Capturing cognitive load management during authentic virtual reality flight training with behavioural and physiological indicators.
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...
| Publicado en: | Journal of Computer Assisted Learning Vol. 39; no. 5; pp. 1553 - 1564 |
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| Autores principales: | , , , , , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Oct2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=171903676&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 171903676 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Oct2023 vid: 39 iid: 5 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 171903676 163245545 171903676 171903676 10.1111/jcal.12817 171903676 ppf: 1553 ppct: 11 formats: tig: atl: Capturing cognitive load management during authentic virtual reality flight training with behavioural and physiological indicators. aug: au: Lämsä, Joni Mannonen, Joonas Tuhkala, Ari Heilala, Ville Helovuo, Arto Tynkkynen, Ilkka Lampi, Emilia Sipiläinen, Katriina Kärkkäinen, Tommi Hämäläinen, Raija affil: Department of Education, University of Jyväskylä, Jyväskylä, Finland sug: subj: Virtual Reality Education Aviation Education Simulations Learning Methods Behavioral Changes Cognition Evaluation Human Videorecording Descriptive Statistics Heart Rate Variability Heart Rate Conceptual Framework Confidence Intervals Coefficient alpha Funding Source ab: 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. Lay Description: What is currently known about the subject matter: The advantages of VR training systems are clear in the safety‐critical fields.Cognitive load (CL) theory may help design of VR training.CL management is part of the professional competence in these fields. What this paper adds: The pilots performed well in CL management in VR flight training.The work experience of the pilot was not associated with the performance.The physiological data improved the explanatory level of the performance. The implications of study findings for practitioners: Pilots need time to get used to the immersive learning environment.Typical 1–2‐hour intensive VR flight training is not too demanding.The physiological data could complement CL management assessment. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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