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1. The Interconnection between Evaluated and Self-Assessed Performance in Full Flight Simulator Training

Author

Ari Tuhkala, Ville Heilala, Joni Lämsä, Arto Helovuo, Ilkka Tynkkynen, Emilia Lampi, Katriina Sipiläinen, Raija Hämäläinen, and Tommi Kärkkäinen

Abstract

This study explores potential disparities between flight instructor evaluations and pilot self-assessments in the context of full flight simulator training. Evaluated performance was based on the Competency-based Training and Assessment framework, a recent development of competency-based education within aviation. Self-assessed performance is derived from survey responses and debriefing interviews. The simulator session involves eight multi-crew pilot training graduates and eight experienced flight captains, encompassing two tasks featuring sudden technical malfunctions during flight. The flight instructor's evaluations reveal no significant differences in pilot performance. However, disparities become apparent when pilots engaged in reflecting their performance. Novice pilots, despite perceiving both tasks as easy, exhibited an overconfidence that led them to underestimate the inherent risks. Conversely, experienced pilots demonstrated greater caution towards the risks and engaged in discussing possible hazards. Furthermore, this study highlights the challenge of designing flight simulator training that incorporates surprise elements. Pilots tend to anticipate anomalies more readily in simulator training than during actual flights. Thus, this study underscores the importance of examining how pilots reflect on their performance, complementing the assessment of observable indicators and predefined competencies.

Published
2024
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2. Capturing cognitive load management during authentic virtual reality flight training with behavioural and physiological indicators

Author

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

Subjects
kognitiivinen kuormitus, cognitive load management, cognitive load, kuormitus, simulation, professional learning, virtuaalitodellisuus, Computer Science Applications, Education, lentäminen, psyykkinen kuormittavuus, mittarit (mittaus), tietokoneavusteinen oppiminen, virtual reality, lentäjät, simulointi, käyttäytyminen, physiological measurements, fysiologiset vaikutukset
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. peerReviewed

Published
2023

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