Flight emotions unleashed: Navigating training phases and difficulty levels in simulated flying

IF 5.1 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Journal of Computer Assisted Learning Pub Date : 2024-07-27 DOI:10.1111/jcal.13037

Alejandra Ruiz-Segura, Andrew Law, Sion Jennings, Alain Bourgon, Ethan Churchill, Susanne Lajoie

{"title":"Flight emotions unleashed: Navigating training phases and difficulty levels in simulated flying","authors":"Alejandra Ruiz-Segura, Andrew Law, Sion Jennings, Alain Bourgon, Ethan Churchill, Susanne Lajoie","doi":"10.1111/jcal.13037","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Flying accuracy is influenced by pilots' affective reactions to task demands. A better understanding of task-related emotions and flying performance is needed to enhance pilot training.</p>\n </section>\n \n <section>\n \n <h3> Objective</h3>\n \n <p>Understand pilot trainees' performance and emotional dynamics (intensity, frequency and variability) based on training phase and difficulty level in a flight simulator.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>Twenty-three volunteers performed basic flight manoeuvres. Trials were divided into three phases: Introduction (trials 1–7), session A (trials 8–15) and session B (trials 16–22). Three task difficulty levels were implemented (low, medium and high). Flying performance was evaluated using root mean square error (RMSE) and expert ratings. Emotional intensity was inferred from physiological (electrodermal activity) and behavioural (facial expressions) emotional responses. Emotional variability was calculated to understand fluctuations among multiple emotions. Emotional responses were mapped into task-relevant emotions, like sadness with boredom, and fear with anxiety.</p>\n </section>\n \n <section>\n \n <h3> Results and Conclusions</h3>\n \n <p>The most frequent facial expressions neutral, anger and surprise. Neutral and anger were interpreted as deep focus states. Surprise was likely a response to unexpected events. Flying performance and emotional dynamics varied across training phases and difficulty levels. During introduction, performance was less accurate, and emotions were less frequent. During session A, performance improved while participants experienced more physiological arousal and emotional variability. During session B, performance was the most accurate. In high-difficulty tasks, performance was the least accurate, participants expressed emotions with more frequency, more variability and higher physiological arousal. Future studies can use simulated flying tasks for trainees to familiarize with their emotional reactions to task demands expecting to improve training outcomes.</p>\n </section>\n </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"40 6","pages":"2926-2947"},"PeriodicalIF":5.1000,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jcal.13037","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer Assisted Learning","FirstCategoryId":"95","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jcal.13037","RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}

引用次数: 0

Abstract

Background

Flying accuracy is influenced by pilots' affective reactions to task demands. A better understanding of task-related emotions and flying performance is needed to enhance pilot training.

Objective

Understand pilot trainees' performance and emotional dynamics (intensity, frequency and variability) based on training phase and difficulty level in a flight simulator.

Methods

Twenty-three volunteers performed basic flight manoeuvres. Trials were divided into three phases: Introduction (trials 1–7), session A (trials 8–15) and session B (trials 16–22). Three task difficulty levels were implemented (low, medium and high). Flying performance was evaluated using root mean square error (RMSE) and expert ratings. Emotional intensity was inferred from physiological (electrodermal activity) and behavioural (facial expressions) emotional responses. Emotional variability was calculated to understand fluctuations among multiple emotions. Emotional responses were mapped into task-relevant emotions, like sadness with boredom, and fear with anxiety.

Results and Conclusions

The most frequent facial expressions neutral, anger and surprise. Neutral and anger were interpreted as deep focus states. Surprise was likely a response to unexpected events. Flying performance and emotional dynamics varied across training phases and difficulty levels. During introduction, performance was less accurate, and emotions were less frequent. During session A, performance improved while participants experienced more physiological arousal and emotional variability. During session B, performance was the most accurate. In high-difficulty tasks, performance was the least accurate, participants expressed emotions with more frequency, more variability and higher physiological arousal. Future studies can use simulated flying tasks for trainees to familiarize with their emotional reactions to task demands expecting to improve training outcomes.

Abstract Image

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

释放飞行情绪在模拟飞行中驾驭训练阶段和难度级别

背景飞行准确性受飞行员对任务要求的情绪反应影响。方法23名志愿者进行了基本的飞行操作。试验分为三个阶段：入门阶段（试验 1-7）、A 阶段（试验 8-15）和 B 阶段（试验 16-22）。任务难度分为三个等级（低、中、高）。飞行表现采用均方根误差（RMSE）和专家评分进行评估。情绪强度根据生理（皮电活动）和行为（面部表情）情绪反应进行推断。计算情绪变异性是为了了解多种情绪之间的波动。情绪反应被映射为与任务相关的情绪，如悲伤与无聊、恐惧与焦虑。中性和愤怒被解释为深度专注状态。惊讶可能是对意外事件的反应。在不同的训练阶段和难度下，飞行表现和情绪动态各不相同。在入门阶段，飞行表现的准确性较低，情绪波动也较小。在 A 阶段，飞行表现有所改善，而参与者的生理唤醒和情绪变化则更多。在 B 阶段，表现最为准确。在高难度任务中，表现的准确性最低，参与者表达情绪的频率更高，变异性更大，生理唤醒程度更高。未来的研究可以利用模拟飞行任务让学员熟悉他们对任务要求的情绪反应，从而提高训练效果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Journal of Computer Assisted Learning EDUCATION & EDUCATIONAL RESEARCH-

CiteScore

9.70

自引率

6.00%

发文量

116

期刊介绍： The Journal of Computer Assisted Learning is an international peer-reviewed journal which covers the whole range of uses of information and communication technology to support learning and knowledge exchange. It aims to provide a medium for communication among researchers as well as a channel linking researchers, practitioners, and policy makers. JCAL is also a rich source of material for master and PhD students in areas such as educational psychology, the learning sciences, instructional technology, instructional design, collaborative learning, intelligent learning systems, learning analytics, open, distance and networked learning, and educational evaluation and assessment. This is the case for formal (e.g., schools), non-formal (e.g., workplace learning) and informal learning (e.g., museums and libraries) situations and environments. Volumes often include one Special Issue which these provides readers with a broad and in-depth perspective on a specific topic. First published in 1985, JCAL continues to have the aim of making the outcomes of contemporary research and experience accessible. During this period there have been major technological advances offering new opportunities and approaches in the use of a wide range of technologies to support learning and knowledge transfer more generally. There is currently much emphasis on the use of network functionality and the challenges its appropriate uses pose to teachers/tutors working with students locally and at a distance. JCAL welcomes: -Empirical reports, single studies or programmatic series of studies on the use of computers and information technologies in learning and assessment -Critical and original meta-reviews of literature on the use of computers for learning -Empirical studies on the design and development of innovative technology-based systems for learning -Conceptual articles on issues relating to the Aims and Scope