從認知歷程角度探討學生線上學習以及論證表現__臺灣人文及社會科學引文索引資料庫

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題名：	從認知歷程角度探討學生線上學習以及論證表現
作者：	鄭嘉惠
作者(外文)：	Cheng, Chia-Hui
校院名稱：	國立臺灣師範大學
系所名稱：	科學教育研究所
指導教授：	楊芳瑩
學位類別：	博士
出版日期：	2020
主題關鍵詞：	科學教育；社會性科學議題；論證表現；科學認識觀；眼球追蹤技術；science education；socio-scientific issues；argument performance；epistemic beliefs in science；eye tracking method
原始連結：	連回原系統網址
相關次數：	被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0) 排除自我引用:0 共同引用:0 點閱:1

本論文的主要目標為探討在社會性科學議題的網路課程中，學生的學習歷程與論證表現。本論文根據研究架構分為四個不同的研究議題，第一個研究為模型建立的理論研究，以Mplus7檢驗三種不同科學認識觀的結構模型，了解三種科學認識觀所包含各面向之間的關連性及預測結構。第二個研究為研究方法的回顧性研究，探討當前眼球追蹤技術應用於科學教育研究的趨勢，然後根據文獻回顧的結果，提出未來運用眼球追蹤技術於科學教育中的研究架構，並根據所提出的建議設計後續的研究內容。第三個研究為實徵研究，探討大學生科學認識觀與論證結構的學習歷程與理解之關係。研究結果指出，當大學生持有越高程度的「確定性」信念時，會對於論證結構付出較少的認知注意力，導致較差的學習表現。第四個研究亦為實徵研究，欲了解融入社會性科學議題的生物醫學網路課程中，大學生的認知學習歷程、論證表現以及個人因素(例如：先備知識、科學認識觀、網路搜尋行為等)對於學習的影響。研究結果發現，學生的認知學習歷程以及論證表現和個人因素皆有其相關性存在。各研究結果皆支持此論文的研究架構，且根據研究結果提出教育上的意涵以及未來研究建議。

以文找文

The ultimate goal of this thesis was to investigate how students reason and evaluate a biomedical socio-scientific issue (SSI). To reach the goal, we prepared several studies that were theoretically, methodologically and empirically related. Previous studies have indicated that some psychological factors may affect students’ cognitive process during learning and their argument performances. Among these factors, epistemic beliefs in science have been frequently mentioned and discussed. In literature, various forms of epistemic beliefs related to reasoning can be found. However, the associations between different epistemic beliefs have not been thoroughly examined. In study 1 (Chapter 2), we examined the associations among beliefs about the nature of knowledge, beliefs about the justification for knowing in science and Internet-specific justification, and then tested a structural model of these epistemic beliefs . In this thesis, a key method for empirical studies was the eye tracking method. Although the eye tracking method has been used by psychological and educational researchers, how this method can be applied specifically to investigate processes of science learning has not been systemically examined. Therefore, the second study of this thesis (presented in Chapter 3) was a methodologically literature review to analyze the research issue, research design and learning dimensions of studies in science education, which apply the eye tracking method. Based on the review result, we applied an inherent eye tracking design to explore information processing behaviors associated with the learning activities involved in the thesis research. Given that the ultimate goal of the study was related to the practice of argumentative reasoning on a SSI, it was hypothesized that the personal epistemic beliefs in science should interact with the understanding about the argument structure. We conducted empirical studies to test the interactions. Accordingly, in Study 3 (Chapter 4), the associations among different types of epistemic beliefs in science, learning of argument structure and understanding of the argument structure were analyzed. At last, another empirical study as presented in Study 4 (Chapter 5) was designed to investigate how students reasoned about a biomedical issue involved in the study. Factors explored in Study 1-3 were taken into consideration in the design. In Study 4, an online learning environment was created first, which allowed students to learn basic scientific knowledge, read the socio-scientific issue with selected articles, search related information through the Internet, and present their opinions. University learners were asked to learn and evaluate the biomedical issue discussed in the study in the online learning environment. Afterwards, we examined the effects of epistemic beliefs, students’ information processing behaviors during the online activities and the uses of argument components in the context of the biomedical issue. The result showed that students’ attention to the online SSI lesson and the web search result were positively correlated with the change in argument performance. Especially, attention to warrant for the opposing opinion positively predicted the change. Interactions among argument performances, visual attention during learning and epistemic beliefs in science were found. Based on the study results as presented in Chapter 2 to 5, suggestions for future research and implications for science education were provided in Chapter 6.

以文找文

Chapter1:
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Bråten, I., Strømsø, H. I., & Samuelstuen, M. S. (2005). The relationship between Internet-specific epistemological beliefs and learning within Internet technologies. Journal of Educational Computing Research, 33, 141-171.
Chen, Y. C., & Yang, F. Y. (2014). Probing the relationship between process of spatial problems solving and science learning: An eye tracking approach. International Journal of Science & Mathematics Education, 12(3), 579-603.
Chin, C. C., Yang, W. C., & Tuan, H. L. (2016). Argumentation in a socioscientific context and its influence on fundamental and derived science literacies. International Journal of Science and Mathematics Education, 14(4), 603-617.
Chiu, Y. L., Tsai, C. C., & Liang, J. C. (2015). Testing measurement invariance and latent mean differences across gender groups in college students’ Internet-specific epistemic beliefs. Australasian Journal of Educational Technology, 31, 486-499.
Conley, A. M., Pintrich, P. R., Vekiri, I. & Harrison, D. (2004). Changes in epistemological beliefs in elementary science students. Contemporary Educational Psychology, 29(2), 186-204.
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Chapter2:
Abd-El-Khalick, F. (2013). Teaching with and about nature of science, and science teacher knowledge domains. Science & Education, 22(9), 2087-2107.
Bentler, P. M. (1990). Comparative ﬁt indexes in structural models. Psychological Bulletin, 107, 238-246.
Brandmo, C., & Bråten, I. (2018). Investigating relations between beliefs about justification for knowing, interest, and knowledge across two socio-scientific topics. Learning and Indiidual Differences, 62, 89-97.
Bråten, I., Brandmo, C., & Kammerer, Y. (2018). A Validation Study of the Internet-Specific Epistemic Justification Inventory With Norwegian Preservice Teachers. Journal of Educational Computing Research, 0(0), 1-24.
Bråten, I., Ferguson, L. E., Strømsø, H. I., & Anmarkrud, Ø. (2013). Justification beliefs and multiple documents comprehension. European Journal of Psychology of Education, 28(3), 879-902.
Bråten, I., Ferguson, L. E., Strømsø, H. I., & Anmarkrud, Ø. (2014). Students working with multiple conflicting documents on a scientific issue: Relations between epistemic cognition while reading and sourcing and argumentation in essays. British Journal of Educational Psychology, 84(1), 58-85.
Bråten, I., Strømsø, H. I., & Samuelstuen, M. S. (2005). The relationship between Internet-specific epistemological beliefs and learning within Internet technologies. Journal of Educational Computing Research, 33, 141-171.
Chen, J. A., & Pajares, F. (2010). Implicit theories of ability of Grade 6 science students: Relation to epistemological beliefs and academic motivation and achievement in science. Contemporary Educational Psychology, 35(1), 75-87.
Chiu, Y. L., Tsai, C. C., & Liang, J. C. (2015). Testing measurement invariance and latent mean differences across gender groups in college students’ Internet-specific epistemic beliefs. Australasian Journal of Educational Technology, 31, 486-499.
Chiu, Y. L., Liang, J. C., & Tsai, C. C. (2013). Internet-specific epistemic beliefs and self-regulated learning in online academic information searching. Metacognition Learning, 8, 235-260.
Conley, A. M., Pintrich, P. R., Vekiri, I. & Harrison, D. (2004). Changes in epistemological beliefs in elementary science students. Contemporary Educational Psychology, 29(2), 186-204.
Ferguson, L. E., Bråten, I., & Strømsø, H. I. (2012). Epistemic cognition when students read multiple documents containing conﬂicting scientiﬁc evidence: A think-aloud study. Learning and Instruction, 22, 103-120.
Ferguson, L.E., & Bråten, I. (2013). Student profiles of knowledge and epistemic beliefs: Changes and relations to multiple-text comprehension. Learning and Instruction, 25, 49-61.
Greene, J. A., Azevedo, R., & Torney-Purta, J. (2008). Modeling epistemic and ontological cognition: Philosophical perspectives and methodological directions. Educational Psychologist, 43, 142-160.
Hofer, B. K. (2016). Epistemic cognition as a psychological construct: Advancements and challenges. Handbook of epistemic cognition, 31-50.
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.
Hsu, C. Y., Tsai, M. J., Hou, H. T., & Tsai, C. C. (2014). Epistemic beliefs, online search strategies, and behavioral patterns while exploring socioscientific issues. Journal of Science Education and Technology, 23(3), 471-480.
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Lee, W. C., Chiu, Y. L., Liang, J. C., & Tsai, C. C. (2014). Exploring the structural relationships between high school students’ Internet-specific epistemic beliefs and their utilization of online academic help seeking. Computers in Human Behavior, 36, 391-400.
Liang, J. C., & Tsai, C. C. (2010). Relational analysis of college science‐major students’ epistemological beliefs toward science and conceptions of learning science. International Journal of Science Education, 32(17), 2273-2289.
Liang, J. C., Lee, M. H., & Tsai, C. C. (2010). The Relations Between Scientific Epistemological Beliefs and Approaches to Learning Science Among Science-Major Undergraduates in Taiwan. Asia-Pacific Education Researcher, 19(1), 43-59.
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Yang, F. Y., Huang, R. T., & Tsai, I. J. (2016). The effects of epistemic beliefs in science and gender differences on university students’ science-text reading: An eye-tracking study. International Journal of Science and Mathematics Education, 14, 473-498.

Chapter3:
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Articles included in the review analysis
Ariasi, N., & Mason, L. (2014). From covert processes to overt outcomes of refutation text reading: The interplay of science text structure and working memory capacity through eye fixations. International Journal of Science and Mathematics Education, 12(3), 493-523.
Ariasi, N., Hyönä, J., Kaakinen, J. K., & Mason, L. (2017). An eye‐movement analysis of the refutation effect in reading science text. Journal of Computer Assisted Learning, 33(3), 202-221.
Chen, Y. C., & Yang, F. Y. (2014). Probing the relationship between process of spatial problems solving and science learning: An eye tracking approach. International Journal of Science & Mathematics Education, 12(3), 579-603.
Chien, K. P., Tsai, C. Y., Chen, H. L., Chang, W. H., & Chen, S. (2015). Learning differences and eye fixation patterns in virtual and physical science laboratories. Computers & Education, 82, 191-201.
Chuang, H. H., & Liu, H. C. (2012). Effects of different multimedia presentations on viewers’ information-processing activities measured by eye-tracking technology. Journal of Science Education and Technology, 21(2), 276-286.
Hinze, S. R., Williamson, V. M., Shultz, M. J., Williamson, K. C., Deslongchamps, G., & Rapp, D. N. (2013). When do spatial abilities support student comprehension of STEM visualizations?. Cognitive processing, 14(2), 129-142.
Ho, H. N. J., Tsai, M. J., Wang, C. Y., & Tsai, C. C. (2014). Prior knowledge and online inquiry-based science reading: Evidence from eye tracking. International Journal of Science and Mathematics Education, 12(3), 525-554.
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Jarodzka, H., Balslev, T., Holmqvist, K., Nyström, M., Scheiter, K., Gerjets, P., & Eika, B. (2012). Conveying clinical reasoning based on visual observation via eye-movement modelling examples. Instructional Science, 40(5), 813-827.
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Jian, Y. C. (2017). Eye-movement patterns and reader characteristics of students with good and poor performance when reading scientific text with diagrams. Reading and Writing, 30(7), 1447-1472.
Jian, Y. C., & Ko, H. W. (2017). Influences of text difficulty and reading ability on learning illustrated science texts for children: An eye movement study. Computers & Education, 113, 263-279
Jian, Y. C. (2018). Reading Instructions Influence Cognitive Processes of Illustrated Text Reading Not Subject Perception: An Eye-Tracking Study. Frontiers in Psychology, 9, 2263.
Jian, Y. C. (2019). Reading instructions facilitate signaling effect on science text for young readers: an eye-movement study. International Journal of Science and Mathematics Education, 17(3), 503-522.
Jung, Y. J., Zimmerman, H. T., & Pérez-Edgar, K. (2018). A methodological case study with mobile eye-tracking of child interaction in a science museum. TechTrends, 62(5), 509-517.
Korbach, A., Brünken, R., & Park, B. (2017). Measurement of cognitive load in multimedia learning: A comparison of different objective measures. Instructional Science, 45(4), 515-536.
Lenzner, A., Schnotz, W., & Müller, A. (2013). The role of decorative pictures in learning. Instructional Science, 41(5), 811-831.
Lim, S., Kim, Y., & Yang, I. (2014). An analysis of students' understanding process about an illustraion and text related to the earth system: An eye-tracking study. International Information Institute (Tokyo). Information, 17(8), 3613.
Lin, L., Lee, C. H., Kalyuga, S., Wang, Y., Guan, S., & Wu, H. (2017). The effect of learner-generated drawing and imagination in comprehending a science text. The Journal of Experimental Education, 85(1), 142-154.
Lindner, M. A., Eitel, A., Strobel, B., & Köller, O. (2017). Identifying processes underlying the multimedia effect in testing: An eye-movement analysis. Learning and instruction, 47, 91-102.
Lin, Y. Y., Holmqvist, K., Miyoshi, K., & Ashida, H. (2017). Effects of detailed illustrations on science learning: an eye-tracking study. Instructional science, 45(5), 557-581.
Mason, L., Pluchino, P., & Tornatora, M. C. (2013). Effects of picture labeling on science text processing and learning: Evidence from eye movements. Reading Research Quarterly, 48(2), 199-214.
Mason, L., Pluchino, P., & Tornatora, M. C. (2015). Eye-movement modeling of integrative reading of an illustrated text: Effects on processing and learning. Contemporary Educational Psychology, 41, 172-187.
Mason, L., Pluchino, P., Tornatora, M. C., & Ariasi, N. (2013). An eye-tracking study of learning from science text with concrete and abstract illustrations. The Journal of Experimental Education, 81(3), 356-384.
Mason, L., Tornatora, M. C., & Pluchino, P. (2013). Do fourth graders integrate text and picture in processing and learning from an illustrated science text? Evidence from eye-movement patterns. Computers & Education, 60(1), 95-109.
Mason, L., Tornatora, M. C., & Pluchino, P. (2015). Integrative processing of verbal and graphical information during re-reading predicts learning from illustrated text: An eye-movement study. Reading and Writing, 28(6), 851-872.
Novick, L. R., Stull, A. T., & Catley, K. M. (2012). Reading phylogenetic trees: The effects of tree orientation and text processing on comprehension. BioScience, 62(8), 757-764.
Or-Kan, S. (2017). Processing academic science reading texts through context effects: Evidence from eye movements. Eurasia Journal of Mathematics, Science & Technology Education, 13(3).
Rau, M. A., Michaelis, J. E., & Fay, N. (2015). Connection making between multiple graphical representations: A multi-methods approach for domain-specific grounding of an intelligent tutoring system for chemistry. Computers & Education, 82, 460-485.
Roach, V. A., Fraser, G. M., Kryklywy, J. H., Mitchell, D. G., & Wilson, T. D. (2016). The eye of the beholder: Can patterns in eye movement reveal aptitudes for spatial reasoning?. Anatomical sciences education, 9(4), 357-366.
Saparova, D., & Nolan, N. S. (2016). Evaluating the appropriateness of electronic information resources for learning. Journal of the Medical Library Association: JMLA, 104(1), 24.
Saß, S., Schütte, K., & Lindner, M. A. (2017). Test-takers’ eye movements: Effects of integration aids and types of graphical representations. Computers & Education, 109, 85-97.
Schneider, B., & Pea, R. (2013). Real-time mutual gaze perception enhances collaborative learning and collaboration quality. International Journal of Computer-supported Collaborative Learning, 8(4), 375-397.
Scrimin, S., & Mason, L. (2015). Does mood influence text processing and comprehension? Evidence from an eye‐movement study. British Journal of Educational Psychology, 85(3), 387-406.
Torkar, G., Veldin, M., Glažar, S., & Podlesek, A. (2018). Eurasia: journal of mathematics & technology education, 14(6), 2265-2276.
Trevors, G., Feyzi-Behnagh, R., Azevedo, R., & Bouchet, F. (2016). Self-regulated learning processes vary as a function of epistemic beliefs and contexts: Mixed method evidence from eye tracking and concurrent and retrospective reports. Learning and Instruction, 42, 31-46.
Tsai, M. J., Hou, H. T., Lai, M. L., Liu, W. Y., & Yang, F. Y. (2012). Visual attention for solving multiple-choice science problem: An eye-tracking analysis. Computers & Education, 58(1), 375-385.
Tsai, P. Y., Yang, T. T., She, H. C., & Chen, S. C. (2019). Leveraging College Students’ Scientific Evidence-Based Reasoning Performance with Eye-Tracking-Supported Metacognition. Journal of Science Education and Technology, 1-15.
Vilppu, H., Mikkilä‐Erdmann, M., Södervik, I., & Österholm‐Matikainen, E. (2017). Exploring eye movements of experienced and novice readers of medical texts concerning the cardiovascular system in making a diagnosis. Anatomical sciences education, 10(1), 23-33.
Yang, F. Y., Chang, C. Y., Chien, W. R., Chien, Y. T., & Tseng, Y. H. (2013). Tracking learners' visual attention during a multimedia presentation in a real classroom. Computers & Education, 62, 208-220.
Yang, F. Y., Huang, R. T., & Tsai, I. J. (2016). The effects of epistemic beliefs in science and gender difference on university students’ science-text reading: an eye-tracking study. International Journal of Science and Mathematics Education, 14(3), 473-498.
Yang, F. Y. (2017). Examining the reasoning of conflicting science information from the information processing perspective—an eye movement analysis. Journal of Research in Science Teaching, 54(10), 1347-1372.

Chapter4:
Bell, P., & Linn, M. C. (2000). Scientiﬁc arguments as learning artifacts: Designing for learning from the Web with KIE. International Journal of Science Education, 22(8), 797-817.
Berland, L. K., & Reiser, B. J. (2009). Making sense of argumentation and explanation. Science Education, 93(1), 26-55.
Bråten, I., Ferguson, L. E., Strømsø, H. I., & Anmarkrud, Ø. (2014). Students working with multiple conflicting documents on a scientific issue: Relations between epistemic cognition while reading and sourcing and argumentation in essays. British Journal of Educational Psychology, 84(1), 58-85.
Bricker, L. A., & Bell, P. (2008). Conceptualizations of argumentation from science studies and the learning sciences and their implications for the practices of science education. Science Education, 92(3), 473-498.
Conley, A. M., Pintrich, P. R., Vekiri, I. & Harrison, D. (2004). Changes in epistemological beliefs in elementary science students. Contemporary Educational Psychology, 29(2), 186-204.
Duschl, R. (2008). Science education in three-part harmony: Balancing conceptual, epistemic, and social learning goals. Review of Research in Education, 32, 268-291.
Duschl, R. A., & Grandy, R. E. (2008). Reconsidering the character and role of inquiry in school science: Framing the debates. In R. A. Duschl & R. E. Grandy (Eds.), Teaching scientiﬁc inquiry: Recommendations for research and implementation (pp. 1-37). Rotterdam: Sense Publishers.
Duschl, R., & Osborne, J. (2002). Supporting and promoting argumentation discourse in science education. Studies in Science Education, 38, 39-72.
Erduran, S., Simon, S., & Osborne, J. (2004). TAPping into argumentation: Developments in the application of Toulmin's argument pattern for studying science discourse. Science education, 88(6), 915-933.
Ferguson, L.E., & Bråten, I. (2013). Student profiles of knowledge and epistemic beliefs: Changes and relations to multiple-text comprehension. Learning and Instruction, 25, 49-61.
Figueira, M. J. S., Nardi, R., & Cortela, B. S. C. (2019, August). Introducing scientific argumentation practices in physics teacher’s undergraduate curricula. In Journal of Physics: Conference Series (Vol. 1286, No. 1, p. 012038). IOP Publishing.
Grooms, J., Sampson, V., & Enderle, P. (2018). How concept familiarity and experience with scientific argumentation are related to the way groups participate in an episode of argumentation. Journal of Research in Science Teaching, 55(9), 1264-1286.
Ho, H. Y., Chang, T. L., Lee, T. N., Chou, C. C., Hsiao, S. H., Chen, Y. H., & Lu, Y. L. (2019). Above-and below-average students think differently: Their scientific argumentation patterns. Thinking Skills and Creativity, 34, 100607.
Iordanou, K., Kendeou, P., & Beker, K. (2016). Argumentative reasoning. In Handbook of epistemic cognition (pp. 51-65). Routledge.
Jiménez-Aleixandre, M. P., & Erduran, S. (2007). Argumentation in science education: An overview. In Argumentation in science education (pp. 3-27). Springer, Dordrecht.
Just, M. A., & Carpenter, P. A. (1980). A theory of reading: From eye ﬁxations to comprehension. Psychological Review, 87, 329-355.
Lai, M. L., Tsai, M. J., Yang, F. Y., Hsu, C. Y., Liu, T. C., Lee, S. W. Y., Lee, M. H., Chiou, G. L., Liang, J. C., & Tsai, C. C. (2013). A review of using eye-tracking technology in exploring learning from 2000 to 2012. Educational research review, 10, 90-115.
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Liversedge, S. P., Paterson, K. B., & Pickering, M. J. (1998). Eye movements and measures of reading time. In Eye guidance in reading and scene perception (pp. 55-75). Elsevier Science Ltd.
National Assessment of Educaional Progress (2013). The Nation’s Report Card.
National Research Council (1996). National Science Education Standards. Washington, DC: National Academy Press.
Noroozi, O. (2016). Considering students’ epistemic beliefs to facilitate their argumentative discourse and attitudinal change with a digital dialogue game. Innovations in Education and Teaching International, 1-9.
Noroozi, O., Kirschner, P., Biemans, H. J. A., & Mulder, M. (2017). Promoting argumentation competence: Extending from first- to second-order scaffolding through adaptive fading. Educational Psychology Review, 1-24.
Noroozi, O., McAlister, S., & Mulder, M. (2016). Impacts of a digital dialogue game and epistemic beliefs on argumentative discourse and willingness to argue. The International Review of Research in Open and Distributed Learning, 17.
Nussbaum, E. M., Sinatra, G. M., & Poliquin, A. (2008). Role of epistemic beliefs and scientific argumentation in science learning. International Journal of Science Education, 30(15), 1977-1999.
Nussbaum, E.M., & Bendixen, L.M. (2003). Approaching and avoiding arguments: The role of epistemological beliefs, need for cognition, and extraverted personality traits. Contemporary Educational Psychology, 28, 573-595.
Nussbaum, E.M., & Sinatra, G.M. (2003). Argument and conceptual engagement. Contemporary Educational Psychology, 28, 384-395.
Osborne, J., Collins, S., Ratcliffe, M., Millar, R., & Duschl, R. (2003). What ‘ideas-about-science’ should be taught in school science? A Delphi study of the expert community. Journal of Research in Science Teaching, 40(7), 692-720.
Rayner, K. (2009). The thirty ﬁfth Sir Frederick Bartlett lecture: Eye movements and attention during reading, scene perception, and visual search. Quarterly Journal of Experimental Psychology, 62(8), 1457-1506.
Sampson, V., Enderle, P., & Grooms, J. (2013). Argumentation in science education. The Science Teacher, 80(5), 30.
Stathopoulou, C., & Vosnidou, S. (2007). Conceptual change in physics and physics-related epistemological beliefs: A relationship under scrutiny. In S. Vosnidou, A. Baltas, & X. Vamvakoussi (Eds.), Re-framing the problem of conceptual change in learning and instruction (pp. 145-163). Amsterdam, The Netherlands: Elsevier.
Toulmin, S. (1958). The uses of argument. Cambridge: Cambridge University Press.
Yang, F. Y. (2005). Student views concerning evidence and the expert in reasoning a socio‐scientific issue and personal epistemology. Educational Studies, 31(1), 65-84.
Yang, F. Y. (2017). Examining the reasoning of conflicting science information from the information processing perspective—an eye movement analysis. Journal of Research in Science Teaching, 54(10), 1347-1372.
Yang, F. Y., & Tsai, C. C. (2010). Reasoning about science-related uncertain issues and epistemological perspectives among children. Instructional Science, 38(4), 325-354.
Yang, F. Y., Bhagat, K. K., & Cheng, C. H. (2019). Associations of epistemic beliefs in science and scientific reasoning in university students from Taiwan and India. International Journal of Science Education, 41(10), 1347-1365.

Chapter5:
Darley, W. K., Blankson, C., & Luethge, D. J. (2010). Toward an integrated framework for online consumer behavior and decision making process: A review. Psychology & marketing, 27(2), 94-116.
Driver, R., Newton, P., & Osborne, J. (2000). Establishing the norms of scientific argumentation in classrooms. Science Education, 84(3), 287-312.
Erduran, S., Simon, S., & Osborne, J. (2004). TAPing into argumentation: Developments in the use of Toulmin’s argument pattern in studying science discourse. Science Education, 88(6), 915-933.
Oulton, C., Dillon, J., & Grace, M. M. (2004). Reconceptualizing the teaching of controversial issues. International Journal of Science Education, 26(4), 411-423.
Roscoe, R. D., Grebitus, C., O'Brian, J., Johnson, A. C., & Kula, I. (2016). Online information search and decision making: Effects of web search stance. Computers in Human Behavior, 56, 103-118.
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., and Donnelly, L. A., 2006. “Socioscientiﬁc Argumentation: The Effects of Content Knowledge and Morality.” International Journal of Science Education 28(12), 1463-1488.
Sadler, T. D., Romine, W. L., & Topçu, M. S. (2016). Learning science content through socio-scientific issues-based instruction: A multi-level assessment study. International Journal of Science Education, 38(10), 1622-1635.
Yang, F. Y., & Tsai, C. C. (2010). An epistemic framework for scientiﬁc reasoning in informal contexts. In L. D. Bendixen & F. C. Feucht (Eds.), Personal epistemology in the classroom (pp. 124–162). Cambridge, UK: Cambridge University Press.
Yang, F. Y., Huang, R. T., & Tsai, C.C. (2016). The effects of epistemic beliefs in science and gender difference on university students’ science-text reading: An eye-tracking study. International Journal of Science and Mathematics Eduction, 14, 473-498.
Zeidler, D. L. (2001). Participating in program development: Standard F. In D. Siebert & W. McIntosh (Eds.), College pathways to the science education standards (pp. 18 – 22). Arlington, VA: National Science Teachers Press.
Zeidler, D. L., & Keefer, M. (2003). The role of moral reasoning and the status of socioscientiﬁc issues in science education: Philosophical, psychological and pedagogical considerations. In D. L. Zeidler (Ed.), The role of moral reasoning on socioscientiﬁc issues and discourse in science education. Dordrecht: Kluwer Academic Publishers.
Zeidler, D. L., Osborne, J., Erduran, S., Simon, S., & Monk, M. (2003). The role of argument and fallacies during discourse about socioscientiﬁc issues. In D. L. Zeidler (Ed.), The role of moral reasoning on socioscientiﬁc issues and discourse in science education. Dordrecht: Kluwer Academic Press.

Chapter6:
Hofer, B. K. (2016). Epistemic cognition as a psychological construct: Advancements and challenges. Handbook of epistemic cognition, 31-50.
Yang, F. Y., Bhagat, K. K., & Cheng, C. H. (2019). Associations of epistemic beliefs in science and scientific reasoning in university students from Taiwan and India. International Journal of Science Education, 41(10), 1347-1365.
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.
Sampson, V., Enderle, P., & Grooms, J. (2013). Argumentation in science education. The Science Teacher, 80(5), 30.

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