The Effectiveness of Gamification-Based Microlearning on Cognitive Load in Histology Education Among Biology Students: A Quasi-Experimental Study

Document Type : Original Article

Authors

1 Department of Educational Studies and Curriculum Planning, Ar.C, Islamic Azad University, Arak, Iran

2 Department of Education, Faculty of Humanities, Arak University, Arak, Iran

3 Department of Biology, Faculty of Sciences, Arak University, Arak, Iran

Abstract

Background: While gamification is increasingly used in higher education, its impact on the specific dimensions of cognitive load particularly in complex subjects like histology remains underexplored. This study aimed to investigate the effect of gamification-based microlearning on students’ overall cognitive load in histology, with a specific interest in its potential differential impact on extraneous and germane cognitive load.
Methods: This quasi-experimental study employed a pretest-posttest design with a control group. The sample consisted of 27 undergraduate biology students from Arak University, enrolled between January and June 2024, who were randomly allocated to either an experimental group (n = 14) or a control group (n = 13). Participants in the experimental group were taught histology using a specially developed gamified microlearning application over a 14-week period, whereas the control group received conventional lecture-based instruction. Cognitive load was assessed using the Paas Cognitive Load Scale, and the primary outcome was evaluated through a change score analysis. All statistical analyses were performed using IBM SPSS Statistics, version 23.
Results: Analysis of change scores indicated a substantial difference between groups. The experimental group demonstrated a significant decrease in cognitive load (Mean = −7.71, SD = 2.76), while the control group experienced a modest increase over time (Mean = 2.31, SD = 5.11). An independent-samples t-test indicated that the difference in change scores between the two groups was statistically significant (p < 0.001). Furthermore, the effect size was exceptionally large (Cohen’s d = 2.47).
Conclusion: Gamified microlearning appears to be an effective instructional approach for reducing cognitive load in complex scientific subjects. The results indicate that this integrated method may enhance the efficient use of cognitive resources. Future studies should include larger sample sizes, distinguish among different types of cognitive load, and investigate long-term outcomes as well as applicability across various disciplines.

Highlights

Parisa Maleki (Google Scholar)

Mozhgan Mohammadi Naeeni (Google Scholar)

Keywords

References

  1. Kasnauskiene G, Badaras R, Pauliene R, Thrassou A. Economic effectiveness of investment in higher education: an evaluation at the individual and national levels. EuroMed J Bus. 2025;20(4):1183–98. doi: 10.1108/EMJB-12-2023-0334.
  2. Alipour A. value Innovative university, moving towards the generation of academic soft technologies. Iranian Pattern of Progress, 2022;10(2):e152042. [In Persian]
  3. Mohiuddin K, Nasr OA, Nadhmi Miladi M, Fatima H, Shahwar S, Noorulhasan Naveed Q. Potentialities and priorities for higher educational development in Saudi Arabia for the next decade: Critical reflections of the vision 2030 framework. Heliyon. 2023;9(5):e16368. doi: 10.1016/j.heliyon.2023.e16368. PubMed PMID: 37251831; PubMed Central PMCID: PMC10220240.
  4. Parvazi Moghaddam Z, FathiVajargah K, Pooshne K, Khosravi Babadi A. Studying the curriculum, proportional to the characteristics of Generationz in the Generation Z in Tehran’s high schools. Theory Pract Curric. 2023;11(21):391–452. doi: 10.22034/tpcj.2023.190249. [In Persian]
  5. Antopolskaya TA, Logvinova MI, Silakov AS, Panov VI. Adolescents of Generation Z: the development of personal agency in the environment of additional education. Eur J Contemp Educ. 2022;11(3):686–95. doi: 10.13187/ejced.2022.3.686.
  6. Hug T. Didactics of Microlearning: Concepts, Discourses and Examples. Münster: Waxmann Verlag; 2007. doi: 10.1515/9783110795252.
  7. Sweller J. Cognitive load theory and educational technology. Educ Technol Res Dev. 2020;68(1):1–16. doi: 10.1007/s11423-019-09701-3.
  8. Sweller J. Cognitive Load During Problem Solving: Effects on Learning. Cogn Sci. 1988;12(2):257–85. doi: 10.1207/s15516709cog1202_4.
  9. Sweller J, Van Merriënboer JJG, Paas F. Cognitive Architecture and Instructional Design: 20 Years Later. Educ Psychol Rev. 2019;31:261–92. doi: 10.1007/s10648-019-09465-5.
  10. Gabrielova K, Buchko AA. Here comes Generation Z: Millennials as managers. Bus Horiz. 2021;64(4):489–99. doi: 10.1016/j.bushor.2021.02.013.
  11. Seemiller C, Grace M. Generation Z: Educating and engaging the next generation of students. About Campus. 2017;22(3):21–6. doi: 10.1002/abc.21293.
  12. Haeri A. Comparative Study of Traditional and Microlearning Methods in Teaching Drug-Loaded Nanoliposomes to Pharmacy Students. Res Med Educ. 2024;16(1):46–55. doi: 10.32592/rmegums.16.1.46. [In Persian]
  13. Senandheera VV, Muthukumarana CK, Ediriweera DS, Rupasinghe TP. Impact of Microlearning on Academic Performance of Students in Higher Education: A Systematic Review and Meta-Analysis. J Multidiscip Transl Res. 2024;9(1). doi: 10.4038/jmtr.v9i1.2.
  14. Fitria TN. Microlearning in teaching and learning process: A review. CENDEKIA J Ilmu Sos Bhs Dan Pendidik. 2022;2(4):114–35. doi: 10.55606/cendikia.v2i4.473.
  15. Deterding S, Dixon D, Khaled R, Nacke L. From Game design Elements to Gamefulness: Defining" Gamification". In: Proceedings of the 15th international academic MindTrek conference: Envisioning future media environments. 2011 Sep 28-30; Tampere, Finland. NY, United States: Association for Computing Machinery; 2011. doi: 10.1145/2181037.2181040.
  16. Sailer M, Hense JU, Mayr SK, Mandl H. How gamification motivates: An experimental study of the effects of specific game design elements on psychological need satisfaction. Comput Human Behav. 2017;69:371–80. doi: 10.1016/j.chb.2016.12.033.
  17. Baniamerian S, Esmaeeli Gojar S. The role of gamification in learning. Educ Psychol. 2021;17(62):107–30. doi: 10.22054/jep.2022.58370.3266. [In Perian]
  18. Ertan K, Kocadere SA. Gamification design to increase motivation in online learning environments: A systematic review. J Learn Teach Digit Age. 2022;7(2):151–9. doi: 10.53850/joltida.1020044.
  19. Ebrahimipur A, Bagheri M. The Effect of Gamifying Virtual Classes on Academic Motivation and Academic Performance of Students. JNTE. 2024;20(1):7–20. doi: 10.22051/jontoe.2022.38773.3567. [In Persian]
  20. Moazen S, Edalatkhah M. The Effect of Gamification on Education Engagement of Architecture Students (Case study: Materials and Construction atelier in Iran University of Science and Technology. New Educational Approaches. 2022;17(1):37–58. doi: 10.22108/nea.2022.130300.1674. [In Persian]
  21. Li M, Ma S and Shi Y. Examining the Effectiveness of Gamification as a Tool Promoting Teaching and Learning in Educational Settings: A Meta-analysis. Front Psychol. 2023;14:1253549. doi: 10.3389/fpsyg.2023.1253549.
  22. Samadi A. Challenges in Biology Education and the Role of Creativity in Increasing its Learning. Research in Biology Education. 2019;1(1):15–30. [In Persian]
  23. Khaldi A, Bouzidi R, Nader F. Gamification of e-learning in higher education: a systematic literature review. Smart Learn Environ. 2023;10(1):10. doi: 10.1186/s40561-023-00227-z. PubMed PMID: 40478066; PubMed Central PMCID: PMC9887250.
  24. Paas FGWC. Training strategies for attaining transfer of problem-solving skill in statistics: a cognitive-load approach. J Educ Psychol. 1992;84(4):429-34. doi: 10.1037/0022-0663.84.4.429.
  25. Ahadi F, Soleimani M. Comparing the Effect of Two Teaching Methods: Presenting a Complete Solved Educational Example and Presenting an Incompletely Solved Example on Students' Cognitive Load in a Medical Language Course. IJME. 2014;14(4): 291-302. [In Persian]
  26. Leppink J, Paas F, Van der Vleuten CP, Van Gog T, Van Merriënboer JJ. Development of an Instrument for Measuring Different Types of Cognitive Load. Behav Res Methods. 2013;45(4):1058-72. doi: 10.3758/s13428-013-0334-1. PubMed PMID: 23572251.
  27. Korbach A, Brünken R, Park B. Measurement of cognitive load in multimedia learning: a comparison of different objective measures. Instr Sci. 2017;45(4):515–36. doi: 10.1007/s11251-017-9413-5.
  28. Mohammadi M, Allah Marzooghi R, Salimi G, Mansoori S. Learners’ Experiences of Mobile Learning in Vocational and Technical Education Courses. Interdiscip J Virtual LearnMed Sci. 2017;8(4):e64424. doi: 10.5812/ijvlms.64424.
  29. Koster R. A Theory of Fun for Game Design. Scottsdale (AZ): Paraglyph Press; 2004.
  30. Nikou SA, Economides AA. Mobile‐Based micro‐Learning and Assessment: Impact on learning performance and motivation of high school students. J Comput Assist Learn. 2018;34(3):269–78. doi: 10.1111/jcal.12240.
  31. Van Merriënboer JJG, Sweller J. Cognitive load theory in health professional education: design principles and strategies. Medical Education. 2010;44(1):85–93. doi: 10.1111/j.1365-2923.2009.03498.x.
  32. Plass JL, Homer BD, Kinzer CK. Foundations of game-based learning. Educ Psychol. 2015;50(4):258–83. doi: 10.1080/00461520.2015.1122533.
  33. Sweller J. Element Interactivity and Intrinsic, Extraneous, and Germane Cognitive Load. Educ Psychol Rev. 2010;22:123–38. doi: 10.1007/s10648-010-9128-5.
  34. Sweller J, van Merriënboer JJG, Paas FGWC. Cognitive Architecture and Instructional Design. Educ Psychol Rev. 1998;10(3):251–96. doi:10.1023/A:1022193728205.
  35. Hattie J , Timperley H. The power of feedback. Review of Educational Research, 2007;77(1):81–112. doi: 10.3102/003465430298487.
  36. Ahmadpour Kasgari Z, Abedini Baltork M, Mansoori S. Efficacy of Electronic Versus Traditional Type of Metalinguistic Feedback in Correct Use of Prepositions: An Experimental Study. Interdiscip J Virtual Learn Med Sci. 2018;9(4):e69552. doi: 10.5812/ijvlms.69552.
  37. Fredrickson BL. The role of positive emotions in positive psychology. The broaden-and-build theory of positive emotions. Am Psychol. 2001;56(3):218-26. doi: 10.1037//0003-066x.56.3.218. PubMed PMID: 11315248; PubMed Central PMCID: PMC3122271.
  38. Yıldız MŞ, Yaman Y. Math education for gifted individuals: Digital gamification. J Learn Teach Digit Age. 2024;9(1):40–9. doi: 10.53850/joltida.1255991.
  39. Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am Psychol. 2000;55(1):68-78. doi: 10.1037//0003-066x.55.1.68. PubMed PMID: 11392867.
  40. Csikszentmihalyi M. Flow: The psychology of Optimal Experience. NY, USA: Harper & Row; 1990.
  41. Deci EL, Koestner R, Ryan RM. A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation. Psychol Bull. 1999;125(6):627-68; discussion 692-700. doi: 10.1037/0033-2909.125.6.627. PubMed PMID: 10589297.
  42. Kapp KM. The gamification of learning and instruction: game-based methods and strategies for training and education. New Jersey; USA: John Wiley & Sons; 2012. doi: 10.1145/2207270.2211316.
  43. Sailer M, Homner L. The Gamification of Learning: A Meta-Analysis. Educ Psychol Rev. 2020;32(1):77–112. doi:10.1007/s10648-019-09498-w.

Files

History

  • Receive Date: 14 December 2025
  • Revise Date: 11 February 2026
  • Accept Date: 16 February 2026
  • Publish Date: 01 March 2026

Share

How to cite

Statistics