Studying the effect of redundancy in a virtual reality classroom

Abstract

Redundancy effect has been investigated in many controlled experimental studies, however, it is seldom investigated whether the same redundant material may cause different results in classroom, which is a major learning place for students. Considering that it is not easy to control the internal validity in classroom environment, this study proposed a new research approach with the use of virtual reality (VR) classroom as the experimental platform to investigate this issue. In the current study, one hundred and four fifth-grade students were randomly assigned to four experimental conditions with two different presentation formats (redundant and non-redundant) and two learning environments (lab and VR classroom). The retention test scores, cognitive load, and performance efficiency were used as dependent variables. The results revealed that the redundancy effect occurred in the lab environment and the reverse redundancy effect occurred in the VR classroom environment. In the lab environment, participants who had learned with non-redundant materials demonstrated better learning performance than those who had learned with redundant materials. On the contrary, the results were reversed in the VR classroom environment. The programmed interferences in the VR classroom are suggested as the main factor influencing the results.

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References

  1. Adesope, O. O., & Nesbit, J. C. (2012). Verbal redundancy in multimedia learning environments: A meta-analysis. Journal of Educational Psychology, 104(1), 250–263. https://doi.org/10.1037/a0026147.

    Article  Google Scholar 

  2. Antonenko, P. D., & Keil, A. (2017). Assessing working memory dynamics with electroencephalography. In R. Z. Zheng (Ed.), Cognitive load measurement and application: A theoretical framework for meaningful research and practice. (pp. 93–111). Routledge.

    Google Scholar 

  3. Baker, J. P., Goodboy, A. K., Bowman, N. D., & Wright, A. A. (2018). Does teaching with PowerPoint increase students’ learning? A meta-analysis. Computers & Education, 126, 376–387. https://doi.org/10.1016/j.compedu.2018.08.003.

    Article  Google Scholar 

  4. Blume, F., Göllner, R., Moeller, K., Dresler, T., Ehlis, A. C., & Gawrilow, C. (2019). Do students learn better when seated close to the teacher? A virtual classroom study considering individual levels of inattention and hyperactivity-impulsivity. Learning and Instruction, 61, 138–147. https://doi.org/10.1016/j.learninstruc.2018.10.004.

    Article  Google Scholar 

  5. Chan, K. Y., Lyons, C., Kon, L. L., Stine, K., Manley, M., & Crossley, A. (2020). Effect of on-screen text on multimedia learning with native and foreign-accented narration. Learning and Instruction, 67, 101305. https://doi.org/10.1016/j.learninstruc.2020.101305.

    Article  Google Scholar 

  6. Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8(4), 293–332. https://doi.org/10.1207/s1532690xci0804_2.

    Article  Google Scholar 

  7. Coleman, B., Marion, S., Rizzo, A., Turnbull, J., & Nolty, A. (2019). Virtual reality assessment of classroom-related attention: An ecologically relevant approach to evaluating the effectiveness of working memory training. Frontiers in Psychology, 10, 1851. https://doi.org/10.3389/fpsyg.2019.01851.

    Article  Google Scholar 

  8. de Koning, B. B., van Hooijdonk, C. M., & Lagerwerf, L. (2017). Verbal redundancy in a procedural animation: On-screen labels improve comprehension and calculation but not behavioral performance. Computers & Education, 107, 45–53. https://doi.org/10.1016/j.compedu.2016.12.013.

    Article  Google Scholar 

  9. Díaz-Orueta, U., Garcia-López, C., Crespo-Eguílaz, N., Sánchez-Carpintero, R., Climent, G., & Narbona, J. (2014). AULA virtual reality test as an attention measure: Convergent validity with Conners’ Continuous Performance Test. Child Neuropsychology, 20(3), 328–342. https://doi.org/10.1080/09297049.2013.792332.

    Article  Google Scholar 

  10. Dockrell, J. E., & Shield, B. M. (2006). Acoustical barriers in classrooms: The impact of noise on performance in the classroom. British Educational Research Journal, 32(3), 509–525. https://doi.org/10.1080/01411920600635494.

    Article  Google Scholar 

  11. Dousay, T. A. (2016). Effects of redundancy and modality on the situational interest of adult learners in multimedia learning. Educational Technology Research and Development, 64, 1251–1271. https://doi.org/10.1007/s11423-016-9456-3.

    Article  Google Scholar 

  12. Florax, M., & Ploetzner, R. (2010). What contributes to the split-attention effect? The role of text segmentation, picture labelling, and spatial proximity. Learning and Instruction, 20(3), 216–224. https://doi.org/10.1016/j.learninstruc.2009.02.021.

    Article  Google Scholar 

  13. Gillath, O., McCall, C., Shaver, P. R., & Blascovich, J. (2008). What can virtual reality teach us about prosocial tendencies in real and virtual environments? Media Psychology, 11(2), 259–282. https://doi.org/10.1080/15213260801906489.

    Article  Google Scholar 

  14. Huang, Y., Richter, E., Kleickmann, T., Wiepke, A., & Richter, D. (2020). Classroom complexity affects student teachers’ behavior in a VR classroom. Computers & Education, 163, 104100. https://doi.org/10.1016/j.compedu.2020.104100.

    Article  Google Scholar 

  15. Kalyuga, S. (2009). Managing cognitive load in adaptive multimedia learning. . Information Science Reference.

    Book  Google Scholar 

  16. Kalyuga, S., Chandler, P., & Sweller, J. (1999). Managing split-attention and redundancy in multimedia instruction. Applied Cognitive Psychology, 13(4), 351–371.

    Article  Google Scholar 

  17. Ke, F., Lee, S., & Xu, X. (2016). Teaching training in a mixed-reality integrated learning environment. Computers in Human Behavior, 62, 212–220. https://doi.org/10.1016/j.chb.2016.03.094.

    Article  Google Scholar 

  18. Klepsch, M., & Seufert, T. (2020). Understanding instructional design effects by differentiated measurement of intrinsic, extraneous, and germane cognitive load. Instructional Science, 48, 45–77. https://doi.org/10.1007/s11251-020-09502-9.

    Article  Google Scholar 

  19. Lamb, R., & Etopio, E. A. (2020). Virtual reality: A tool for preservice science teachers to put theory into practice. Journal of Science Education and Technology, 29, 573–585. https://doi.org/10.1007/s10956-020-09837-5.

    Article  Google Scholar 

  20. Leahy, W., Chandler, P., & Sweller, J. (2003). When auditory presentations should and should not be a component of multimedia instruction. Applied Cognitive Psychology, 17(4), 401–418. https://doi.org/10.1002/acp.877.

    Article  Google Scholar 

  21. Leahy, W., & Sweller, J. (2011). Cognitive load theory, modality of presentation and the transient information effect. Applied Cognitive Psychology, 25(6), 943–951. https://doi.org/10.1002/acp.1787.

    Article  Google Scholar 

  22. Leppink, J., Paas, F., Van der Vleuten, C. P., Van Gog, T., & Van Merriënboer, J. J. (2013). Development of an instrument for measuring different types of cognitive load. Behavior Research Methods, 45, 1058–1072. https://doi.org/10.3758/s13428-013-0334-1.

    Article  Google Scholar 

  23. Liu, T.-C., Lin, Y.-C., Gao, Y., Yeh, S.-C., & Kalyuga, S. (2015). Does the redundancy effect exist in electronic slideshow assisted lecturing? Computers & Education, 88, 303–314. https://doi.org/10.1016/j.compedu.2015.04.014.

    Article  Google Scholar 

  24. Liu, T.-C., Lin, Y.-C., & Kuo, Y.-C. (2020). Using arrow-lines to integrate pictorial and textual information in electronic slideshow assisted lecturing. In S. Tindall-Ford, S. Agostinho, & J. Sweller (Eds.), Advances in cognitive load theory: Rethinking teaching. (pp. 55–65). Routledge.

    Google Scholar 

  25. Mayer, R. E. (2014). The Cambridge handbook of multimedia learning. Cambridge University Press.

    Book  Google Scholar 

  26. Mayer, R. E. (2017). Using multimedia for e-learning. Journal of Computer Assisted Learning, 33(5), 403–423. https://doi.org/10.1111/jcal.12197.

    Article  Google Scholar 

  27. Mayer, R. E., Heiser, J., & Lonn, S. (2001). Cognitive constraints on multimedia learning: When presenting more material results in less understanding. Journal of Educational Psychology, 93(1), 187–198. https://doi.org/10.1037/0022-0663.93.1.187.

    Article  Google Scholar 

  28. Mayer, R. E., Howarth, J. T., Kaplan, M., & Hanna, S. (2018). Applying the segmenting principle to online geography slideshow lessons. Educational Technology Research and Development, 66(3), 563–577. https://doi.org/10.1007/s11423-017-9554-x.

    Article  Google Scholar 

  29. Mayer, R. E., & Johnson, C. I. (2008). Revising the redundancy principle in multimedia learning. Journal of Educational Psychology, 100(2), 380–386. https://doi.org/10.1037/0022-0663.100.2.380.

    Article  Google Scholar 

  30. Mayer, R. E., & Moreno, R. (2002). Aids to computer-based multimedia learning. Learning and Instruction, 12(1), 107–119. https://doi.org/10.1016/S0959-4752(01)00018-4.

    Article  Google Scholar 

  31. Moreno, R., & Mayer, R. E. (2002). Verbal redundancy in multimedia learning: When reading helps listening. Journal of Educational Psychology, 94(1), 156–163. https://doi.org/10.1037/0022-0663.94.1.156.

    Article  Google Scholar 

  32. Morrison, G. R., & Anglin, G. J. (2005). Research on cognitive load theory: Application to e-learning. Educational Technology Research and Development, 53(3), 94–104. https://doi.org/10.1007/BF02504801.

    Article  Google Scholar 

  33. Mousavi, S. Y., Low, R., & Sweller, J. (1995). Reducing cognitive load by mixing auditory and visual presentation modes. Journal of Educational Psychology, 87(2), 319–334. https://doi.org/10.1037/0022-0663.87.2.319.

    Article  Google Scholar 

  34. Muller, D. A., Lee, K. J., & Sharma, M. D. (2008). Coherence or interest: Which is most important in online multimedia learning? Australasian Journal of Educational Technology, 24(2), 211–221. https://doi.org/10.14742/ajet.1223.

    Article  Google Scholar 

  35. Neguț, A., Jurma, A. M., & David, D. (2017). Virtual-reality-based attention assessment of ADHD: ClinicaVR: Classroom-CPT versus a traditional continuous performance test. Child Neuropsychology, 23(6), 692–712. https://doi.org/10.1080/09297049.2016.1186617.

    Article  Google Scholar 

  36. Nunnally, J. (1978). Psychometric theory. . McGraw-Hill.

    Google Scholar 

  37. Paas, F., Tuovinen, J., Tabbers, H., & van Gerven, P. (2003). Cognitive load measurement as a means to advance cognitive load theory. Educational Psychologist, 38(1), 63–71. https://doi.org/10.1207/S15326985EP3801_8.

    Article  Google Scholar 

  38. Paas, F., & Van Merriënboer, J. J. G. (1993). The efficiency of instructional conditions: An approach to combine mental-effort and performance measures. Human Factors, 35(4), 737–743. https://doi.org/10.1177/001872089303500412.

    Article  Google Scholar 

  39. Paas, F., & Van Merriënboer, J. J. G. (1994). Variability of worked examples and transfer of geometrical problem-solving skills: A cognitive-load approach. Journal of Educational Psychology, 86(1), 122–133. https://doi.org/10.1037/0022-0663.86.1.122.

    Article  Google Scholar 

  40. Parsons, T. D. (2015). Virtual reality for enhanced ecological validity and experimental control in the clinical, affective and social neurosciences. Frontiers in Human Neuroscience, 9, 660. https://doi.org/10.3389/fnhum.2015.00660.

    Article  Google Scholar 

  41. Rizzo, A., Thomas, D., Parsons, T. D., & Buckwalter, J. G. (2012). Using virtual reality for clinical assessment and intervention. In L. L’Abate & D. A. Kaiser (Eds.), Handbook of technology in psychology, psychiatry, and neurology: Theory, research, and practice. (pp. 277–318). Nova Science Publishers.

    Google Scholar 

  42. Rockwell, S. C., & Singleton, L. A. (2007). The effect of the modality of presentation of streaming multimedia on information acquisition. Media Psychology, 9(1), 179–191. https://doi.org/10.1080/15213260709336808.

    Article  Google Scholar 

  43. Shelton, J. T., Elliott, E. M., Eaves, S. D., & Exner, A. L. (2009). The distracting effects of a ringing cell phone: An investigation of the laboratory and the classroom setting. Journal of Environmental Psychology, 29(4), 513–521. https://doi.org/10.1016/j.jenvp.2009.03.001.

    Article  Google Scholar 

  44. Stavroulia, K. E., Christofi, M., Baka, E., Michael-Grigoriou, D., Magnenat-Thalmann, N., & Lanitis, A. (2019). Assessing the emotional impact of virtual reality-based teacher training. The International Journal of Information and Learning Technology, 36(3), 192–217. https://doi.org/10.1108/IJILT-11-2018-0127.

    Article  Google Scholar 

  45. Sweller, J. (2010). Element interactivity and intrinsic, extraneous and germane cognitive load. Educational Psychology Review, 22(2), 123–138.

    Article  Google Scholar 

  46. Sweller, J. (2019). Cognitive load theory and educational technology. Educational Technology Research and Development, 68, 1–16. https://doi.org/10.1007/s11423-019-09701-3.

    Article  Google Scholar 

  47. Sweller, J., Ayres, P., & Kalyuga, S. (2011). The redundancy effect. Cognitive load theory. (pp. 141–154). Springer.

    Google Scholar 

  48. Van Gog, T., & Paas, F. (2008). Instructional efficiency: Revisiting the original construct in educational research. Educational Psychologist, 43(1), 16–26. https://doi.org/10.1080/00461520701756248.

    Article  Google Scholar 

  49. Witmer, B. G., & Singer, M. J. (1998). Measuring presence in virtual environments: A presence questionnaire. Presence, 7(3), 225–240. https://doi.org/10.1162/105474698565686.

    Article  Google Scholar 

  50. Yang, F.-Y., Chang, C.-Y., Chien, W.-R., Chien, Y.-T., & Tseng, Y.-H. (2013). Tracking learners’ visual attention during a multimedia presentation in a real classroom. Computers & Education, 62, 208–220. https://doi.org/10.1016/j.compedu.2012.10.009.

    Article  Google Scholar 

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Acknowledgements

We would like to thank the editor of Educational Technology Research & Development and anonymous reviewers, who provided all the valuable comments and suggestions. Also, we would like to express our gratitude to the Ministry of Science and Technology (MOST) in Taiwan for its financial support to this research under Grant No. MOST 101-2511-S-003 -061 -MY3 and MOST 109-2511-H-003 -016 -MY3. Moreover, we sincerely appreciate the funding offered by the “Institute for Research Excellence in Learning Sciences” of National Taiwan Normal University (NTNU) from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan. Finally, we would like to thank the research assistants who assisted with the experiments and the students who participated in this study. This research would not have been possible without them.

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Correspondence to Tzu-Chien Liu.

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Liu, TC., Lin, YC., Wang, TN. et al. Studying the effect of redundancy in a virtual reality classroom. Education Tech Research Dev 69, 1183–1200 (2021). https://doi.org/10.1007/s11423-021-09991-6

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Keywords

  • Cognitive load theory
  • Redundancy effect
  • VR classroom
  • Multimedia