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 editorsLämsä, Joni; Mannonen, Joonas; Tuhkala, Ari; Heilala, Ville; Helovuo, Arto; Tynkkynen, Ilkka; Lampi, Emilia; Sipiläinen, Katriina; Kärkkäinen, Tommi; Hämäläinen, Raija

Journal or seriesJournal of Computer Assisted Learning

ISSN0266-4909

eISSN1365-2729

Publication year2023

Publication date24/04/2023

Volume39

Issue number5

Pages range1553-1563

PublisherWiley

Publication countryUnited Kingdom

Publication languageEnglish

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

Publication open accessOpenly available

Publication channel open accessPartially 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.


Keywordsstrains and stressespsychological strainflyingair pilotsvirtual realitysimulationcomputer-assisted learningphysiological effectsbehaviourmeasuring instruments (indicators)

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


Contributing organizations


Related projects


Ministry reportingYes

Reporting Year2023

JUFO rating2


Last updated on 2024-15-06 at 22:26