The multi-representational ability profile of physics students in the interactive multimedia assisted problem-based learning during the Covid-19 pandemic
Abstract
This study aims to analyze the multi-representation ability profile of physics students in the interactive multimedia assisted problem-based learning during the Covid-19 pandemic. This research is a qualitative descriptive study. This research involved 9 female teachers and 1 male teacher. Data on the multi-representation abilities of Physics teachers were obtained by using the 5 item multi-representation problem instrument in the form of representing image to verbal, verbal to mathematics, verbal to picture, table to graph, and mathematics to verbal. Meanwhile, researchers utilized interviews to gather information on the difficulties that prospective physics teachers had in working on multi-representational problems. The results of the analysis show that the multi-representation ability of prospective physics teachers is generally good. This can be seen from the average percentage obtained by 63%. However, there are two indicators that are still not good, namely verbal to mathematics representation and mathematics to verbal representation with an average percentage of 30% and 43% respectively. For this reason, it is necessary to make efforts to increase the multi-representational abilities of prospective physics teachers by using approaches, teaching materials, and learning media that are able to teach and present physics concepts in various forms of representation so that it is easier to understand the concepts presented.
References
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Nousiainen, M. (2013). Coherence of Pre-service Physics Teachers’ Views of the Relatedness of Physics Concepts. Science and Education, 22(3), 505–525. doi: 10.1007/s11191-012-9500-6
Nurrahmawati, N., Sa’dijah, C., Sudirman, S., & Muksa, M. (2019). Multiple representations’ ability in solving word problem. International Journal of Recent Technology and Engineering, 8(1C2), 737–745. doi: 10.4108/eai.20-9-2019.2292114
Nussifera, L., Sinaga, P., & Setiawan, A. (2017). the Use of Multimodal Representation in the Physics Learning Material Development To Promote Students ’ Cognitive and Critical Thinking Competences. IMPACT: International Journal of Research in Applied, 5(4), 9–18.
Park, J., Chang, J., Tang, K. S., Treagust, D. F., & Won, M. (2020). Sequential patterns of students’ drawing in constructing scientific explanations: focusing on the interplay among three levels of pictorial representation. International Journal of Science Education, 42(5), 677–702. doi: 10.1080/09500693.2020.1724351
Selçuk, G. S. (2010). The effects of problem-based learning on pre-service teachers’ achievement, approaches and attitudes towards learning physics. International Journal of Physical Sciences, 5(6), 711–723.
Selçuk, G. S., & Çalişkan, S. (2010). A small-scale study comparing the impacts of problem-based learning and traditional methods on student satisfaction in the introductory physics course. Procedia - Social and Behavioral Sciences, 2(2), 809–813. doi: 10.1016/j.sbspro.2010.03.108
Sezen, N., Uzun, M. S., & Bulbul, A. (2012). An Investigation of Preservice Physics Teacher’s Use of Graphical Representations. Procedia - Social and Behavioral Sciences, 46(December), 3006–3010. doi: 10.1016/j.sbspro.2012.05.605
Simbolon, M., Sinaga, P., & Utari, S. (2017). Effect of Application of Physics Learning material Using Multimode representation to Improve Problem Solving Ability. Advances in Social Science,Education and Humanities Research, 57, 150–153. doi: 10.2991/icmsed-16.2017.33
Soeharto, S., & Csapó, B. (2021). Evaluating item difficulty patterns for assessing student misconceptions in science across physics, chemistry, and biology concepts. Heliyon, 7(11). doi: 10.1016/j.heliyon.2021.e08352
Sulaiman, F. (2010). Students’ perceptions of implementing problem-based learning in a physics course. Procedia - Social and Behavioral Sciences, 7(2), 355–362. doi: 10.1016/j.sbspro.2010.10.048
van Laar, E., van Deursen, A. J. A. M., van Dijk, J. A. G. M., & de Haan, J. (2017). The relation between 21st-century skills and digital skills: A systematic literature review. Computers in Human Behavior, 72, 577–588. doi: 10.1016/j.chb.2017.03.010
Yao, Y., Wang, P., Jiang, Y., Li, Q., & Li, Y. (2022). Innovative Online learning strategies for the successful construction of student Self-awareness during the COVID-19 pandemic: Merging TAM with TPB. Journal of Innovation & Knowledge, 7(4), 100252. doi: 10.1016/j.jik.2022.100252
Yew, E. H. J., & Goh, K. (2016). Problem-Based Learning: An Overview of its Process and Impact on Learning. Health Professions Education, 2(2), 75–79. doi: 10.1016/j.hpe.2016.01.004
Zhuang, H., Xiao, Y., Liu, Q., Yu, B., Xiong, J., & Bao, L. (2021). Comparison of nature of science representations in five Chinese high school physics textbooks. International Journal of Science Education, 43(11), 1779–1798. doi: 10.1080/09500693.2021.1933647
Aisyah, Okta. Sudarti, S. (2021). ANALISIS KEMAMPUAN MULTIREPRESENTASI VERBAL DAN. Silampari Jurnal Pendidikan Ilmu Fisika, 3(1), 29–38.
Ak, S. (2011). The Effects of Computer Supported Problem Based Learning on Students’ Approaches to Learning. Current Issues in Education, 14(1), 19.
Bajracharya, R. R., Emigh, P. J., & Manogue, C. A. (2019). Students’ strategies for solving a multirepresentational partial derivative problem in thermodynamics. Physical Review Physics Education Research, 15(2), 20124. doi: 10.1103/PhysRevPhysEducRes.15.020124
Çepni, S., Ülger, B. B., & Ormanci, Ü. (2017). Pre-service science teachers’ views towards the process of associating science concepts with everyday life. Journal of Turkish Science Education, 14(4), 1–15. doi: 10.12973/tused.10208
Cheng, Y. M. (2012). Effects of quality antecedents on e-learning acceptance. Internet Research, 22(3), 361–390. doi: 10.1108/10662241211235699
Coleman, J. M., McTigue, E. M., & Smolkin, L. B. (2011). Elementary Teachers’ Use of Graphical Representations in Science Teaching. Journal of Science Teacher Education, 22(7), 613–643. doi: 10.1007/s10972-010-9204-1
Costa, G. J. M., & Silva, N. S. A. (2010). Knowledge versus content in e-learning: A philosophical discussion. Information Systems Frontiers, 12(4), 399–413. doi: 10.1007/s10796-009-9200-1
Davidson, N., & Major, C. H. (2014). Boundary Crossings: Cooperative Learning, Collaborative Learning, and Problem-Based Learning. Journal on Excellence in College Teaching, 25(3&4), 7–55.
Demirbag, M., & Gunel, M. (2014). Integrating Argument-Based Science Inquiry with Modal Representations: Impact on Science Achievement, Argumentation, and Writing Skills. Educational Science: Theory & Practice, 14(1), 386–391. doi: 10.12738/estp.2014.1.1632
Dolmans, D. H. J. M., Loyens, S. M. M., Marcq, H., & Gijbels, D. (2016). Deep and surface learning in problem-based learning: a review of the literature. Advances in Health Sciences Education, 21(5), 1087–1112.
Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, Supplement, 14(1), 4–58. doi: 10.1177/1529100612453266
Fidan, M., & Tuncel, M. (2019). Integrating augmented reality into problem based learning: The effects on learning achievement and attitude in physics education. Computers and Education, 142(July), 103635. doi: 10.1016/j.compedu.2019.103635
Franco, G. M., Muis, K. R., Kendeou, P., Ranellucci, J., Sampasivam, L., & Wang, X. (2012). Examining the influences of epistemic beliefs and knowledge representations on cognitive processing and conceptual change when learning physics. Learning and Instruction, 22(1), 62–77. doi: 10.1016/j.learninstruc.2011.06.003
Hand, B., Gunel, M., & Ulu, C. (2009). Sequencing embedded multimodal representations in a writing to learn approach to the teaching of electricity. Journal of Research in Science Teaching, 46(3), 225–247. doi: 10.1002/tea.20282
Hill, M., & Sharma, M. D. (2015). Students’ representational fluency at university: A cross-sectional measure of how multiple representations are used by physics students Using the representational fluency survey. Eurasia Journal of Mathematics, Science and Technology Education, 11(6), 1633–1655. doi: 10.12973/eurasia.2015.1427a
Hsieh, W. M., & Tsai, C. C. (2017). Exploring students’ conceptions of science learning via drawing: a cross-sectional analysis. International Journal of Science Education, 39(3), 274–298. doi: 10.1080/09500693.2017.1280640
Hu, K., Godfrey, K., Ren, Q., Wang, S., Yang, X., & Li, Q. (2022). The impact of the COVID-19 pandemic on college students in USA: Two years later. Psychiatry Research, 315(April). doi: 10.1016/j.psychres.2022.114685
Iglesias-Pradas, S., Hernández-García, Á., Chaparro-Peláez, J., & Prieto, J. L. (2021). Emergency remote teaching and students’ academic performance in higher education during the COVID-19 pandemic: A case study. Computers in Human Behavior, 119(October 2020). doi: 10.1016/j.chb.2021.106713
Kohl, P. B., Rosengrant, D., & Finkelstein, N. D. (2007). Strongly and weakly directed approaches to teaching multiple representation use in physics. Physical Review Special Topics - Physics Education Research, 3(1), 1–10. doi: 10.1103/PhysRevSTPER.3.010108
Mäntylä, T., & Hämäläinen, A. (2015). Obtaining Laws Through Quantifying Experiments: Justifications of Pre-service Physics Teachers in the Case of Electric Current, Voltage and Resistance. Science and Education, 24(5), 699–723. doi: 10.1007/s11191-015-9752-z
Masrifah, M., Setiawan, A., Sinaga, P., & Setiawan, W. (2020). An Investigation of Physics Teachers’ Multiple Representation Ability on Newton’s Law Concept. Jurnal Penelitian & Pengembangan Pendidikan Fisika, 6(1), 105–112. doi: 10.21009/1.06112
Nasution, A. A., Harahap, B., Harahap, R. A., & Wahdi, N. (2022). Socialization of the Use of Multimedia as a Learning Tool to Improve the Skills of MAS Darul Ilmi Students. International Journal of Community Service (IJCS), 1(1), 48–61. doi: 10.55299/ijcs.v1i1.88
Nousiainen, M. (2013). Coherence of Pre-service Physics Teachers’ Views of the Relatedness of Physics Concepts. Science and Education, 22(3), 505–525. doi: 10.1007/s11191-012-9500-6
Nurrahmawati, N., Sa’dijah, C., Sudirman, S., & Muksa, M. (2019). Multiple representations’ ability in solving word problem. International Journal of Recent Technology and Engineering, 8(1C2), 737–745. doi: 10.4108/eai.20-9-2019.2292114
Nussifera, L., Sinaga, P., & Setiawan, A. (2017). the Use of Multimodal Representation in the Physics Learning Material Development To Promote Students ’ Cognitive and Critical Thinking Competences. IMPACT: International Journal of Research in Applied, 5(4), 9–18.
Park, J., Chang, J., Tang, K. S., Treagust, D. F., & Won, M. (2020). Sequential patterns of students’ drawing in constructing scientific explanations: focusing on the interplay among three levels of pictorial representation. International Journal of Science Education, 42(5), 677–702. doi: 10.1080/09500693.2020.1724351
Selçuk, G. S. (2010). The effects of problem-based learning on pre-service teachers’ achievement, approaches and attitudes towards learning physics. International Journal of Physical Sciences, 5(6), 711–723.
Selçuk, G. S., & Çalişkan, S. (2010). A small-scale study comparing the impacts of problem-based learning and traditional methods on student satisfaction in the introductory physics course. Procedia - Social and Behavioral Sciences, 2(2), 809–813. doi: 10.1016/j.sbspro.2010.03.108
Sezen, N., Uzun, M. S., & Bulbul, A. (2012). An Investigation of Preservice Physics Teacher’s Use of Graphical Representations. Procedia - Social and Behavioral Sciences, 46(December), 3006–3010. doi: 10.1016/j.sbspro.2012.05.605
Simbolon, M., Sinaga, P., & Utari, S. (2017). Effect of Application of Physics Learning material Using Multimode representation to Improve Problem Solving Ability. Advances in Social Science,Education and Humanities Research, 57, 150–153. doi: 10.2991/icmsed-16.2017.33
Soeharto, S., & Csapó, B. (2021). Evaluating item difficulty patterns for assessing student misconceptions in science across physics, chemistry, and biology concepts. Heliyon, 7(11). doi: 10.1016/j.heliyon.2021.e08352
Sulaiman, F. (2010). Students’ perceptions of implementing problem-based learning in a physics course. Procedia - Social and Behavioral Sciences, 7(2), 355–362. doi: 10.1016/j.sbspro.2010.10.048
van Laar, E., van Deursen, A. J. A. M., van Dijk, J. A. G. M., & de Haan, J. (2017). The relation between 21st-century skills and digital skills: A systematic literature review. Computers in Human Behavior, 72, 577–588. doi: 10.1016/j.chb.2017.03.010
Yao, Y., Wang, P., Jiang, Y., Li, Q., & Li, Y. (2022). Innovative Online learning strategies for the successful construction of student Self-awareness during the COVID-19 pandemic: Merging TAM with TPB. Journal of Innovation & Knowledge, 7(4), 100252. doi: 10.1016/j.jik.2022.100252
Yew, E. H. J., & Goh, K. (2016). Problem-Based Learning: An Overview of its Process and Impact on Learning. Health Professions Education, 2(2), 75–79. doi: 10.1016/j.hpe.2016.01.004
Zhuang, H., Xiao, Y., Liu, Q., Yu, B., Xiong, J., & Bao, L. (2021). Comparison of nature of science representations in five Chinese high school physics textbooks. International Journal of Science Education, 43(11), 1779–1798. doi: 10.1080/09500693.2021.1933647
Authors
Masrifah, M., & Amiroh, D. (2023). The multi-representational ability profile of physics students in the interactive multimedia assisted problem-based learning during the Covid-19 pandemic. Momentum: Physics Education Journal, 7(2), 188–200. https://doi.org/10.21067/mpej.v7i2.7501
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