臺灣博碩士論文加值系統

At the 21st century, preparing learners’ ability to deal with socio-scientific issues has been recognized as an important goal for science education. In science education, previous studies regarding learners’ informal reasoning on socio-scientific issues were mainly conducted with qualitative analyses. With 68 tenth graders in Taiwan, this study initially attempted to explore students’ informal reasoning on a socio-scientific issue both qualitatively and quantitatively. In this study, “nuclear power usage” was used as the socio-scientific issue for the participants to reason. The conduct of this study was divided into two phases: the “informal reasoning exploration phase”, mainly examining the relationship between students’ informal reasoning and scientific epistemological beliefs (SEBs) as well as their cognitive structures, and the “on-line searching task phase”, mainly focusing on the effects of different on-line searching activities on students’ informal reasoning.
In the first phase, the students’ SEBs were accessed by a questionnaire; the data regarding the students’ cognitive structures were collected by tape-recorded interviews; and, an open-ended questionnaire was utilized to gather the data about the participants’ informal reasoning on nuclear power usage. The findings derived from the first phase imply that learners’ informal reasoning on a socio-scientific issue is, in general, correlated with their SEBs as well as their cognitive structures regarding this issue. Moreover, it was also found that the students’ usage of the “comparing” information processing mode was the best predictor for their informal reasoning quality, while their beliefs about the nature of science knowing was the second best predictor for their informal reasoning quality. Besides, the importance of the richness of students’ cognitive structures on their informal reasoning regarding a socio-scientific issue was also highlighted.
In the second phase, by using a quasi-experimental research approach, thirty-three students were assigned to a “guided searching task group”, while thirty-five students were assigned to an “unguided searching task group”. Both the students in the two groups were asked to search relevant information regarding nuclear power usage on the Internet and integrate what they had searched into a report during the period of two classes (100 minutes). However, the students in the un-guided searching task group were asked to search freely, while those in the guided searching task group were provided with a searching guideline. The results of second phase showed that the two groups of students did not show any significant difference on their searching outcomes (p>0.05), but it revealed significant effects of guided on-line searching task on students’ cognitive structure outcomes as well as on their supportive argument construction (p<0.05). However, the guided on-line searching task in this study did not significantly facilitate students’ reasoning quality. Besides, the interaction between students’ SEBs and instructional conditions on students’ searching outcomes as well as on their cognitive structure outcomes was found; also, the interaction between students’ information commitments and instructional condition on students’ cognitive structure outcomes as well as on their informal reasoning outcomes was revealed. It suggests that, when trying to improve students’ informal reasoning ability in Internet-based learning environments, science instructors should pay more attention to the role of learners’ SEBs and the information commitments in their learning outcomes.
In sum, the findings in current study did provide more insights into the nature of students’ informal reasoning on a socio-scientific issue, and also showed some initial evidences on the usefulness of on-line searching activities on learners’ informal reasoning on this issue.

At the 21st century, preparing learners’ ability to deal with socio-scientific issues has been recognized as an important goal for science education. In science education, previous studies regarding learners’ informal reasoning on socio-scientific issues were mainly conducted with qualitative analyses. With 68 tenth graders in Taiwan, this study initially attempted to explore students’ informal reasoning on a socio-scientific issue both qualitatively and quantitatively. In this study, “nuclear power usage” was used as the socio-scientific issue for the participants to reason. The conduct of this study was divided into two phases: the “informal reasoning exploration phase”, mainly examining the relationship between students’ informal reasoning and scientific epistemological beliefs (SEBs) as well as their cognitive structures, and the “on-line searching task phase”, mainly focusing on the effects of different on-line searching activities on students’ informal reasoning.
In the first phase, the students’ SEBs were accessed by a questionnaire; the data regarding the students’ cognitive structures were collected by tape-recorded interviews; and, an open-ended questionnaire was utilized to gather the data about the participants’ informal reasoning on nuclear power usage. The findings derived from the first phase imply that learners’ informal reasoning on a socio-scientific issue is, in general, correlated with their SEBs as well as their cognitive structures regarding this issue. Moreover, it was also found that the students’ usage of the “comparing” information processing mode was the best predictor for their informal reasoning quality, while their beliefs about the nature of science knowing was the second best predictor for their informal reasoning quality. Besides, the importance of the richness of students’ cognitive structures on their informal reasoning regarding a socio-scientific issue was also highlighted.
In the second phase, by using a quasi-experimental research approach, thirty-three students were assigned to a “guided searching task group”, while thirty-five students were assigned to an “unguided searching task group”. Both the students in the two groups were asked to search relevant information regarding nuclear power usage on the Internet and integrate what they had searched into a report during the period of two classes (100 minutes). However, the students in the un-guided searching task group were asked to search freely, while those in the guided searching task group were provided with a searching guideline. The results of second phase showed that the two groups of students did not show any significant difference on their searching outcomes (p>0.05), but it revealed significant effects of guided on-line searching task on students’ cognitive structure outcomes as well as on their supportive argument construction (p<0.05). However, the guided on-line searching task in this study did not significantly facilitate students’ reasoning quality. Besides, the interaction between students’ SEBs and instructional conditions on students’ searching outcomes as well as on their cognitive structure outcomes was found; also, the interaction between students’ information commitments and instructional condition on students’ cognitive structure outcomes as well as on their informal reasoning outcomes was revealed. It suggests that, when trying to improve students’ informal reasoning ability in Internet-based learning environments, science instructors should pay more attention to the role of learners’ SEBs and the information commitments in their learning outcomes.
In sum, the findings in current study did provide more insights into the nature of students’ informal reasoning on a socio-scientific issue, and also showed some initial evidences on the usefulness of on-line searching activities on learners’ informal reasoning on this issue.

TABLE OF CONTENTS
page
CHAPTER I: INTRODUCTION…………………………………
1
I.1 Background of the Study………………………………………………...
1
I.2 Need for the Study……………………………………………………….
2
I.3 Overview of the study...………………………………………………….
5
I.4 Research Questions………………………………………………………
7
CHAPTER II: LITERATURE REVIEW………………………...
9
II.1 Informal reasoning on socio-scientific issues………………………….
9
II.1.1 What is informal reasoning?................................................................
9
II.1.1.1 Formal reasoning and informal reasoning……………………
9
II.1.1.2 The mechanism of informal reasoning……………………….
11
II.1.2 Socio-scientific issues and its relation to informal reasoning……….
14
II.1.3 Previous studies regarding informal reasoning in educational psychology………………………………………………………….. 16
II.1.3.1 The relationship between learners’ conceptual understanding and their informal reasoning…………………………………. 16
II.1.3.2 The relationship between learners’ epistemological beliefs and their Informal reasoning…………………………………. 16
II.1.4 Previous studies regarding informal reasoning on socio-scientific issues………………………………………………………………...
18
II.1.4.1 Representing learners’ informal reasoning on socio-scientific issues…………………………………………………………. 18
II.1.4.2 The criteria students use to evaluative scientific information regarding a socio-scientific issue…………………………….. 21
II.1.4.3 The relationship between learners’ conceptual understanding and their Informal reasoning on socio-scientific issues……… 21
II.1.4.4 The relationship between learners’ beliefs about the nature of science and their Informal reasoning on socio-scientific issues………………………………………………………….
24
II.2 Scientific epistemological beliefs……………………………………….
27
II.2.1 Conceptualization of personal epistemology………………………..
27
II.2.1.1 Developmental models for personal epistemology…………..
28
II.2.1.2 Independent beliefs model of personal epistemology………..
34
II.2.1.3 Alternative models of personal epistemology………………..
36
II.2.1.4 Consistent dimensions summarized by Hofer and Pintrich…..
37
II.2.1.5 Is personal epistemology domain general or domain specific?.................................................................................... 38
II.2.2 Scientific epistemological beliefs and science learning……………..
39
II.2.2.1 Scientific epistemological beliefs (SEBs) and beliefs on nature of science (NOS)……………………………………… 40
II.3. Exploration of cognitive structures…………………………………...
44
II.3.1 Cognitive structure and its dimensions……………….......................
44
II.3.2 The assessment of cognitive structure……………………………….
47
II.3.3 Findings derived from previous studies conducted with the flow map method…………………………………………………………. 47
II.3.3.1 The methodological issue regarding the flow map method…..
47
II.3.3.2 Exploring learners’ knowledge construction or development with the flow map method…………………………………… 48
II.3.3.3 The relationships between students’ performances on the variables obtained from their flow maps…………………….. 50
II.3.3.4 Learners’ achievement, performances on laboratory work, SEBs and their cognitive structure outcomes derived from flow maps……………………………………………………. 51
II.3.3.5 The effects of science learning activities on students’ cognitive structure outcomes………………………………… 53
II.3.3.6 The role of teachers’ knowledge structures in their ability to diagnose students’ conceptual understanding……………….. 55
II.4 Internet-based science learning, on-line searching activities, and information commitments……………………………………………... 55
II.4.1 The Internet and science learning……………………………………
55
II.4.2 On-line searching activities and learners’ information commitments……………………………………………………....... 56
II.4.3 The role of epistemological beliefs on Internet-based learning……..
61
II.5 Theoretical Model………………………………………………………
63
CHAPTER III: METHODOLOGY................................................
67
III.1. Methodology of the Informal Reasoning Exploration Phase………
67
III.1.1 Subjects and the socio-scientific issue……………………………...
67
III.1.2 General research design…………………………………………….
68
III.1.3 Instruments, data collection and data analyses……………………..
69
III.1.3.1. Assessing students’ scientific epistemological beliefs……...
69
III.1.3.2. Exploring students’ cognitive structure regarding nuclear power………………………………………………………... 71
III.1.3.3 Evaluating students’ informal reasoning on nuclear power usage………………………………………………………… 74
III.2. Methodology of the On-line searching Task Phase………………….
82
III.2.1 General research design…………………………………………….
82
III.2.2 On-line searching tasks……………………………………………..
83
III.2.3 Instruments………………………………………………………….
84
III.2.4 Data collection and data analyses…………………………………..
86
III.2.4.1 Exploring students’ on-line searching outcomes…………….
86
III.2.4.2 Exploring students’ cognitive outcomes, and informal reasoning outcomes…………………………………………. 88
CHAPTER IV: MAJOR FINDINGS……………………………..
90
IV.1. Results derived from the Informal Reasoning Exploration Phase…
90
IV.1.1 Results derived from the initial analyses of students' informal reasoning Outcomes……………………………………………….. 93
IV.1.1.1 Students’ decision-making modes…………………………...
93
IV.1.1.2 Students’ argument-construction for different purposes and usage of different reasoning modes………………………….. 93
IV.1.1.3 Students’ evaluative standard formation and justification…..
96
IV.1.2 Results derived from the follow-up analyses of students' informal reasoning Outcomes……………………………………………….. 100
IV.1.2.1 Students’ informal reasoning outcomes between different decision-making mode groups………………………………. 100
IV.1.2.2 Students’ informal reasoning outcomes between two different evaluative standard formation groups…………….. 102
IV.1.2.3 Students’ informal reasoning outcomes between two different self-perceived rationality groups………………….. 104
IV.1.2.4 Students’ informal reasoning outcomes between two different reasoning level groups…………………………….. 104
IV.1.2.5 Correlations between students’ argument construction for different purposes and usage of reasoning modes………….. 108
IV.1.3 Descriptive data regarding students’ scientific epistemological beliefs and their cognitive structure regarding nuclear power usage……………………………………………………………….. 110
IV.1.3.1 Descriptive data regarding students’ scientific epistemological beliefs……………………………………… 109
IV.1.3.2 Descriptive data regarding students’ cognitive structure regarding nuclear power usage……………………………... 110
IV.1.4 The interplay between students’ SEBs and their informal reasoning outcomes…………………………………………………………... 111
IV.1.4.1 Students’ SEBs and their decision-making modes………….
111
IV.1.4.2 The relationships between students’ SEBs and their argument-construction for different purposes (as well as their usage of reasoning modes)…………………………….. 113
IV.1.4.3 Students’ SEBs and their initial perspective for forming their initial position toward nuclear power usage…………... 114
IV.1.4.4 Students’ SEBs and their self-perceived rationality for their decision-making…………………………………………….. 116
IV.1.5 The interplay between students’ cognitive structure outcomes and their informal reasoning outcomes………………………………… 118
IV.1.5.1 Students’ cognitive structure outcomes and their decision-making modes……………………………………... 118
IV.1.5.2 The relationships between students’ cognitive structure outcomes and their argument-construction for different purposes (as well as their usage of reasoning modes)………. 118
IV.1.5.3 Students’ cognitive structure outcomes and their initial perspective for forming their initial position toward nuclear power usage…………………………………………………. 120
IV.1.6 The ability of students’ SEBs as predictors for their informal reasoning outcomes………………………………………………... 122
IV.1.6.1 The ability of students’ SEBs as predictors for their rebuttal construction…………………………………………………. 122
IV.1.6.2 The ability of students’ SEBs as the predictors for their usage of reasoning modes…………………………………... 123
IV.1.7 The ability of students’ cognitive structure outcomes as predictors for their informal reasoning outcomes…………………………….. 123
IV.1.7.1 The ability of the extent, the richness and the integratedness of students’ cognitive structure as the predictors for their rebuttal construction………………………………………... 124
IV.1.7.2 The ability of the extent, the richness and the integratedness of students’ cognitive structure as the predictors for their usage of reasoning modes…………………………………... 124
IV.1.7.3 The ability of students’ usage of different information processing modes as the predictors for their rebuttal construction…………………………………………………. 125
IV.1.7.4 The ability of students’ usage of different information processing modes as the predictors for their usage of reasoning modes……………………………………………. 126
IV.1.7.5 The ability of all the students’ cognitive structure outcomes as the predictors for their for their rebuttal construction…… 126
IV.1.7.6 The ability of all the students’ cognitive structure outcomes as the predictors for their for their usage of reasoning modes……………………………………………………….. 126
IV.1.8. The ability of students’ SEBs and cognitive structure outcomes as predictors for their informal reasoning outcomes…………………. 127
IV.1.8.1 The ability of students’ SEBs and cognitive structure outcomes as the predictors for their rebuttal construction….. 127
IV.1.8.2 The ability of students’ SEBs and cognitive structure outcomes as the predictors for their usage of reasoning modes……………………………………………………….. 128
IV.2. Results derived from the on-line searching task Phase……………..
129
IV.2.1 Results regarding the initial conditions of the students in the two on-line searching task groups……………………………………… 130
IV.1.2.1 Students’ SEBs, cognitive structure outcomes and informal reasoning outcomes before the conduct of on-line searching tasks…………………………………………………………. 130
IV.1.2.2 Students’ information commitments and their on-line hours per-week…………………………………………………….. 133
IV.2.2 The effects of different on-line searching tasks on the students’ learning outcomes…………………………………………………. 134
IV.2.2.1 The effects of different on-line searching tasks on the students’ searching outcomes……………………………….. 134
IV.2.2.2 The effects of different on-line searching tasks on the students’ cognitive structure outcomes……………………... 135
IV.2.2.3 The effects of different on-line searching tasks on the students’ informal reasoning outcomes……………………... 137
IV.2.3 The interaction between the students’ SEBs and on-line searching tasks on the students’ learning outcomes………………………….. 139
IV.2.3.1 The interaction between the students’ SEBs and on-line searching tasks on the students’ searching outcomes………. 139
IV.2.3.2 The interaction between the students’ SEBs and on-line searching tasks on the students’ cognitive structure outcomes……………………………………………………. 146
IV.2.3.3 The interaction between the students’ SEBs and on-line searching tasks on the students’ informal reasoning outcomes……………………………………………………. 152
IV.2.4 The interaction between the students’ information commitments and on-line searching tasks on the students’ learning outcomes…………………………………………………………… 157
IV.2.4.1 The interaction between the students’ information commitments and on-line searching tasks on the students’ searching outcomes…………………………………………. 157
IV.2.4.2 The interaction between the students’ information commitments and on-line searching tasks on the students’ cognitive structure outcomes……………………………….. 164
IV.2.4.3 The interaction between the students’ information commitments and on-line searching tasks on the students’ informal reasoning outcomes……………………………….. 172
IV.3. Summarization of the findings derived from the two Phases………
180
IV.3.1 Summarization of the findings derived from the informal reasoning exploration phase…………………………………………………... 180
IV.3.2 Summarization of the findings derived from the on-line searching task phase…………………………………………………………... 186
CHAPTER V DISSCUSSION AND CONCLUSION……………
189
V.1 Discussions on the major findings derived from the informal reasoning exploration phase…………………………………………… 190
V.1.1 Students’ usage of reasoning modes, decision-making modes, and reasoning quality……………………………………………………. 190
V.1.2 Students’ supportive argument and counter argument construction before and after making personal positions………………………… 191
V.1.3 The formation of students’ initial positions…………………………
191
V.1.4 Students’ evaluative criteria for arguments regarding two opposite positions…………………………………………………………….. 192
V.1.5 Students’ further need for making rational decisions………………..
193
V.1.6 Students’ self-perceived rationality…………………………………..
195
V.1.7 Gender difference on students’ informal reasoning regarding a socio-scientific issue………………………………………………... 196
V.1.8 Students’ cognitive structure and informal reasoning outcomes between different decision-making mode groups…………………... 196
V.1.9 The characteristics of students of higher-level reasoning quality…...
197
V.1.10 Students’ SEBs and their informal reasoning quality……………...
198
V.1.11 Students’ cognitive structure outcomes and their reasoning quality (as well as their usage of different reasoning modes)………………. 200
V.1.12 The ability of students’ SEBs and cognitive structure outcomes as predictors for their informal reasoning……………………………... 202
V.2 Discussions on the major findings derived from the on-line searching task phase……………………………………………………………….. 204
V.2.1 The effects of different on-line searching tasks on the students’ learning outcomes…………………………………………………... 204
V.2.2 The interaction between the students’ SEBs and on-line searching tasks on the students’ learning outcomes…………………………… 206
V.2.3 The interaction between the students’ information commitments and on-line searching tasks on the students’ learning outcomes……. 208
V.3 Re-examination of the theoretical model of this study………………..
209
V.4 Conclusions……………………………………………………………...
214
REFERENCES……………………………………………………... 216
APPENDIXES………………………………………………………………. 235
Appendix 1: Questionnaire for assessing scientific epistemological beliefs… 235
Appendix 2: Open-ended questionnaire for evaluating informal reasoning on nuclear power usage……………………………………………. 237
Appendix 3: Work sheet provided to the unguided on-line searching task group…………………………………………………………… 238
Appendix 4: Work sheet provided to the guided on-line searching task group…………………………………………………………… 239
Appendix 5: Appendix 5: Components, scales and items of the ICS……………………….. 240



LIST OF TABLES
page
Table 2.1: Important distinctions between the two cognitive systems in dual-process theories……………………………………………….. 12
Table 2.2: Summary of the representations of informal reasoning in previous studies………………………………………………………………. 20
Table 2.3: Summary of studies regarding students’ conceptual understanding and their informal reasoning on socio-scientific issues……………. 23
Table 2.4: Summary of studies regarding students’ views on the nature of science and their informal reasoning on socio-scientific issue…….. 26
Table 2.5: Five developmental models for epistemological development…….. 33
Table 2.6: A summary of Schommer’s main points of Epistemological Belief System……………………………………………………………… 35
Table 3.1: A rubric for grading students’ report regarding nuclear power and nuclear power usage………………………………………………... 87
Table 4.1: Gender comparison on students’ decision-making modes…………. 93
Table 4.2: Students’ argument-construction for different purposes and usage of different reasoning modes……………………………………….. 94
Table 4.3: Gender comparisons on students’ argument-construction for different purposes and usage of different reasoning modes………... 95
Table 4.4: Comparisons of students’ argument construction before and after making their personal decisions on nuclear power usage………….. 96
Table 4.5: Gender comparison on students’ initial perspectives for forming their personal positions in the beginning…………………………...
97
Table 4.6: Students’ evaluative criteria for making their personal decisions on nuclear power usage………………………………………………... 98
Table 4.7: Gender comparison on students’ self-perceived rationality ……….. 98
Table 4.8: Students’ responses on what they further need for making rational decisions on nuclear power usage………………………………….. 99
Table 4.9: Comparisons on students’ argument-construction and usage of reasoning modes across two different decision-making mode groups………………………………………………………………. 100
Table 4.10: Students’ initial perspectives and decision-making modes……….. 101
Table 4.11: Students’ self-perceived rationality and decision-making modes… 102
Table 4.12: Comparisons on students’ argument-construction and usage of reasoning modes across evaluative standard groups……………… 103
Table 4.13: Students’ reasoning levels and decision-making modes………….. 103
Table 4.14: Comparisons on students’ argument-construction and usage of reasoning modes across different perceived rationality groups…... 104
Table 4.15: Students’ reasoning levels and decision-making modes………….. 105
Table 4.16: Comparisons on students’ argument-construction and usage of reasoning modes across different reasoning level groups………….. 106
Table 4.17: Students’ reasoning levels and decision-making modes………….. 107
Table 4.18: Students’ reasoning levels and their self-perceived rationality…… 107
Table 4.19: Correlations between students’ usage of arguments for different purposes and their usage of reasoning modes…………………….. 109
Table 4.20: Students’ scores on the scales of questionnaire for assessing scientific epistemological beliefs…………………………………. 110
Table 4.21: Students’ cognitive structure outcomes and information processing modes regarding nuclear power………………………. 111
Table 4.22: Students’ responses on the scales of SEBS between different decision-making mode groups……………………………………... 112
Table 4.23: Correlations between students’ responses on the scales of SEBs and their informal reasoning outcomes…………………………… 113
Table 4.24: Comparisons on students’ responses on the scales of SEBs between different reasoning level groups………………….……… 115
Table 4.25: Comparisons on students’ responses on the scales of SEBs between different initial perspective groups……………………… 115
Table 4.26: Comparisons on students’ responses on the scales of SEBs between different perceived rationality groups…………………….. 117
Table 4.27: Students’ cognitive structure outcomes between different decision-making mode groups……………………………………... 117
Table 4.28: Correlations between students’ cognitive structure outcomes and their argument-construction for different purposes (as well as their usage of reasoning modes)…………………………………... 119
Table 4.29: Comparisons on students’ cognitive structure outcomes between different reasoning level groups…………………………………... 119
Table 4.30: Comparisons on students’ cognitive structure outcomes between different initial perspective groups………………………………... 121
Table 4.31: Comparisons on students’ cognitive structure outcomes between different self-perceived rationality groups………………………... 121
Table 4.32: Stepwise regression model testing the predictors of the amount of students’ rebuttal construction…………………………………….. 123
Table 4.33: Stepwise regression model testing the extent, the richness and the integratedness of students’ cognitive structure as the predictors for their rebuttal construction……………………………………... 124
Table 4.34: Stepwise regression model testing the ability of the extent, the richness and the integratedness of students’ cognitive structure as the predictors of students’ use of different reasoning modes……... 125
Table 4.35: Stepwise regression model testing the predictors of the amount of students’ rebuttal construction…………………………………….. 125
Table 4.36: Stepwise regression model testing the ability of all the students’ cognitive structure outcomes as the predictors of the amount of students’ rebuttal construction…………………………………….. 126
Table 4.37: Stepwise regression model testing the ability of all the students’ cognitive structure outcomes as the predictors of their usage of reasoning modes…………………………………………………... 127
Table 4.38: Stepwise regression model testing the predictors of students’ rebuttal construction………………………………………………. 128
Table 4.39: Stepwise regression model testing the predictors of the amount of students’ reasoning modes………………………………………… 129
Table 4.40: Comparisons on students’ scientific epistemological beliefs between two different on-line searching task groups……………... 131
Table 4.41: Comparisons on students’ cognitive structure regarding nuclear power between two different on-line searching task groups before the conduct of searching tasks (pretest)…………………………... 131
Table 4.42: Comparisons on students’ informal reasoning outcomes regarding nuclear power usage between two different on-line searching task groups before the conduct of searching tasks……………………..

132
Table 4.43: Comparisons on students’ information commitments and on-line hours per week between two different on-line searching task groups……………………………………………………………... 133
Table 4.44: Comparisons on students’ on-line searching outcomes between two different on-line searching task groups………………………. 134
Table 4.45: Comparisons on students’ cognitive structure regarding nuclear power between two different on-line searching task groups after the conduct of searching tasks……………………………………. 136
Table 4.46: Comparisons on students’ informal reasoning outcomes regarding nuclear power usage between two different on-line searching task groups after the conduct of searching tasks………………………. 138
Table 4.47: Regression model testing the predictors of the interaction between students’ SEBs (source) and on-line searching activities for their on-line searching outcomes……………………………………….. 140
Table 4.48: Regression model testing the predictors of the interaction between students’ SEBs (certainty) and on-line searching activities for their on-line searching outcomes…………………………………. 141
Table 4.49: Regression model testing the predictors of the interaction between students’ SEBs (development) and on-line searching activities for their on-line searching outcomes…………………………………. 142
Table 4.50: Regression model testing the predictors of the interaction between students’ SEBs (justification) and on-line searching activities for their on-line searching outcomes…………………………………. 143
Table 4.51: Regression model testing the predictors of the interaction between students’ SEBs (source) and on-line searching activities for the cognitive structure outcomes……………………………………… 147
Table 4.52: Regression model testing the predictors of the interaction between students’ SEBs (certainty) and on-line searching activities for the cognitive structure outcomes………………………………………

148
Table 4.53: Regression model testing the predictors of the interaction between students’ SEBs (development) and on-line searching activities for the cognitive structure outcomes………………………………….. 149
Table 4.54: Regression model testing the predictors of the interaction between students’ SEBs (justification) and on-line searching activities for the cognitive structure outcomes………………………………….. 150
Table 4.55: Regression model testing the predictors of the interaction between students’ SEBs (source) and on-line searching activities for the informal reasoning outcomes……………………………………... 153
Table 4.56: Regression model testing the predictors of the interaction between students’ SEBs (certainty) and on-line searching activities for the informal reasoning outcomes……………………………………... 154
Table 4.57: Regression model testing the predictors of the interaction between students’ SEBs (development) and on-line searching activities for the informal reasoning outcomes…………………………………. 155
Table 4.58: Regression model testing the predictors of the interaction between students’ SEBs (justification) and on-line searching activities for the informal reasoning outcomes………………………………….. 156
Table 4.59: Regression model testing the predictors of the interaction between students’ ICs (multiple sources) and on-line searching activities for their on-line searching outcomes……………………………… 158
Table 4.60: Regression model testing the predictors of the interaction between students’ ICs (authority) and on-line searching activities for their on-line searching outcomes……………………………………….. 159
Table 4.61: Regression model testing the predictors of the interaction between students’ ICs (content) and on-line searching activities for their on-line searching outcomes………………………………………..

160
Table 4.62: Regression model testing the predictors of the interaction between students’ ICs (technical) and on-line searching activities for their on-line searching outcomes……………………………………….. 161
Table 4.63: Regression model testing the predictors of the interaction between students’ ICs (elaboration) and on-line searching activities for their on-line searching outcomes…………………………………. 162
Table 4.64: Regression model testing the predictors of the interaction between students’ ICs (match) and on-line searching activities for their on-line searching outcomes……………………………………….. 163
Table 4.65: Regression model testing the predictors of the interaction between students’ ICs (multiple sources) and on-line searching activities for the cognitive structure outcomes……………………………… 165
Table 4.66: Regression model testing the predictors of the interaction between students’ ICs (authority) and on-line searching activities for the cognitive structure outcomes……………………………………… 166
Table 4.67: Regression model testing the predictors of the interaction between students’ ICs (content) and on-line searching activities for the cognitive structure outcomes……………………………………… 167
Table 4.68: Regression model testing the predictors of the interaction between students’ ICs (technical) and on-line searching activities for the cognitive structure outcomes……………………………………… 168
Table 4.69: Regression model testing the predictors of the interaction between students’ ICs (elaboration) and on-line searching activities for the cognitive structure outcomes……………………………………… 169
Table 4.70: Regression model testing the predictors of the interaction between students’ ICs (match) and on-line searching activities for the cognitive structure outcomes……………………………………… 170
Table 4.71: Regression model testing the predictors of the interaction between students’ ICs (multiple sources) and on-line searching activities for the informal reasoning outcomes……………………………… 173
Table 4.72: Regression model testing the predictors of the interaction between students’ ICs (authority) and on-line searching activities for the informal reasoning outcomes …………………………………….. 174
Table 4.73: Regression model testing the predictors of the interaction between students’ ICs (content) and on-line searching activities for the informal reasoning outcomes in the post-test…………………….. 175
Table 4.74: Regression model testing the predictors of the interaction between students’ ICs (technical) and on-line searching activities for the informal reasoning outcomes in the post-test……………………... 176
Table 4.75: Regression model testing the predictors of the interaction between students’ ICs (elaboration) and on-line searching activities for the informal reasoning outcomes in the post-test…………………….. 177
Table 4.76: Regression model testing the predictors of the interaction between students’ ICs (authority) and on-line searching activities for the cognitive structure outcomes……………………………………… 178
Table 4.77 Summary of the major findings derived from the informal reasoning exploration phase………………………………………. 181
Table 4.78 Summary of the major findings derived from the on-line searching task phase…………………………………………………………. 186



LIST OF FIGURES
page
Figure 2.1: The process of learners’ informal reasoning……………………… 14
Figure 2.2: Students’ scientific epistemological beliefs and their science learning……………………………………………………………. 43
Figure 2.3: The theoretical model of this study……………………………….. 66
Figure 3.1: A student’s flow map about nuclear power……………………….. 72
Figure 3.2: An integrated framework for analyzing students’ informal reasoning on nuclear power usage………………………………… 77
Figure 4.1: A framework for presenting the results derived from the informal reasoning exploration phase………………………………………. 92
Figure 4.2: Framework for presenting the results derived from the on-line searching task phase………………………………………………. 130
Figure 4.3: The interaction between SEBs (source) and on-line searching task on the amount of student on-line searching outcomes……………. 145
Figure 4.4: The interaction between SEBs (source) and on-line searching task on the organization of student on-line searching outcomes……….. 145
Figure 4.5: The interaction between SEBs (development) and on-line searching task on student usage of the “inferring or explaining” information processing mode……………………………………... 151
Figure 4.6: The interaction between information commitments (match) and on-line searching task on the integrateness of student cognitive structures………………………………………………………….
171
Figure 4.7: The interaction between information commitments (multiple sources) and on-line searching task on the total number of arguments…………………………………………………………. 179
Figure 5.1: Re-examination of the theoretical model of this study……………. 213

Adamson, A. B., Foster, M. A., Roark, M L., & Reed, D. B. (1998). Doing a science project: Gender differences during childhood. Journal of Research in Science Teaching, 35, 845-857.
American Association for the Advancement of Science (1989). Science for All Americans. New York: Oxford University Press.
American Association for the Advancement of Science (1993). Benchmarks for Science Literacy. New York: Oxford University Press.
Anderson, O. R., & Demetrius, O. J. (1993). A flow-map method of representing cognitive structure based on respondents’ narrative using science content. Journal of Research in Science Teaching, 30, 953-969.
Anderson, O. R., Randle, D., & Covotsos, T. (2001). The role of ideational networks in laboratory inquiry learning and knowledge of evolution among seventh grade students. Science Education, 85, 410-425.
Ausubel, D. P. (1968). Educational psychology: A cognitive viewpoint. New York: Rinehart & Winston.
Baxter Magolda, M. B. (1992). Students’ epistemologies and academic experiences: Implications for pedagogy. The Review of Higher Education, 15, 265-287.
Baxter Magolda, M. B. (2002). Epistemological reflection: The evolution of epistemological assumptions from age 18 to 30. In B. Hofer & P. Pintrich (Eds.), Personal epistemology: The psychology of beliefs about knowledge and knowing (pp. 89-102). Erlbaum: Mahwah, N.J.
Belenky, M. F., Clinchy, B. M., Goldberger, N. R., & Tarule, J. M. (1986). Woman's ways of knowing: The development of self, voice and mind. New York: Basic Books
Bendixen, L. D. (2002). A process model of epistemic belief change. In B. Hofer & P. Pintrich (Eds.), Personal epistemology: The psychology of beliefs about knowledge and knowing (pp. 191-208). Erlbaum: Mahwah, N.J.
Bendixen, L. D., & Hartley, K. (2003). Successful learning with hypermedia: The role of epistemological beliefs and metacognitive awareness. Journal of Educational Computing Research, 28, 15-30.
Bell, R. L., & Lederman, N. G. (2003). Understandings of the nature of science and decision making on science and technology based issues. Science Education, 87, 352-377.
Bischoff, P. J. (2006). The role of knowledge structures in the ability of preservice elementary teachers to diagnose a child's understanding of molecular kinetics, Science Education, 90, 936-951.
Bischoff, P. J., & Anderson, O. R. (1998). A case study analysis of the development of knowledge schema, ideational network, and higher cognitive operations among high school students who studied ecology. School Science and Mathematics, 98, 228-237.
Bischoff, P. J., & Anderson, O. R. (2001). Development of knowledge frameworks and higher order cognitive operations among secondary school students who studied a unit on ecology. Journal of Biological Education, 35, 81-88.
Braine, M. D. S., & O’Brien, D. P. (1995). Predicting intermediate and multiple conclusions in propositional logic inference problems: Further evidence for a mental logic. Journal of Experimental Psychology: General, 3, 263–292.
Brandt, D. S. (1996). Evaluating information on the Internet. Computers in Libraries, 16, 44-46.
Braten, I., & Stromso, H. I. (2006). Epistemological beliefs, interest, and gender as predictors of Internet-based learning activities. Computers in Human Behavior, 22, 1027-1042.
Brem, S. K., Russell, J., & Weems, L. (2001). Science on the Web: Student evaluations of scientific arguments. Discourse Processes, 32, 191-213.
Bilal, D. (2001). Children’s use of the Yahooligans! Web search engine: II. Cognitive and physical behaviors on research tasks. Journal of the American Society for Information Science and Technology, 52, 118-136.
Buehl, M. M., & Alexander, P. A. (2001). Beliefs about academic knowledge. Educational Psychology Review, 13, 385-418.
Buehl, M. M., Alexander, P. A., & Murphy, P. K. (2002). Beliefs about schooled knowledge: Domain specific or domain general? Contemporary Educational Psychology, 27, 415-449.
Bybee, R. W., & DeBoer, G. E. (1994). Research goals for the science curriculum. In D. L. Gabel (Ed.), Handbook of Research on Science Teaching. New York: Macmillan Publishing Company.
Cajas, F. (2001). The science/technology interaction: Implications for science literacy. Journal of Research in Science Teaching, 38, 715-729.
Chiu, C.-H., Huang, C.-C., & Chang, W.-D. (2000). The evaluation and influence of interaction in network supported collaborative concept mapping. Computers & Education, 34, 17-25.
Chou, C., & Tsai, C.-C. (2002). Developing Web-based curricula: Issues and challenges. Journal of Curriculum Studies, 34, 623-636.
Chuang, S.-C., & Tsai, C.-C. (2005). Preferences toward the constructivist internet-based learning environments among high school students in Taiwan. Computers in Human Behavior, 21, 255-272.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, New Jersey: Lawrence.
Conley, A. M., Pintrich, P. R., Vekiri, I., & Harrison, D. (2004). Changes in epistemological beliefs in elementary science students. Contemporary Educational Psychology, 29, 186-204.
Driver, R, & Bell, B. (1986). Students’ thinking and the learning of science: A constructivist view. School Science Review, 67, 443-456.
Driver, R., Newton, P., & Osborne, J. (2000). Establishing the norms of scientific argumentation in classrooms. Science Education, 23, 689-698.
Duell, O. K., & Schommer-Aikins, M. (2001). Measures of people‘s beliefs about knowledge and learning. Educational Psychology Review 13, 419-449.
Duschl, R. A. (1990). Restructuring Science Education. New York: Teachers College Press.
Edmondson, K., & Novak, J. (1993). The interplay of scientific epistemological views, learning strategies, and attitude of college students. Journal of Research in Science Teaching, 30, 547-559.
Elder, A. D. (2002). Characterizing fifth grade students’ epistemological beliefs in science. In B. Hofer & P. Pintrich (Eds.), Personal epistemology: The psychology of beliefs about knowledge and knowing (pp. 347-364). Erlbaum: Mahwah, N.J.
Evans, J. St. B. T. (1996). Deciding before you think: Relevance and reasoning in the selection task. British Journal of Psychology, 87, 223-240
Evans, J. St. B. T. (2002). Logic and human reasoning: An assessment of the deduction paradigm. Psychological Bulletin, 128, 978-996.
Evans, J. St. B. T. (2003). In two minds: Dual-process accounts of reasoning. Trends in Cognitive Sciences, 7, 454-459.
Evans, J. St. B. T., & Curtis-Holmes, J. (2005). Rapid responding increases belief bias: Evidence for the dual-process theory for reasoning. Thinking & Reasoning, 11, 382-389.
Evans, J. St. B. T., & Thompson, V. A. (2004). Informal reasoning: Theory and method. Canadian Journal of Experimental Psychology, 58, 69-74.
Eylon, B., & Linn, M. C. (1988). Learning and Instruction: An examination of four research perspectives in science education. Review of Educational Research, 58, 251-301.
Fidel, R., Davies, R. K., Douglass, M. H., Holder, J. K., Hopkins, C. J., Kushner, E. J., Miyagishima, B. K., & Toney, C. D. (1999). A visit to the information mall: Web searching behavior of high school students. Journal of the American Society for Information Science, 50, 24-37.
Glaser, R. (1984). Education and thinking. American Psychologist, 39, 93-104.
Hammer, D., & Elby, A. (2002). On the Form of a Personal Epistemology. In B. Hofer & P. Pintrich (Eds.), Personal epistemology: The psychology of beliefs about knowledge and knowing (pp. 169-190). Erlbaum: Mahwah, N.J.
Hammer, D., & Elby, A. (2004). Epistemological resources: Applying a new epistemological framework to science instruction. Educational Psychologist, 39, 57-68.
Haskell, R. E. (2001). Transfer of learning: Cognition, instruction, and reasoning. San Diego: Academic Press.
Head, J. O., & Sutton, C. R. (1985). Language, understanding, and commitment. In L. H. T. West & A. L. Pines (Eds.), Cognitive structures and conceptual change, (pp. 91-100). Orlando: Academic Press.
Hofer, B. K. (2000). Dimensionality and disciplinary differences in personal epistemology. Contemporary Educational Psychology, 25, 378-405.
Hofer, B. K. (2001). Personal epistemology research: Implications for learning and teaching. Educational Psychological Review, 13, 353-383.
Hofer, B. K. (2004). Epistemological understanding as a metacognitive process: Thinking aloud during online searching. Educational Psychologist, 39, 43-55.
Hofer, B. K., & Pintrich, P. R. (1997). The development of epistemological theories: Beliefs about knowledge and knowing and their relation to learning. Review of Educational Research, 67, 88-140.
Hofer, B. K., & Pintrich, P. R. (1997). Personal epistemology: The psychology of beliefs about knowledge and knowing. Erlbaum: Mahwah, N.J.
Hofferman, J. L., Wu, H. K., Krajcik, J. S., & Soloway, E. (2003). The nature of middle school learners’ science content understandings with the use of on-line resources. Journal of Research in Science Teaching, 40, 323-346.
Hogan, K. (2002). Small groups’ ecological reasoning while making an environmental management decision. Journal of Research in Science Teaching, 39, 341-368.
Honderich, T. (1995). The Oxford Companion to Philosophy. New York, Oxford University Press.
Jamieson, S. (2004). Likert scales: how to (ab)use them. Medical Education, 38, 1212-1218.
Jean-Francois, R. (2003). What was I looking for? The influence of task specificity and prior knowledge on students’ search strategies in hypertext. Interacting with Computers, 15, 409-428.
Johnson, R. L., Penny, J., & Gordon, B. (2000). The relation between score resolution methods and interrater reliability: An empirical study of an analytic scoring rubric. Applied Measurement in Education, 13, 121-138.
Jonassen, D. H. (1996). Computers in the classroom: Mindtools for critical thinking. Columbus, OH: Merrill/Prentice-Hall.
Jonassen, D. H. (2000). Computers as mindtools for schools. Prentice Hall, Inc. New Jersey.
Jonassen, D. H., Peck, K.L., & Wilson, B. G. (1999). Learning with technology: A constructivist perspective. Upper Saddle River, New Jersey: Merrill.
Johnson-Laird, P. N. (1983). Mental models: Towards a cognitive science of language, inference, and consciousness. Cambridge, England: Cambridge University Press.
Johnson, R. B., & Onwuegbuzie, A. J. (2004). Mixed Methods Research: A research paradigm whose time has come. Educational Researcher, 33, 14-26.
Jones, M. G.., Howe, A., & Rua, M. J. (2000). Gender differences in students' experiences, interests, and attitudes toward science and scientists. Science Education, 84, 180-192.
Knapp, T. R. (1990). Treating ordinal scales as interval scales: An attempt to resolve the controversy. Nursing Research, 39, 121-123.
Kardash, C. M., & Scholes, R. J. (1996). Effects of preexisting beliefs, epistemological beliefs and need for cognition on interpretation of controversial issues. Journal of Educational Psychology, 88, 260-271.
Kerlinger, F. N., & Lee, H. B. (2000). Foundations of Behavioral Research (4th ed.). Fort Worth, TX: Harcourt College Publishers.
King, P. M., & Kitchener, K. S. (2002). The reflective judgment model: Twenty years of research on epistemic cognition. In B. Hofer & P. Pintrich (Eds.), Personal epistemology: The psychology of beliefs about knowledge and knowing (pp.37-62). Erlbaum: Mahwah, N.J.
Knezek, G.., & Christensen, R. (2002). Impact of new information technologies on teachers and students. Education and Information Technologies, 7, 369-376.
Koballa, T. R. (1984). Goals of science education. In D. Holdzkom & P. B. Lutz (Eds.) Research within reach: science education (pp. 25-39). Washington, D.C.: NSTA.
Kolsto, S. D. (2001). Scientific literacy for citizenship: Tools for dealing with the science dimension of controversial socioscientific issues. Science Education, 85, 291-310.
Kolsto, S. D. (2006). Patterns in students’ argumentation confronted with a risk-focused socio-scientific issue. International Journal Science Education, 28, 1689-1716.
Kolsto, S. D., Bungum, B., Arnesen, E., Isnes, A., Kristensen, T., Mathiassen, K., et al. (2006). Science students' critical examination of scientific information related to socioscientific issues. Science Education, 90, 632-655.
Kuechler, M. (1999). Using the Web in the classroom. Social Science Computer Review, 17, 144-161.
Kuhn, D. (1991). The skills of argument. Cambridge, England: Cambridge University Press.
Kuhn, D. (1993). Connecting scientific and informal reasoning. Merrill-Palmer Quarterly, 39, 74-103.
Kuhn, D., Cheney, R., & Weinstock, M. (2000). The development of epistemological understanding. Cognitive Development, 15, 309-328.
Kuiper, E., Volman, M., & Terwel, J. (2005). The Web as an information resource in K-12 education: Strategies for supporting students in searching and processing information. Review of Educational Research, 75, 285-328.
Lawson, A. E. (2001). Using the learning cycle to teach biology concepts and reasoning patterns. Journal of Biological Education, 35, 165-169.
Lawson, A. E. (2004). The nature and development of scientific reasoning: A synthetic view. International Journal of Science and Mathematics Education, 2, 307-338.
Lazonder, A. W. (2000). Exploring novice users’ training needs in searching information on the WWW. Journal of Computer Assisted Learning, 16, 326-335.
Lederman, N. G. (1992). Students’ and teachers’ conceptions of the nature of science: A review of the research. Journal of Research in Science Education, 29, 331-359.
Lee, V. E., & Burkam, D. T. (1996). Gender differences in middle grade science achievement: Subject domain, ability level, and course emphasis. Science Education, 80, 613-650.
Lin, H. S., Chiu, H. L., & Chou, C. Y. (2004). Students’ understanding of the nature of science and their problem-solving strategies. International Journal of Science Education, 26, 101-112.
Lin, C.-C., & Tsai, C.-C. (2005). A “navigation flow map” method of representing students’ searching strategies on the Web. Paper presented at 2005 World Conference on Educational Multimedia, Hypermedia & Telecommunications, Montreal, Canada.
Linn. M. C. (2003). Technology and science education: Start point, research program, and trends. International Journal of Science Education, 25, 727 – 758.
Linn. M. C., Bell, P., & Davis, E. A. (2004). Special design principle: Elaborating the scaffolded knowledge integration framework. In M. Linn, E. A. Davis & P. Bell (Eds.), Internet environments for science education (pp. 315-341). Mahwah, NJ: Lawrence Erlbaum Associates.
Linn. M. C., Clark, D., & Slotta, J. D. (2003). WISE design for knowledge integration. Science Education, 87, 517-538.
Mason, L., & Boscolo, P. (2004). Role of epistemological understanding and interest in interpreting a controversy and in topic-specific belief change. Contemporary Educational Psychology, 29, 103-128.
Mason, L., & Scirica, F. (2006). Prediction of students’ argumentation skills about controversial topics by epistemological understanding. Learning and Instruction, 16, 492-509.
McDowell, L. (2002). Electronic information resources in undergraduate education: an exploratory study of opportunities for student learning and independence. British Journal of Educational Technology, 33, 255-266.
Means, M. L., & Voss, J. F. (1996). Who reasons well? Two studies of informal reasoning among children of different grade, ability, and knowledge levels. Cognition and Instruction, 14, 139-178.
Metzger, M. J., Flanagin, A. J., & Zwarun, L. (2003). College student Web use, perceptions of information credibility, and verification behavior. Computers & Education, 41, 271-290.
Miller, S. M., & Miller, K. L. (2000). Theoretical and practical considerations in the design of Web-Based Instruction. In B. Abbey (Ed.), Instructional and cognitive impacts of Web-Based Instruction. Hershey, PA: Idea Group Publishing.
Mintzes, J. J., Wandersee, J. H., & Novak, J. D. (2001). Assessing understanding in biology. Journal of Biological Education, 35, 118-124.
Mistler-Jackson, M., & Songer, N. B. (2000). Student motivation and internet technology: Are students empowered to learn science? Journal of Research in Science Teaching, 37, 459--479.
Moore, W. S. (2002). Understanding learning in a Postmodem World: Reconsidering the Perry Scheme of ethical and intellectual development. In B. Hofer & P. Pintrich (Eds.), Personal epistemology: The psychology of beliefs about knowledge and knowing (pp. 17-36). Erlbaum: Mahwah, N.J.
Muis, K. (2004). Personal epistemology and mathematics. Review of Educational Research, 74, 317-378.
National Research Council (1996). National Science Education Standards. Washington, DC: National Academy Press.
Novak, J. D., & Gowin, D. B. (1984). Concept mapping for meaningful learning. In J. D. Novak & D. B. Gowin (Eds.), Learning how to learn, (pp. 15-54). NY: Cambridge University Press.
Osborne, J., Erduran, S., & Simon, S. (2004). Enhancing the quality of argument in school science. Journal of Research in Science Teaching, 41, 994-1024.
Patronis, T., Potari, D., & Spiliotopoulou, V. (1999). Students’ argumentation in decision-making on a socio-scientific issue: Implications for teaching. International Journal of Science Education, 21, 745-754.
Perkins, D. N. (1985). Post-primary education has little impact upon informal reasoning. Journal of Educational Psychology, 77, 562-571.
Perry, W.G. (1970). Forms of intellectual and ethical development in the college years: A scheme. New York: Holt, Rinehart and Winston.
Pines, A. L. (1985). Toward a taxonomy of conceptual relations and the implications for the evaluation of cognitive structures. In L. H. T. West & A. L. Pines (Eds.), Cognitive structures and conceptual change, (pp. 101-115). Orlando: Academic Press.
Randel, J. M., Pugh, H. L., & Reed, S. K. (1996). Differences in expert and novice situation awareness in naturalistic decision making. International Journal of Human Computer Studies, 45, 579-597.
Relan, A., & Gillani, B. B. (1997). Web-Based Instruction and traditional classroom: Similarities and difference. In B.H. Khan (Ed.), Web-Based Instruction. (pp. 41-46.) Englewood Cliffs, NJ: Educational Technology.
Rennie, L. J. (1998). Improving the interpretation and reporting of quantitative research. Journal of Research in Science Teaching, 35, 237-248.
Roth, W. (2001). Learning science through technological design. Journal of Research in Science Teaching, 38, 768-790.
Ruthven, K., Hennessy, S., & Deaney, R. (2005). Incorporating Internet resources into classroom practice: Pedagogical perspectives and strategies of secondary-school subject teachers. Computers and Education, 44, 1-34.
Ryan, A. G., & Aikenhead, G. S. (1992). Students’ preconceptions about the epistemology of science. Science Education, 76, 559-580.
Sadler, T. D. (2004). Informal reasoning regarding socioscientific issues: A critical review of research. Journal of Research in Science Teaching, 41, 513-536.
Sadler, T. D. (2005). Evolutionary theory as a guide to socioscientific decision-making. Journal of Biological Education, 39, 68-72.
Sadler, T. D., Chambers, F. W., & Zeidler, D. L. (2004). Student conceptualizations of the nature of science in response to a socioscientific issue. International Journal of Science Education, 26, 387-409.
Sadler, T. D., & Zeidler, D. L. (2004). The significance of content knowledge for informal reasoning regarding socioscientific issues: Applying genetic knowledge to genetic engineering issues. Science Education, 88, 683-706.
Sadler, T. D., & Zeidler, D. L. (2005). Patterns of informal reasoning in the context of socioscientific decision making. Journal of Research in Science Teaching, 42, 112-138.
Schommer, M. (1990). Effects of beliefs about the nature of knowledge on comprehension. Journal of Educational Psychology, 82, 498-504.
Schommer, M. (1994). Synthesizing epistemological belief research: Tentative understandings and provocative confusions. Educational Psychology Review, 6, 292-319.
Schommer, M. A., & Walker, K. (1997). Epistemological beliefs and valuing school: Considerations for college admissions and retention. Research in Higher Education, 38, 173-185.
Schommer-Aikins, M. (2002). An Evolving Theoretical framework for an epistemological belief system. In B. Hofer & P. Pintrich (Eds.), Personal epistemology: The psychology of beliefs about knowledge and knowing (pp. 103-118). Erlbaum: Mahwah, N.J.
Schommer-Aikins, M., Duell, O. K., & Barker, S. (2003). Epistemological beliefs across domains using Biglan’s classification of academic disciplines. Research in Higher Education, 44, 347-366.
Schommer-Aikins, M., & Hutter, R. (2002). Epistemological beliefs and thinking about everyday controversial issues. The Journal of Psychology, 136, 5-20.
Schraw, G. (2001). Current themes and future directions on epistemological research: A commentary. Educational Psychology Review, 13, 451-464
Schraw, G., Bendixen, L. D., & Dunkle, M. E. (2002). Development and validation of the epistemic belief inventory (EBI). In B. Hofer & P. Pintrich (Eds.), Personal epistemology: The psychology of beliefs about knowledge and knowing (pp. 261-276). Erlbaum: Mahwah, N.J.
Schraw, G., Dunkle, M., & Bendixen, L. (1995). Cognitive processes in well-defined and ill-defined problem solving. Applied Cognitive Psychology, 9, 523-538.
Schraw, G., & Sinatra, G. (2004). Epistemological development and its impact on cognition in academic domains. Contemporary Educational Psychology, 29, 95-102.
Shavelson, R. J. (1974). Methods for examining representations of a subject-matter structure in a student’s memory. Journal of Research in Science Teaching, 11, 231-249.
Shavelson, R. J., Carey, N. B., & Web, N. M. (1990). Indicators of science achievement: Options for a powerful policy instrument. Phi Delta Lappan, 71, 692-697.
Shaw, V. F. (1996). The cognitive processes in informal reasoning. Thinking and Reasoning, 2, 51-80.
Sloman, S. A. (1996). The empirical case for two systems of reasoning. Psychological Bulletin, 119, 3-22.
Skinner, N. C., & Preece, P. W. (2003). The use of information and communications technology to support the teaching of science in primary schools. International Journal of Science Education, 25, 205-219.
Songer, N. B., & Linn, M. C. (1991). How do students’ views of science influence knowledge integration? Journal of Research in Science Teaching, 28, 761-784.
Strike, K., & Posner, G. (1992). A revisionist theory of conceptual change. In R. Duschl & R. Hamilton (Eds.), Philosophy of science, cognitive psychology, and educational theory and practice (pp. 147-176). Albany, NY: State University of New York Press.
Tsai, C.-C. (1998a). An analysis of Taiwanese eighth graders’ science achievement, scientific epistemological beliefs and cognitive structure outcomes after learning basic atomic theory. International Journal of Science Education, 20, 413-425.
Tsai, C.-C. (1998b). An analysis of scientific epistemological beliefs and learning orientations of Taiwanese eighth graders. Science Education, 82, 473-489.
Tsai, C.-C. (1999). Content analysis of Taiwanese 14 year olds’ information processing operations shown in cognitive structures following physics instruction, with relations to science attainment and scientific epistemological beliefs. Research in Science & Technological Education, 17, 125-138.
Tsai, C.-C. (2000a). Relationships between student scientific epistemological beliefs and perceptions of constructivist learning environments. Educational Research, 42, 193-205.
Tsai, C.-C. (2000b). The effects of STS-oriented instruction on female tenth graders’ cognitive structure outcomes and the role of student scientific epistemological beliefs. International Journal of Science Education, 22, 1099-1115.
Tsai, C.-C. (2001a). A review and discussion of epistemological commitments, metacognition, and critical thinking with suggestions on their enhancement in Internet-assisted chemistry classrooms. Journal of Chemical Education, 78, 970-974.
Tsai, C.-C. (2001b). Probing students’ cognitive structures in science: The use of a flow map method coupled with a meta-listening technique. Studies in Educational Evaluation, 27, 257-268.
Tsai, C.-C. (2001c). The interpretation construction design model for teaching science and its applications to Internet-based instruction in Taiwan. International Journal of Educational Development, 21, 401-415.
Tsai, C.-C. (2003). Using a “conflict map” as an instructional tool to change student alternative conceptions in simple series electric-circuits. International Journal of Science Education, 25, 307-327.
Tsai, C.-C. (2004a). Beyond cognitive and metacognitive tools: the use of the Internet as an “epistemological” tool for instruction. British Journal of Educational Technology, 35, 525-536.
Tsai, C.-C. (2004b). Information commitments in Web-based learning environments. Innovations in Education and Teaching International, 41, 105-112.
Tsai, C.-C., & Chou, Y.-R. (2005). The role of “core” and “anchored” concepts in knowledge recall: A study of knowledge organization of learning thermal physics. Knowledge Organization, 32, 143-158.
Tsai, C.-C., Lin, S. S. J., & Yuan, S.-M. (2000). Taiwanese high school science students’ views of using a www-based concept map testing system. International Journal of Instructional Media, 27, 363-368.
Tsai, C.-C., & Huang, C.-M. (2001). Development of cognitive structures and information processing strategies of elementary school students learning about biological reproduction. Journal of Biological Education, 36, 21-26.
Tsai, C.-C., & Huang, C.-M. (2002). Exploring students’ cognitive structures in learning science: A review of relevant methods. Journal of Biological Education, 36, 163-169.
Tsai, C.-C., & Liu, S.-Y. (2005). Developing a multi-dimensional instrument for assessing students epistemological views toward science. International Journal of Science Education, 28, 1621-1638.
Tweney, R. D. (1991). Informal reasoning in science. In J. F. Voss, D. N. Perkins, & J. W. Segal (Eds.), Informal reasoning and education (pp. 3-16). Hillsdale, NJ: Erlbaum.
West, L. H. T., Fensham, P. J., & Garrard, J. E. (1985). Describing the cognitive structures of learners following instruction in chemistry. In L. H. T. West & A. L. Pines (Eds.), Cognitive structures and conceptual change, (pp. 29-48). Orlando: Academic Press.
White, R., & Gunstone, R. (1992). Prediction-observation-explanation. In R. White & R. Gunstone (Eds.), Probing Understanding, (pp. 44-64). London: The Falmer Press.
Whitmire, E. (2003). Epistemological beliefs and the information-seeking behavior of undergraduates. Library & Information Science Research, 25, 127-142.
Whitmire, E. (2004). The relationship between undergraduates’ epistemological beliefs, reflective judgment, and their information-seeking behavior. Information Processing and Management, 40, 97-111.
Wu, Y.-T., & Tsai, C.-C. (2005a). Development of elementary school students’ cognitive structures and information processing strategies under long-term constructivist-oriented science instruction. Science Education, 89, 657-674.
Wu, Y.-T., & Tsai, C.-C. (2005b). The effects of constructivist-oriented instruction on elementary school students’ cognitive structures. Journal of Biological Education, 39, 113-119.
Wu, Y.-T., & Tsai, C.-C. (2005c). Information commitments: Evaluative standards and information searching strategies in web-based learning environments. Journal of Computer Assisted Learning, 21, 374-385.
Wu, Y. -T., & Tsai, C. -C. (2007a). High school students’ informal reasoning on a socio-scientific issue: Qualitative and quantitative analyses. International Journal of Science Education.
Wu, Y. -T., & Tsai, C. -C. (2007b). Developing an Information Commitments Survey for assessing students’ Web information searching strategies and their evaluative standards for Web materials. Educational Technology & Society, 10, 120-132.
Yang, F. Y. (2004). Exploring high school students’ use of theory and evidence in an everyday context: the role of scientific thinking in environmental science decision-making. International Journal of Science Education, 26, 1345-1364.
Yang, F. Y., & Anderson, O. R. (2003). Senior high school students’ preference and reasoning modes about nuclear energy use. International Journal of Science Education, 25, 221-244.
Yore, L. D. (2003) Examining the literacy component of science literacy: 25 years of language arts and science research. International Journal of Science Education, 25, 689-725.
Zeidler, D. L., Walker, K. A., Ackett, W. A., & Simmons, M. L. (2002). Tangled up in views: Beliefs in the nature of science and responses to socioscientific dilemmas. Science Education, 86, 343-367.
Zohar, A., & Nemet, F. (2002). Fostering students’ knowledge and argumentation skills through dilemmas in human genetics. Journal of Research in Science Teaching, 39, 35-62.