A1 Journal article (refereed)
Capturing cognitive load management during authentic virtual reality flight training with behavioural and physiological indicators (2023)


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. https://doi.org/10.1111/jcal.12817


JYU authors or editors


Publication details

All authors or editors: Lämsä, Joni; Mannonen, Joonas; Tuhkala, Ari; Heilala, Ville; Helovuo, Arto; Tynkkynen, Ilkka; Lampi, Emilia; Sipiläinen, Katriina; Kärkkäinen, Tommi; Hämäläinen, Raija

Journal or series: Journal of Computer Assisted Learning

ISSN: 0266-4909

eISSN: 1365-2729

Publication year: 2023

Publication date: 24/04/2023

Volume: 39

Issue number: 5

Pages range: 1553-1563

Publisher: Wiley

Publication country: United Kingdom

Publication language: English

DOI: https://doi.org/10.1111/jcal.12817

Publication open access: Openly available

Publication channel open access: Partially open access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/86849


Abstract

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.


Keywords: strains and stresses; psychological strain; flying; air pilots; virtual reality; simulation; computer-assisted learning; physiological effects; behaviour; measuring instruments (indicators)

Free keywords: cognitive load; cognitive load management; physiological measurements; professional learning; simulation; virtual reality


Contributing organizations


Related projects


Ministry reporting: Yes

Reporting Year: 2023

JUFO rating: 2


Last updated on 2024-03-07 at 00:25