Pilot Trainees Benefit from Modelling and Adaptive Feedback

Limited training capacity has contributed to a critical shortage of licensed commercial pilots.Adaptive educational technologies and simulators could alleviate current training bottlenecks if these technologies could assess trainee performance and provide appropriate feedback.Agents can be used to assess trainee performance, but there is insufficient guidance on how to provide concurrent feedback in simulation-based learning environments.So, we designed 4 feedback conditions that provide varying degrees of elaboration and used a within-subject study ( = 20) to compare feedback approaches.Trainee performance was best when they received highly-elaborative feedback that modeled expert behaviour.Variability in participant performance and preferences indicates a need to adapt the feedback type to individual learners and provides insight into the use of concurrent feedback in simulation-based learning environments.Specifically, learners appreciated the expert model because it facilitated a sense of control which was associated with lower negative affect and lower extraneous cognitive load.

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Publication Details

Published
2025-06-13
DOI
https://doi.org/10.1145/3699682.3728337
Citations
1
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
2.48

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Pilot Trainees Benefit from Modelling and Adaptive Feedback

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Pilot Trainees Benefit from Modelling and Adaptive Feedback

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article en
1 citations

Abstract

Limited training capacity has contributed to a critical shortage of licensed commercial pilots.Adaptive educational technologies and simulators could alleviate current training bottlenecks if these technologies could assess trainee performance and provide appropriate feedback.Agents can be used to assess trainee performance, but there is insufficient guidance on how to provide concurrent feedback in simulation-based learning environments.So, we designed 4 feedback conditions that provide varying degrees of elaboration and used a within-subject study ( = 20) to compare feedback approaches.Trainee performance was best when they received highly-elaborative feedback that modeled expert behaviour.Variability in participant performance and preferences indicates a need to adapt the feedback type to individual learners and provides insight into the use of concurrent feedback in simulation-based learning environments.Specifically, learners appreciated the expert model because it facilitated a sense of control which was associated with lower negative affect and lower extraneous cognitive load.

University of Alberta (CA)
Canadian Institute for Advanced Research, University of Alberta, Mitacs, Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 10%
Intelligent Tutoring Systems and Adaptive Learning
2.48
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