Contribution of Computer-Assisted Simulation on Students’ Learning of Chemical Bonding in selected secondary Schools of Rwanda
##article.abstract##
This study delves into the impact of computer-assisted simulations on students' comprehension of chemical bonding. Employing an explanatory sequential design, the research initially gathered and analyzed quantitative data before delving into qualitative perspectives. The study involved 86 students, aged 16 to 17, from a twelve-year secondary school. Two classes were selected, with one designated as the experimental group and the other as the control group. The experimental group received instruction utilizing computer-assisted simulations, while the control group received traditional instruction methods. Both groups underwent pre- and post-tests to evaluate their understanding of chemical bonding. The chemical bonding achievement test yielded quantitative data with a reliability coefficient of 0.791, supplemented by qualitative insights from participant interviews. Statistical analysis of the quantitative data, conducted using the Statistical Package for the Social Sciences (SPSS) software, indicated a statistically significant difference in performance between students taught with computer-assisted simulations and those without it, favoring the experimental group (df=85, p<.05). Additionally, within the experimental group, no statistically significant difference in performance was observed between male and female students (df=85, p>.05). Interviewed students expressed that the integration of computer-assisted simulations significantly enhanced their understanding of chemical bonding compared to conventional teaching methods. These findings highlight the effectiveness of computer-assisted simulations in improving students' comprehension of chemical bonding, suggesting its integration into chemistry education.
References
Allouche, A. (2012). Software News and Updates Gabedit — A Graphical User Interface for Computational Chemistry Softwares. Journal of Computational Chemistry, 32, 174–182. https://doi.org/10.1002/jcc
Alshenqeeti, H. (2014). Interviewing as a Data Collection Method: A Critical Review. English Linguistics Research, 3(1). https://doi.org/10.5430/elr.v3n1p39
Dawadi, S., Shrestha, S., & Giri, R. A. (2021). Mixed-Methods Research: A Discussion on its Types, Challenges, and Criticisms. Journal of Practical Studies in Education, 2(2), 25–36. https://doi.org/10.46809/jpse.v2i2.20
Dawati, F. M., Yamtinah, S., Rahardjo, S. B., Ashadi, A., & Indriyanti, N. Y. (2019). Analysis of students’ difficulties in chemical bonding based on computerized two-tier multiple choice (CTTMC) test. Journal of Physics: Conference Series, 1157(4). https://doi.org/10.1088/1742-6596/1157/4/042017
Doyle, L., Brady, A. M., & Byrne, G. (2009). An overview of mixed methods research. Journal of Research in Nursing, 14(2), 175–185. https://doi.org/10.1177/1744987108093962
Falvo, D. A. (2008). Animations and Simulations for Teaching and Learning Molecular Chemistry. 4, 68–77.
Jabeen, F., & Afzal, M. T. (2020). Effect of Simulated Chemistry Practicals on Students’ Performance At Secondary School Level. Journal of Education and Educational Development, 7(1), 119. https://doi.org/10.22555/joeed.v7i1.2600
Jhenly, Asedillas and Maria T, Qu. (2019). Computer-assisted-Simulation-and-its-Effects-on-Student’s-Knowledge-in-Chemistry.pdf (pp. 8–9).
Joki, J., & Aksela, M. (2018). The challenges of learning and teaching chemical bonding at different school levels using electrostatic interactions instead of the octet rule as a teaching model. Chemistry Education Research and Practice, 19(3), 932–953. https://doi.org/10.1039/c8rp00110c
Kabigting, L. D. C. (2021). Computer Simulation on Teaching and Learning of Selected Topics in Physics. European Journal of Interactive Multimedia and Education, 2(2), e02108. https://doi.org/10.30935/ejimed/10909
Kanyaru, P., & Maina, E. (2019). Enhancing Exploratory Learning Using Computer Simulation in an E-learning Environment: A Literature Review. Open Journal for Information Technology, 2(2), 35–40. https://doi.org/10.32591/coas.ojit.0202.02035k
Mihindo, W. J., Wachanga, S. W., & Anditi, Z. O. (2017). Effects of Computer-assisted Simulations Teaching Approach on Students’ Achievement in the Learning of Chemistry among Secondary School Students in Nakuru Sub County, Kenya. Journal of Education and Practice, 8(5), 65–75. http://search.ebscohost.com/login.aspx?direct=true&db=eric&AN=EJ1133108&lang=es&scope=site
Mohsen, M. A. (2011). The Use of Computer-assisted Simulation to Aid Comprehension and Incidental Vocabulary Learning. Journal of Educational Computing Research, 54(6), 1–4. https://doi.org/10.5688/ajpe756113
Nahum, T. L., Mamlok-Naaman, R., Hofstein, A., & Taber, K. S. (2010). Teaching and learning the concept of chemical bonding. Studies in Science Education, 46(2), 179–207. https://doi.org/10.1080/03057267.2010.504548
Nsabayezu, E., & Iyamuremye, A. (2022). Impact of computer-assisted simulations on students’ learning of organic chemistry in the selected secondary schools of Gicumbi District in Rwanda. Education and Information Technologies, 2(1), 7. https://doi.org/10.1007/s10639-022-11344-6
Nsabayezu, E., Iyamuremye, A., Kwitonda, J. D., & Mbonyiryivuze, A. (2020). Teachers ’ perceptions towards the utilization of WhatsApp in supporting teaching and learning of chemistry during COVID-19 pandemic in Rwandan secondary schools. African Journal of Educational Studies in Mathematics and Sciences Vol. 16, No. 2, 2020, 16(2), 84.
Nsabayezu, E., Iyamuremye, A., & Mbonyiryivuze, A. (2023). Digital ‑ based formative assessment to support students ’ learning of organic chemistry in selected secondary schools of Nyarugenge District in Rwanda. Education and Information Technologies, 28(1), 1–5. https://doi.org/10.1007/s10639-023-11599-7
Nsabayezu, E., Iyamuremye, A., Nahimana, J. P., Mukiza, J., Kampire, E., & Nsengimana, T. (2022). The progress in the application of rubric materials in chemistry teaching and students’ learning enhancement during 21st century: a systematic review. Discover Education, 1(1), 1–8. https://doi.org/10.1007/s44217-022-00005-y
Nsabayezu, E., Iyamuremye, A., & Nungu, L. (2023). Online periodic table of elements to support students ’ learning of trends in properties of chemical elements. Education and Information Technologies, 28(2), 1–13. https://doi.org/10.1007/s10639-023-11650-7
Nsabayezu, E., Iyamuremye, A., & Urengejeho, V. (2022). Computer ‑ based learning to enhance chemistry instruction in the inclusive classroom : Teachers ’ and students ’ perceptions. Education and Information Technologies, 27(3), 1–4. https://doi.org/10.1007/s10639-022-11082-9
Nsabayezu, E., Mukiza, J., Iyamuremye, A., Mukamanzi, O. U., & Mbonyiryivuze, A. (2022). Rubric-based formative assessment to support students’ learning of organic chemistry in the selected secondary schools in Rwanda: A technology-based learning. Education and Information Technologies, 27(4), 1–18. https://doi.org/10.1007/s10639-022-11113-5
Oladejo, A. I. (2021a). Teaching Chemistry With Computer Simulation : Would Senior Crawford Journal of Multidisciplinary Research ( Cjmr ) 2021. Crawford Journal of Multidisciplinary Research (Cjmr), 2(2), 16–32.
Oladejo, A. I. (2021b). Teaching chemistry with computer simulation : would senior crawford journal of multidisciplinary research ( CJMR ) 2021. Crawford journal of multidisciplinary research (CJMR), 2(2), 16–32.
Raeker, T. J., & Depristo, A. E. (1991). Theory of chemical bonding based on the atom-homogeneous electron gas system. International Reviews in Physical Chemistry, 10(1), 1–54. https://doi.org/10.1080/01442359109353253
Raman, R., & Vinuesa, R. (2021). Acquisition and User Behavior in Online Science Laboratories before and during the COVID-19 Pandemic.
Riley, T., Rowell, K., Mcgoldrick, K., Maier, M., & Simkins, S. (2019). Teaching with Simulations How to Teach with Simulations. 1–2.
Samuel, N. N. C., & Ikwuka, O. I. (2017). Effect of computer animation on chemistry academic achievement of secondary school students in Anambra State, Nigeria. Journal of Emerging Trends in Educational Research and Policy Studies, 8(2), 98–102.
