DIGITAL GAME-BASED LEARNING IN SCHOOL CHEMISTRY AND MATHEMATICS: DUAL CASE STUDIES IN STOICHIOMETRY AND PROBABILITY THEORY AND IMPLICATIONS FOR HIGHER EDUCATION TEACHER PREPARATION IN KAZAKHSTAN

Authors

  • Kaisar Tursyngozhayev* Abai Kazakh National Pedagogical University
  • Zhadyra Kaiyngbayeva Abai Kazakh National Pedagogical University
  • Kavak Nusret Gazi University

DOI:

https://doi.org/10.59787/2413-5488-2026-54-2-%25p

Keywords:

digital game-based learning, PhET simulations, stoichiometry, probability theory, mathematics education, chemistry education, higher education, teacher preparation, gamification

Abstract

This article reports on two complementary multi-year case studies of integrating open-access PhET Interactive Simulations into the teaching of two notoriously demanding topics in the Kazakhstani school curriculum – stoichiometry in chemistry and probability theory in mathematics – and translates the resulting evidence into a unified set of design principles and curricular recommendations for higher education teacher preparation. Case 1 examines the use of “Reactants, Products and Leftovers” in 8th-grade chemistry across three Almaty schools; Case 2 examines the use of “Plinko Probability” in 10th-11th-grade mathematics across two Almaty institutions. Both interventions used a structured Predict-Observe-Explain design with parallel 15-item pre/post-tests, student questionnaires, and lesson-time logs. Across both subjects, simulation-supported instruction was associated with substantial gains in conceptual understanding (median Cohen’s d ≈ 1.0-1.1), increased intrinsic engagement, and a measurable reduction in the time required to reach class-level mastery. Crucially, the same four cross-cutting themes emerged in both subjects: visualisation of abstract sub-microscopic and stochastic phenomena, productive failure under low-stakes simulation, the limited appeal of competitive game elements, and the centrality of teacher coaching. We argue that this convergence across two very different STEM subjects strengthens the case for embedding digital game-based learning (DGBL) into Kazakhstani higher education through a four-component framework – conceptual orientation, simulation literacy, gamified lesson design and reflective practicum – applicable equally to chemistry and mathematics teacher preparation. Implications are discussed for university curriculum developers, methodologists and policymakers seeking to scale evidence-based gamification across the school-university continuum.

Author Biographies

  • Kaisar Tursyngozhayev*, Abai Kazakh National Pedagogical University

    Doctoral student, Abai Kazakh National Pedagogical University, Almaty, Kazakhstan; tursyngozha.k@gmail.com; ORCID 0009-0001-8249-5988 (corresponding author)

  • Zhadyra Kaiyngbayeva , Abai Kazakh National Pedagogical University

    Doctoral student, Abai Kazakh National Pedagogical University, Almaty, Kazakhstan; kaiynbayeva.zh@gmail.com; ORCID 0000-0002-4727-4151.

  • Kavak Nusret, Gazi University

    Professor, Department of Chemistry, Gazi University, Ankara, Turkey; nkavak@gazi.edu.tr; ORCID 0000-0001-6509-2653.

References

Teacher competencies and digital integration into teaching practices: perceptions from pre-service biology teachers in Kazakhstan. Frontiers in Education, 10, 1628034. https://doi.org/10.3389/feduc.2025.1628034

Banda, H. J., & Nzabahimana, J. (2023). The impact of Physics Education Technology (PhET) interactive simulation-based learning on motivation and academic achievement among Malawian physics students. Journal of Science Education and Technology, 32(1), 127-141. https://doi.org/10.1007/s10956-022-10010-3

Fischbein, E. (1975). The intuitive sources of probabilistic thinking in children. D. Reidel. https://doi.org/10.1007/978-94-010-1858-6

Franklin, C., Kader, G., Mewborn, D., Moreno, J., Peck, R., Perry, M., & Scheaffer, R. (2007). Guidelines for Assessment and Instruction in Statistics Education (GAISE) report: A pre-K-12 curriculum framework. American Statistical Association. https://www.amstat.org/asa/files/pdfs/gaise/gaiseprek-12_full.pdf

Hammad, R., Khan, Z., Safieddine, F., & Ahmed, A. (2020). A review of learning theories and models underpinning technology-enhanced learning artefacts. World Journal of Science, Technology and Sustainable Development, 17(4), 341-354. https://doi.org/10.1108/WJSTSD-06-2020-0062

Hawlitschek, A., & Joeckel, S. (2017). Increasing the effectiveness of digital educational games: The effects of a learning instruction on students’ learning, motivation and cognitive load. Computers in Human Behavior, 72, 79-86. https://doi.org/10.1016/j.chb.2017.01.040

Hu, Y., Gallagher, T., Wouters, P., Van der Schaaf, M., & Kester, L. (2022). Game-based learning has good chemistry with chemistry education: A three-level meta-analysis. Journal of Research in Science Teaching, 59(9), 1499-1543. https://doi.org/10.1002/tea.21765

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

Kaiyngbayeva, Z., Shukayev, M., & Kossanov, B. (2021). The current state of teaching probability theory and mathematical statistics in secondary schools in Kazakhstan. Review of International Geographical Education (RIGEO), 11(5), 2467-2478. https://doi.org/10.48047/rigeo.11.05.172

Kalogiannakis, M., Papadakis, S., & Zourmpakis, A.-I. (2021). Gamification in science education: A systematic review of the literature. Education Sciences, 11(1), 22. https://doi.org/10.3390/educsci11010022

Karmanova, A., Madybekova, G., Kavak, N., Ualikhanova, B., Zharylkassyn, A., & Umarova, Z. (2024). Developing the professional competence of future chemistry teachers through digital technologies: A case study of Kazakhstan. International Journal of Information and Education Technology, 14(8), 1119-1126. https://doi.org/10.18178/ijiet.2024.14.8.2140

Lampropoulos, G., & Kinshuk. (2024). Virtual reality and gamification in education: A systematic review. Educational Technology Research and Development, 72(3), 1691-1785. https://doi.org/10.1007/s11423-024-10351-3

Miles, M. B., Huberman, A. M., & Saldaña, J. (2018). Qualitative data analysis: A methods sourcebook (4th ed.). SAGE Publications.

Montenegro-Rueda, M., Fernández-Cerero, J., Mena-Guacas, A. F., & Reyes-Rebollo, M. M. (2023). Impact of gamified teaching on university student learning. Education Sciences, 13(5), 470. https://doi.org/10.3390/educsci13050470

OECD (2023). PISA 2022 Results (Volume I): The State of Learning and Equity in Education. OECD Publishing. https://doi.org/10.1787/53f23881-en

Park, S., & Kim, S. (2021). Is sustainable online learning possible with gamification? The effect of gamified online learning on student learning. Sustainability, 13(8), 4267. https://doi.org/10.3390/su13084267

Perkins, K., Adams, W., Dubson, M., Finkelstein, N., Reid, S., Wieman, C., & LeMaster, R. (2006). PhET: Interactive simulations for teaching and learning physics. The Physics Teacher, 44(1), 18-23. https://doi.org/10.1119/1.2150754

Pratt, D., & Kazak, S. (2018). Research on uncertainty. In D. Ben-Zvi, K. Makar, & J. Garfield (Eds.), International handbook of research in statistics education (pp. 193-228). Springer. https://doi.org/10.1007/978-3-319-66195-7_6

Salame, I. I., & Makki, J. (2021). Examining the use of PhET simulations on students’ attitudes and learning in general chemistry II. Interdisciplinary Journal of Environmental and Science Education, 17(4), e2247. https://doi.org/10.21601/ijese/10966

Sardarova, E., Baigunakova, A., & Shubayeva, G. (2026). Gamification and interactive learning in secondary and higher education in Kazakhstan. Higher Education in Kazakhstan, 53(1), 89-105. https://doi.org/10.59787/2413-5488-2025-53-1-89-105

Schindler, L. A., Burkholder, G. J., Morad, O. A., & Marsh, C. (2017). Computer-based technology and student engagement: A critical review of the literature. International Journal of Educational Technology in Higher Education, 14, 25. https://doi.org/10.1186/s41239-017-0063-0

Stohl, H. (2005). Probability in teacher education and development. In G. A. Jones (Ed.), Exploring probability in school: Challenges for teaching and learning (pp. 345-366). Springer. https://doi.org/10.1007/0-387-24530-8_15

Vrcelj, A., Hoić-Božić, N., & Dlab, M. H. (2023). Use of gamification in primary and secondary education: A systematic literature review. International Journal of Educational Methodology, 9(1), 13-27. https://doi.org/10.12973/ijem.9.1.13

Yespenbetova, S., Abyzbekova, G., Tapalova, A., Arynova, K., & Balykbayeva, G. (2024). Features of online teaching of laboratory practices in physical chemistry at the university. Open Learning: The Journal of Open, Distance and e-Learning, 1-15. https://doi.org/10.1080/02680513.2024.2442387

Zainuddin, Z., Chu, S. K. W., Shujahat, M., & Perera, C. J. (2020). The impact of gamification on learning and instruction: A systematic review of empirical evidence. Educational Research Review, 30, 100326. https://doi.org/10.1016/j.edurev.2020.100326

Downloads

Published

2026-06-30

Issue

Section

ISSUES OF QUALITY ASSURANCE IN HIGHER EDUCATION