Moleküler Modelleme Yazılımlarının Biyoloji Eğitiminde Kullanımının Sistematik Alanyazın Yöntemi ile İncelenmesi
Özet
Üç boyutlu moleküler yapıları öğrenmek, öğrenci için kavramsal olarak zorlayıcı bir konudur ve geleneksel yaklaşımların dışında yaklaşımlar gerektirmektedir. Öğretmenlerin öğrenmeyi kolaylaştırmakla ilgili öğretim stratejilerini tasarlayabilmeleri için teorik bilişsel görselleştirme sürecinin her bir aşamasının önemini anlamaları önemlidir. Bu araştırmada, 2010-2022 yılları arasında fen eğitiminde moleküler modelleme yazılımlarının kullanılmasının öğrenme ve öğretme süreçlerine etkisini inceleyen akademik yayınların sistematik alanyazın yöntemi ile incelenerek değerlendirilmesi hedeflenmiştir. Bu durumda biyolojik moleküllerin bilgisayar destekli modellemesine yönelik araçların kullanılmasının eğitim sürecine etkisinin olumlu/olumsuz yönleri kapsamında yanıtlar aranmıştır.
Referanslar
Aalbergsjø, S. G., & Sollid, P. Ø. (2021). Learning through modelling in science: Reflections by pre-service teachers. Nordic Studies in Science Education, 17(2), 206-224
Akıllı, M., & Seven, S. (2014). 3D bilgisayar modellerinin akademik başarıya ve uzamsal canlandırmaya etkisi: atom modelleri. Turkish Journal of Education, 3(1), 11-23.
Arnold, K., Bordoli, L., Kopp, J., & Schwede, T. (2006). The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics, 22(2), 195-201.
Baloğlu, M. C. (2020). Biyoinformatik temelleri ve uygulamaları. Ankara; Pegem Akademik.
Bell, E. (2011). Using research to teach an “introduction to biological thinking”. Biochem. Mol. Biol. Educ., 39: 10-16.
Bergqvist, A., Drechsler, M., De Jong, O., & Rundgren, S. N. C. (2013). Representations of chemical bonding models in school textbooks–help or hindrance for understanding?. Chemistry Education Research and Practice, 14(4), 589-606.
Berry, C., & Baker, M. D. (2010). Inside protein structures: Teaching in three dimensions. Biochemistry and molecular biology education, 38(6), 425-429.
Bottomley, S., Chandler, D., Morgan, E., & Helmerhorst, E. (2006). JAMVLE, A new integrated molecular visualization learning environment. Biochemistry and Molecular Biology Education, 34(5), 343-349.
Bourn, D. (2018). Globalisation, education and skills. In understanding global skills for 21st Century professions (pp. 17-35). Cham, Switzerland: Palgrave Macmillan.
Burgin, S. R., Oramous, J., Kaminski, M., Stocker, L., & Moradi, M. (2018). High school biology students use of visual molecular dynamics as an authentic tool for learning about modeling as a professional scientific practice. Biochemistry and Molecular Biology Education, 46(3), 230-236.
Čablová, L., R. Pates, M. Miovský, & J. Noel. (2017). How to write a systematic review article and meta-analysis. ın addiction science: a guide for the perplexed. 3rd ed., edited by T. F. Babor, K.
Cox, J. R. (2006). Screen capture on the fly: Combining molecular visualization and a tablet PC in the biochemistry lecture. Biochemistry and Molecular Biology Education, 34(1), 12-16.
Deane, C. M., & Blundell, T. L. (2003). Protein comparative modelling and drug discovery. The Practice of Medicinal Chemistry, 27, 445-458.
Duit, R &Treagust, D.F. (2003). Conceptual change: a powerful framework for improving science teaching and learning. International Journal of Science Teaching, 36(5), 597-615.
Emery, L. R., & Morgan, S. L. (2017). The application of project-based learning in bioinformatics training. PLoS computational biology, 13(8), e1005620.
Ergen, A. (2019). Moleküler biyoloji lisans eğitiminde dinamik hücresel süreçlerin anlaşılmasında üç boyutlu (3B) animasyonun etkisi. Yüksek Lisans Tezi, Mimar Sinan Güzel Sanatlar Üniversitesi Fen Bilimleri Enstitüsü, İstanbul.
Fernandes, P. L. (2010). The GTPB training programme in Portugal. Briefings in bioinformatics, 11(6), 626-634.
Fernandes, P., Jain, P., & Moita, C. (2012). Training experimental biologists in bioinformatics. Advances in bioinformatics, 2012.
Giere, R. N. (2010). Scientific perspectivism. University of Chicago.
Gobert, J.D. (2000). A topology of casual models for plate tectonics: inferential power and barriers to understanding. International Journal of Science Education, 22(9), 937–977.
Goode, E., & Trajkovski, G. (2007). Developing a truly interdisciplinary bioinformatics track: work in progress. Journal of Computing Sciences in Colleges, 22(6), 73-79.
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Gürkan, B. (2023). Moleküler Modelleme Yazılımlarının Biyoloji Eğitiminde Kullanımının İncelenmesi. Yüksek Lisans Tezi, Gazi Üniversitesi Eğitim Bilimleri Enstitüsü, Ankara.
Hall, L. M., & Vardar‐Ulu, D. (2014). An inquiry‐based biochemistry laboratory structure emphasizing competency in the scientific process: A guided approach with an electronic notebook format. Biochemistry and Molecular Biology Education, 42(1), 58-67.
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Honey, D. W., & Cox, J. R. (2003). Lesson plan for protein exploration in a large biochemistry class. Biochemistry and Molecular Biology Education, 31(5), 356-362.
Jaswal, S. S., O'Hara, P. B., Williamson, P. L., & Springer, A. L. (2013). Teaching structure: student use of software tools for understanding macromolecular structure in an undergraduate biochemistry course. Biochemistry and Molecular Biology Education, 41(5), 351-359.
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Justi, R., & J. Gilbert. 2002. Science teachers’ knowledge about and attitudes towards the use of models and modelling in learning science. International Journal of Science Education 24, 1273–1292.
Justi, R., & Van Driel, J. (2005). The development of science teachers' knowledge on models and modelling: promoting, characterizing, and understanding the process. International Journal of Science Education, 27(5), 549-573.
Knutson, K., Smith, J., Wallert, M. A., & Provost, J. J. (2010). Bringing the excitement and motivation of research to students; using inquiry and research‐based learning in a year‐long biochemistry laboratory: part ı–guided inquiry–purification and characterization of a fusion protein: histidine tag, malate dehydrogenase, and green fluorescent protein. Biochemistry and Molecular Biology Education, 38(5), 317-323.
Koponen, I.T. (2007). Models and modeling in physics education: a critical re-analysis of philosophical underpinnings and suggestions for revisions. Science Education, 16, 751–753.
Krell, M., & Krüger, D. (2016). Testing models: a key aspect to promote teaching activities related to models and modelling in biology lessons?. Journal of Biological Education, 50(2), 160-173.
Kubiatko, M., and Z. Haláková. 2009. Slovak high school students’ attitudes to ICT using in biology lesson. Computers in Human Behavior 25 (3), 743–748.
Kumar, A., & Chordia, N. (2017). Role of bioinformatics in biotechnology. Res Rev Biosci, 12(1), 116.
Lehrer, R., & Schauble, L. (2005). Developing modeling and argument in the elementary grades. In T. A. Rombert, T. P. Carpenter, & F. Dremock (Eds.), Understanding mathematics and science matters (Part II: Learning with understanding). Mahway, NJ: Lawrence Erlbaum Associates.
Liu, X. (2006). Effects of combined hands-on laboratory and computer modeling on student learning of gas laws: a quasi-experimental study. Journal of Science Education and Technology, 15(1), 89–100.
Lucke, T., Dunn, P. K. & Christie, M. (2017). Activating learning in engineering education using ICT and the concept of ‘Flipping the classroom’. European Journal of Engineering Education, 42(1), 45-57.
Lundquist, K., Herndon, C., Harty, T. H., & Gumbart, J. C. (2016). Accelerating the use of molecular modeling in the high school classroom with VMD Lite. Biochemistry and molecular biology education, 44(2), 124-129.
McNally, B., Chipperfield, J., Dorsett, P., Del Fabbro, L., Frommolt, V., Goetz, S., Lewohl, J., Molineux, M., Pearson, A., Reddan, G., Roiko, A. and Rung, A. (2017). Flipped classroom experiences: Student preferences and flip strategy in a higher education context. Higher Education, 73(2), 281-298.
Mnguni, L. E. (2014). The theoretical cognitive process of visualization for science education. SpringerPlus, 3(1), 184.
Mulder, N., Schwartz, R., Brazas, M. D., Brooksbank, C., Gaeta, B., Morgan, S. L., ... & Welch, L. (2018). The development and application of bioinformatics core competencies to improve bioinformatics training and education. PLoS computational biology, 14(2), e1005772.
Oh, P. S., & Oh, S. J. (2011). What teachers of science need to know about models: An overview. International Journal of Science Education, 33(8), 1109–1130.
Özbay, Ö., & Sarıca, R. (2019). Ters yüz sınıfa yönelik gerçekleştirilen çalışmaların eğilimleri: Bir sistematik alanyazın taraması. Ahi Evran Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 5(2), 332-348.
Phankingthongkum, S., & Limpanuparb, T. (2021). A virtual alternative to molecular model sets: a beginners’ guide to constructing and visualizing molecules in open-source molecular graphics software. BMC Research Notes, 14(1), 1-7.
Rayan, B., & Rayan, A. (2017). Avogadro program for chemistry education: To what extent can molecular visualization and three-dimensional simulations enhance meaningful chemistry learning. World Journal of Chemical Education, 5(4), 136-141.
Rosenwald, A. G., Pauley, M. A., Welch, L., Elgin, S. C., Wright, R., & Blum, J. (2016). The CourseSource bioinformatics learning framework. CBE—Life Sciences Education, 15(1), le2.
Saudale, F. Z., Lerrick, R. I., Parikesit, A. A., & Mariti, F. (2019). Chemistry teachers awareness, understanding, and confidence toward computational tools for molecular visualization. Jurnal Pendidikan IPA Indonesia, 8(4), 436-446.
Schneider, M. V., Watson, J., Attwood, T., Rother, K., Budd, A., McDowall, J., ... & Brooksbank, C. (2010). Bioinformatics training: a review of challenges, actions and support requirements. Briefings in bioinformatics, 11(6), 544-551.
Schneider, M. V., Walter, P., Blatter, M. C., Watson, J., Brazas, M. D., Rother, K., ... & Brooksbank, C. (2012). Bioinformatics Training Network (BTN): a community resource for bioinformatics trainers. Briefings in bioinformatics, 13(3), 383-389.
Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational researcher, 15(2), 4-14.
Siddaway, A. 2014. What Is a Systematic Literature Review and How Do I Do One.”University of Stirling 1(1):1–13.
Šorgo, A., & Kocijančič, S. (2012). False reality or hidden messages: Reading graphs obtained in computerized biological experiments. Eurasia Journal of Mathematics, Science and Technology Education, 8(2), 129-137.
Špernjak, A., and A. Šorgo. 2009. Perspectives on the ıntroduction of computer-supported real laboratory exercises into biology teaching in secondary schools: teachers as part of the problem. Problems of education in the 21st century 14, 135–143.
Špernjak, A., & Šorgo, A. (2018). Differences in acquired knowledge and attitudes achieved with traditional, computer-supported and virtual laboratory biology laboratory exercises. Journal of Biological Education, 52(2), 206-220.
Svoboda, J., Passmore, C. The Strategies of Modeling in Biology Education. Sci & Educ 22, 119–142 (2013).
Tapprich, W. E., Reichart, L., Simon, D. M., Duncan, G., McClung, W., Grandgenett, N., & Pauley, M. A. (2021). An instructional definition and assessment rubric for bioinformatics instruction. Biochemistry and Molecular Biology Education, 49(1), 38-45.
Terrell, C. R., & Listenberger, L. L. (2017). Using molecular visualization to explore protein structure and function and enhance student facility with computational tools. Biochemistry and Molecular Biology Education, 45(4), 318-328.
Treagust, D. F., Chittleborough, G., & Mamiala, T. L. (2002). Students' understanding of the role of scientific models in learning science. International journal of science education, 24(4), 357-368.
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Referanslar
Aalbergsjø, S. G., & Sollid, P. Ø. (2021). Learning through modelling in science: Reflections by pre-service teachers. Nordic Studies in Science Education, 17(2), 206-224
Akıllı, M., & Seven, S. (2014). 3D bilgisayar modellerinin akademik başarıya ve uzamsal canlandırmaya etkisi: atom modelleri. Turkish Journal of Education, 3(1), 11-23.
Arnold, K., Bordoli, L., Kopp, J., & Schwede, T. (2006). The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics, 22(2), 195-201.
Baloğlu, M. C. (2020). Biyoinformatik temelleri ve uygulamaları. Ankara; Pegem Akademik.
Bell, E. (2011). Using research to teach an “introduction to biological thinking”. Biochem. Mol. Biol. Educ., 39: 10-16.
Bergqvist, A., Drechsler, M., De Jong, O., & Rundgren, S. N. C. (2013). Representations of chemical bonding models in school textbooks–help or hindrance for understanding?. Chemistry Education Research and Practice, 14(4), 589-606.
Berry, C., & Baker, M. D. (2010). Inside protein structures: Teaching in three dimensions. Biochemistry and molecular biology education, 38(6), 425-429.
Bottomley, S., Chandler, D., Morgan, E., & Helmerhorst, E. (2006). JAMVLE, A new integrated molecular visualization learning environment. Biochemistry and Molecular Biology Education, 34(5), 343-349.
Bourn, D. (2018). Globalisation, education and skills. In understanding global skills for 21st Century professions (pp. 17-35). Cham, Switzerland: Palgrave Macmillan.
Burgin, S. R., Oramous, J., Kaminski, M., Stocker, L., & Moradi, M. (2018). High school biology students use of visual molecular dynamics as an authentic tool for learning about modeling as a professional scientific practice. Biochemistry and Molecular Biology Education, 46(3), 230-236.
Čablová, L., R. Pates, M. Miovský, & J. Noel. (2017). How to write a systematic review article and meta-analysis. ın addiction science: a guide for the perplexed. 3rd ed., edited by T. F. Babor, K.
Cox, J. R. (2006). Screen capture on the fly: Combining molecular visualization and a tablet PC in the biochemistry lecture. Biochemistry and Molecular Biology Education, 34(1), 12-16.
Deane, C. M., & Blundell, T. L. (2003). Protein comparative modelling and drug discovery. The Practice of Medicinal Chemistry, 27, 445-458.
Duit, R &Treagust, D.F. (2003). Conceptual change: a powerful framework for improving science teaching and learning. International Journal of Science Teaching, 36(5), 597-615.
Emery, L. R., & Morgan, S. L. (2017). The application of project-based learning in bioinformatics training. PLoS computational biology, 13(8), e1005620.
Ergen, A. (2019). Moleküler biyoloji lisans eğitiminde dinamik hücresel süreçlerin anlaşılmasında üç boyutlu (3B) animasyonun etkisi. Yüksek Lisans Tezi, Mimar Sinan Güzel Sanatlar Üniversitesi Fen Bilimleri Enstitüsü, İstanbul.
Fernandes, P. L. (2010). The GTPB training programme in Portugal. Briefings in bioinformatics, 11(6), 626-634.
Fernandes, P., Jain, P., & Moita, C. (2012). Training experimental biologists in bioinformatics. Advances in bioinformatics, 2012.
Giere, R. N. (2010). Scientific perspectivism. University of Chicago.
Gobert, J.D. (2000). A topology of casual models for plate tectonics: inferential power and barriers to understanding. International Journal of Science Education, 22(9), 937–977.
Goode, E., & Trajkovski, G. (2007). Developing a truly interdisciplinary bioinformatics track: work in progress. Journal of Computing Sciences in Colleges, 22(6), 73-79.
Göğebakan Yıldız, D., Kıyıcı, G. & Altıntaş, G. (2016). Ters-yüz edilmiş sınıf modelinin öğretmen adaylarının erişileri ve görüşleri açısından incelenmesi. Sakarya University Journal of Education, 6(3), 186-200.
Gökmen, A., Gürkan, B., & Katırcıoğlu, H. T. (2021). Preservice biology teachers’ knowledge and usage level regarding lab equipment and materials. Journal of Education and Learning (EduLearn), 15(3), 397-405.
Gürkan, B. (2023). Moleküler Modelleme Yazılımlarının Biyoloji Eğitiminde Kullanımının İncelenmesi. Yüksek Lisans Tezi, Gazi Üniversitesi Eğitim Bilimleri Enstitüsü, Ankara.
Hall, L. M., & Vardar‐Ulu, D. (2014). An inquiry‐based biochemistry laboratory structure emphasizing competency in the scientific process: A guided approach with an electronic notebook format. Biochemistry and Molecular Biology Education, 42(1), 58-67.
Hemminger, B. M., Losi, T., & Bauers, A. (2005). Survey of bioinformatics programs in the United States. Journal of the American Society for Information Science and Technology, 56(5), 529-537.
Honey, D. W., & Cox, J. R. (2003). Lesson plan for protein exploration in a large biochemistry class. Biochemistry and Molecular Biology Education, 31(5), 356-362.
Jaswal, S. S., O'Hara, P. B., Williamson, P. L., & Springer, A. L. (2013). Teaching structure: student use of software tools for understanding macromolecular structure in an undergraduate biochemistry course. Biochemistry and Molecular Biology Education, 41(5), 351-359.
Jungck, J. R., Donovan, S. S., Weisstein, A. E., Khiripet, N., & Everse, S. J. (2010). Bioinformatics education dissemination with an evolutionary problem solving perspective. Briefings in bioinformatics, 11(6), 570-581.
Justi, R., & J. Gilbert. 2002. Science teachers’ knowledge about and attitudes towards the use of models and modelling in learning science. International Journal of Science Education 24, 1273–1292.
Justi, R., & Van Driel, J. (2005). The development of science teachers' knowledge on models and modelling: promoting, characterizing, and understanding the process. International Journal of Science Education, 27(5), 549-573.
Knutson, K., Smith, J., Wallert, M. A., & Provost, J. J. (2010). Bringing the excitement and motivation of research to students; using inquiry and research‐based learning in a year‐long biochemistry laboratory: part ı–guided inquiry–purification and characterization of a fusion protein: histidine tag, malate dehydrogenase, and green fluorescent protein. Biochemistry and Molecular Biology Education, 38(5), 317-323.
Koponen, I.T. (2007). Models and modeling in physics education: a critical re-analysis of philosophical underpinnings and suggestions for revisions. Science Education, 16, 751–753.
Krell, M., & Krüger, D. (2016). Testing models: a key aspect to promote teaching activities related to models and modelling in biology lessons?. Journal of Biological Education, 50(2), 160-173.
Kubiatko, M., and Z. Haláková. 2009. Slovak high school students’ attitudes to ICT using in biology lesson. Computers in Human Behavior 25 (3), 743–748.
Kumar, A., & Chordia, N. (2017). Role of bioinformatics in biotechnology. Res Rev Biosci, 12(1), 116.
Lehrer, R., & Schauble, L. (2005). Developing modeling and argument in the elementary grades. In T. A. Rombert, T. P. Carpenter, & F. Dremock (Eds.), Understanding mathematics and science matters (Part II: Learning with understanding). Mahway, NJ: Lawrence Erlbaum Associates.
Liu, X. (2006). Effects of combined hands-on laboratory and computer modeling on student learning of gas laws: a quasi-experimental study. Journal of Science Education and Technology, 15(1), 89–100.
Lucke, T., Dunn, P. K. & Christie, M. (2017). Activating learning in engineering education using ICT and the concept of ‘Flipping the classroom’. European Journal of Engineering Education, 42(1), 45-57.
Lundquist, K., Herndon, C., Harty, T. H., & Gumbart, J. C. (2016). Accelerating the use of molecular modeling in the high school classroom with VMD Lite. Biochemistry and molecular biology education, 44(2), 124-129.
McNally, B., Chipperfield, J., Dorsett, P., Del Fabbro, L., Frommolt, V., Goetz, S., Lewohl, J., Molineux, M., Pearson, A., Reddan, G., Roiko, A. and Rung, A. (2017). Flipped classroom experiences: Student preferences and flip strategy in a higher education context. Higher Education, 73(2), 281-298.
Mnguni, L. E. (2014). The theoretical cognitive process of visualization for science education. SpringerPlus, 3(1), 184.
Mulder, N., Schwartz, R., Brazas, M. D., Brooksbank, C., Gaeta, B., Morgan, S. L., ... & Welch, L. (2018). The development and application of bioinformatics core competencies to improve bioinformatics training and education. PLoS computational biology, 14(2), e1005772.
Oh, P. S., & Oh, S. J. (2011). What teachers of science need to know about models: An overview. International Journal of Science Education, 33(8), 1109–1130.
Özbay, Ö., & Sarıca, R. (2019). Ters yüz sınıfa yönelik gerçekleştirilen çalışmaların eğilimleri: Bir sistematik alanyazın taraması. Ahi Evran Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 5(2), 332-348.
Phankingthongkum, S., & Limpanuparb, T. (2021). A virtual alternative to molecular model sets: a beginners’ guide to constructing and visualizing molecules in open-source molecular graphics software. BMC Research Notes, 14(1), 1-7.
Rayan, B., & Rayan, A. (2017). Avogadro program for chemistry education: To what extent can molecular visualization and three-dimensional simulations enhance meaningful chemistry learning. World Journal of Chemical Education, 5(4), 136-141.
Rosenwald, A. G., Pauley, M. A., Welch, L., Elgin, S. C., Wright, R., & Blum, J. (2016). The CourseSource bioinformatics learning framework. CBE—Life Sciences Education, 15(1), le2.
Saudale, F. Z., Lerrick, R. I., Parikesit, A. A., & Mariti, F. (2019). Chemistry teachers awareness, understanding, and confidence toward computational tools for molecular visualization. Jurnal Pendidikan IPA Indonesia, 8(4), 436-446.
Schneider, M. V., Watson, J., Attwood, T., Rother, K., Budd, A., McDowall, J., ... & Brooksbank, C. (2010). Bioinformatics training: a review of challenges, actions and support requirements. Briefings in bioinformatics, 11(6), 544-551.
Schneider, M. V., Walter, P., Blatter, M. C., Watson, J., Brazas, M. D., Rother, K., ... & Brooksbank, C. (2012). Bioinformatics Training Network (BTN): a community resource for bioinformatics trainers. Briefings in bioinformatics, 13(3), 383-389.
Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational researcher, 15(2), 4-14.
Siddaway, A. 2014. What Is a Systematic Literature Review and How Do I Do One.”University of Stirling 1(1):1–13.
Šorgo, A., & Kocijančič, S. (2012). False reality or hidden messages: Reading graphs obtained in computerized biological experiments. Eurasia Journal of Mathematics, Science and Technology Education, 8(2), 129-137.
Špernjak, A., and A. Šorgo. 2009. Perspectives on the ıntroduction of computer-supported real laboratory exercises into biology teaching in secondary schools: teachers as part of the problem. Problems of education in the 21st century 14, 135–143.
Špernjak, A., & Šorgo, A. (2018). Differences in acquired knowledge and attitudes achieved with traditional, computer-supported and virtual laboratory biology laboratory exercises. Journal of Biological Education, 52(2), 206-220.
Svoboda, J., Passmore, C. The Strategies of Modeling in Biology Education. Sci & Educ 22, 119–142 (2013).
Tapprich, W. E., Reichart, L., Simon, D. M., Duncan, G., McClung, W., Grandgenett, N., & Pauley, M. A. (2021). An instructional definition and assessment rubric for bioinformatics instruction. Biochemistry and Molecular Biology Education, 49(1), 38-45.
Terrell, C. R., & Listenberger, L. L. (2017). Using molecular visualization to explore protein structure and function and enhance student facility with computational tools. Biochemistry and Molecular Biology Education, 45(4), 318-328.
Treagust, D. F., Chittleborough, G., & Mamiala, T. L. (2002). Students' understanding of the role of scientific models in learning science. International journal of science education, 24(4), 357-368.
Van Eijck, M., & Roth, W. M. (2010). Theorizing scientific literacy in the wild. Educational research review, 5(2), 184-194.
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