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Sonja Holmer, Daniel Zander, Joel Waye, Kaspian Jakobsson
pp.  … – …, download
(https://doi.org/10.55612/s-5002-063-002)

Abstract

The use of virtual learning environments is increasing, and it raises the question of how the environments are designed to benefit learning outcomes. The Cognitive Load Theory is a well-established framework for instructional design of learning environments, and introduces different design principles, based on a working memory model. This paper describes how these principles can be used in the design of a virtual physics lab environment, and its possible implications for learning processes related to cognitive load. Future research using the software may yield further insight in the applicability of these design principles in Virtual Reality.

Keywords: virtual reality, educational technology, physics education, cognitive load theory.

References

1. Chernikova O., Heitzmann N., Stadler M., Holzberger D., Seidel T., Fischer F.: Simulation-based learning in higher education: a meta-analysis, Review of Educational Research, 90(4), pp 499–541 (2020)
https://doi.org/10.3102/0034654320933544
2. Hamilton D., McKechnie J., Edgerton E. et al.: Immersive virtual reality as a pedagogical tool in education: a systematic literature review of quantitative learning outcomes and experimental design, J. Comput. Educ. 8, pp 1-32 (2021) https://doi.org/10.1007/s40692-020-00169-2
3. Maresky H. S., Oikonomou A., Ali I., Ditkofsky N., Pakkal M., Ballyk B.: Virtual reality and cardiac anatomy: Exploring immersive three-dimensional cardiac imaging, a pilot study in undergraduate medical anatomy education. Clinical Anatomy, 32, pp 238–243 (2019)
https://doi.org/10.1002/ca.23292
4. Sweller J.: Cognitive load during problem solving: effects on learning. Cognitive Science, 12, pp 275–285 (1988) https://doi.org/10.1016/0364-0213(88)90023-7
5. Paas F., Renkl A., Sweller J.: Cognitive Load Theory: Instructional Implications of the Interaction between Information Structures and Cognitive Architecture, Instructional Science, 32(1/2), pp 1–8 (2004)
https://doi.org/10.1023/B:TRUC.0000021806.17516.d0
6. Edda Knowledge, www.eddaknowledge.com. (2024)
7. Sweller J., Ayres P., Kalyuga S.: Intrinsic and extraneous cognitive load. In J. Sweller, P. Ayres, S. Kalyuga (Eds.), Cognitive load theory, pp 57–69. Basel: Springer. (2011)

https://doi.org/10.1007/978-1-4419-8126-4_5
8. Sweller J., van Merriënboer J., Paas F.: Cognitive architecture and instructional design: 20 years later. Educational Psychology Review, 31, pp 261-292 (2019) https://doi.org/10.1007/s10648-019-09465-5
9. Baddeley A.D.: Working Memory, Clarendon Press (1986)
10. Sweller J, Sweller S.: Natural information processing systems. Evolutionary Psychology, 4, pp 434–458 (2006) https://doi.org/10.1177/147470490600400135
11. Miller G. A.: The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, pp 81–97 (1956) https://doi.org/10.1037/h0043158
12. Peterson L., Peterson M. J.: Short-term retention of individual verbal items. Journal of Experimental Psychology, 58, pp 193–198 (1959) https://doi.org/10.1037/h0049234
13. Sweller J.: Cognitive load theory and educational technology. Education Tech Research Dev 68, pp 1-16 (2020) https://doi.org/10.1007/s11423-019-09701-3
14. Kirschner P., Sweller J., Clark R.: Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential and inquiry-based teaching, Educational Psychologist, 41, pp 75-86. (2006) https://doi.org/10.1207/s15326985ep4102_1
15. Albus, P., Seufert, T.: The modality effect reverses in a virtual reality learning environment and influences cognitive load, Instructional Science 51, pp 545–570 (2023) https://doi.org/10.1007/s11251-022-09611-7
16. Chen O., Castro-Alonso J. C., Paas F., Sweller J.: Extending Cognitive Load Theory to Incorporate Working Memory Resource Depletion: Evidence from the Spacing Effect. Educ Psychol Rev, 30(2), pp 483–501 (2018) https://doi.org/10.1007/s10648-017-9426-2
17. Lee J. Y., Donkers J., Jarodzka H., Sellenraad G., van Merriënboer J. J. G.: Different effects of pausing on cognitive load in a medical simulation game. Computers in Human Behavior, 110 (2020)
https://doi.org/10.1016/j.chb.2020.106385
18. Molland, A. F.: Chapter 3: Flotation and stability, The Maritime Engineering Reference Book, Butterworth-Heinemann, pp 75–115 (2008) https://doi.org/10.1016/B978-0-7506-8987-8.00003-2
19. Zander D., Holmer S., Lundell J., Waye J., Jakobsson K.: Arkimedes övertygelse: Inlärning och övertygelse av verkliga fenomen i virtuella lärmiljöer. In B. Johansson, A. Gulz, M. Haake, M. Wallergård, J. Nirme, E. Ternblad, B. Tärning (Eds), Intelligent, socially oriented technology VI: Projects by teams of master level students in cognitive science and engineering, pp 115-127 (2023)
20. Unity Technologies. Unity. https://unity.com/ (2022)
21. Kullberg, A., Runesson Kempe, U. Marton, F.: What is made possible to learn when using the variation theory of learning in teaching mathematics?, ZDM, 49(4), pp 559–569 (2017) https://doi.org/10.1007/s11858-017-0858-4
22. Åkerlind, G.: From phenomenography to variation theory: A review of the development of the variation theory of learning and implications for pedagogical design in higher education, HERDSA Review of Higher Education, 2, pp 5–26 (2015)
23. Hutchins E.: Cognition in the wild. Cambridge, Mass.: MIT Press, (1995) https://doi.org/10.7551/mitpress/1881.001.0001

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