Author

Heather Whoopi G. De Dios*
Cebu Technological University – Main Campus, Cebu City, Philippines

Abstract

This study examined the impact of interactive simulations on visualization, problem-solving, academic performance, perceptions, and learning experiences in Cell and Molecular Biology laboratory instruction. This study utilized a convergent mixed-methods research design, where 24 participants took part in simulation-integrated lesson discussion on topics related to DNA replication, mutations, gene expression, and DNA repair. The quantitative data were obtained from visualization, problem-solving, achievement, and perception tools, whereas the qualitative data were collected from student interviews that were analyzed using thematic analysis. The findings indicated that students initially demonstrated poor visualization and problem-solving skills, as well as poor academic achievement, particularly in mutation and gene expression. However, after the intervention, significant changes were observed in students’ visualization and problem-solving skills, as well as in academic achievement, with large effect sizes. The students rated interactive simulations very positively for learning outcomes, engagement, and satisfaction. Students reported that interactive simulations increased their understanding of concepts, engagement, and motivation, and helped develop higher-order thinking skills. However, they also faced problems such as technical problems, internet connections, and control over simulations. This study provides empirical data on the use of simulation in laboratory instruction to enhance cognitive and higher-order skills. The results of this study prove that the use of simulations in teaching can be beneficial in Cell and Molecular Biology laboratory instructions.

Keywords:  Interactive simulation, cell and molecular biology, visualization skills, problem-solving skills, academic achievement, laboratory instruction, student perceptions.

*Corresponding author / Email: heatherwhoopid@gmail.com
DOI: http://doi.org/10.69651/PIJHSS05031475

Recommended citation:
De Dios, H. W. G. (2026). Integrating interactive simulation in cell and molecular biology laboratory instruction: Effects on students’ visualization skills, problem-solving ability, academic achievement, perceptions, and learning experience. Pantao (International Journal of the Humanities and Social Sciences) 5 (3), 3529-3547. http://doi.org/10.69651/PIJHSS05031475

Read the full text

References

Ahmad, C. N., Osman, K., & Halim, L. (2014). The establishment of physical aspects of Science Laboratory Environment Inventory (PSLEI). Journal of Turkish Science Education, 11(2). https://doi.org/10.12973/tused.10112a

Alsahi, N. R., Abdelkader, A. F. I., Ismail, A. A. K. H., Alqatawneh, S., Alqawasmi, A., & Salem, O. (2024). The effect of using PhET interactive simulations on academic achievement of physics students in higher education institutions. Educational Sciences: Theory & Practice, 24(1), 65–78. https://doi.org/10.12738/jestp.2024.1.006

Avena, J. S., McIntosh, B. B., Whitney, O. N., Wiens, A., & Knight, J. K. (2021). Successful problem solving in genetics varies based on question content. CBE—Life Sciences Education, 20(4), ar51. https://doi.org/10.1187/cbe.21-01-0016

Beckham, J. T., Dries, D. R., Hall, B. L., Mitton-Fry, R. M., Engelman, S., Burch, C., Acevedo, R., Mertz, P. S., Vardar-Ulu, D., Agrawal, S., Fox, K. M., Austin, S., Franzen, M. A., Jakubowski, H. V., Novak, W. R. P., Roberts, R., Roca, A. I., & Procko, K. (2024). Seeing eye to eye? Comparing faculty and student perceptions of biomolecular visualization assessments. Education Sciences, 14(1), 94. https://doi.org/10.3390/educsci14010094

Bilbokaite, R. (2015). Effect of computer-based visualization on students’ cognitive processes in education process. Society. Integration. Education. Proceedings of the International Scientific Conference, 4, 349–357. https://doi.org/10.17770/sie2015vol4.417

Bond, M., Bedenlier, S., Marín, V. I., & Händel, M. (2021). Emergency remote teaching in higher education: Mapping the first global online semester. International Journal of Educational Technology in Higher Education, 18, 50. https://doi.org/10.1186/s41239-021-00282-x

Carroll, J., Najafi, H., & Steiner, M. (2023). Evaluating the effectiveness of virtual laboratory simulations for graduate-level training in genetic methodologies. Biochemistry and Molecular Biology Education. https://doi.org/10.1002/bmb.21898

Cayani Caceres, K. S., & Machaca Viza, R. (2023). Science and inquiry-based teaching and learning: A systematic review. Frontiers in Education, 8, 1170487. https://doi.org/10.3389/feduc.2023.1170487

Chen, M. J., She, H. C., & Tsai, P. Y. (2024). The effects of online simulation-based collaborative problem-solving on students’ problem-solving, communication and collaboration attitudes. Education and Information Technologies. https://doi.org/10.1007/s10639-024-12609-y

Chernikova, O., Heitzmann, N., Stadler, M., Holzberger, D., Seidel, T., & Fischer, F. (2020). Simulation-based learning in higher education: A meta-analysis. Review of Educational Research, 90(4), 499–541. https://doi.org/10.3102/0034654320933544

Cosentino, G., Anton, J., Sharma, K., Gelsomini, M., Giannakos, M., & Abrahamson, D. (2025). Hybrid teaching intelligence: Lessons learned from an embodied mathematics learning experience. British Journal of Educational Technology, 56, 621–649. https://doi.org/10.1111/bjet.13525

Costabile, M., Birbeck, D., & Aitchison, C. (2025). Using simulations to meld didactic and constructivist teaching methods in complex second year STEM courses. International Journal of Science Education, 47(2), 173–190. https://doi.org/10.1080/09500693.2024.2314010

Delgado-Algarra, E., Cuenca-López, J., & Navarro-Medina, E. (2023). Students’ perceived learning outcomes in technology-enhanced environments. Computers in Human Behavior Reports, 9, 100245. https://doi.org/10.3390/apps14177513

Ewais, A., Mystakidis, S., Khalilia, W., Diab, S., Christopoulos, A., Khasib, S., Yahya, B., & Hatzilygeroudis, I. (2024). Virtual reality immersive simulations for a forensic molecular biology course—A quantitative comparative study. Applied Sciences, 14(17), 7513. https://doi.org/10.3390/app14177513

Fibriana, F., Abidin, Z., Naufal, M. A., Febriyanto, H., Alma’ruf, F., Nurazizah, K. S., Ningrum, N. S., & Upaichit, A. (2025). A story-based virtual laboratory practicum in an undergraduate genetics course to improve concept understanding and visual literacy. Biosaintifika: Journal of Biology & Biology Education, 17(2), 281–291. https://doi.org/10.15294/biosaintifika.v17i2.23901

Fiorella, L., & Mayer, R. E. (Eds.). (2022). The Cambridge handbook of multimedia learning (3rd ed.). Cambridge University Press. https://doi.org/10.1017/9781108894333

Gauthier, A. (2024). Game and simulation stimulate conceptual change about molecular emergence in different ways, with potential cultural implications. Education Sciences, 14(4), 366. https://doi.org/10.3390/educsci14040366

Griffin, C., Loughran, S., Kelly, B., Healy, E., Lambe, G., Rossum, A., Murphy, B., Moore, E., Burke, C., Morrin, A., Breslin, C., Heaney, F., Rooney, D., Bree, R., & Drumm, B. (2025). Advances in physiology education. Advances in Physiology Education. https://doi.org/10.1152/advan.00227.2024

Herrington, D. G., & Sweeder, R. D. (2024). Using simulations and screencasts in online preclass activities to support student building of mental models. Education Sciences, 14(2), 115. https://doi.org/10.3390/educsci14020115

Jenkinson, J. (2018). Molecular biology meets the learning sciences: Visualizations in education and outreach. Journal of Molecular Biology, 430(21), 4013–4027. https://doi.org/10.1016/j.jmb.2018.08.020

Ji, M., Le, J., Chen, B., & Zhe, L. (2024). A predictive model for classifying college students’ academic performance based on visual-spatial skills. Frontiers in Psychology, 15, 1434015. https://doi.org/10.3389/fpsyg.2024.1434015

Kahu, E. R., & Nelson, K. (2018). Student engagement in the educational interface: Understanding the mechanisms of student success. Higher Education Research & Development, 37(1), 58–71. https://doi.org/10.1080/07294360.2017.1344197

Kaldaras, L., Wang, K. D., Nardo, J. E., Price, A., Perkins, K., Wieman, C., & Salehi, S. (2024). Employing technology-enhanced feedback and scaffolding to support the development of deep science understanding using computer simulations. International Journal of STEM Education, 11(1), 30. https://doi.org/10.1186/s40594-024-00490-7

Klingenberg, S., Bosse, R., Mayer, R., & Makransky, G. (2024). Does embodiment in virtual reality boost learning transfer? Testing an immersion interactivity framework. Educational Psychology Review. https://doi.org/10.1007/s10648-024-09956-0

Lazonder, A. W., & Harmsen, R. (2016). Meta-analysis of inquiry-based learning: Effects of guidance. Review of Educational Research, 86(3), 681–718. https://doi.org/10.3102/003465431562736

Li, L., Zhang, R., & Piper, A. M. (2023). Predictors of student engagement and perceived learning in emergency online education amidst COVID-19: A community of inquiry perspective. Computers in Human Behavior Reports, 12, 100326. https://doi.org/10.1016/j.chbr.2023.100326

Makransky, G., Petersen, G. B., & Klingenberg, S. (2025). Immersive virtual learning environments and student outcomes. Educational Psychology Review, 37(1), 89–112. https://doi.org/10.1007/s10648-024-09859-8

Mao, P., Cai, Z., He, J., Chen, X., & Fan, X. (2021). The relationship between attitude toward science and academic achievement in science: A three-level meta-analysis. Frontiers in Psychology, 12, 784068. https://doi.org/10.3389/fpsyg.2021.784068

Mayer, R. E. (2020). Multimedia learning (3rd ed.). Cambridge University Press. https://doi.org/10.1017/9781316941355

Mayer, R. E. (2024). The past, present, and future of the cognitive theory of multimedia learning. Educational Psychology Review, 36, 8. https://doi.org/10.1007/s10648-023-09842-1

Miller, V., Marks, T., & Thompson, D. (2025). Student performance and perceptions in a hybrid laboratory model: An exploratory study of interactive virtual simulations and in-person integration in a foundational microbiology course. Journal of Microbiology & Biology Education. https://doi.org/10.1128/jmbe.00203-24

Mnguni, L. E. (2014). The theoretical cognitive process of visualization for science education. SpringerPlus, 3, 184. https://doi.org/10.1186/2193-1801-3-184

Nabizadeh, S., Hajian, S., Sheikhan, Z., & Khoshnood, K. (2019). Prediction of academic achievement based on learning strategies and outcome expectations among medical students. BMC Medical Education, 19, 99. https://doi.org/10.1186/s12909-019-1527-9

Navarro, C., Arias-Calderón, M., Henríquez, C. A., & Riquelme, P. (2024). Assessment of student and teacher perceptions on the use of virtual simulation in cell biology laboratory education. Education Sciences, 14(3), 243. https://doi.org/10.3390/educsci14030243

Newman, D., Spector, H., Neuenschwander, A., Miller, A., Trumpore, L., & Wright, K. (2023). Visual literacy of molecular biology revealed through a card-sorting task. Journal of Microbiology & Biology Education, 24(1). https://doi.org/10.1128/jmbe.00198-22

Nyiramukama, D. K. (2024). Virtual laboratories in science education: Benefits and challenges. Eurasian Experiment Journal of Scientific and Applied Research, 5(2), 21–25.

Paivio, A. (1986). Mental representations: A dual coding approach. Oxford University Press.

Paivio, A. (2014). Mind and its evolution: A dual coding theoretical approach. Psychology Press.

Pane, E. P., Lubis, N. F., & Simarmata, G. (2024). Application of interactive virtual lab media based on a STEM approach in improving students’ scientific literacy and learning motivation. Jurnal Penelitian Pendidikan IPA, 10(12), 10736–10744. https://doi.org/10.29303/jppipa.v10i12.8589

Ploetzner, R. (2024). Learning changes in educational animation: Visuospatial working memory is more predictive than subjective task load. Frontiers in Psychology, 15, 1389604. https://doi.org/10.3389/fpsyg.2024.1389604

Reen, F. J., Jump, O., McEvoy, G., McSharry, B. P., Morgan, J., Murphy, D., … Supple, B. (2025). Student informed development of virtual reality simulations for teaching and learning in the molecular sciences. Journal of Biological Education, 59(4), 604–620. https://doi.org/10.1080/00219266.2024.2386250

Reen, F. J., Jump, O., McEvoy, G., McSharry, B., Morgan, J., Murphy, D., O’Leary, N., O’Mahony, B., Scallan, M., Walsh, C., & Supple, B. (2022). Developing students codesigned immersive virtual reality simulations for teaching of challenging concepts in molecular and cellular biology. FEMS Letters. https://doi.org/10.1093/femsle/fnac051

Samosino, J. R. A., Bugawan, E. J. F., Amper, R. J. B., Armenton, I. C., Alicante, J. S., & Sagandilan, R. D. (2025). Students’ perception of traditional and online laboratories toward academic achievement in biology. International Journal of Research and Innovation in Applied Science, 10(7), 183–211. https://doi.org/10.51584/IJRIAS.2025.100700016

Singh-Pillay, A. (2024). Exploring science and technology teachers’ experiences with integrating simulation-based learning. Education Sciences, 14(8), 803. https://doi.org/10.3390/educsci14080803

Southard, K., Wince, T., Meddleton, S., & Bolger, M. S. (2016). Features of knowledge building in biology: Understanding undergraduate students’ ideas about molecular mechanisms. CBE—Life Sciences Education, 15, ar7. https://doi.org/10.1187/cbe.15-05-0114

Spencer, D., McKeown, C., Tredwell, D., Huckaby, B., Wiedner, A., Dums, J. T., et al. (2024). Student experiences with a molecular biotechnology course containing an interactive 3D immersive simulation and its impact on motivational beliefs. PLOS ONE, 19(7), e0306224. https://doi.org/10.1371/journal.pone.0306224

Swanson, H. L., Arizmendi, G. D., & Li, J.-T. (2024). Mathematical problem solving in emergent bilingual children: Is growth related to the navigation between two working memory systems? Journal of Educational Psychology, 116(5), 657–685. https://doi.org/10.1037/edu0000869

Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1016/0364-0213(88)90023-7

Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive load theory. Springer.

Tan, A. L., Ong, Y. S., Ng, Y. S., et al. (2023). STEM problem solving: Inquiry, concepts, and reasoning. Science & Education, 32, 381–397. https://doi.org/10.1007/s11191-021-00310-2

Tatlı, Z., & Ayas, A. (2012). Virtual chemistry laboratory: Effect of constructivist learning environment. Turkish Online Journal of Distance Education, 13(1), 183–199.

Tolentino, A., & Varela, B. (2025). Learning biology through virtual reality instructional approach: Effects on conceptual understanding, performance, and perceived usefulness. International Journal of Research and Innovation in Social Science. https://dx.doi.org/10.47772/IJRISS.2025.903SEDU0124

Uminski, C., Newman, D., & Wright, K. (2025). Probing visual literacy skills reveals unexpected student conceptions of chromosomes. CBE—Life Sciences Education, 24, ar17, 1–20.

Valeeva, R., Biktagirova, G., Lesev, V., Mikhailenko, O., Skudareva, G., & Valentovinis, A. (2023). Exploring the impact of modeling in science education: A systematic review. EURASIA Journal of Mathematics, Science and Technology Education, 19(6), em2284. https://doi.org/10.29333/ejmste/13268

Wahidin, W., Gutierrez, G., Osman, K., Akkapin, S., & Tan, M. L. T. (2025). Digital simulations in science learning: A student perspective on interactive engagement, conceptual understanding, and learning satisfaction. International Journal of Educational Qualitative Quantitative Research, 4(1). https://doi.org/10.58418/ijeqqr.v4i1.138

Zhang, F., Bae, C. L., & Broda, M. (2022). Science self-concept, relatedness, and teaching quality: A multilevel approach to examining factors that predict science achievement. International Journal of Science and Mathematics Education, 20, 503–529. https://doi.org/10.1007/s10763-021-10165-2

Zhang, K. E., & Jenkinson, J. (2024). The visual science communication toolkit: Responding to the need for visual science communication training in undergraduate life sciences education. Education Sciences, 14(3), 296. https://doi.org/10.3390/educsci14030296

Zonca, J., Del Mauro, L., Rustichini, A., Polonio, L., & Reverberi, C. (2025). Learning in interactive decision-making: The interplay between cognitive abilities and the strategic environment. Open Mind: Discoveries in Cognitive Science, 9, 210–239. https://doi.org/10.1162/opmi_a_00186