 0 0053* * 5 0.8865 0.6509 0.4654 0.6056 • 6 0.8810 0.5201 0.3168 0.4835 0.9962 • 7 0.9230 0.3192 0.0883 0.7350 0.7559 0.6577 • 8 0.5538 0.9161 0.7431 0.1510 0.5839 0.4490 0.2065
Note: * Significant at the .05 alpha level i and j represent any combination of LSMean numbers in Table 36
Interaction between DE 2 and DE 8 revealed that male respondents whose parents were farmers appeared to be more knowledgeable about human population issues than those who did not specify their parents1 occupation. Parental occupation differences were not found among female respondents (see Tables 36, 37, and Fig 2). 101
Table 38
ANOVA of Water Quality Knowledge Mean Scores bv Independent Variables
Source df SS MS F-value Pr> F
Model 42 73.4422 1.7486 2.14 0.0001 Error 516 422.1462 0.8181 Total 558 495.5885 Model Breakdown School category 1 3.5822 3.5822 1.65 0.2104 Class (EDUCA) 26 56.4838 2.1724 2.66 0.0001* Age 2 0.8367 04183 0.51 0.6000 Gender 1 0.4778 0.4778 0.58 0.4451 Location 3 2.4994 0.8331 1.02 0.3841 Information source 3 3.7170 1.2390 1.51 0.2098 Parents’ occupation 3 0.3496 0.1165 0.14 0.9345 Parents’ degree 3 3.8420 1.2806 1.57 0.1963 R-Square = 0.1481
Note: * Significant at the .05 alpha level Class ( EDUCA) = Any particular thirteenth grade classroom subjects
Neither school category nor any other demographic variable accounted for a significant amount of variability in respondents' knowledge of water quality issues (see Table 38). Fifteen percent of the variability encountered in the model was probably due to the differences within classes. 102
Table 39 ANOVA of Natural Resources Knowledge Mean Scores bv Independent Variables
Source df SS MS F-value Pr> F
Model 44 106.5330 2.4212 2.71 0.0001 Error 514 459.3059 0.8935 Total 558 565.8389 Model Breakdown: School category 1 3.4832 3.4832 1.07 0.3108 Class (EDUCA) 26 84.7695 3.2603 3.65 0.0001’ Age 2 1.9080 0.9540 1.07 0.3446 Gender 1 0.1619 0.1619 0.18 0.6705 Location 3 0.8963 0.2987 0.33 0.8005 Information source 3 0.9748 0.3249 0.36 0.7793 Parents’ occupation 3 0.3278 0.1092 0.12 0.9470 Parents' degree 3 0.1976 0.0658 0.07 0.9741 DE 1 by DE 2 2 5.4327 2.7163 3.04 0.0487’ R-Square = 0.1882
Note: * Significant at the .05 alpha level, DE1: Age, DE2: Gender Class (EDUCA): Any particular thirteenth grade classroom subjects DE1 by DE2: Interaction of age and gender Although an interaction was detected between age category (DE 1) and respondents' gender (DE 2); the graphical representation did not capture the significantly different groups (see Tables 40, 41, and Fig 3). 103
Table 40 LSMeans of DE 1 and DE 2 bv Knowledge of Natural Resources Issues
Level of Std. Error LSMean DE 1 DE 2 n LSMean LSMean number
1 1 73 3.17 0.15 1 1 2 75 3.21 0.15 2 2 1 210 3 25 0.11 3 2 2 92 343 0.14 4 3 1 82 3.46 0.13 5 3 2 27 3.04 0.21 6
LSMean: Adjusted or Least Square Mean DE1: Age DE2: Gender LSMean number: Any combination of adjusted means corresponding to different level of DE1 and DE2 NATURAL RESOURCES IUE3 INTERACTIONFIGURE3: OF AGE AND GENDER 82 2 2 23-25 21 -22 18-20 AGEGROUP MALE ■ FEMALE ■ 104 105
Table 41 Probability Matrix for Means in Table 40
i / i 1 2 3 4 5
1 •
2 0.8145 •
3 0.5764 0 8383 •
4 0.1667 0.1496 0.2085 •
5 0.0812 0.1723 0.0896 0.8832 • 6 0.6337 0.4460 0.3562 0.0647 0.0745
Note: i and j represent any combination of LSMean numbers in Table 40 106
Table 42
ANOVA of Ecological Issues Knowledge Mean Scores bv Independent Variables
Source df SS MS F-value Pr > F
Model 42 161.1131 3.8360 4.62 0.0001* Error 516 428.3465 0.8301 Total 558 589.4597 Model Breakdown: School category 1 2.7022 2.7022 0.48 0.4959 Class (EDUCA) 26 147.2575 5.6637 6.82 0.0001* Age 2 2.7043 1.3521 1.63 0.1972 Gender 1 0.8349 0.8349 1.01 0.3164 Location 3 1.1248 0.3749 0.45 0.7162 Information source 3 4.0291 1.3430 1.62 0.1842 Parents’ occupation 3 1.3615 0 4538 0.55 0.6505 Parents’ degree 3 4.6658 1.5552 1.87 0.1330 R-Square = 0.2733
Note: Class (EDUCA) = Any particular thirteenth grade classroom subjects
Neither school category nor either of the demographic variables accounted for a significant amount of variability in respondents’ knowledge of ecological principles (see Table 42). 107
Table 43
ANOVA of Global Issues Knowledge Mean Scores bv Independent Variables
Source df SS MS F-value Pr > F
Model 48 107.5526 2.2406 2.79 0.0001 * Error 510 409.3846 0.8027 Total 558 516.9373 Model Breakdown: School category 1 1.7069 1.7069 0.56 0.4629 Class (EDUCA) 26 79.9548 3.0751 3.83 0.0001* Age 2 1.9513 0.9756 1.22 0.2974 Gender 1 0.4698 0.4698 0.59 0.4446 Location 3 3.0017 1.0005 1.25 0.2922 Information source 3 3.0416 1.0138 1.26 0.2864 Parents’ occupation 3 3.5991 1.1997 1.49 0.2151 Parents’ degree 3 0.0228 0.0076 0.01 0.9987 DE 1 by DE 4 6 12.7692 2.1282 2.65 0.0153* R-Square = 0.2080
Note: * Significant at the .05 alpha level Class (EDUCA): Any particular thirteenth grade classroom subjects DE1: Age DE4: Respondents' residential location DE1 by DE4: Interaction of respondents' age and residential location 108
Table 44
LSMeans of DE 1 and DE 4 bv Knowledge of Global Environmental Issues
Level of Std. Error LSMean DE 1 DE 4 n LSMean LSMean number
1 1 31 2 32 0.18 1 1 2 6 1.58 0.40 2 1 3 99 2 28 0.11 3 1 4 12 2.20 0.28 4 2 1 55 2.25 0.14 5 2 2 22 2.70 0.21 6 2 3 205 2.32 0.09 7 2 4 20 2.05 0.22 8 3 1 15 2.65 0.24 9 3 2 4 1.54 0.48 10 3 3 73 2.21 0.12 11 3 4 17 2.64 0.24 12
Note: LSMean = Adjusted or Least Square Mean DE1: Age DE4: Respondents’ residential location LSMean number: Any combination of adjusted means corresponding to different levels of DE1 and DE4 KNOWLEDGE OF GLOBAL ISSUES FIGURE INTERACTION 4: OF AGE AND LOCATION 3 2 LOCATION 23-25 H ■ 18-20 ■ AGE 3. Rural3. LOCATION 4. Farm 4. . Suburban 2. 1-Cfly 21-22 109
Table 45
Probability Matrix for Means in Table 44
'/j 1 2 3 4 5 6 7 8 9 10 11 12 i1 2 0.0914 • 3 0.8215 0.0940 • 4 0.7084 0.1982 0.7933 9 5 0.7561 0.1044 0.8948 0.8612 • 6 0.1527 0.0102* 0.0675 0.1464 0.0616 • 7 0.9899 0,0710 0.7273 0.6804 0.6592 0.0721 • 8 0.3117 0.2927 0.3297 0.6453 0,4015 0.0238* 0.2243 t 9 0.2602 0.0207* 0.1568 0.2210 0.1416 0.8665 0.1890 0.0601 * 10 0.1225 0.9486 0.1336 0.2302 0.1451 0.0234* 0.1087 0.3290 0.0379* 11 0.5785 0.1334 0.6471 0.9857 0.7775 0.0331* 0.3766 0.5052 0.0951 0.1758 12 0.2615 0.0214* 0.1489 0.2181 0.1413 0.8347 0.1768 0.0512 0.9767 0.0906
Note: * Significant at the .05 alpha level
i and j represent any combination of LSMean number in Table 44 111 An interaction between respondents' age category and their residential location was shown (see Table 43). No main effect was observed. Among suburban residents, those 21 to 22 years of age scored higher than did those 18 to 20 years of age on the global environmental issues knowledge section. They also did better compared to farm residents 21 to 22 years old, 23 to 25 year old respondents, and 23 to 25 year old rural (not on a farm) respondents. City respondents aged 21 to 22 appeared more knowledgeable about global environmental issues than did their 18 to 20 and 23 to 25 year old peers. Farm residents 23 to 25 year old performed better on the global issues section than city residents 23 to 25 years of age and 21 to 22 year olds on farm residents (see Tables 44, 45, and Fig 4). Although significant differences have been found between respondents’ knowledge levels pertaining to human population and global environmental issues when demographic factors are considered, those differences were too minor to allow the researcher to generalize those findings to participating populations except from a statistical standpoint. 112 Data Analysis for Objective 5
Objective 5: To examine any variation between the respondents' attitudes toward the environment due to their age, gender, residential location, source of environmental information, type of school, parents' occupation and level of education.
An analysis of variance (ANOVA) was employed in order to investigate any difference in environmental attitude scores of students possessing different demographic characteristics. Tables 46, 49, 52, 55, 57, 60, and 63 furnish summaries of the findings and also reveal the effect of each independent variable. The analysis was performed for the overall environmental attitude group response mean scores and the five environmental subgroup mean scores. Significant interactions were found between age category and gender (p < 0.0038) for the overall attitude mean scores, and between gender and source of environmental information (p < 0.0287) for human population issues. Age category and respondents’ parents’ level of education (p < 0.0371) were significant for natural resources; gender, and respondents’ parents’ occupation were also significant for natural resources (p = 0.0492). Significant interactions were also found between, age category and respondents’ parents’ occupation (p < 0.0169) for water quality, and between age category and respondents’ parents’ level of education for water quality. Interaction between age category and gender (p < 0.0456) for ecological principles, age category and respondents' residential location (p < 0.0196), and gender and respondents’ parents’ level of education (p < 0.0247) were significant for global environmental issues. 113 Main effects were also detected for school category in the overall environmental attitude, natural resources, water quality, and ecological principles, a main effect was also observed for respondents’ residential location in human population issues. To visualize and interpret the interactions, graphs have been constructed and levels of significance for individual comparisons among the least square means are listed. The use of adjusted means (least square means) was required because the cell sizes involved in the present study were unbalanced. Respondents’ major (DE 3), school geographic location (DE 5), and respondents' type of school (DE 7) information were confounding with other independent variable information, therefore, the researcher excluded them from the analysis of Objective 5. During the process of simplifying each model (which included main effects and two-way interaction), non-significant interactions were dropped from the analysis one at a time in a backward elimination approach. The null hypothesis associated with Objective 5 was that no significant difference existed between respondents' environmental attitudes based upon their age, gender, residential location, source of environmental information, school category, or parents’ occupation and level of education. The goal for Objective 5 was to examine whether the variability found in the respondents' attitude scores was explained by demographic variables (independent variables). In the model, the two-way interaction ANOVA was used like a t-test. 114
Table 46
ANOVA of The Overall Environmental Attitude Mean Scores bv Independent Variables
Source df SS MS F-value Pr> F
Model 44 16.0068 0.3637 8 38 0.0001* Error 514 22.3217 0.0434 Total 558 38.3285 Model Breakdown: School category 1 2.8173 2.8173 7.83 0.0095* Class (EDUCA) 26 9.3494 0.3595 8.28 0.0001* Age 2 0.0587 0.0293 0.68 0.5091 Gender 1 0.1108 0.1108 2.55 0.1107 Location 3 0.0939 0.0313 0.72 0.5397 Information source 3 0.0375 0.0125 0.29 0.8337 Parents’ occupation 3 0.0354 0.1183 0.27 0.8453 Parents’ degree 3 0.0163 0.0054 0.13 0.9448 DE 1 by DE 2 2 0.4887 0.2443 5 63 0.0038* R-Square = 0.4176
Note: * Significant at the .05 alpha level Class (EDUCA): Any particular thirteenth grade classroom subjects DE1: Age DE2: Gender DE1 by DE2: Interaction of age and gender 115 A significant interaction was found (p < 0.0038) between respondents' age category and gender for the overall environmental attitude mean scores. A significant main effect (p < 0.0095) was also revealed by the school category for the overall environmental attitude mean scores. Table 46 shows the least square or adjusted mean scores, the standard error of the least square means, and the least square mean number appropriate for unbalanced data analysis pertaining to interaction between DE 1(age category) and DE 2 { gender) for the overall environmental attitude mean scores. Table 48 displays the probability matrix for means in Table 47 and Figure 5 provides a graphical representation of significant interactions between levels of DE 1 and DE 2 on the overall environmental attitude mean scores. Table 47 LSMeans of DE 1 and DE 2 bv the Overall Environmental Attitudes
Level of Std. Error LSMean DE 1 DE 2 n LSMean LSMean number
1 1 73 3.57 0.03 1 1 2 75 3.63 0.03 2 2 1 210 3.62 0.02 3 2 2 92 3.58 0.03 4 3 1 82 3.56 0.03 5 3 2 27 3.70 0.05 6
Note: LSMean = Adjusted or Least Square Mean DE1: Age, DE2: Gender LSnumber: Any combination of adjusted means corresponding to different levels of DE1 and DE2 116
■ MALE B FEMALE
18-20 21-22 23-25 AGE GROUP
FIGURE 5: INTERACTION OF AGE AND GENDER 117
Table 48 Probability Matrix in Table 47 i / j 1 2 3 4 5 6 1 • 2 0.1977 • 3 0.1598 0.7189 « 4 0.9060 0.1270 0.2383 * • 5 0.8272 0.1041 0.0610 0.7315 • 6 0.0282* 0.1893 0.1108 0.0133* 0.0125 * •
Note: * Significant at the .05 alpha level i and j represent any combination of LSMean number in Table 47 118 As shown by Fig 5, female respondents 23 to 25 years of age had more positive attitudes than did males 18 to 20 year old, females 21 to 22 year old and males 23 to 25 year old. No other interactions between the levels of DE 1 (age) and DE 2 (gender) were found significant (see Tables 47, 48, and Fig 5).
Table 49 ANOVA of Human Population Attitude Mean Scores bv Independent Variables
Source df SS MS F-value Pr > F
Model 45 32.4215 0.7204 4.01 0.0001* Error 513 92.2427 0.1798 Total 558 124.6643 Model Breakdown: School category 1 0.2231 0.2231 0.23 0.6340 Class (EDUCA) 26 24.9903 0.9611 5.35 0.0001 * Age 2 0.0616 0.0308 0.17 0.8425 Gender 1 0.2491 0.2491 1.39 0.2397 Location 3 1.9338 0.6446 3.58 0.0138* Information source 3 0.5208 0.1736 0.97 0.4086 Parents’ occupation 3 1.2756 0.4252 2.36 0.0702 Parents’ degree 3 0.2783 0.0927 0.52 0.6714 DE 2 by DE 6 3 1.6387 0.5462 3.04 0.0287* R-Square = 0.2600
Note: * Significant at the .05 alpha level DE2: Gender, DE6: Source of environmental information DE2 by DE6: Interaction of gender and residential location 119 Interaction between DE 2 (gender) and DE 6 (respondents’ source of environmental information) was observed (p < 0.0287) and a main effect of respondents’ source of environmental information was observed ( see Table 49) for human population issues
Table 50 LSMeans of DE 2 and DE 6 bv Attitudes toward Human Population Issues
Level of Std. Error LSMean DE 2 DE 6 n LSMean LSMean number
1 1 60 3.54 0.07 1 1 2 182 3.50 0.04 2 1 3 92 3.55 0.06 3 1 4 31 3.62 0.09 4 2 1 28 3.53 0.09 5 2 2 112 3.59 0.06 6 2 3 45 3.37 0.08 7 2 4 9 3.40 0.15 8
Note: LSMean = Adjusted or Least Square Mean DE2: Gender, DE6: Residential location LSMean number: any combination of adjusted means corresponding to different levels of DE2 and DE6 IUE6 INTERACTIONFIGURE6: OFGENDER AND SOURCE OF INFORMATION
TOWARD 4 3 2 1 INFORMATION SOURCE MALE ■ FEMALE H SOURCES: . Classroom2. . Books 1. 3. Radio or3. TV 4. Parents 4. 120
121
Table 51 Probability Matrix of Means in Table 50
i / i 1 2 3 4 5 6 7 8 1 ♦ 2 0.6340 • 3 0.8370 0.3960 • 4 0.4465 0.2020 0.5010 • 5 0.9210 0.8262 0.7983 0.4677 • 6 0.5249 0.1952 0.6034 0.8142 0.4675 « 7 0.1134 0.1401 00542 0 0351* 0 1704 0.0066* 8 0.3823 0.4823 0.3179 0.1901 0.4420 0.1985 0.9013
Note: Significant at the .05 alpha level i and j represent any combination of LSMean numbers in Table 50
Male respondents who cited parents as their major source of environmental information appeared to have more positive attitudes toward human population issues than did females who reported radio or TV as their major source of environmental information. Females with classroom instruction as a major source of information had higher positive attitudes toward human population issues than did females with radio or TV as major sources (see Tables 50, 51, and Fig 6), 122
Table 52
ANOVA of Natural Resources Attitude Mean Scores bv Independent Variables
Source df SS MS F-value Pr > F
Model 51 25.3574 0.4972 1.83 0.0006* Error 507 137.4437 0.2710 Total 558 162.8012 Model Breakdown: School category 1 2.6808 2.6808 6.25 0.0190* Class (EDUCA) 26 11.1442 0.4286 1.58 0.0352* Age 2 0.0140 0.0070 0.03 0.9744 Gender 1 0.0550 0.0550 0.20 0.6525 Location 3 0.5568 0.1856 0.68 0.5617 Information source 3 1.5065 0.5021 1.85 0.1367 Parents’ occupation 3 0.4487 0.1495 0.55 0.6471 Parents’ degree 3 1.0577 0.3525 1.30 0.2735 DE 1 by DE 9 6 3.6665 0.6110 2 25 0.0371* DE 2 by DE 8 3 2.1428 0.7142 263 0.0492* R-Square = 0.1557
Note: ‘ Significant at .05 alpha level DE1: Age, DE2: Gender, DE8: Parents’ occupation DE9: Parents’ highest degree DE1 by DE9: Interaction of age and parents’ highest degree DE2 by DE8: Interaction of gender and parents’ occupation 123 Over and above other factors in the model, it was shown (Table 52) that the school category accounted for a significant (p < 0.0190) amount of variability of mean scores in respondents' attitudes toward natural resources issues. Interactions between respondents’ age category and parents' level of education, and gender and parents' occupation were observed.
Table 53 LSMeans of DE 1 and DE 9 bv Attitudes toward Natural Resources Issues
Level of Std. Error LSMean DE 1 DE 9 n LSMean LSMean number
1 1 71 3.41 0.09 1 1 2 38 3.38 0.10 2 1 3 14 3.50 0.16 3 1 4 25 3.34 0.13 4 2 1 144 3.36 0.07 5 2 2 66 3.40 0.08 6 2 3 47 3.36 0.10 7 2 4 45 3.52 0.10 8 3 1 48 3 56 0.10 9 3 2 22 3.11 0.13 10 3 3 16 3.54 0.14 11 3 4 23 3.38 0.12 12
Note: LSMean: Adjusted or Least Square Mean DE1: Age, DE9: Respondents’ parents’ highest degree LSMean number: Any combination of adjusted means corresponding to different levels of DE1 and D9 NATURAL RESOURCES FIGURE 7: INTERACTION OF AGE AND PARENTS’ DEGREE PARENTS’ AND AGE OF INTERACTION 7: FIGURE 4 -i 3.41
3.36 2 3 2 1
356
3.30 PARENTS’DEGREE 3.50
3.36 3.54 3.34
353
3-33 4. Other 3.College . ih School High 2. . Elementary 1. ■ ■ 25 -2 3 2 0 School AGE DEGREE: 21-22 10-20 10-20 124
Table 54
Probability Matrix for Means in Table 53
i / j 1 2 3 4 5 6 7 8 9 10 11 1 2 0.7957 • 3 0.6060 0.4733 • 4 0.6323 0.8241 0.4038 • 5 0.5472 0.8933 0.4111 0.8990 • 6 0.9739 0.7841 0.5659 0.6376 0.6492 • 7 0.7199 0.9150 0.3912 0.9001 0.9850 0.7088 t 8 0.2988 0.2516 0.9018 0.2013 0.0836 0.2862 0.2096 * 9 0.1429 0.1757 0.7480 0.1337 0.0246* 0.1933 0.1436 0.7455 • 10 0.0570 0.0783 0.0476* 0.1733 0.0874 0,0299* 0.1016 0.0059 * 0,0045* • 11 0.4408 0.3182 0.8434 0.2895 0.2645 0.3897 0.2427 0.9215 0.9060 0.0207* • 12 0.8065 0.9981 0.5179 0.8403 0.8952 0.8243 0.9248 0.2827 0.1916 0.1159 0.3720
Note: * Significant at the .05 alpha level
i and j represent any combination of LSMean numbers in Table 53 126 As reported in Fig 7, among respondents who selected elementary school as their parents’ highest degree, 23 to 25 year olds showed a more positive attitude toward natural resources than did their 21 to 22 year old counterparts, and 23 to 25 year olds who reported that their parents have high school as the highest degree. Eighteen to twenty year old respondents whose parents had college degrees outscored 21 to 22 year old students who reported their parents had a high school degree. Twenty three to twenty live year old respondents who reported their parents were college graduates had a more positive attitude toward natural resources issues than did those those who were 23 to 25 years old, but had high school graduate parents (Tables 53, 54, and Fig 7).
Table 55 LSMeans of DE 2 and DE 8 bv Attitudes toward Natural Resources Issues
Level of Std Error LSMean DE 2 DE 8 n LSMean LSMean number
1 1 11 3.54 0.18 1 1 2 96 3.40 0.08 2 1 3 177 333 0.07 3 1 4 81 3.44 0.08 4 2 1 19 3.38 0.15 5 2 2 66 343 0.10 6 2 3 75 3.50 0.09 7 2 4 34 3.24 0.11 8
Note: LSMean = Adjusted or Least Square Mean DE2: Gender, DE8: Respondents’ parents’ occupation LSMean number: Any combination of adjusted means corresponding to different levels of DE2 and DE8 ATTITUDES TOWARD
IUE8 ITRCINO EDRAD PARENTS' INTERACTIONOCCUPATIONOFGENDER AND FIGURE 8: NATURAL RESOURCES 3 4 3 2 AET’ OCCUPATION PARENTS’ OCCUPATION MALE ■ FEMALE ■ . Other 4. Farmer 3. . v servant Gvt 2. . v official Gvt 1. 127 128
Table 56 Probability Matrix for Means in Table 55 i / j 1 2 3 4 5 6 7 8 1 • 2 0.4954 • 3 0.2897 0.4181 • 4 0.6049 0.7735 0.1974 • 5 0.4917 0.8786 0.7547 0.7599 • 6 0.6109 0.8454 0.4111 0.9637 0.7666 • 7 0.8594 0.4631 0.0777 0.5717 0.5104 0.5811 * 8 0.1567 0.1747 0.4374 0.0930 0.4088 0.1311 0.0287 * •
Note: * Significant at the .05 alpha level i and j represent any combination of LSMean numbers in Table 55 129 There was a difference between female respondents who reported that their parents were farmers and those who did not specify their parents’ occupation. Those with farmer parents scored higher than those who did not specify their parents’ occupation. No other significant relationships were found between different respondent groups with regard to attitudes toward natural resources ( see Tables 55, 56, and Figure 8). 130
Table 57
ANOVA of Water Quality Attitude Mean Scores bv independent Variables
Source df SS MS F-value Pr> F
Model 54 54.8724 1.0161 4.77 0.0001* Error 501 106.6505 0.2126 Total 555 161.5229 Model Breakdown: School category 1 7.9715 7.9715 7.46 0.0112* Class (EDUCA) 26 27.7824 1.0685 5.02 0.0001* Age 2 0.1209 0.0604 0.28 0.7529 Gender 1 0.0365 0.0365 0.17 0.6786 Location 3 1.2073 0.4024 1.89 0.1302 information source 3 0.0897 0.0299 0.14 0.9357 Parents’ occupation 3 0.6878 0.2292 1.08 0.3583 Parents’ degree 3 0.0785 0.0261 0.12 0.9466 DE 1 by DE 8 6 3.3323 0.5553 2.61 0.0169* DE 1 by DE 9 6 23255 0.3875 1.82 0.0931 R-Square = 0.3397
Note: Significant at the .05 alpha level Class (EDUCA): Any particular thirteenth grade classroom subjects DE1: Age, DE8: Parents’ occupation, DE9: Parents’ highest degree DE1 by DE8: Interaction of age and parents' occupation DE1 by DE9: Interaction of age and parents’ highest degree 131 Over and above other independent variables in the model, it was observed that school category accounted for a significant (p < 0.0112) amount of the variability of mean scores in respondents’ attitudes toward water quality issues. An interaction between DE 1 (age category) and DE 8 (parents' occupation) was also found.
Table 58 LSMeans of DE 1 and DE 8 bv Attitudes toward Water Quality Issues
Level of Std. Error LSMean DE 1 DE 8 n LSMean LSMean number
1 1 7 3.76 0.20 1 1 2 50 3.83 0.09 2 1 3 75 4.01 0.11 3 1 4 15 3.62 0.13 4 2 1 17 3.71 0.14 5 2 2 79 3.93 0.08 6 2 3 129 3.84 0.07 7 2 4 76 3.90 0.07 8 3 1 6 4.29 0.24 9 3 2 33 3.91 0.10 10 3 3 47 3.57 0.11 11 3 4 22 3.72 0.12 12
Note: LSMean: Adjusted or Least Square Mean DE1: Age, DE9: Parents’ highest degree LSMean number: Any combination of adjusted means corresponding to different levels of DE1 and DE9 ATTITUDES TOWARD IUE9 ITRCINO G N PARENTS'OCCUPATION INTERACTION OFAGEAND 9: FIFURE PRENTS'OCCUPATION 3.Farmer 25 -2 3 2 0 B ■ 4.Other AGE 1.official Gvt 2.Gvt servant OCCUPATION 21-22 18-20 132
Table 59
Probability Matrix of Means in Table 58
i/j 1 2 3 4 5 6 7 8 9 10 11 12
1 2 0.7496 • 3 0.3094 0 2263 * 4 0.5819 0.1956 0.0101* • 5 0.8261 0.4533 0.0849 0.6647 * 6 0.4272 0.3486 0.4916 0.0369* 0.1440 • 7 0.6868 0.8760 0.1733 0.1281 0.4089 0.4459 • 8 0.5115 0,5126 0.3574 0.0588 0.2225 0.7577 0.5127 • 9 0.0906 0.0674 0.6647 0.0142* 0.0321* 0.1432 0.0703 0.1100 • 10 0.4946 0.5165 0.0369* 0.0759 0.2240 0.8958 0.5691 0.9010 0.1328 • 11 0.4338 0.0732 0.1281 0.0793 0.4700 0.0065* 0.0338* 0.0107* 0.0137" 0.0437* * 12 0.8641 0.4525 0.0588 0.5825 0.9447 0.1182 0.3548 0.1682 0.0437* 0.2434 0.2701 •
Note: * Significant at the .05 alpha level
i and j represent any combination of LSMean numbers in Table 58 134 Significant differences were found between respondents' attitudes about water quality issues. Those students whose parents were farmers scored significantly higher compared to respondents whose parents were government officials, government servants or those who did not specify their parents occupation. Eighteen to twenty year old respondents whose parents were farmers did better than 18 to 20 year old students whose parental occupation was not specified. Twenty one to twenty two year old respondents scored higher than those with farmer parents and who were 23 to 25 years old. Twenty three to twenty five year old respondents also did better on the water quality section than their 18 to 20 year old counterparts. When considering parents who were government officials, 23 to 25 year old students had a more positive attitude toward water quality than 18 to 20 year old respondents who did not specify their parents’ occupation, 18 to 20 year old students whose parents were government officials, 23 to 25 year old students whose parents were farmers, and 23 to 25 year old respondents who did not specify their parents' occupation. Twenty one to 22 year old students whose parents were government servants scored significantly higher on the water quality issues compared to 18 to 20 year old students who did not specify their parents' occupation, and 23 to 25 years of age for those respondents whose parents were farmers. Students who reported that their parents were government servants and who were 23 to 25 years old had more positive attitudes toward water quality issues than 23 to 25 year old respondents whose parents were farmers. Twenty one to 22 year old students who did not specify their parents’ occupation scored significantly higher on issues relative to attitude 135 about water quality than 23 to 25 year old respondents whose parents were farmers (see Tables 58, 59, and Fig 9).
Table 60 ANOVA of Ecological Principles Attitude Mean Scores bv Independent Variables
Source df SS MS F-value Pr > F
Model 47 37.9458 0.8073 3.54 0.0001 * Error 509 116.1751 0.2284 Total 556 154.1209 Model Breakdown: School category 1 6.0170 6 0170 8.07 0.0086* Class (EDUCA) 26 19.3762 0.7452 3.27 0.0001* Age 2 0.5370 0.2685 1.18 0.3092 Gender 1 0.7436 0.7436 3.26 0.0717 Location 3 1.6782 0.5594 2.45 0.0627 Information source 3 0.7076 0.2358 1.03 0.3773 Parents' occupation 3 0.6492 0.2164 0.95 0.4170 Parents’ degree 3 0.0471 0.0157 0.07 0.9765 DE 1 by DE 2 2 1.4176 0.7088 3.11 0.0456* DE 2 by DE 4 3 1.5307 0.5102 2.24 0.0832 R-Square = 0.2462
Note: * Significant at the .05 alpha level Class (EDUCA): Any particular thirteenth grade classroom subjects DE1: Age, DE2: Gender, DE4: Residential location DE1 by DE2: Interaction of age and gender DE2 by DE4: Interaction of gender and residential location 136 Over and above the other factors in the model, it was observed that school category accounted for a significant {p < 0.0086) amount of variability of mean scores in the in respondents' attitudes toward ecological principles. An interaction (p < 0 0456) of DE 1 (age category) and DE 2 (gender) was also found (see Table 60).
Table 61 LSMeans of DE 1 and DE 2 bv Attitudes toward Ecological Principles
Level of Std. Error LSMean DE 1 DE 2 n LSMean LSMean number
1 1 73 3.78 0.08 1 1 2 74 3.99 0.09 2 2 1 209 3.80 0.06 3 2 2 92 3.80 0.08 4 3 1 82 3.69 0.07 5 3 2 27 3.96 0.11 6
Note: LSMean: Adjusted or Least Square Mean DE1: Age, DE2: Gender LSMean number: Any combination of adjusted means corresponding to different levels of DE1 and DE2 MALE FEMALE 138
Table 62
Probability Matrix for Means in Table 61
i / j 1 2 3 4 5 6
1 •
2 0.0783 •
3 0.8070 0.0571 «
4 0.8401 0.0207* 0.9573 •
5 0.3149 0.0064* 0.1068 0.2836 •
6 0.1931 0.7924 0.1860 0.1466 0.0392* •
Note : 'Significant at the .05 alpha level i and j represent any combination of LSMean numbers in Table 61
Eighteen to twenty year old female respondents had more positive attitudes toward ecological principles than did females who were 21 to 22 years old. Females 21 to 22 years of age, however, scored significantly higher than males who were 23 to 25 years old; and finally, females who were 23 to 25 years old outscored males of the same age category (see Tables 61, 62, and Fig 10). 139
Table 63 ANOVA of Global Issues Attitude Mean Scores bv Independent Variables
Source df SS MS F-value Pr > F
Model 51 49.2405 0.9655 4.45 0.0001* Error 505 109.6851 0.2171 Total 556 158.9256 Model Breakdown: School category 1 1.2014 1.2014 1.04 0.3164 Class (EDUCA) 26 29.9340 1.1513 5 30 0.0001* Age 2 2.3005 1.1502 5.30 0.0053* Gender 1 0.1336 0.1336 0.62 0.4331 Location 3 0.6533 0.2177 1.00 0.3913 Information source 3 0.4066 0.1355 0.62 0.5996 Parents' occupation 3 0.6459 0.2153 0.99 0.3966 Parents’ degree 3 0.2561 0.0853 0.39 0.7580 DE 1 by DE 4 6 3.3128 0.5521 2.54 0.0196* DE 2 by DE 9 3 2.0527 0.6842 3.15 0.0247* fl-Square = 0.3098
Note: * Significant at the .05 alpha level Class (EDUCA): Any particular thirteenth grade classroom subjects DE1: Age, DE2: Gender, DE4: Location. DE9: Parents’ degree DE1 by DE4: Interaction of age and residential location DE2 by DE9: Interaction of gender and parents' degree 140 Table 63 reveals the existence of two significant interactions between age category and respondents’ residential location {p < 0.0196), and between gender and parents’ level of education (p < 0.0247). No main effects were detected.
Table 64
LSMeans of DE 1 and DE 4 bv Attitudes toward Global Environmental Issues
Level of Std. Error LSMean DE 1 DE 4 n LSMean LSMean number
1 1 31 3.56 0 09 1 1 2 6 3.92 0.21 2 1 3 99 3.30 0.06 3 1 4 11 3.11 0.15 4 2 1 55 3.46 0.07 5 2 2 22 3.57 0.11 6 2 3 204 3.40 0.05 7 2 4 20 3 50 0.11 8 3 1 14 3.34 0.13 9 3 2 4 3.25 0.25 10 3 3 73 3.49 0.06 11 3 4 17 3.41 0.12 12
Note: LSMean: Adjusted or Least Square Mean DE1: Age, DE4. Residential location LSMean number: Any combination of adjusted means corresponding to different levels of DE1 and DE4 ATTITUDES TOWARD GLOBAL ISSUES FIGURE INTERACTION 11: OF AGE AND LOCATION LOCATION .9 3.50 3.49 3.41 4. Farm 4. 1. City 3.Rural . Suburban 2. LOCATION ■ 18-20 ■ E3 AGE 141 23-25 21-22
Table 65
Probability Matrix for Means in Table 64 Ho: LSMean (h - LSMean (i)
i/j 1 2 3 4 5 6 7 8 9 10 11 i1 2 0.0061* • 3 0.0113* 0.0891 • 4 0.0094* 0.4654 0.2319 • 5 0.3754 0.0150* 0.0601 0.0337* * 6 0.9514 0.0052* 0.0266 0.0139* 0.3874 • 7 0.1104 0.0265* 0.0942 0.0590 0.4591 0.1400 * 8 0.6839 0.0140* 0.0971 0.0318* 0.7469 0.6613 0.4001 • 9 0.1515 0.0865 0.7507 0.2418 0.3956 0.1683 0.6349 0.3360 • 10 0.2508 0.2877 0.8713 0.6243 0.4262 0.2429 0.5603 0.3652 0.7599 • 11 0.5106 0.0106* 0.0154 0.0196* 0.7410 0.5160 01934 0.9197 0.2836 0.3653 • 12 0.3161 0.0439* 0.3864 0.1172 0.7215 0.3185 0.9509 0.5674 0.6872 0.5748 0.5583
Note: * Significant at the .05 alpha level
i and j represent any combination of LSMean numbers in Table 64 143 Fifteen significant interactions were found between the levels of DE 1 (age category) and the levels of DE 4 (respondents’ residential location). City residents between the age of 18 to 20 scored higher on issues relating to global environmental concerns than suburban and rural (not on a farm) respondents of the same age category. City residents between the age of 20 to 22 also outscored 18 to 20 year old suburban and farm resident peers. Suburban respondents between 18 to 20 years of age performed at a lower level on issues pertaining to global issues than rural (not on a farm) 21 to 22 year olds, on a farm respondents between 21 to 22 years of age. rural (not on a farm) 23 to 25 years of age, and on a farm 23 to 25 year olds. Suburban 20 to 22 year olds, however, had more positive attitudes toward global environmental concerns than suburban 18 to 20 year olds, rural (not on a farm) 18 to 20 year olds, and on a farm residents 18 to 20 years old. Rural (not on a farm) residents 23 to 25 years old scored significantly higher than 18 to 20 year olds rural (not on a farm), and on a farm residents of the same age group. On a farm residents 21 to 22 years of age also outscored on a farm counterparts 18 to 20 years old (see Tables 63. 64. 65, and Fig 11). 144
Table 66 LSMeans o1 DE 2 and DE 9 bv Attitudes toward Global Environmental Issues
Level of Std. Error LSMean DE 2 DE 9 n LSMean LSMean number
1 1 181 3.31 0.07 1 1 2 78 342 0.08 2 1 3 45 3.30 0.09 3 1 4 60 3.32 0.08 4 2 1 80 3.38 0.09 5 2 2 48 3.24 0.10 6 2 3 32 3.57 0.11 7 2 4 33 3.36 0.10 8
Note: LSMean: Adjusted or Least Square Mean DE2: Gender, DE9: Parents’ highest degree LSMean number: Any combination of adjusted means corresponding to different level of DE2 and DE9 FIGURE 12: INTERACTION OF GENDER AND PARENTS' DEGREE PARENTS' AND GENDER OF INTERACTION 12: FIGURE ATTITUDES TOWARD GLOBAL ISSUES 3.31
338 AET' DEGREE PARENTS' . Elementary1. . ih School High 2. . College 3. 4. 4. Other School DEGREE: 145 FEMALE MALE
146 Table 67
Probability Matrix for Means in Table 66
i / j 1 2 3 4 5 6 7 8 1 • 2 0.2314 * 3 0.7771 0.1863 • 4 0.8910 0.2964 0.7120 • 5 0.4203 0.7067 0.4517 0.5793 • 6 0.5633 0.1107 0.7797 0.5048 0.2453 • 7 0.0619 0.2618 0.0327* 0.0785 0.1552 0.0126* * 8 0 6770 0.5914 0.5543 0.7595 0.8552 0.3466 0.1296
Note: * Significant at the .05 alpha level i and j represent any combination of LSMean numbers in Table 66
Considering Table 63, 66, 67, and Fig 12, significant differences appeared between male and female respondents and among female respondents alone. Females whose parents held a college degree had higher attitude scores on global environmental issues than did males who reported their parents had college degrees. Females whose parents were college degree holders outscored females whose parents had high school degrees. No significant difference was found between male respondents regardless of the kind of degrees their parents held. CHAPTER V SUMMARY DISCUSSION, IMPLICATIONS, AND RECOMMENDATIONS
Summary The main purpose of this research was to explore, describe, and compare environmental knowledge and attitudes toward the environment held by thirteenth grade General and Technical Education students in the Republic of Burundi. To date, no attempt to assess students1 environmental knowledge levels and/or their attitudes toward the environment has been initiated in Burundi. In terms of school curricula, no materials or other resources are or have been allocated specifically to environmental education. Therefore, students at the thirteenth grade level, their environmental knowledge, their attitudes toward the environment and possible relationships between their knowledge and their attitudes with selected demographic variables (age, gender, residential location, source of environmental information, school category, parents’ occupation and level of education) were investigated in this research. Based upon previous research studies and their findings, the Burundi Environmental Policy Guidelines (1991), and the Burundi School Curriculum Guidelines (1980; 1988), five issues and/or problems have been considered in this study: (1) human population, (2) water quality, (3) natural resources, (4) ecological principles, and (5) global environmental issues. 147 148 With regard to the above selected environmental issues and/or problems, the following objectives have been employed: 1. To assess and compare the levels of environmental knowledge held by two selected samples of thirteenth grade General and Technical Education students in the Republic of Burundi.
2. To assess and compare the attitudes toward the environment held by two selected groups of thirteenth grade General and Technical Education students in the Republic of Burundi.
3. To investigate possible relationships among the respondents' environmental knowledge levels and their attitudes toward the environment for the two categories of schools.
4. To investigate any variation between the respondents’ environmental knowledge levels related to their age, gender, residential location, source of environmental information, school category, parents’ occupation and level of education.
5. To examine any variation between the respondents’ attitudes toward the environment due to their age, gender, residential location, source of environmental information, school category, parents’ occupation and level cf education. In this descriptive survey research, the researcher utilized three self-developed instruments to collect data (see Appendix A): 1 A knowledge instrument comprising a 25 item self-administered multiple-choice test; 2. An attitudinal instrument utilizing a Likert Scale of 25 items on a continuum from Strongly Disagree “1" to Strongly Agree “5” for each statement; 3. An 8 item demographic instrument which allowed respondents to check the answers that apply to their specific and individual characteristics; Prior to the data collection phase, validity and reliability of the 149 instruments were tested in the United States and Burundi. The validity of the instrument was determined using a panel of experts in the United States, and a panel of experts and a field test in Burundi. Instrument reliability was established using the method of rational equivalence reliability. The Kuder-Richardson (KR20) formula was used for the knowledge instrument and Cronbach’s Alpha was utilized for the attitude instrument yielding the rational reliability values of 0.63 and 0.61, respectively. Thirteenth grade General and Technical Education students were identified as the target population for this study. The target population was about 2,000 students; however, because it could be very time consuming and expensive to collect data from the entire target population; data were collected using a multistage sampling technique advocated by Fowler (1988) . probability probability overall of selection X of selection = probability at stage I at stage II selection
Because of the political instability in the country during the data collection period, the sample sizes for both the General and Technical Education were not reached in the desired proportion (50% for each school category). Twenty eight schools (97%) participated in the data collection instead of 29 schools planned. Of the 28 schools, 20 (71.4%) were General Education schools with an overall sample of 411 students (73.4%). Only eight Technical Education schools (28.6%) participated in the data collection with an overall sample of 148 students (26.4%). Prior to the data collection phase, the researcher sent a letter to the Department of Primary and Secondary School (see Appendix D) requesting authorization to use the thirteenth grade General and Technical Education 150 students as data sources. The letter was written in French because French is the official and main instructional language in Burundi. In order to ensure the validity and the reliability of the data, students who had participated in pilot or field testing were excluded from the data collection phase. Data collection with students were conducted by the researcher and two trained interviewers through interviews (face to face) and self-administered questionnaires (respondents’ written responses). Having not yielded the anticipated data, the interview schedule has been removed from data analysis. The analysis of data involved the use of descriptive and inferential statistics. Frequencies, percentages, and measures of central tendency were used to describe the samples. Pearson Product Moment Correlation coefficients were computed to show possible associations or relationships between respondents’ knowledge of and attitudes toward the environment. A t-test was used to compare the attitudes and knowledge mean scores between General and Technical Education respondents, and an analysis of variance (ANOVA) was also computed to analyze the variability of the differences in knowledge or attitudes of students possessing different demographic characteristics on the average. Summary, conclusions, implications, and recommendations were also formulated. The summary section highlights different section contents and their structures. The conclusion section summarizes the findings derived from the data analysis. The implications section includes the major implications pertaining to the results of the present research. The recommendations section underlines suggestions for practice and recommendations for further research endeavors. 151 Discussion The primary purpose of the present research was to assess whether thirteenth grade General and Technical Education students differed in their knowledge of and attitudes toward the environment, and whether significant relationships and/or differences existed between respondents’ environmental knowledge levels and attitudes toward the environment. Respondents’ knowledge and attitudes toward the environment were also assessed with regard to independent variables of age category, gender, residential location, source of environmental information, school category, parents’ occupation, and levels of education were considered. Roth and Batista (1990), Kellert and Berry (1984), Kellert and Westervelt (1983), Atwater; Salwen, and Anderson (1985), Bowman (1978), Fortner and Lyon (1985), Hanaford (1977), Dona (1969), Hardy and Fox (1976), Van Liere and Dunlap (1980) had found that the levels of respondents’ environmental knowledge and attitudes were explained by the above demographic variables in different ways. Without considering the effects of independent variables mentioned above, some minor differences in students’ environmental knowledge and attitudes toward the environment were observed between General Education and Technical Education thirteenth grade students in the Republic of Burundi (see Tables 11 and 21). 152 Environmental Knowledge Levels for General and Technical Education Respondents
On the knowledge instrument, participants seemed to be more knowledgeable on issues relative to natural resources, followed by issues pertaining to human population, global environmental issues, and water quality, respectively (see Tables 19 and 20.) Although the respondents’ mean scores were very close, a statistically significant difference (p = 0.0030) was found between General and Technical Education respondents' environmental knowledge mean scores (see Tables 11, 18, 19, and 20). It was also established that a significant difference (p < 0.0329) existed between the two group mean scores pertaining to natural resources. No significant differences were found between group means on the issues dealing with human population, water quality, ecological principles, and global environmental concerns (see Table 20). In addition, the respondents’ environmental knowledge mean scores were relatively low and highly variable for both types of schools (see Table 13 through Table 19). These results were consistent with findings reported by Perkes (1973), Batista and Roth (1990), they found low respondents’ environmental knowledge levels in their respective studies. The fact that the Burundi System of Education does not include environmental units in school curricula may partially explain the low levels of respondents’ environmental knowledge observed in this study. This explanation is supported by Buethe s (1987) finding, in his study on 153 environmental literacy of Indiana teachers. He concluded that if teachers are not intellectually equipped to deal with environmental problems and/or issues, their students will not acquire the competence and the skills they need to act responsibly in resolving environmental problems. The low environmental knowledge and attitude scores encountered in this study may be the result of teachers little emphasis on environmental topics in Biology, Chemistry, Geography, and Agriculture Education. These subject matters occasionally deal with some environmental problems and/or issues such as human population, land use and misuse, pesticides in the environment, biodiversity, and the like. These results, therefore, highlight the need for the Burundi System of Education to include environmental units in school curricula at all levels of education. Environmental Attitude Levels for General and Technical Education Respondents
On the attitude instrument, respondents’ scores were highly variable ranging from 7 percent to 89.9 percent. The results revealed that, on the average, General Education students had more positive attitudes toward environmental issues included in this study than did their Technical Education peers. A significant difference between respondents' attitude scores was found for the General and Technical Education groups with the General Education respondents outscoring the Technical Education students on the overall and on all five environmental attitude subscales (see Table 30). Issues which revealed significant differences were about water quality, ecological principles,and global 154 environmental concerns. No significant differences were found between respondents’ attitude scores with regard to human population and natural resources issues (see Table 29). Although a statistically significant difference existed between the attitude mean scores between General and Technical Education respondents, it is shown in Table 21 and Table 29 that those mean scores were almost the same on the overall and for the five environmental attitude subscales. Therefore, it can be concluded that .practically, General Education students’ attitudes toward environmental issues included in this study were not very different from those of Technical Education counterparts. The major differences encountered between the two groups' environmental attitudes may be influenced by students’ knowledge from other school subject matters, personal experience, or individual characteristics. This observation may suggest that school audiences in Burundi should be prepared to learn from informal learning settings and to blend formal learning with out-of-school learning because informal learning media such as radio, TV, songs, exhibitions, and other extra curricula activities can reach bigger and various audiences than formal education.
Relationships Between Environmental Knowledge and Attitudes toward the Environment Prior studies in the field of environmental education focused interests on investigating possible relationships between respondents’ environmental knowledge and their attitudes toward the environment, Batista and Roth (1990), Fortner and Mayer (1983), Manning (1991), Perkes (1973), Christianson and Arcury (1993), Hardy and Fox (1976), Karst (1985), Cohen (1973), and others. 155 For General Education respondents, low, significant, and positive relationships were found for the total scores, human population, ecological principles, and global environmental issues in the knowledge section. No significant relationships were observed between respondents’ environmental knowledge and attitudes on the issues related to water quality and natural resources. These results are consistent with findings reported by Fortner and Mayer (1983). In their study of Ohio students’ knowledge and attitudes about the oceans and Great Lakes, these researchers found that when specific items were analyzed (as was the case in this study) in relation to knowledge scores (as was the case in this study), high scores, on knowledge items were associated with positive attitudes. The results of the present study also agreed with lozzi’s (1989) findings. He pointed out that several studies showed a positive relationship between environmental knowledge and attitudes, while others revealed no relationship at all, and still others showed a negative relationship between environmental knowledge and attitudes. Cohen (1973), on the other hand, compared the environmental attitudes of two groups of high school students who had different levels of environmental knowledge. He found that groups with more knowledge had different attitudes and were more willing to express environmental attitudes than were their less knowledgeable counterparts. The results of this study are consistent with Cohen’s findings. For the Technical Education respondents, a low, significant, and positive association between respondents' environmental knowledge and attitudes was observed for water quality issues. A negative, significant, and low association was seen for ecological principles. No significant relationship was found for 156 total scores, human population, natural resources, or global environmental issues. These results were consistent with the findings of lozzi (1989), Eyers (1975), Fortner and Mayer (1983). Although some significant relationships between respondents’ environmental knowledge and attitudes were demonstrated, the strengths of those associations were so low that they can be practically considered negligible ( see p. 87). Because of the political instability in Burundi and financial constraints during the data collection phase, the researcher was unable to meet the predetermined sample sizes for both General and the Technical Education schools. The present research utilized only 411 students from General Education and 148 students for the Technical Education settings. It would therefore be recommended to replicate the present study with bigger sample sizes and more representation of Burundi General and Technical Education audiences from all natural regions. Financial support also needs to become available to assist the growth of specific projects dedicated to enhance students’ environmental awareness, knowledge, attitudes, and positive actions in Burundi.
Variation Between the Respondents' Environmental Knowledge in Relation to Independent Variables
When sociodemographics (independent variables) were considered, minor significant variations and/or relationships were found between respondents’ knowledge of human population issues and global environmental concerns by student gender, age, residential location and parents’ occupation. An analysis of Variance (ANOVA) was utilized in order to examine any 157 differences in environmental knowledge mean scores of students possessing different demographic characteristics. No significant main effects or interactions were found in the overall group of mean scores. However, the model employed revealed a significant amount of variability (p < 0.0001). probably due to differences in mean scores within schools and differences in sample sizes. Tables 38 and 42 reveal that neither respondents1 type of school or other demographic variables included in the study accounted for a significant amount of the variability in the knowledge of water quality issues and ecological principles. Significant interactions were found for human population issues, and global environmental issues. On the knowledge of human population issues, suburban males scored higher on the average than rural (not on a farm) male residents. This result is not supported by Christianson and Arcury (1993) findings on similar issues. City female residents outscored rural and farm residents, a result not consistent with Fortner and Mayer (1983) who found that regional differences occurred primarily among males. City female residents also scored higher on knowledge of human population issues than did rural (not on a farm) and farm male residents. Male respondents whose parents were farmers appeared to be more knowledgeable about human population issues than those who did not specify their parents' occupation. Significant differences were not found between female respondents on human population issues with regard to their parents’ occupation. The gender differences observed in this section about the knowledge of population issues may suggest that sex role In the Burundi culture is an 158 important factor that curriculum planners and decision-makers should take into account in the development of environmental education in Burundi. Women in Burundi are assigned almost ail the domestic works The high scores observed for females in this study are probably linked with female respondent experiences in their every day lives and their societal position. On the knowledge of global environmental issues, suburban respondents who are 21 to 22 years old scored higher than their 18 to 20 year old suburban peers, and higher than 21 to 22 year old and 23 to 25 year old farm residents. City residents 21 to 22 years of age appeared more knowledgeable about global environmental issues than any other age group in that category. Twenty three to 25 year old farm residents performed better on the global environmental issues section than did city residents of the same age category and farm residents 21 to 22 years old. These results are supported by Weisenmayer and Rubba. (1984). They pointed out that individuals living in rural areas are more knowledgeable about environmental problems than are individuals living in urban areas. It appears that students had different knowledge levels depending on their age category and residential location. Suburban and rural (on a farm) residents between 21 and 22 years old were more knowledgeable on global environmental issues than any other group of respondents. In general, the respondents had low scores on the knowledge of issues related to global environmental concerns except for item 23 dealing with DDT. More than 85% General and Technical Education students got the item correct (see Table 17). This pesticide is extensively used for crop pest control in rural 159 and suburban, it is therefore understandable that students living in those areas would have a better knowledge of that product. Twenty one to 22 age category respondents were the most represented in the overall study samples (54 3% for General Education, 53.4% for Technical Education). Eighteen to 20, and 23 to 25 age categories were less represented groups in the study. Although significant differences were found between respondents’ knowledge levels pertaining to human population and global environmental issues, these differences were very low negating any meaningful generalization of these findings to the participating populations except from a statistical standpoint.
Variation Between the Respondents’ Environmental Attitudes in Relation to Independent Variables
When demographics (independent variables) were considered, significant variations and/or relationships became evident between respondents’ attitudes toward the environment and independent variables of age, gender, residential location, source of environmental information, type of school, parents' occupation and level of education. An analysis of variance (ANOVA) was employed in order to investigate any difference in environmental attitude scores of students possessing different demographic variables (see Tables 46, 49, 52, 57, 60, and 63.) Main effects were detected for school category, natural resources, water and ecological principles. A main effect was observed for respondents’ residential location in attitudes toward human population issues. 160 Female respondents 23 to 25 years of age had more positive attitudes on the overall environmental attitude instrument than did 18 to 20 year old males, 21 to 22 year old females, and 23 to 25 years old males. Since environmental education, which is believed to induce positive environmental attitudes is not included in Burundi school curricula, the respondents' differences in environmental attitudes observed in this section may be attributed to differences in individual life experiences, personal characteristics, or interests toward environmental issues. Kostka (1976) reported that life experiences, such as the environment in which a person grew up, have been found to correlate with environmental attitudes. This may be true for this study, females being the most exposed to environmental disturbances in Burundi, and 23 to 25 year old respondents who are supposed to have more experience than 18 to 20 and 21 to 22 year old peers. The sex role component may also have been an important influence on female attitudes because females in Burundi are responsible for traditional agriculture practices which are harmful to the environment, slash and burn methods of land use, sewage in drinking water, etc. The fact that the 23 to 25 age category is the least represented in the study samples (see Table 4), but the most significant on the overall respondents' attitudes, is probably due to more experience held by the respondents in that category. Male respondents who cited parents as their major source of environmental information appeared to have more positive attitudes toward human population issues than did females who reported radio or TV as their major sources of environmental information. Females with classroom 161 instruction as a major source of information had higher positive attitudes toward human population issues than did females with radio or TV as major sources, These findings differ from those of Fortner and Mayer (1983) who found that TV was selected frequently as being the most important source of information about oceans and Great Lakes. In Burundi, very few people own a radio or a TV compared to the total population, and even when a TV or a radio is owned by a family or a school institution, environmental programs are rarely broadcast. This may explain why students chose radio or TV least as their sources of environmental information. Since this is the case, Burundi should explore other channels to environmentally educate the youth and the general public. The best avenue seems to be school instruction. On the issues relative to natural resources, it was shown that the school category accounted for a significant (p < 0.0190) amount of variability in attitude mean scores. Although the attitude mean scores of the two types of schools were very close, the General Education (LSMean = 3.49) respondents appeared to have more positive attitudes toward natural resources than the Technical Education (LSMean = 3.32) respondents , on the average. Interactions between respondents1 age category and the parents’ level of education, and gender and parents’ occupation were also observed. These findings are consistent with Perkes (1973) results on a study about student environmental knowledge and attitudes. Students whose parents had elementary school as their highest degree and were 23 to 25 years old had more positive attitudes toward natural resources than did 21 to 22 year old students of the same category, and 23 to 25 year old students who selected high school as their parents’ highest degree. 162 Respondents who selected college as their parents' highest degree and who were 18 to 20 years old scored higher on attitudes toward natural resources than did those who were 21 to 22 years old and selected high school as their parents’ highest degree. Twenty three to 25 year old students with college graduate parents had more positive attitudes toward natural resources than did students of the same age category but with high school graduate parents. Van Liere and Dunlap (1980) demonstrated that the level of education was related to information, the greater amount of education, the greater amount of environmental information. Those who were active politically also knew more about the environment. It is therefore understandable that students whose parents were college graduates scored higher than any other groups of respondents. Those parents hold a certain amount of information about the environment, they are active politically, and can afford to purchase radios and televisions which are supposed to constitute major sources of environmental information for their children. Females who identified farmers as their parents’ occupation scored significantly higher on attitudes toward natural resources than did those who did not specify their parents’ occupation. Since different audiences appear to have different attitudes about environmental issues, in depth assessment of curriculum needs appropriate for each group is needed. Over and above other independent variables, school category accounted for a significant (p < 0.0112) amount of the variability in the respondents’ attitude scores on water quality issues. The General Education respondents (LSMean = 3.99) outscored their Technical Education (LSMean = 3.70) peers. 163 An interaction between age category and parents’ occupation was also found. Respondents 18 to 20 years old who had chosen “farmer" as their parents’ occupation had a more positive attitude toward water quality issues than did students who did not specify their parents’ occupation. Twenty one to 22 year old students with farmer parents also outscored 23 to 25 year old students of the same group. These observations suggest that students whose parents are farmers have more opportunity to be in touch with the natural environment compared to other respondent groups. Students who reported that their parents were government officials and who were 23 to 25 years old scored higher on issues related to attitude toward water quality than 18 to 20 year olds who did not specify their parents’ occupation, 23 to 25 year olds with farmer parents, and 23 to 25 year old respondents who did not specify their parents' occupation. As stated earlier, in general, government officials have better educations and can help their children to learn more about the natural world. They also have a better environment for their children’s intellectual growth than any other group involved in this study. It is therefore important to include environmental units into existing subject matters in school curricula so that children of different social backgrounds can be provided environmental awareness and skills needed to act responsibly toward improving the quality of the environment. Respondents with government servant parents and who were 21 to 22 years old scored higher on issues related to attitude toward water quality than did their peers 18 to 20 years old who did not specify their parents’ occupation and 23 to 25 year old respondents with farmer parents. Also, respondents with government servant parents who were 23 to 25 years old outscored 164
respondents of the same age category whose parents were farmers. These students in addition to their access to supplemental learning materials such as radio, TV, and books also reside mostly in the rural area. The group of 23 to 25 years old is supposed to have more experience than younger groups of respondents but school instruction provides little about environmental awareness and the development of positive environmental attitudes. Twenty one to 22 year old students who did not specify their parents’ occupation scored higher on the average than did those 23 to 25 years old who selected "farmer" as their parents' occupation. Most of the time, students who do not reveal their parents’ occupation are those who live in poor conditions, probably in rural or suburban areas. It may also be the difference in sample sizes which made a difference in respondents’ attitude scores toward water quality issues for these groups. Birch and Schwab (1983) indicated that water education programs are effective in developing students’ knowledge and positive attitudes concerning water conservation, as well as establishing a water use ethic that permanently improves their water-using habits as adults. The School category independent variable accounted for a significant (p < 0.0086) amount of the variability in the attitudes toward ecological principles. Interactions {p < 0.0456) between respondents’ age category and gender were also observed. Female respondents of all categories appeared to have more positive attitudes toward ecological principles than did males. The sex role factor further specify that females tend to have more knowledge and positive attitudes toward environmental issues than do males. These results may help legislators, decision-makers, and school curriculum 165 developers to elaborate a consistent and integrated environmental education program aimed at helping women understand and participate in the improvement of the quality of the environment and the development of positive attitudes toward the natural world Concerning the respondents’ attitudes toward global environmental issues,Table 62 reveals the existence of two significant interactions between age category and respondents’ residential location {p < 0.0196) and between gender and parents' level of education. No main effects were detected. It was found that city residents 18 to 20 years old scored higher on issues relative to attitudes toward ecological issues than did suburban and rural (not on a farm) peers of the same age category. City residents 21 to 22 years old also scored higher than did suburban and farm residents 18 to 20 years of age. Suburban residents 18 to 20 years of age scored lower on attitudes toward global environmental concerns than did rural (not on a farm) respondent 21 to 22 and 23 to 25 year olds. Rural (not on a farm) 23 to 25 year olds had more positive attitudes toward global environmental issues than did rural (not on a farm) 18 to 20 year olds and farm respondents 23 to 25 years of age. Farm residents 21 to 22 years old, on the other hand, scored higher than respondents of the same category 18 to 20 years old. These results did not support Christianson and Arcury (1993) findings. They concluded that the relationship of urban-rural residence to environmental characteristics had little importance. However, these results were consistent with Hardy and Fox (1976) findings. In their study on environmental awareness in rural, suburban, and urban settings, they found that attitudinal differences between subgroups tested were significantly different Kostka (1976) also found that residential location correlated with 166 environmental attitudes. It therefore appears that respondents' regional differences and their ages are good indicators of attitudes toward environmental issues in general and toward global issues included in this particular study. Any assessment in environmental attitudes should include these variables in their instruments. Female respondents who indicated college as their parents’ highest degree scored higher than did females whose parents had a high school degree and males whose parents had a college degree on the attitudes toward global environmental issues. These results suggest that the more education one has, the more positive attitudes toward the environment one is likely to have. This observation highlights the need to infuse environmental topics in school subject matters at all levels of education in Burundi. Gender differences also have to be taken into account in any attempt to enhance people’s environmental awareness and appreciation. As was the case for knowledge, the observed differences or variations in respondents’ attitudes toward different issues involved in this study were very low to practically consider them different. It can be concluded that the demographic variables considered added very little variability in the respondents' environmental knowledge and attitude scores for both the General and the Technical Education settings. An analysis of the above findings highlights the fact that natural resources use in conjunction with population pressures have profound impacts on the world environment in general and that of Burundi in particular. Since ecosystem destruction is related to human needs, it is not easy to make a rapid change in people's attitudes and behaviors toward natural 167 resources consumption. As a result, resources are depleted, human population pressures increase, pollution increases, biodiversity declines, and global environmental issues are ignored or overlooked by both the school communities and the general public. In Burundi for example, people have very limited economic alternatives to satisfy their needs, and their pressures on natural resources such as forests, water, plants and animals, soil and other resources constitute real threats to the natural environment. Considering that youths lack useful knowledge and positive attitudes toward local environments and that they constitute the biggest fraction of consumers and decision-makers of tomorrow, it would seem to be advantageous to teach them about environmental issues, related problems, and management strategies in order to prevent future disasters originating mostly from human action. Since this research aims at producing a foundation for an environmental education curriculum and relevant materials in Burundi, issues such as: (1) human population growth control, (2) wise use of natural resources, (3) water pollution, (4) study of new technologies to radically transform our food crops, (5) the ability of the nation to feed itself as well as to produce exporting crops for cash, (6) careful study of chemical use in agriculture and pest control, (7) law enforcement, and others should be included in the forthcoming program. To succeed in such an enterprise, improved teaching methods and environmental materials will be needed. In addition, the development and dissemination of a variety of educational and training materials appropriate for the general public will be needed. By fostering youth and general public education, the current knowledge of the importance of the balance of natural resource use, environmental quality and integrity should improve, the destruction of natural ecosystems should be minimized, and the quality of life in Burundi should improve. Environmental educators in Burundi, therefore, may need to investigate and teach ways of reversing the current trends of exponential population growth, forest disappearance, land exhaustion, soil erosion, plant and animal species extinction, slash and burn agricultural practices, water pollution, and other harms to the natural environment. 169 Implications As stated in previous chapters of this study, the shortage of economic resources, limited school supplies, and experienced teachers prevented the Burundi System of Education from becoming a changing institution dedicated to meeting today s societal needs. At the same time, environmental degradation is continuing at an accelerating pace. Since this is the case, the present research was conducted in order to investigate ways of providing baseline data on which to initiate the development of environmental programs for schools and the general public, with which to build appropriate materials to support those programs, and on which further research efforts could proceed.
Following are implications drawn from the study: 1. There is need for inclusion of environmental units in school curricula at all levels of education in Burundi: It was demonstrated that the levels of environmental knowledge and attitudes were relatively low for both the General and Technical Education respondents. Since environmental education is nonexistent in Burundi school curricula, students rely on other sources such as residential location, personal experience, sex role, media, parents, and peers for their environmental knowledge and the development of positive attitudes toward the environment. 2. School audiences in Burundi should be prepared to learn from informal settings and blend formal learning with out-of-school learning. 3. Sex related domestic activities were presumed to be an important factor 170 in opinion formation about environmental issues: Females showed more positive attitudes toward environmental issues than did males, a fact possibly explained by the tasks assigned to them by Burundi society. 4. The information collected could be used to help develop a conceptual framework for environmental educators, planners, decision-makers, legislators, students, and the general public dedicated to improve the quality of the environment and the quality of life in Burundi. 5. Considering the effects of demographic variables in the assessment of student environmental knowledge and attitudes does not add much to the variability of knowledge levels and attitudes toward the environment in Burundi: It was shown that by considering for the respondents’ demographic factors, their knowledge levels and their attitudes were relatively similar to what had been revealed without considering these variables. The lack of emphasis on environmental issues in school communities may explain this situation. 6. Practical differences between knowledge and attitudes toward the issues included in the study were not found for the General and the Technical Education respondents: These results indicate that any attempt to introduce environmental education in Burundi schools should target both types of schools. The results also will be generalized only to the target populations. 171
7. Water quality issues were the least correctly answered on the knowledge instrument and respondents displayed less positive attitudes toward the same issues. It can be suggested to give these issues priority in the forthcoming environmental programs. 8. More time and an in-depth systematic analysis of students' knowledge and attitudes toward the environment are necessary. 9, Since economic resources, school materials, and environmentally prepared teachers are still (acking, it may well be that informal learning could become a valuable and less expensive adjunct to formal learning. 10. Age, gender, residential location, and parents' occupation were the most significant demographic factors in this study: Inclusion of these variables in further evaluation of student environmental knowledge levels and/or their attitudes toward the environment will be needed. 172 Recommendations Based on the findings of the study, following are recommendations formulated for consideration for practice and for further research:
a) Recommendation for Practice 1. Results of knowledge and attitudes toward issues such as human population, natural resources, water quality, ecological principles, and global environmental issues provide baseline data and should be used for the design, development, implementation, and the evaluation of an applied environmental education program in Burundi. 2. Educators are advised to set priorities for infusion of environmental topics into existing environmental school curricula and foster environmental initiatives that produce maximum benefits while addressing the most critical issues identified in previous chapters 3. There is a need to make available environmental education programs for in-service teachers in combination with student preparation for that career 4 Based on the results of this study, it is necessary to plan an ongoing review of environmental education strategies in order to determine the need for improvement and/or modification. 5. Better use of existing materials such as books, TV, radio, school surroundings, and the like is an option for improving environmental education. 6. The responsibility of the Burundi government to design, implement, and develop environmental education programs with regard to 173 student grade levels and the most challenging environmental problems and/or issues should be recognized. 7. Local, regional, and international cooperation in developing environmental education strategies would be helpful in Burundi and throughout the world, b) Recommendation for Further Study Further studies and activities were envisioned as follows: 1. Further studies which may replicate the present research should avoid the discrepancy in the study sample sizes so that the results obtained can be generalized to large study populations without violating statistical rules. 2. It is also necessary to replicate the present study using bigger and equally represented samples from both school categories and have data collected in all natural regions of Burundi and at all grade levels. 3. Based on the results of this research, a process to identify emerging environmental issues and bring them to the attention of school policy-makers and curriculum developers is needed. 4. Financial support needs to be available to encourage the growth of specific projects dedicated to enhancing student environmental awareness, knowledge, and positive attitudes toward the environment. 5. It is necessary to identify environmental education activities appropriate to student grade level, residential location, age category, source of environmental information, parents' occupation and level of education in Burundi. 174 6. The significant differences revealed between environmental Knowledge, environmental attitudes, and the demographic variables should provide researchers with baseline data on which to tailor further research endeavors. 7. Instruments more adaptable and suitable to Burundi's cultural, educational, and social context need to be developed. 8. A need exists to do a longitudinal study to follow up on the population used in this study to ascertain whether the environmental attitudes remain unchanged throughout an interval of years. While such an initiative is desirable, it may be difficult locating most of the students after the thirteenth grade level. APPENDIX A Instruments (English Version)
175 176 A. (KNOWLEDGE INSTRUMENT). Please circle the letter of the most correct answer to the following questions ( there Is only one correct answer for each question ). 1 . The size of human population in a given country is determined toy: A. Rate of immigration B. Death rate C. Birth rate D. Rate of immigration and emigration 2. The current total population of Burundi is approximately: A. 10 million B. 8 .5 million C. 6 million D. Less than 4 million 3. What Is the current most threatening environmental protolem in the Republic of Burundi ? A. Desertification B. Hunting C. Rapid population growth D. Rapid urbanization 4. Populations (human or others) grow until they use up the resources available to them, and then growth is limited by catastrophes such as famines, disease, and violence. This is known as: A. Exponential growth C. Logistic growth B. Competition D. Malthusian growth 177 5. Which method offers the best results in planning human birth control? A. Abstinence B. Abortion C. Prolonged breast feeding D. Modern contraceptive devices 6. As the amount of products discarded by humans increases in the environment, iarge quantities of disease- causing organisms in the drinking water will: A. Decrease B. Remain the same C Increase D. Die out 7 Certain chemicals, such as pesticides, and other organic pollutants found in the wafer may: A. Not be directly poisonous to aquatic organisms B. Cause fish and other aquatic creatures to live longer C. Set up a chain reaction that robs water of the oxygen normally present D None of the above 8. The most challenging environmental problem in Lake Tanganika is: A. Sewage disposal B. Industrial waste disposal C. Over-fishing D. Pesticide disposal. 178
9. What are the three broad classes of impurities that influence the safety of water supply for drinking? A. Calcium carbonate - Magnesium carbonate - Salt B. Phytoplankton - Zooplankton * Dead fish C Inorganic chemicals - Organic chemicals - Microorganisms D. Pesticides - Domestic wastes - Industrial wastes 10. Which inorganic elements In waste water cause excessive growths of the microscopic green water plants called algae? A. Oxygen and Hydrogen B. Calcium and Sodium C. Nitrogen and Phosphorus D. Calcium and Hydrogen 11. In which of the following habitats would you expect the largest amount of energy to be produced by photosynthesis ? A. Desert B. Tropical jungle C. Pond of water D. Deforested land 12. Natural resources such as oil, natural gas, oil, and coal are known as : A Renewable resources B. Vblcanic products C. Non- renewable resources D. High density resources 179 13. What are the most encountered environmental problems subsequent to slash and burn agriculture practices? A. Deforestation B. Deforestation and flooding C. Soil erosion and flooding D. Deforestation, flooding, and soil erosion 14. Which of the following biomes contains the greatest diversity of life, (that is the largest number of different species per square m eter are found there): A. Grasslands biome B. Taiga biome C. Tropical rain forest D. Tundra biome 15. Which of the following is the largest source of water pollution in a deforested enWronmenf ? A. Fertilizers B. Pesticides C. Sediment from soil erosion D. Animal grazing 16. A n area in which specific living things grow, breed, seek food, and find shelter is known as: A. Succession B. Food chain C. Ecosystem D. Habitat 180 17. In many areas, a community finally appears that It is not supplanted by another one, as long as major climate changes do not occur. This relatively stable community Is called: A. Diversity B. Tundra C. Deciduous forest D. Climax 18. In any particular community, the organisms are linked together in a pattern of preying and being preyed upon, of eating and being eaten. This pattern Is known as: A. Food production B. Trophic structure C. Diversity of the ecosystem D. The niche 19. The abiotic factors in an environment along with the community of organisms found there form a functional unit known as: A. The dominance B. Complex food web C. Ecological pyramids D. Ecosystem 20. What are two fundamental processes the evolution of species depend upon? A. Adaptation and predation B. Camouflage and variation C. Predation and selection D. Variation and selection 181 21. Some scientists advance that solar energy would continue to reach the earth without being affected by the carbon dioxide, but the radiation of heat away from the earth would be slowed by that gas and the earth would then heat up. This phenomenon Is called: A. Carbon cycling B. Solar radiation C. Radioactivity D. The greenhouse effect 22 The most Important toss of soil and land resources Is the process known as: A. Erosion B. Land exhaustion C. Salinization D. Desertification 23. Which of the following pesticides Is banned in most of the developed countries but extensively used in Burundi? A. Lindane C. Chlordane B. Aldrine D. DDT 24. Scientists are now aware of the build-up of carbon dioxide in the earth's atmosphere, their concern is : A. The earth’s atmosphere will cool down B. The earth’s atmosphere will remain the same C. The carbon dioxide will react with acid rain D. The carbon dioxide will trap heat in the earth’s atmosphere 182 25. Acid rain is caused by which of the following phenomena? A. Solution in rain of nitrogen oxides B. Pollutants produced primarily from the burning of coal and residual oil C. Solution in the rain of oxygen dioxides D. Seasonal climate changes 183 B. (ATTITUDE INSTRUMENT ) Pleaae Indicate the degree to which you agree with each statement by circling one of the five numbers following each statement.
KEYS: 1 = Strongly Disagree 4 = Agree 2 = Disagree 5 - Strongly Agree 3 = Neutral
Strongly Strongly Disagree Agree
( Circle your answer)
1. I do not believe in the danger 1 2 3 4 5 of a rapid population growth in Burundi. 2. Over -population is not a barrier 1 2 3 4 5 to economic growth and the quality of the environment in the Third World. 184
Strongly Strongly Disagree Agree
(Circle your answer) 3. Considerable effort is being made 1 2 3 4 5 to lower current population growth trends in the Republic of Burundi.
4. Humans can live in harmony with the 1 2 3 4 5 environment regardless of the size of their populations.
5. No population control program 1 2 3 4 5 will work in Africa if it is imported.
6. The clearing of Burundi large forest 1 2 3 4 5 tracts and the soil erosion that accompanies intensive agriculture will not impact the country’s economic growth.
7. Protection of endangered wildlife 1 2 3 4 5 is a high priority in the developing nations.
8. Humans have the right to modify 1 2 3 4 5 the environment to fit their needs. Strongly Strongly Disagree Agree
( Circle your answer) 9. Until people's primary needs are 1 2 3 4 met, they will have little enthusiasm seeking a quality environment.
10. Conservation of natural resources 1 2 3 4 implies that those resources cannot be utilized. 11. Water pollution is not a big 1 2 3 4 problem in the Republic of Burundi.
12. Treatment is not required to make 1 2 3 4 water free from hazardous chemicals and disease-causing organisms.
13. Quality water supply is not 1 2 3 4 a concern for developing countries
14. Irrigated agriculture using 1 2 3 4 polluted water is an activity to encourage. Strongly Strongly Disagree Agree
( Circle your answer) 15. It is a good idea to dispose of 1 2 3 4 domestic and industrial waste waters into the nearest river, lake, or ocean.
16. Environmental degradation 1 2 3 4 and ecological problems are not threats for the poor countries . 17. Biodiversity conservation 1 2 3 4 is a formula invented by the rich countries to make the less developed nations die with hunger.
18. Living things are interdependent 1 2 3 4 with one another and their physical environment.
19. Slash and burn activities do not 1 2 3 4 disturb ecological relationships in a given environment.
20. Humans should stop harvesting 1 2 3 4 trees because they harbor wildlife 187
Strongly Strongly Disagree Agree
( Circle your answer)
21. Global warming is a hypothetical issue; it 1 2 3 4 5 will not happen. 22. Desertification cannot prevent plants and 1 2 3 4 5 animals from proliferating.
23. Acid rain is a concern for only the 1 2 3 4 5 developed countries.
24. Pesticide use is the best method to 1 2 3 4 5 increase crop production.
25. Pesticides have harmful effects 1 2 3 4 5 on crop disease-causing organisms; not on people. 188 C. (DEMOGRAPHIC INSTRUMENT ) To finish this survey, we would like to ssk questions about you and your family. All information is confidential and will not be Identified by your name. 1. In which age category are you? ( Please circle your answer.) 1. 18 to 20 2. 21 to 22 3. 23 to 25 2. What is your gender? ( Please circle your answer.) 1. Mate 2. Female 3. What is your major? ( Please write in ) ______major 4. Where do you live ? (Please circle your answer.) 1. City 2. Suburban 3. Rural, but not a farm 4. On a farm 5. In which ecological zone do you live ? (Please write in ) _ecological zone 6. In which ecological zone is your school located ? ( Please write in ) ______ecological zone 189 7. Please choose one delivery method that you think is your best source of environmental information. 1. Books 2. Classroom instruction 3. Radio or TV 4. Parents' occupation
best source of environmental information 8. In which type of school are you enrolled 7 (Please circle your answer. ): 1. General Education School 2. Technical School 9. Please circle the following that best describes your parents’ occupation now ( only one correct answer is needed. ) 1. Government official 2. Government servant 3. Farmers) 4. Other 10. What is your parents’ highest degree? (Please circle your answer.) 1. Elementary school 2. High school 3. College 4. Other Appendix B instruments (French Version)
190 191 A. QUESTIONS A CHOIX MULTIPLE Consianes: Chaque queation eat sulvie de quatrea reponaes notea A, B, C, D, dont une aeute eat correcte. Repondre an encerclant aur votre copie ia letttre correapondant it la bonne r&ponae . (Merci beaucoup)
1. La population humaine d' un paya eat dAterminAe par:
A. Le taux d'immigration C. Le taux de natality
B Le taux de mortality D. Le taux d’ immigration et d’ Emigration
2. La population actuellm du Burundi eat eatimAa a environ:
A. 10 miltions d ’ habitants C. 6 millions d' habitants
B. 8.5 millions d ’ habitants D. Motns de quatre millions d ’ habitants
3. Quml eat la problAma qui risque la plus da compromattra la quatftA da I'
anvironnamant au Burundi?
A. La desertification C. Rapide croissance dEmographique
B. Lachasse D. Rapide urbanisation
4. Lea populations humainas, vAgAtalaa ou animalaa aont capablea d’axploiter laur potential biotlque at croltre A daa vitaaaaa fantaatiquea at allaa ne aont paa tenues an Achac par daa forcaa naturalism. Cm principa aat connu sous la nom da:
A. La croissance exponentielle C. La croissance logistique
B. La competition D. Le spectre de Matthus
5. Quelle aat la mAthoda qul otfra tea maillaura rAsultats dana la regulation dam naiaaancaa chaz f’homme?
A. Abstinence C. Allaitement prolongE
B. Avortement D. Usage des contraceptives modernes 192
6. A me sure que le» eaux rtsiduaires des ttablissements humairts sont amendes aux eaux douces, lea bacttries at autres organlamea pathogtnes subissent quel p h tn o m tn e ?
A. Leurs populations diminuent C. Leurs populations augmentent
B. Leurs populations restent Ies mdmes D. (Is meurent
7. Certains prt>dulta chimiquea tela que tea pesticides at autres poliuanta organiquea amenta aux eaux douces par rulaaeltement ou drainage lattral poaatdent une dea caracttriatiques auivantea:
A. II ne sont pas nocifs pour Ies organismes aquatiques
B. II permettent aux poissons et autres organismes aquatiques de vivre longtemps
C. II favonsent une chains de reactions chimiques utilisant I' oxygPne normalement
present dans I'eau
D. Aucune bonne rPponse
8. Le grand problime que connatt ie Lac Tanganyika actueliement pourratt
4 tre :
A. Accumulation des eaux r6siduares des Ptablissements humains C. La pdche
excessive
B. Accumulation des eaux r6siduaires industrielles D. L' accumulation des
pesticides
9. La qualitt d’ une eau potable eat influences par la combinatson de troia classes d' impuretta; choiaiaaez la bonne rtponae:
A. Carbonates de Calcium -Carbonates de Magn6sium-Sels
B. Phytoplancton-Zooplancton-Poissons morts
C. Produits inorganiques-Produits organiques-Microorganismes
D. Pesticides-DSchets industriels-D6chets domestiques 193
10. Certains dtdments fnorganiques trouvds dans I’ eau sont 4 /' origins d' une croissance excessive des algues vertes. Choisissex la bonne rdponse:
A. Oxyg6ne et Hydrogene C. Azote et Phosphors
B. Calcium et Sodium O. Calcium el Hydrog6ne
11. Dans quel milieu pourriez-vous espdrer trouver la plus grande production
d'dnergie par photoaynthdse? A. Le desert C. Une mare
B. La Foret tropical© D. Un terrain nu
12. Lea ressourcea naturelles teltes que: le sol, le gaz nature!, le petrols et le
charbon sont connuea sous le nom de:
A. Ressources renouvelabtes C. Les ressources non-renouvelables
B. Les produits volcaniques D. Les ressources ft haute densitd
13. La mise en valeur progressive des terras Incultes peut dtre 4 / ’ origins cT
un certain nombre de probldmes lids 4 V environnement:
A. Deforestation C. Erosion des sols et inondation
B. Deforestation et inondation D. Deforestation, inondation et erosion des sols
14. Quel eat le milieu qui contient fa plus grande diveraitd de vies ( le plus
grand nombre d ’espdces par metre carrd):
A. La Prairie C. La Foret tropicale
B. La Taiga D. LaToundra
15. Quelle eat la plus grande source de la pollution de / ’ eau dans un milieu
ddboiad?
A. Les engrais chimiques C. Les sediments provenant de I1 erosion du sol
B. Les pesticides D. Le broutage par des animaux
16. Un milieu dans iequei les dtrea vivants grandissent, se reproduisent, s’
approvisionnent en nourriture, et cherchent de I’abri est connu sous le
nom der.
A. Succession C. Ecosystem©
B. Chatne alimentaire D. Habitat 194
17. Dans beaucoup de milieux naturals, une communaute d ’ Stres vivants finlt
par rSslater 4 la dominance par d'autres espScea aussi longtemps que les
conditions cllmatlques demeurent favorabtes. Ce phSnomSne est connu
sous le nom de:
A. Diversity C. For6t decidude
B. Toundra D. Climax
18. Dans n’ imports quelle communaute d ’St res vivants, les organismes sont
U4s par des relations allmentalres connues sous le nom de:
A. Productions alimentaires C. Les diversites dcologiques
B. Les liaisons trophiques D. Les niches dcologiques
19. Dans un milieu determine, les facteurs ablotlquea et lea communaute s
d’St res vivants torment des unites fonctlonnelles appelSes
A. Dominances C. Pyramides dcologiques
B. Chaines alimentaires D. Ecosystdmes
20. Quels sont les deux processus fondamentaux dont dependent Involution
des espSces?
A. Adaptation et predation C. Predation et selection
B. Camouflage et variation D. Variation et selection
21. Des hommes de sciences soutlennent que I'Snergie solaire attaint la
surface terrestre sans Stre arrStee par le dioxyide de carbons; mala la
chaleur Smise par la surface terrestre pouralt Stre relentie par ce gaz et
occasionneralt le rSchauffement de la basse atmosphSre. Ce phSnomSne
s’ appetle:
A. Le cycle du carbone C. La radioactrvite
B. La radiation solaire D. L’ effect de serre
22 La plus importante perte de sol et autres ressources terrestres est connue
sous le nom de:
A. Erosion C. Salinite du sol
B. Fatigue du sol D. Desertification 195
23. Quel eat le pesticide dont rusage eat interdit dana beaucoup de pays
developpds maia largement utilise au Burundi cea derniires ann6es7
A, Lindane C. Chloridane
B. Aldrine D. DDT
24. L’ accumulation du dioxyide de tmrbone dans /' air pourrait avoir comma
consequence:
A. L' atmosphere terrestre se refroidira
B. L' atmosphere terrestre ne subira aucun changement
C. Le dioxyide de carbone r£agira avec les pluies acides
D. L’ atmosphere terrestre se r6chauffera
25. Par quel phenomena aont cauaeea les pluies acides ?
A. La dissolution des oxyides d' Azote dans la pluie
B. Les polluants provenant principalement de la combustion du charbon et des huiles
C. La dissolution du dioxygene dans la pluie
D. Les changements ciimatiques saisoniers 196 B. QUESTIONS D A P PR R EC I A TION ET D’ OPINIONS Consfane: Cheque question est sulvle de cinq chiffres not6s ( 1, 2, 3 , 4 et 5 ). Encerdez uniquement un seui chiffre pour cheque question. Le chiffre encercIS indiquera le degrS de votre appreciation ou de votre opinion pour cheque question. ( Merci beaucoup )
Indication:
1 = Extrgmement contre 2 = Contre 3 = Pas d’avis 4 = Pour 5 = Extr6mement pour
Extrdmement Extrdmement
Contre Pour
( Encerdez le chiffre de votre choix )
1. Je ne croix pas ;u ’ il y ait une rapide explosion
ddmographique au Burundi 1 2 3 4 5
2. La croissance d6mographique exagdrde
n’ est pas un obstacle pour la croissance
6conomique et la quality de I’ environnement
dans les pays du Tiers Monde 1 2 3 4 5
3. Des efforts considerables sont consentis
pour rdduire la croissance d6mographique au Burundi 1 2 3 4 5 4. Les populations humaines peuvent vivre
en harmonie avec leur environnement physique
quel que soit le nombre de leurs habitants 1
5. Aucun contrdle de populations humaines
imports d’ Occident rdussira en Afrique 1
6. L’ installation de nouvelles cultures dans
des tordts et I' drosion du soil qui s’ en suit
ont peu de consequences sur la croissance
dconomique d’ un pays 1
7. La protection des espdces mdnacdes de
disparition est une grande priority dans les
pays en ddveloppement 1
8. L' homme a le droit de sacrifier la quality
et la richesse de I’ environnement pour
satisfaire a ses besoins 1
9. Aussi longtemps que les besoins
primaires de I’ homme ne seront
pas satisfaits, il aura peu d’ intdrdt
pour la protection de I' environnement 1
10. La conservation des resources naturelies
implique que ces resources ne peuvent
pas dire utilisdes 1 198
11. La pollution de I’ eau n' est pas un grand
problems au Burundi 1 2 3 4 5
12. Le traitement de I’ eau potable n’ est pas
nOcessaire pour eiiminer les produits
chimiques et les organismes pathogdnes 1 2 3 4 5
13. La quality d’ une eau potable n' est pas un grand souci pour les pays en d6veloppement 1 2 3 4 5
14. L’ irrigation des cultures par des eaux usees
est une activity a encourager 1 2 3 4 5
15. II est conseilie de rejeter ies eaux rOsiduaires
des Otablissements domestiques et industrials
dans la plus proche rivipre, le plus proche lac,
fleuve ou ocean 1 2 3 4 5
16. La degradation de I' environnement et les
probl6mes Ocologiques ne constituent pa
des menaces pour les pays pauvres 1 2 3 4 5
17. La conservation des espOces est une
formule importee d’ Occident qui ne
profile pas aux pays en deveioppement 1 2 3 4 5
18. Les etres vivants sont interdependants
entre eux et avec leur environnement
physique 1 2 3 4 5 19. Dans un environnement determine,
le deboisement et I’ usage de feux
de brousse nl affectent pas les equilibres
ecologiques 1
20. L' homme pourrait renoncer & la
consommation du bois sauvage
parce que ce dernier abrite des animaux 1
21. Le rdchauffement de I' atmosphere £
I’ echelon mondial est un mythe, il
n’ arrivera pas 1
22. La desertification n' est pas un frein
pour la proliferation des plantes et des
animaux 1
23. Les pluies acides sont un souci majeur
uniquement pour les pays industrialises 1
24. L’ usage des insecticides est la meilleure
methods & utiliser pour augmenter
les productions agricoles 1
25. Les pesticides ont des effets nefastes
sur les animaux destructeurs des vegetaux,
mais des effets positifs pour I’ homme 1 200 C. POUR TERMINER CET EXERCICE, NOUS VOUDRIONS VOUS POSER QUELOUES QUESTIONS SUR VOUS ET VOTRE FAMILLE. L’ INFORMATION FOURNIE SERA CONFIDENTIELLE ET VOUS NE SEREZ PAS IDENTIFIE PAR VOTRE NOM. ( MERC! BEAUCOUP ).
1. Dana quetta categoric d' Age Atea-voua? ( Encerclez la bonne teponse )
A. Moins de 18 ans B. Entre 18 et 20 ans C. Entre 20 et 22 ans
D. Entre 22 et 25 ans E. Plus de 25 ans
2. Etes - vous gargon ou fille ?
A. Garmon B. Fille
3. Qualls aat votra aaction?
( Remplissez cet espace ) ______
4. OO habitez-vous? ( Encerclez la bonne rOponse )
A. En ville B. Dans un faubourg C. A la campagne
D. Dans une ferme E. A la Cite
5. Dana quelle region naturella habitez - voua?
( Remplissez cet espace ) ______
6. Dana quelle region naturelle eat altuAe votre Acole?
( Remplissez cet espace ) ______
7. Indiquez la meilleure source da votre Information concamant I’
environnement en gAnAral:
A. La lecture B. L’ enseignement re<;u & I' dcole C. La radio D. La television
E. L’ enseignement regu des parents F. Lesjournaux G. Les magazines 201
8. Quelle cat4gorie d' 4cole frOquentez - vous7 ( Encerclez la bonne r6ponse )
A. Enseignement G6n6rai 8. Enseignement Techique
9. Encerclez la riponse qui dOcrtt le mieux I' occupation actuelle de vos parents
A. Haut cadre {s) du Gouvernement B. Fonctionnaire (s) moyen (s)
C C u ttiva te u r(s ) D. Autre(s)
10 . Quel est le niveau de formation le plus 4!ev6 de vos parents?
( Encerclez la bonne rtjponse )
A. Ecole Primaire B. Ecole Secondaire C. University
D. Autre ( Remplissez cet espace) ______APPENDIX C Pane! of Experts and Field Test Reports
202 203 As specified in Chapter 3; three instruments have been used to collect data for the present research; a knowledge instrument comprising of a 25 item self administered multiple-choice achievement test, an attitudinal instrument made by a 25 item Likert Scale, and an eight item demographic component. It was necessary to check for the validity and the reliability of the knowledge and the attitudinal instruments before the research could be undertaken. To fuffill the requirement about the validity of the instruments, two panels of experts and a field test were employed. A series of changes were made on the instrument based on the panel of experts suggestions and the field test results:
1. Panel of U.S. Experts The dissertation committee, which is a body of four members, followed closely the development of the two instruments and provided needed advice for improvement until the researcher was about to embark on the data collection phase. Dr. Robert Warmbrod (College of Agriculture, Ohio State University) suggested the strategies necessary to consider in the instrument development based on the types of research objectives and the kinds of statistics anticipated to be used in the study. Dr. Emmalou Norland (College of Agriculture, Ohio State University) reviewed the two instruments and suggested ways to make them appropriate for the nature of the data to be collected. The instruments have been periodically reviewed until the English version reached an acceptable level of usefulness. 204 Dr. Nancy Chism of the Center for Teaching Excellence (Ohio State University): - If categories are relatively known for a survey (one can predict the possible answers well) one does not need an interview, but only afield test to verify his / her assumptions. - If categories are not clear or you want people to give you reasons for why they are choosing other information, then you should use an interview or an open-ended survey. - One can use both with different samples to have triangulation of methods which adds reliability in a multi-method study.
2. Panel of Burundi Experts The panel of experts in Burundi (French Version) included five Secondary School curriculum developers: one expert in Biology two in Chemistry, one in Geography, and one expert in Agriculture Education. The biology expert mostly concentrated on the content and the structure of different items and constructive changes suggested. The two experts in chemistry concentrated on the principles of multiple-choice question formulation, the strength of the distracters, their structures and their relationships to the correct answer for each item. Changes have been suggested also. The geography expert advised the researcher to apply the multiple-choice evaluation rules and to avoid long questions. The Agriculture Education expert found the instruments appropriate for use at the thirteenth grade level in both Technical and General Education settings. 205 3. Field Test Results The results of the field test were less reliable than those of the panel of experts: - The format used was not familiar to the students. - It was the first time students were asked to evaluate questionnaires and give their opinions and / or appreciation about them, - Eighteen students out of forty found the questionnaires too difficult, and the remaining participants said they were of moderate difficulty. - Except for spelling mistakes; General and Technical Education students did not suggest any change in the content and / or the structure of the instrument items. Appendix D Letter to the Ministry of Primary and Secondary Education
206 207 Bujumbura 25, Aout 1993
A Monsieur le Directeur du Departement de I’ Enseignement Technique & Bujumbura
Monsieur le Directeur,
J'ai I’ honneur de bien vouloir vous demander I’ autorisation d’ utiliser les Classes de derni6res annGes de I’Enseigement Technique niveau A2 pour ma recherche doctorale. En effect, Monsieur le Directeur le sujet de ma recherche s'intiiule: "Assessment and Comparison of Environmental Knowledge and Attitudes held by Thirteenth Grade General and Technical Education Students in the Republic of Burundi". Les r6sultats escomptes pourraient servir de donnees de base necessaire pour introduce & notre systeme educatif I' Enseignement de I’ Environnement Ms pourraient egalement servir comme donnees de reference pour des recherches environnementales ulterieures et & tous les niveaux de I’ ennseignement general et technique. Le Minist£re de r environnement pourrait egalement utiliser ces donnees pour orienter la politique de recherche et l education environmentale deja pr§conis6e. Dans I’espoir d’une suite favorable que vous rgserverez a ma demande, Veuillez agreer, Monsieur le Directeur, I’assurance de ma haute consideration, Albert Ndayitwayeko Ohio State University Appendix E Planned Participating Schools
208 209
MAJOR ECOLOGICAL REGIONS SCHOOLS
1. BUTUTSI: Lycee Bururi Kiremba Matana Rubanga Rutovu ETAS Mahwa* Seminaire Buta 2, MUGAMBA Lycee Bukeye Ijenda Muranvya Mwaro* Tora ETAS Gisozi*
3. BUYOGOMA Lycee Muyaga* Rusengo Ruyigi Seminaire Dutwe ETAS Kigamba* 4. BURAGANE Lycee Makamba* Rutana* *: Technical, vacational, or teacher training schools having the thirteenth grade level. 210
5. BUYENZI Lycee Busiga* Gatara* Kayanza* Musenyi* Burengo Seminaire Bur a sir a Mureke
6. IMBO Lycee Kamenge Ngagara Rohero Vugizo Cibitoke’ Ngagara* Nyakabiga* Rumonge* ESTA* ETS Kamenge* ETG Mutumba*
*; Technical, Vocational, or teacher training schools having the thirteenth grade level 211 7. KIRIMIRO Lycee Gitega Kibimba Mushasha Musinzira Nyabiharage Gishubi* Kiganda* Muyebe* Mweya* Ecole Paramedicale de Gitega* ETP Gitega* ECOSO* ENEFA Kibumbu* Seminaire de Mugera
8. BUGESERA Lycee Gisanze Mukenke* Rugari* Seminaire de Muyinga 9 BWERU Lycee Buhiga ITAB Karusi*
10. MUMIRWA 0 * : Technical, \focational, or teacher training schools having the thirteenth grade level. TOTAL. 28 general education schools 30 technical schools ( technical, vocational, or teacher training schools ). Appendix F Coding Keys
212 213 CODES: A KNOWLEDGE INSTRUMENT 1. The scoring is: 0 = wrong answer 1 = correct answer
2. Alternative answers for each item: A, B, C, D, (missing data)
3. Correct answer for each item:
1 2 3 4 5 6 7 8 9 10 D C C D D C C C C
11 12 13 14 15 16 17 18 19 20 B C D C C D D B D D
21 22 23 24 25 D D D D B
4. Knowledge Sub-Scales: Q1------Q5 Human Population (POPK) Q6...... Q10 Water Quality ( WATQK) Q11...... Q15 Natural Resources ( NATRK) Q16 ------Q20 Ecology (ECOK) Q21...... Q25 Global Issues (GLOBK) 214
B. ATTITUDE INSTRUMENT
1 KEY : 1 = Strongly Disagree 2 = Disagree 3 = Neutral 4 = Agree 5 = Strongly agree . = Missing data
2. Desired Responses for Each Item:
AT1 AT 2 AT3 AT4 ATS AT 6 AT7 AT8 AT9 AT 10 AT11 AT 12
1 1 1 AT 13 AT 14 AT 15 AT 16 AT 17AT18 AT 19 AT20 AT21 AT22 AT23 AT24 AT25 4 2 2 2 1 51231222
3. Attitude Sub- Scales:
AT 1...... -ATS Human Population ( POPAT) AT 6- ...... AT 10 Natural Resources ( NATRAT ) AT 11.....-AT 15 Water Quality ( WATQAT ) AT 16— AT20 Ecology (ECOAT)
AT21 AT25 Global Issues ( GLOBAT) 215
C. DEMOGRAPHIC INSTRUMENT
1. Age Category: 1 = 18 to 20 (DE1 ) 2 = 20 to 22 3 = 22 to 25
2. Gender: 1 = Male (D E 2) 2 = Female
3. Major: 1 = Scientific
( DE3 ) 2 = Humanities 4 = Professional
4. Residential Location 1 = City
( DE4 ) 2 - Suburban 3 = Rural, but not on a Farm 4 = On a Farm
5. School Geographic Location 1 - Bututsi (D E 5) 2 = Buragane 3 = Buyenzi 4 - Imbo 5 = Mugamba
6. Source of Environmental 1 = Books
Information 2 = Classroom Instruction (D E 6) 3 = Radio or TV 4 = Parents 5 = Other 216
DEMOGRAPHIC INSTRUMENT ( Continued)
7. Type of School 1 = General Education (DE7) 2= Technical Education
8. Parents Occupation 1 = Government Official(s) ( D E8) 2 = Government Servant(s) 3 = Farmer(s) 4 = Other
9 Parents Highest Degree 1 = Elementary School (D E 9) 2 = High School 3 = College 4 = Other Bibliography
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