Predicting Aviation Training Performance with Multimodal Affective Inferences
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| Title: | Predicting Aviation Training Performance with Multimodal Affective Inferences |
|---|---|
| Language: | English |
| Authors: | Li, Tianshu (ORCID |
| Source: | International Journal of Training and Development. Sep 2021 25(3):301-315. |
| Availability: | Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us |
| Peer Reviewed: | Y |
| Page Count: | 15 |
| Publication Date: | 2021 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Predictor Variables, Aviation Education, Performance, Psychological Patterns, Accuracy, Arousal Patterns, Cognitive Processes, Flight Training |
| DOI: | 10.1111/ijtd.12232 |
| ISSN: | 1360-3736 |
| Abstract: | Affect influences learning and training through various cognitive, psychomotor and motivational processes. This research aims to examine the role of affect in aviation training. Participants' (N = 19) affect and performance were examined in simulated aviation training while they performed ten tasks. Affective states were inferred from electrodermal activity, facial expression and NASA Taskload Index. Performance accuracy was graded with the rubrics provided by pilot instructors in CAE Inc. We found that arousal (inferred from electrodermal activity) positively predicted performance in the level 2 (easy) task (F(1, 17) = 7.408, p < 0.05, std [beta] = 0.55). Mental workload (as measured from self-report) negatively predicted performance in the level 3 (medium difficulty) (F(1, 15) = 4.598, p < 0.05, std [beta] = -0.54) and level 4 (difficult) tasks (F(1, 15) = 12.85, p < 0.01, std [beta] = -0.73), controlling for affect valence and arousal. This research is a preliminary step to a reconsideration of affect in theoretical frameworks in aviation. It demonstrates a comprehensive assessment of affect in aviation training, which could provide guidelines for instructional interventions to improve the overall training experience and pilot performance. |
| Abstractor: | As Provided |
| Entry Date: | 2021 |
| Accession Number: | EJ1307106 |
| Database: | ERIC |
| FullText | Links: – Type: pdflink Url: https://content.ebscohost.com/cds/retrieve?content=AQICAHj0k_4E0hTGH8RJwT4gCJyBsGNe_WN95AvKlDbXJGqwxwHpj5d-26_KoMi3ynyj0wnbAAAA4zCB4AYJKoZIhvcNAQcGoIHSMIHPAgEAMIHJBgkqhkiG9w0BBwEwHgYJYIZIAWUDBAEuMBEEDF_HIpgTf0WcdX2nHQIBEICBm6DrL7wphp_7t33rk6qQ4XU802fspZXVi-M8zF7ldQsEL5W6Cs3mn8NDGrMiuXzgRwK-oh83OP4pVaLHYvZ98XTBtyCMqY9SybAC2flqfPiRmOnvCqMtYu4Ks5yyeyLo1myBm_05mMYAVxHdWAV_uX3ODeck5SuhGFRKTbyPYML4w43HI37Z8zZMbiJ16hy_N-jgUHsbILadyC3e Text: Availability: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Predicting Aviation Training Performance with Multimodal Affective Inferences – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Li%2C+Tianshu%22">Li, Tianshu</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-8226-993X">0000-0002-8226-993X</externalLink>)<br /><searchLink fieldCode="AR" term="%22Lajoie%2C+Susanne%22">Lajoie, Susanne</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22International+Journal+of+Training+and+Development%22"><i>International Journal of Training and Development</i></searchLink>. Sep 2021 25(3):301-315. – Name: Avail Label: Availability Group: Avail Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 15 – Name: DatePubCY Label: Publication Date Group: Date Data: 2021 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Research – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22Predictor+Variables%22">Predictor Variables</searchLink><br /><searchLink fieldCode="DE" term="%22Aviation+Education%22">Aviation Education</searchLink><br /><searchLink fieldCode="DE" term="%22Performance%22">Performance</searchLink><br /><searchLink fieldCode="DE" term="%22Psychological+Patterns%22">Psychological Patterns</searchLink><br /><searchLink fieldCode="DE" term="%22Accuracy%22">Accuracy</searchLink><br /><searchLink fieldCode="DE" term="%22Arousal+Patterns%22">Arousal Patterns</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Processes%22">Cognitive Processes</searchLink><br /><searchLink fieldCode="DE" term="%22Flight+Training%22">Flight Training</searchLink> – Name: DOI Label: DOI Group: ID Data: 10.1111/ijtd.12232 – Name: ISSN Label: ISSN Group: ISSN Data: 1360-3736 – Name: Abstract Label: Abstract Group: Ab Data: Affect influences learning and training through various cognitive, psychomotor and motivational processes. This research aims to examine the role of affect in aviation training. Participants' (N = 19) affect and performance were examined in simulated aviation training while they performed ten tasks. Affective states were inferred from electrodermal activity, facial expression and NASA Taskload Index. Performance accuracy was graded with the rubrics provided by pilot instructors in CAE Inc. We found that arousal (inferred from electrodermal activity) positively predicted performance in the level 2 (easy) task (F(1, 17) = 7.408, p < 0.05, std [beta] = 0.55). Mental workload (as measured from self-report) negatively predicted performance in the level 3 (medium difficulty) (F(1, 15) = 4.598, p < 0.05, std [beta] = -0.54) and level 4 (difficult) tasks (F(1, 15) = 12.85, p < 0.01, std [beta] = -0.73), controlling for affect valence and arousal. This research is a preliminary step to a reconsideration of affect in theoretical frameworks in aviation. It demonstrates a comprehensive assessment of affect in aviation training, which could provide guidelines for instructional interventions to improve the overall training experience and pilot performance. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2021 – Name: AN Label: Accession Number Group: ID Data: EJ1307106 |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1307106 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/ijtd.12232 Languages: – Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 301 Subjects: – SubjectFull: Predictor Variables Type: general – SubjectFull: Aviation Education Type: general – SubjectFull: Performance Type: general – SubjectFull: Psychological Patterns Type: general – SubjectFull: Accuracy Type: general – SubjectFull: Arousal Patterns Type: general – SubjectFull: Cognitive Processes Type: general – SubjectFull: Flight Training Type: general Titles: – TitleFull: Predicting Aviation Training Performance with Multimodal Affective Inferences Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Li, Tianshu – PersonEntity: Name: NameFull: Lajoie, Susanne IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Type: published Y: 2021 Identifiers: – Type: issn-print Value: 1360-3736 Numbering: – Type: volume Value: 25 – Type: issue Value: 3 Titles: – TitleFull: International Journal of Training and Development Type: main |
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