University of Oulu

Lämsä, J., Mannonen, J., Tuhkala, A., Heilala, V., Helovuo, A., Tynkkynen, I., Lampi, E., Sipiläinen, K., Kärkkäinen, T., & Hämäläinen, R. (2023). Capturing cognitive load management during authentic virtual reality flight training with behavioural and physiological indicators. Journal of Computer Assisted Learning, 39(5), 1553–1563.

Capturing cognitive load management during authentic virtual reality flight training with behavioural and physiological indicators

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Author: Lämsä, Joni1,2; Mannonen, Joonas3; Tuhkala, Ari1;
Organizations: 1Department of Education, University of Jyväskylä, Jyväskylä, Finland
2Learning and Educational Technology (LET) Research Lab, University of Oulu, Oulu, Finland
3Finnish Institute for Educational Research, University of Jyväskylä, Jyväskylä, Finland
4Faculty of Information Technology, University of Jyväskylä; Department of Education, University of Jyväskylä, Jyväskylä, Finland
5Finnair, Helsinki-Uusimaa, Finland
6Faculty of Education and Psychology, University of Jyväskylä, Jyväskylä, Finland
7Faculty of Information Technology, University of Jyväskylä, Jyväskylä, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.8 MB)
Persistent link:
Language: English
Published: John Wiley & Sons, 2023
Publish Date: 2023-09-18


Background: Cognitive load (CL) management is essential in safety-critical fields so that professionals can monitor and control their cognitive resources efficiently to perform and solve scenarios in a timely and safe manner, even in complex and unexpected circumstances. Thus, cognitive load theory (CLT) can be used to design virtual reality (VR) training programmes for professional learning in these fields.

Objectives: We studied CL management performance through behavioural indicators in authentic VR flight training and explored if and to what extent physiological data was associated with CL management performance.

Methods: The expert (n = 8) and novice pilots (n = 6) performed three approach and landing scenarios with increasing element interactivity. We used video recordings of the training to assess CL management performance based on the behavioural indicators. Then, we used the heart rate (HR) and heart rate variability (HRV) data to study the associations between the physiological data and CL management performance.

Results and Conclusions: The pilots performed effectively in CL management. The experience of the pilots did not remarkably explain the variation in CL management performance. The scenario with the highest element interactivity and an increase in the very low-frequency band of HRV were associated with decreased performance in CL management.

Takeaways: Our study sheds light on the association between physiological indicators and CL management performance, which has traditionally been assessed with behavioural indicators in professional learning in safety-critical fields. Thus, physiological measurements can be used to supplement the assessment of CL management performance, as relying solely on behavioural indicators can be time consuming.

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Series: Journal of computer assisted learning
ISSN: 0266-4909
ISSN-E: 1365-2729
ISSN-L: 0266-4909
Volume: 39
Issue: 5
Pages: 1553 - 1563
DOI: 10.1111/jcal.12817
Type of Publication: A1 Journal article – refereed
Field of Science: 516 Educational sciences
Funding: The work was supported by the Academy of Finland under Grant numbers 292466, 311877, 318905, and 331817.
Copyright information: © 2023 The Authors. Journal of Computer Assisted Learning published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.