Energy Quest: A Quasi-Experimental Study of Game-Based Learning on Conceptual Understanding of Mechanical Energy in Secondary Physics Education
DOI:
https://doi.org/10.64420/ijitl.v3i2.578Keywords:
game-based learning, mechanical energy, physics education, conceptual understanding, quasi-experimental designAbstract
Background: Many secondary students struggle with abstract concepts and formula reliance in mechanical energy. Objective: This study evaluated Energy Quest, a curriculum-aligned card game, to enhance Grade 9 students' conceptual understanding and problem-solving skills in kinetic and potential energy. Method: Employing a quasi-experimental pretest–posttest non-equivalent control group design, 77 students across two intact classes participated. The experimental group (n = 40) engaged in structured game-based learning, while the control group (n = 37) received conventional instruction over two weeks. Data were collected using a validated 20-item achievement test α = 0.860) and analyzed via paired and independent samples t-tests and Cohen's d. Result: Posttest performance significantly favored the experimental group ($M = 16.40, SD = 1.74$) over the control group (M = 13.20, SD = 1.23), t (75) = 9.26, p < .001. The intervention demonstrated an extraordinarily large effect size (d = 2.11), indicating substantial learning gains. Conclusion: Structured game-based learning effectively strengthens conceptual understanding and problem-solving abilities beyond conventional teaching methods. Contribution: This study provides empirical evidence that low-cost, non-digital, and curriculum-aligned instructional innovations can successfully bridge persistent physics learning gaps, offering a scalable pedagogical solution for resource-constrained science classrooms.
References
Acido, J. V., & Caballes, D. G. (2024). Assessing educational progress: A comparative analysis of PISA results (2018 vs. 2022) and HDI correlation in the Philippines. World Journal of Advanced Research and Reviews, 21(1), 462–474. https://doi.org/10.30574/wjarr.2024.21.1.0020
Amaliyah, S., Fajar, D. M., & Aminulloh. (2024). Analysis of factors causing students learning difficulties in learning science. Science Education and Application Journal, 6(1), 61–74. https://doi.org/10.30736/seaj.v6i1.1015
Anandita, A. S., Adi, N. P., & Baihaqi, H. K. (2025). Enhancing Physics Learning with Advance Organizer: A Meta-Cognitive Approach. Konstan - Jurnal Fisika Dan Pendidikan Fisika, 10(01), 14–22. https://doi.org/10.20414/konstan.v10i01.641
Bernardo, A. B. I., Cordel, M. O., Calleja, M. O., Teves, J. M. M., Yap, S. A., & Chua, U. C. (2023). Profiling low-proficiency science students in the Philippines using machine learning. Humanities and Social Sciences Communications, 10(1), 192. https://doi.org/10.1057/s41599-023-01705-y
Cabural, A. (2024). Beyond Benchmarking: A Diagnostic Inquiry into the Underlying Determinants of Low Performance in Philippine PISA Science. Journal of Tertiary Education and Learning, 2(3), 46–57. https://doi.org/10.54536/jtel.v2i3.3063
Calo, J. R., & De Vera, M. (2025). The Quality of Science Education: Viewpoints of Secondary school science Teachers. Journal of Research in Education and Pedagogy., 2(1), 95–109. https://doi.org/10.70232/jrep.v2i1.26
Campbell, D. T., & Stanley, J. C. (1963). Experimental and quasi-experimental designs for research. Houghton Mifflin.
Caparoso, J. K. V., & Orleans, A. V. (2024). DiGIBST: An inquiry-based digital game-based learning pedagogical model for science teaching. STEM Education, 4(3), 282–298. https://doi.org/10.3934/steme.2024017
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates
Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE Publications
Darling-Hammond, L., Flook, L., Cook-Harvey, C., Barron, B., & Osher, D. (2019). Implications for educational practice of the science of learning and development. Applied Developmental Science, 24(2), 97–140. https://doi.org/10.1080/10888691.2018.1537791
De Borja, J. M. A. (2020). A Literature Review towards Pre-service Science Education Policy. International Journal of Research Publications, 46(1). https://doi.org/10.47119/ijrp10046122020955
Department of Education. (2019). DepEd Order No. 21, s. 2019: Policy guidelines on the K to 12 basic education program. https://www.deped.gov.ph/wp-content/uploads/2019/08/DO_s2019_021.pdf
Eslami, Z. R., & Chowdhury, M. (2021). Digital game-based learning. In Springer texts in education (pp. 621–625). https://doi.org/10.1007/978-3-030-79143-8_108
Eviota, J. S., & Liangco, M. M. (2020). Students’ Performance on Inquiry-Based Physics Instruction through Virtual Simulation. Jurnal Pendidikan MIPA, 21(1), 22–34. https://doi.org/10.23960/jpmipa/v21i1.pp22-34
Frey, R. F., McDaniel, M. A., Bunce, D. M., Cahill, M. J., & Perry, M. D. (2020). Using students’ concept-building tendencies to better characterize Average-Performing student learning and Problem-Solving approaches in general chemistry. CBE—Life Sciences Education, 19(3), ar42. https://doi.org/10.1187/cbe.19-11-0240
Fuente, J. a. D. (2019). Driving Forces of Students’ choice in Specializing Science: A science Education context in the Philippines perspective. The Normal Lights, 13(2). https://doi.org/10.56278/tnl.v13i2.1393
George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference (4th ed.). Allyn & Bacon.
Gui, M. D., & Akuba, M. (2023). Analysis of learning Difficulties in Class V Elementary School Science material. Journal of Education Method and Learning Strategy, 2(01), 70–78. https://doi.org/10.59653/jemls.v2i01.369
Halilović, A., Mešić, V., Hasović, E., & Vidak, A. (2021). Teaching upper-secondary students about conservation of mechanical energy: two variants of the system approach to energy analysis. Journal of Baltic Science Education. https://www.scientiasocialis.lt/jbse/?q=node/992
Jiménez-Valverde, G., Heras-Paniagua, C., Fabre-Mitjans, N., & Calafell-Subirà, G. (2024). Gamifying Teacher Education with FantasyClass: Effects on Attitudes towards Physics and Chemistry among Preservice Primary Teachers. Education Sciences, 14(8), 822. https://doi.org/10.3390/educsci14080822
Khoo, Y. Y., Ramdan, M. R., Abdullah, N. L., Aziz, N. a. A., & Mahjom, N. (2025). The Impacts of Game-based Learning on thinking and Learning in Higher Education Context: A scoping review. International Journal of Education in Mathematics Science and Technology, 13(3), 623–637. https://doi.org/10.46328/ijemst.4776
Kubsch, M., Opitz, S., Nordine, J., Neumann, K., Fortus, D., & Krajcik, J. (2021). Exploring a pathway towards energy conservation through emphasizing the connections between energy, systems, and fields. Disciplinary and Interdisciplinary Science Education Research, 3(1). https://doi.org/10.1186/s43031-020-00030-7
Liu, Z., Pan, S., Zhang, X., & Bao, L. (2022). Assessment of knowledge integration in student learning of simple electric circuits. Physical Review Physics Education Research, 18(2). https://doi.org/10.1103/physrevphyseducres.18.020102
Matthew, G., Pelser-Carstens, V., Bunt, B., & Bunt, L. (2025). Enhancing Student Engagement and Knowledge Retention through Game-Based Learning: A Comprehensive Framework Integrating Game Design and Learning Theories. European Conference on Games Based Learning, 19(2), 591–599. https://doi.org/10.34190/ecgbl.19.2.3873
Mayer, R. E. (2009). Multimedia learning (2nd ed.). Cambridge University Press. https://doi.org/10.1017/CBO9780511811678
Mayer, R. E. (2014). Cognitive Theory of Multimedia Learning. In Cambridge University Press eBooks (pp. 43–71). https://doi.org/10.1017/cbo9781139547369.005
Mayer, R. E. (2020). Multimedia learning. Cambridge Aspire Website. https://doi.org/10.1017/9781316941355
Mikrouli, P., Tzafilkou, K., & Protogeros, N. (2024). Applications and learning outcomes of game based learning in education. International Educational Review, 25–54. https://doi.org/10.58693/ier.212
Munfaridah, N., Avraamidou, L., & Goedhart, M. (2021). Preservice Physics Teachers’ Development of Physics Identities: the Role of Multiple Representations. Research in Science Education, 52(6), 1699–1715. https://doi.org/10.1007/s11165-021-10019-5
Muthiyan, G., Kasat, P., Vij, V., Solanki, R. S., C, K., & Sontakke, B. (2023). Effectiveness of an innovative card game as a supplement for teaching factual content to medical students: A mixed method study. Cureus, 15(10), e47768. https://doi.org/10.7759/cureus.47768
Nadeem, M., Oroszlanyova, M., & Farag, W. (2023). Effect of Digital Game-Based Learning on student engagement and motivation. Computers, 12(9), 177. https://doi.org/10.3390/computers12090177
Novianti, S., Sari, L. Y., & Afza, A. (2022). Factors caused difficulty in learning science for students. Journal of Biology Education Research (JBER), 3(2), 50–59. https://doi.org/10.55215/jber.v3i2.5949
Padolina, W. (2023). NAST PHL: Harnessing Science and Technology to Build the Philippines of the Future. Transactions of the National Academy of Science and Technology, 45(2023), 1–6. https://doi.org/10.57043/transnastphl.2023.3322
Patton, M, Q. (2002). Qualitative Research and Evaluation Methods, 3rd Ed. (3). California: SAGE Publications.
Piaget, J. (1952). The origins of intelligence in children. International Universities Press. https://doi.org/10.1037/11494-000
Piaget, J. (1970). Science of education and the psychology of the child. Orion Press.
Plass, J. L., Homer, B. D., & Kinzer, C. K. (2015). Foundations of game-based learning. Educational Psychologist, 50(4), 258–283. https://doi.org/10.1080/00461520.2015.1122533
Resbiantoro, G., Setiani, R., & Dwikoranto. (2022, June 30). A review of misconception in physics: The diagnosis, causes, and remediation: Research Article. https://www.tused.org/index.php/tused/article/view/924
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi.org/10.1037/0003-066X.55.1.68
Ryan, R. M., & Deci, E. L. (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness. Guilford Press.
Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Houghton, Mifflin and Company.
Suriyabutr, A., & Yasri, P. (2023). Enhancing High School Students’ Understanding of Plant Diversity through an Innovative and Engaging Educational Card Game. Education Quarterly Reviews, 6(2). https://doi.org/10.31014/aior.1993.06.02.738
Sweller, J. (2024). Cognitive load theory and individual differences. Learning and Individual Differences, 110, 102423. https://doi.org/10.1016/j.lindif.2024.102423
Tabamo, A. J. C. (2023). The use of primary literature in teaching science as a strategy in addressing surface learning: a synthesis. International Journal of Research Publication and Reviews, 4(7), 2191–2197. https://doi.org/10.55248/gengpi.4.723.46962
Taber, K. S. (2017). The use of Cronbach’s Alpha when developing and reporting research instruments in science education. Research in Science Education, 48(6), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press
Wardani, A. D. P., Mufidah, A., Mufidah, R., & Aristiawan. (2023). The effect of self efficacy on the creative thinking ability learners on environmental material. Islamic Journal of Integrated Science Education (IJISE), 2(2), 99–110. https://doi.org/10.30762/ijise.v2i2.1528
Weller, J. (2020). Cognitive load theory and educational technology. Educational Technology Research and Development, 68(1), 1–16. https://doi.org/10.1007/s11423-019-09701-3
Wilcox, B. R., Pollock, S. J., & Bolton, D. R. (2020). Retention of conceptual learning after an interactive introductory mechanics course. Physical Review Physics Education Research, 16(1). https://doi.org/10.1103/physrevphyseducres.16.010140
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Aldrin Boocan, Zyrene Joy Naggoc, Juana Guinid, Christzon Pasigon

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms: (1) License & Copyright: Authors retain full copyright and grant the journal the right of first publication. The work is simultaneously licensed under a CC BY-SA 4.0 International License, which allows others to share and adapt the material for any purpose, even commercially, provided proper credit is given and derivative works are shared under the same license. (2) Secondary Distribution: Authors may enter into separate, non-exclusive contractual arrangements for the distribution of the journal's published version (e.g., institutional repositories or book chapters), acknowledging its initial publication in this journal. (3) Self-Archiving: Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or personal websites) prior to and during the submission process.





