Main Article Content


This paper explored the teaching experiences of physics teachers in integrating computer simulations in their pedagogy to promote a constructivist learning environment. Its objectives are to determine how physics teachers describe computer simulations based on how they are used, how these are embedded in the teaching-learning process, their impact on the teaching-learning process, and the challenges of integrating these into physics teaching. Using the phenomenological design, two themes emerged for the first objectives, which are process-based and system-based. First, the teacher-manipulated with sub-themes of engaging, demonstrating, elaborating, and evaluating, and student-manipulated emerged on how the simulations are used. Second, the impact to teaching generated knowledge-based, skill-based, and value-based learning-based primarily on the three learning domains. Also, respondents emphasized that the integrations of computer simulations are convenience, efficacy, and heterogeneity. Finally, the challenges in the integration process are classified as teacher and school-related.  The results showed that teachers are integrating computer simulations differently depending on their resources and the TPACK knowledge.


Computer simulation Secondary physics

Article Details

How to Cite
Abiasen, J., & Reyes, G. (2021). Computer Simulation Integration in Secondary Physics: Understanding its Nature, Impacts, and Challenges. International Journal of Asian Education, 2(4), 480–492.


  1. Adams, W. K., Reid, S., Lemaster, R., McKagan, S. B., Perkins, K. K., Dubson, M., & Wieman, C. E. (2008). A study of educational simulations: Part 1 - Engagement and learning. Journal of Interactive Learning Research, 19(3), 397–419
  2. Altun, S., & Yücel-Toy, B. (2015). The methods of teaching course based on constructivist learning approach: An action research. Journal of Education and Training Studies, 3(6).
  3. Ayasun, S., & Karbeyaz, G. (2007). DC motor speed control methods using MATLAB/Simulink and their integration into undergraduate electric machinery courses. Computer Applications in Engineering Education, 15(4), 347-354.
  4. Baltzis, K. B., & Koukias, K. D. (2009). Using laboratory experiments and circuit simulation IT tools in an undergraduate course in analog electronics. Journal of Science Education and Technology, 18(6), 546-555.
  5. Bell, R. L., & Trundle, K. C. (2008). The use of a computer simulation to promote scientific conceptions of moon phases. Journal of Research in Science Teaching, 45(3), 346-372.
  6. Boopathiraj, C., & Chellamani, K. (2015). Pre-Service Post Graduate Teachers’ First Time Experience with Constructivist Learning Environment (CLE) Using MOODLE. Journal on School Educational Technology, 10(4), 23-27.
  7. Chang, K., Chen, Y., Lin, H., & Sung, Y. (2008). Effects of learning support in simulation-based physics learning. Computers & Education, 51(4), 1486-1498.
  8. Clark, D., & Jorde, D. (2003). Helping students revise disruptive experientially supported ideas about thermodynamics: Computer visualizations and tactile models. Journal of Research in Science Teaching, 41(1), 1-23.
  9. Creswell, J. W. (2008). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. Prentice Hall.
  10. Dalgarno, B., Bishop, A. G., Adlong, W., & Bedgood, D. R. (2009). Effectiveness of a virtual laboratory as a preparatory resource for distance education chemistry students. Computers & Education, 53(3), 853-865.
  11. Department of Education. (2019). PISA 2018 National Report of the Philippines.
  12. De Jong, T., & Van Joolingen, W. R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research, 68(2), 179-201.
  13. De Jong, T. D. (2011). Instruction based on computer simulations. Handbook of Research on Learning and Instruction.
  14. De Jong, T., Linn, M. C., & Zacharia, Z. C. (2013). Physical and virtual laboratories in science and engineering education. Science, 340(6130), 305-308.
  15. Dudduan, C., Nirat, & Sumalee, C. (2015). Development of learning management model based on constructivist theory and reasoning strategies for enhancing the critical thinking of secondary students. Educational Research and Reviews, 10(16), 2324-2330.
  16. Durán, M. J., Gallardo, S., Toral, S. L., Martínez-Torres, R., & Barrero, F. J. (2007). A learning methodology using Matlab/Simulink for undergraduate electrical engineering courses attending to learner satisfaction outcomes. International Journal of Technology and Design Education, 17(1), 55-73.
  17. D’Angelo, C., Rutstein, D., Harris, C., Bernard, R., Borokhovski, E., & Haertel, G. (2014). Simulations for STEM learning: Systematic review and meta-analysis. Menlo Park: SRI International.
  18. Garard, D. L., Lippert, L., Hunt, S. K., & Paynton, S. T. (1998). Alternatives to traditional instruction: Using games and simulations to increase student learning and motivation. Communication Research Reports, 15(1), 36-44.
  19. Hennessy, S., Wishart, J., Whitelock, D., Deaney, R., Brawn, R., Velle, L. L., McFarlane, A., Ruthven, K., & Winterbottom, M. (2007). Pedagogical approaches for technology-integrated science teaching. Computers & Education, 48(1), 137-152.
  20. Kranjc, T. (2011). Simulations as a complement and a motivation element in the teaching of physics. Metodički obzori/Methodological Horizons, 6(2), 175-187.
  21. Limniou, M., Papadopoulos, N., Giannakoudakis, A., Roberts, D., & Otto, O. (2007). The integration of a viscosity simulator in a chemistry laboratory. Chem. Educ. Res. Pract, 8(2), 220-231.
  22. Marshall, C., & Rossman, G. B. (2006). Designing qualitative research. SAGE.
  23. Merriam, S. B., & Tisdell, E. J. (2015). Qualitative research: A guide to design and implementation. John Wiley & Sons
  24. Mihindo, W. J., Wachanga, S. W., & Anditi, Z. O. (2017). Effects of Computer-Based 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.
  25. Mitnik, R., Recabarren, M., Nussbaum, M., & Soto, A. (2009). Collaborative robotic instruction: A graph teaching experience. Computers & Education, 53(2), 330-342.
  26. Ocampo, C. A., de Mesa, D. M. B., Ole, A. F., Auditor, E., Morales, M. P. E., Sia, S. R. D., & Palomar, B. C. (2015). Development and evaluation of physics microlab (P6-μLab) kit. The Normal Lights, 9(1).
  27. Oon, P., & Subramaniam, R. (2010). On the declining interest in physics among students—From the perspective of teachers. International Journal of Science Education, 33(5), 727-746.
  28. Orb, A., Eisenhauer, L., & Wynaden, D. (2001). Ethics in qualitative research. Journal of Nursing Scholarship, 33(1), 93-96.
  29. Orleans, A. V. (2007). The condition of secondary school physics education in the Philippines: Recent developments and remaining challenges for substantive improvements. The Australian Educational Researcher, 34(1), 33-54.
  30. Osborne, J., & Hennessy, S. (2003). Literature review in science education and the role of ICT: Promise, problems and future directions. Futurelab.
  31. Pecay, R. K. (2017). YouTube integration in science classes: Understanding its roots, ways, and selection criteria. The Qualitative Report.
  32. Ploetzner, R., Lippitsch, S., Galmbacher, M., Heuer, D., & Scherrer, S. (2009). Students’ difficulties in learning from dynamic visualisations and how they may be overcome. Computers in Human Behavior, 25(1), 56-65.
  33. Rutten, N., Van Joolingen, W. R., & Van der Veen, J. T. (2012). The learning effects of computer simulations in science education. Computers & Education, 58(1), 136-153.
  34. Saab, N., Van Joolingen, W. R., & Van Hout-Wolters, B. H. (2006). Supporting communication in a collaborative discovery learning environment: The effect of instruction. Instructional Science, 35(1), 73-98.
  35. Sahin, S. (2006). Computer simulations in science education: Implications for Distance Education. Turkish Online Journal of Distance Education 7(4).
  36. Salameh Al-Rsa’i, M. (2013). Promoting scientific literacy by using ICT in science teaching. International Education Studies, 6(9).
  37. Sarabando, C., Cravino, J. P., & Soares, A. A. (2014). Contribution of a computer simulation to students’ learning of the physics concepts of weight and mass. Procedia Technology, 13, 112-121.
  38. SEI-DOST, & UP NISMED. (2011). Science framework for Philippine basic education. Manila: SEI-DOST & UP NISMED.
  39. Shieh, R. S., Chang, W., & Tang, J. (2010). The impact of implementing technology-enabled active learning (TEAL) in university physics in Taiwan. The Asia-Pacific Education Researcher, 19(3).
  40. Smetana, L. K., & Bell, R. L. (2012). Computer simulations to support science instruction and learning: A critical review of the literature. International Journal of Science Education, 34(9), 1337-1370.
  41. Stern, L., Barnea, N., & Shauli, S. (2008). The effect of a computerized simulation on middle school students’ understanding of the kinetic molecular theory. Journal of Science Education and Technology, 17(4), 305-315.
  42. Van Manen, M. (2017). Phenomenology in its original sense. Qualitative Health Research, 27(6), 810-825.
  43. Veermans, K., Joolingen, W. V., & De Jong, T. (2006). Use of heuristics to facilitate scientific discovery learning in a simulation learning environment in a physics domain. International Journal of Science Education, 28(4), 341-361.
  44. White, B., Kahriman, A., Luberice, L., & Idleh, F. (2010). Evaluation of software for introducing protein structure. Biochemistry and Molecular Biology Education, 38(5), 284-289.
  45. Winberg, T. M., & Berg, C. A. (2007). Students’ cognitive focus during a chemistry laboratory exercise: Effects of a computer-simulated prelab. Journal of Research in Science Teaching, 44(8), 1108-1133.
  46. World Economic Forum. (2019). The global competitiveness report 2017-2018.
  47. Wu, H., & Huang, Y. (2007). Ninth-grade student engagement in teacher-centered and student-centered technology-enhanced learning environments. Science Education, 91(5), 727-749.
  48. Yüksel, P., & Yıldırım, S. (2015). Theoretical frameworks, methods, and procedures for conducting phenomenological studies. Turkish Online Journal of Qualitative Inquiry, 6(1).
  49. Zacharia, Z. (2007). Comparing and combining real and virtual experimentation: An effort to enhance students’ conceptual understanding of electric circuits. Journal of Computer Assisted Learning, 23(2), 120-132.
  50. Zhang, J., Chen, Q., Sun, Y., & Reid, D. J. (2004). Triple scheme of learning support design for scientific discovery learning based on computer simulation: Experimental research. Journal of Computer Assisted Learning, 20(4), 269-282.