Article Sidebar

Download
Statistic
Read Counter : 13

Main Article Content

Abstract

Although self-efficacy is widely acknowledged as a crucial determinant of academic success, especially in mathematics, limited research has examined how social persuasion strategies can be systematically integrated into multimedia learning environments to enhance self-efficacy and manage cognitive load. Previous studies have largely overlooked the potential of embedding verbal persuasion within digital instructional contexts, revealing a gap in understanding how these elements interact to influence learning processes and outcomes. To address this gap, the present study investigates the impact of integrated social persuasion prompts within mathematics multimedia instruction, focusing on cognitive load, self-efficacy, and academic performance. A 2×2 factorial experimental design was employed, involving 122 undergraduate students enrolled in a multivariable calculus course. Participants were randomly assigned to four learning conditions: multimedia instruction with and without social persuasion, and non-multimedia instruction with and without social persuasion. Instructional materials on parametric equations were delivered via a Learning Management System and designed in alignment with Cognitive Load Theory. Social persuasion prompts were embedded in multimedia content through audio narration and in print materials as written feedback. The findings reveal that audio-based social persuasion integrated into multimedia learning significantly reduces cognitive load and enhances students' performance in solving mathematics problems. Moreover, this approach demonstrated stronger effects on self-efficacy and achievement compared to written persuasion in non-multimedia formats. However, the inclusion of written persuasion in printed materials was found to increase cognitive load, despite modest gains in performance. These results underscore the importance of modality in delivering self-efficacy interventions and highlight the potential of multimedia learning environments to support learners’ cognitive and motivational needs. This study contributes to the design of evidence-based instructional strategies that leverage social persuasion to foster mathematical understanding and learner confidence. It also offers practical implications for the development of multimedia resources that optimize both cognitive efficiency and motivational support in mathematics education.

Keywords

Cognitive Load Theory Mathematics Multimedia Learning Social Persuasion Learning Management Systems Self-efficacy and Performance

Article Details

License

Copyright (c) 2025 Yanuar Hery Murtianto, Endah Retnowati, Jose Hanham

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.

All articles published Open Access will be immediately and permanently free for everyone to read and download. We are continuously working with our author communities to select the best choice of license options, Creative Commons Attribution-ShareAlike (CC BY-NC-SA).

How to Cite
Murtianto, Y. H., Retnowati, E., & Hanham, J. (2025). Reducing Cognitive Load using Social Persuasion Prompts in Mathematics Multimedia Learning. Mathematics Education Journal, 19(3), 465–488. https://doi.org/10.22342/mej.v19i3.pp465-488
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX

References

  1. Bandura, A. (1997). Self-efficacy: The exercise of control. W.H. Freeman. https://archive.org/details/selfefficacyexer0000band/page/n629/mode/2up
  2. Chen, O., Chan, B. K. Y., Anderson, E., O’Sullivan, R., Jay, T., Ouwehand, K., Paas, F., & Sweller, J. (2024). The effect of element interactivity and mental rehearsal on working memory resource depletion and the spacing effect. Contemporary Educational Psychology, 77, 102281. https://doi.org/10.1016/j.cedpsych.2024.102281
  3. Chen, O., Retnowati, E., Chan, B. K. Y., & Kalyuga, S. (2023). The effect of worked examples on learning solution steps and knowledge transfer. Educational Psychology, 43(8), 914–928. https://doi.org/10.1080/01443410.2023.2273762
  4. Hsu, Y. (2020). Teaching geometrics to young learners using computer-based simulation: The interaction effect of guidance, in relation to representation and manipulation, with socio-cultural background. Interactive Learning Environments, 31(1), 282-298. https://doi.org/10.1080/10494820.2020.1777168
  5. Huang, X., & Mayer, R. E. (2016). Benefits of adding anxiety-reducing features to a computer-based multimedia lesson on statistics. Computers in Human Behavior, 63, 293–303. https://doi.org/10.1016/j.chb.2016.05.034
  6. Huang, X., Mayer, R. E., & Usher, E. L. (2020). Better together: Effects of four self efficacy building strategies on online statistical learning. Contemporary Educational Psychology, 63, 101924. https://doi.org/10.1016/j.cedpsych.2020.101924
  7. Kaewsa Ard, A. (2021). A development of instructional video for increasing learners’ motivation and content mastery in video learning environment. In International Conference on Computers in Education. https://library.apsce.net/index.php/ICCE/article/view/4281
  8. Kalyuga, S. (2007). Expertise Reversal Effect and Its Implications for Learner-Tailored Instruction. Educational Psychology Review, 19, 509–539. https://doi.org/10.1007/s10648-007-9054-3
  9. Lawson, A. P., & Mayer, R. E. (2024). Generative learning activities for online multimedia learning: When summarizing is effective but drawing is not. Frontiers in Psychology, 15. https://doi.org/10.3389/fpsyg.2024.1452385
  10. Mayer, R. E. (2014). Incorporating motivation into multimedia learning. Learning and Instruction, 29, 171–173. https://doi.org/10.1016/j.learninstruc.2013.04.003
  11. Mayer, R. E. (2019). Thirty years of research on online learning. Applied Cognitive Psychology, 33(2), 152–159. https://doi.org/10.1002/acp.3482
  12. Mayer, R. E. (2021). The Cambridge handbook of multimedia learning (3rd ed.). Cambridge University Press. https://doi.org/10.1017/9781108894333
  13. Moreno, R., & Mayer, R. E. (2000). Engaging students in active learning: The case for personalized multimedia messages. Journal of Educational Psychology, 92(4), 724–733. https://doi.org/10.1037/0022-0663.92.4.724
  14. Morris, M. (2010). Design of Experiments: An Introduction Based on Linear Models. Chapman and Hall/CRC. https://doi.org/10.1201/9781439894903
  15. Mukanova, M., Adamo, N., Mousas, C., Choi, M., Hauser, K., Mayer, R., & Zhao, F. (2024). Animated pedagogical agents performing affective gestures extracted from the GEMEP dataset: Can people recognize their emotions?. In International Conference on ArtsIT, Interactivity and Game Creation (pp. 271-280). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-55312-7_20
  16. Murtianto, Y. H., Muhtarom, M., & Herlambang, B. A. (2022). Virtual mathematics laboratory based on cognitive load theory. KnE Social Sciences, 654–660. https://doi.org/10.18502/kss.v7i14.12018
  17. Mutlu-Bayraktar, D., Cosgun, V., Altan, T. (2019). Cognitive load in multimedia learning environments: A systematic review. Computers & Education, 141. https://doi.org/10.1016/j.compedu.2019.103618
  18. Paas, F., & Sweller, J. (2014). Implications of cognitive load theory for multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (2nd ed., pp. 27–42). Cambridge University Press. https://doi.org/10.1017/CBO9781139547369.004
  19. Pajares, F. (1996). Self efficacy beliefs in academic settings. Review of Educational Research, 66(4), 543–578. https://doi.org/10.3102/00346543066004543
  20. Pajares, F. (2002). Overview of social cognitive theory and of self efficacy. Educational Psychology, 25(2), 56–63. https://people.wku.edu/richard.miller/banduratheory.pdf
  21. Pintrich, P. R. (2003). A motivational science perspective on the role of student motivation in learning and teaching contexts. Journal of Educational Psychology, 95(4), 667–686. https://doi.org/10.1037/0022-0663.95.4.667
  22. Schunk, D. H. (1991). Self efficacy and academic motivation. Educational Psychologist, 26(3), 207–231. https://doi.org/10.1080/00461520.1991.9653133
  23. Schunk, D. H., & Usher, E. L. (2012). Social cognitive theory and motivation. In R. M. Ryan (Ed.), The Oxford handbook of human motivation (pp. 13–27). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780195399820.013.0002
  24. Sweller, J., van Merriënboer, J. J. G., & Paas, F. (2019). Cognitive Architecture and Instructional Design: 20 Years Later. Educational Psychology Review, 31(2), 261–292. https://doi.org/10.1007/s10648-019-09465-5
  25. 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
  26. Sweller, 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
  27. Sweller, J. (2023). The development of cognitive load theory: Replication crises and incorporation of other theories can lead to theory expansion. Educational Psychology Review, 35(4). https://doi.org/10.1007/s10648-023-09817-2
  28. Tugtekin, U., & Odabasi, H. F. (2022). Do interactive learning environments have an effect on learning outcomes, cognitive load and metacognitive judgments? Education and Information Technologies, 27(5), 7019–7058. https://doi.org/10.1007/s10639-022-10912-0
  29. van Merriënboer, J.J.G., Sweller, J. (2005). Cognitive Load Theory and Complex Learning: Recent Developments and Future Directions. Educational Psychology Review, 17, 147–177. https://doi.org/10.1007/s10648-005-3951-0
  30. Wang, C., Fang, T., & Gu, Y. (2020). Learning performance and behavioral patterns of online collaborative learning: Impact of cognitive load and affordances of different multimedia. Computers & Education, 143, 103683. https://doi.org/10.1016/j.compedu. 2019.103683
  31. Zimmerman, B. J. (2000). Attaining self regulated learning: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self regulation (pp. 13–39). Academic Press. https://doi.org/10.1016/B978-012109890-2/50031-7
  32. Zimmerman, B. J. (1990). Self regulated learning and academic achievement: An overview. Educational Psychologist, 25(1), 3–17. https://doi.org/10.1207/s15326985ep2501_2

Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.