Effectiveness interactive digital modul physics (IDMP) based interactive lecture demonstration of concepts vector

Firmanul Catur Wibowo, Siti Rubihatul Awaliyah, Hadi Nasbey, Cecep E Rustana, Dina Rahmi Darman, Nur Jahan Ahmad, Bayram Costu, Binar Kurnia Prahani, Achmad Samsudin

Abstract


This research explores the effectiveness of Interactive Digital Module Physics (IDMP) for additional teaching materials in vector concepts. The IDMP which was developed according to the ADDIE model and its implementation uses the Interactive Lecture Demonstration (ILD) learning model. A total of 65 participants were students enrolled in a Basic Physics course at a university in a special area in the central district of Indonesia. The instrument used to validate the IDMP uses a scale of 1-5 and has a scoring rubric and processing effectiveness data using technique Cohen's D formula. The intervention group was given training assignments in using ILD-based IDMPs while the control group was given ILD-based assignments only. The results of this study obtained data that the intervention group was significantly better than the control group, found there was no significant increase. Cohen's D score in the intervention group had a large impact on the control group of 1.17 with a 95% confidence interval. Furthermore, they get learning experience by providing feedback that the course material using ILD-based IDMP can challenge students to learn independently.

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Abidin, Z., & Wulandari, T. C. (2022). The Model of Analytical Geometry Interactive Module using Systematic , Active , Effective ( SAE ) Model to Support Students ’ Autonomous Learning and Mathematics Education Competence. American Journal of Humanities and Social Sciences Research (AJHSSR), 6(5), 76–80.

Abramovich, S., Grinshpan, A. Z., & Milligan, D. L. (2019). Teaching Mathematics through Concept Motivation and Action Learning. Education Research International, 1–13. https://doi.org/10.1155/2019/3745406

Awaliyah, S. R., Wibowo, F. C., & Rustana, C. E. (2022). Desain Modul Elektronik Dengan Pendekatan Interactive Lecture Demonstration Pada Materi Vektor. Prosiding Seminar Nasional Fisika (E-Journal), 10(1), 105–110. https://doi.org/10.21009/03.SNF2022.02.PF.16

Carney, M. C. (2021). Designed for the Digital Age: Teacher Preparation at TEACH-NOW Graduate School of Education. The New Educator, 17(1), 21–38. https://doi.org/10.1080/1547688X.2020.1826072

Conradty, C., Sotiriou, S. A., & Bogner, F. X. (2020). How creativity in STEAM modules intervenes with self-efficacy and motivation. Education Sciences, 10(3), 1–15. https://doi.org/10.3390/educsci10030070

Delgado-Gómez, D., González-Landero, F., Montes-Botella, C., Sujar, A., Bayona, S., & Martino, L. (2020). Improving the teaching of hypothesis testing using a divide-and-conquer strategy and content exposure control in a gamified environment. Mathematics, 8(12), 1–14. https://doi.org/10.3390/math8122244

Desnita, D., Festiyed, F., Novitra, F., Ardiva, A., & Navis, M. Y. (2022). The Effectiveness of CTL-based Physics E-module on the Improvement of the Creative and Critical Thinking Skills of Senior High School Students. TEM Journal, 11(2), 802–810. https://doi.org/10.18421/TEM112-38

Ebner, M., Schön, S., Braun, C., Ebner, M., Grigoriadis, Y., Haas, M., Leitner, P., & Taraghi, B. (2020). COVID-19 epidemic as E-learning boost? Chronological development and effects at an Austrian university against the background of the concept of “E-learning readiness.” Future Internet, 12(6), 1–20. https://doi.org/10.3390/FI12060094

Gong, C., & Ribiere, V. (2021). Developing a unified definition of digital transformation. Technovation, 102, 1–17. https://doi.org/10.1016/j.technovation.2020.102217

Hadianto, A., & Festiyed. (2020). Meta analysis the use of e-modules based on research based learning models. Journal of Physics: Conference Series, 1481(1), 1–5. https://doi.org/10.1088/1742-6596/1481/1/012067

Hew, K. F., Hu, X., Qiao, C., & Tang, Y. (2020). What predicts student satisfaction with MOOCs: A gradient boosting trees supervised machine learning and sentiment analysis approach. Computers and Education, 145, 1–38. https://doi.org/10.1016/j.compedu.2019.103724

Lämsä, J., Uribe, P., Jiménez, A., Caballero, D., Hämäläinen, R., & Araya, R. (2021). Deep networks for collaboration analytics: Promoting automatic analysis of face-to-face interaction in the context of inquiry-based learning. Journal of Learning Analytics, 8(1), 113–125. https://doi.org/10.18608/JLA.2021.7118

Lovakov, A., & Agadullina, E. R. (2021). Empirically derived guidelines for effect size interpretation in social psychology. European Journal of Social Psychology, 51(3), 1–20. https://doi.org/10.1002/ejsp.2752

Mamun, M. A. Al, Lawrie, G., & Wright, T. (2020). Instructional design of scaffolded online learning modules for self-directed and inquiry-based learning environments. Computers and Education, 144, 1–17. https://doi.org/10.1016/j.compedu.2019.103695

Marwanti, K., Suherman, S., Wibowo, F. C., Darman, D. R., & Guntara, Y. (2020). Assessment Virtual Test (ASVITE): Assessment Virtual Based on Interactive Lecture Demonstration (ILD) to Support Employability Skills. Jurnal Penelitian & Pengembangan Pendidikan Fisika, 6(1), 1–8. https://doi.org/10.21009/1.06101

Mills, K., Roper, F., & Cesare, S. (2020). Accelerating student learning in communication and research skills: the adoption of adaptive learning technologies for scenario-based modules. In Technology, Change and the Academic Library: Case Studies, Trends and Reflections (pp. 75–84). https://doi.org/10.1016/B978-0-12-822807-4.00007-5

Moradi, M., Liu, L., Luchies, C., Patterson, M. M., & Darban, B. (2018). Enhancing teaching-learning effectiveness by creating online interactive instructional modules for fundamental concepts of physics and mathematics. Education Sciences, 8(3), 1–14. https://doi.org/10.3390/educsci8030109

Mubarak, A. A., Cao, H., & Zhang, W. (2020). Prediction of students’ early dropout based on their interaction logs in online learning environment. Interactive Learning Environments, 30(8), 1414–1433. https://doi.org/10.1080/10494820.2020.1727529

Nurlaily, V. A., Soegiyanto, H., & Usodo, B. (2019). Elementary school teacher’s obstacles in the implementation of problem-based learning model in mathematics learning. Journal on Mathematics Education, 10(2), 229–238. https://doi.org/10.22342/jme.10.2.5386.229-238

Osman, K., & Lay, A. N. (2022). MyKimDG module: an interactive platform towards development of twenty-first century skills and improvement of students’ knowledge in chemistry. Interactive Learning Environments, 30(8), 1–14. https://doi.org/10.1080/10494820.2020.1729208

Rahayu, I., & Sukardi, S. (2021). The Development Of E-Modules Project Based Learning for Students of Computer and Basic Networks at Vocational School. Journal of Education Technology, 4(4), 398–403. https://doi.org/10.23887/jet.v4i4.29230

Rajabalee, Y. B., & Santally, M. I. (2021). Learner satisfaction, engagement and performances in an online module: Implications for institutional e-learning policy. Education and Information Technologies, 26(3), 2623–2656. https://doi.org/10.1007/s10639-020-10375-1

Sharma, M. D., Johnston, I. D., Johnston, H., Varvell, K., Robertson, G., Hopkins, A., Stewart, C., Cooper, I., & Thornton, R. (2010). Use of interactive lecture demonstrations: A ten year study. Physical Review Special Topics - Physics Education Research, 6(2), 1–9. https://doi.org/10.1103/PhysRevSTPER.6.020119

Sidiq, R., & Suhendro, P. (2021). Utilization of Interactive E-Modules in Formation of Students’s Independent Characters in the Era of Pandemic. International Journal of Educational Research and Social Sciences (IJERSC), 2(6), 1651–1657.

Simanjuntak, M. P., Hutahaean, J., Marpaung, N., & Ramadhani, D. (2021). Effectiveness of problem-based learning combined with computer simulation on students’ problem-solving and creative thinking skills. International Journal of Instruction, 14(3), 519–534. https://doi.org/10.29333/iji.2021.14330a

Sokoloff, D. R., Thornton, R. K., & Laws, P. W. (2012). RealTime physics Active learning laboratories. John Wiley & Sons, Inc.

Spatioti, A. G., Kazanidis, I., & Pange, J. (2022). A Comparative Study of the ADDIE Instructional Design Model in Distance Education. In Information (Switzerland) (Vol. 13, Issue 9, pp. 1–20). https://doi.org/10.3390/info13090402

Stankova, E. N., Barmasov, A. V., Dyachenko, N. V., Bukina, M. N., Barmasova, A. M., & Yakovleva, T. Y. (2016). The use of computer technology as a way to increase efficiency of teaching physics and other natural sciences. International Conference on Computational Science and Its Applications, 9789, 581–594. https://doi.org/10.1007/978-3-319-42089-9_41

Uwamahoro, J., Ndihokubwayo, K., Ralph, M., & Ndayambaje, I. (2021). Physics Students’ Conceptual Understanding of Geometric Optics: Revisited Analysis. Journal of Science Education and Technology, 30(5). https://doi.org/10.1007/s10956-021-09913-4

Wibowo, F. C., Darman, D. R., Prahani, B. K., & Faizin, M. N. (2022). Optics Virtual Laboratory (OVL) Based on Physics Independent Learning (PIL) for Improving Critical Thinking Skill. Journal of Physics: Conference Series, 2377(1), 1–6. https://doi.org/10.1088/1742-6596/2377/1/012077

Wilson, D. B. (2022). The Relative Incident Rate Ratio Effect Size for Count-Based Impact Evaluations: When an Odds Ratio is Not an Odds Ratio. Journal of Quantitative Criminology, 38(2), 323–341. https://doi.org/10.1007/s10940-021-09494-w

Zimrot, R., & Ashkenazi, G. (2007). Interactive lecture demonstrations: A tool for exploring and enhancing conceptual change. Chemistry Education Research and Practice, 8(2), 197–211. https://doi.org/10.1039/B6RP90030E




DOI: http://dx.doi.org/10.21043/thabiea.v6i2.19808

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