Combining Virtual Reality and Machine Learning for Leadership Styles Recognition
The aim of this study was to evaluate the viability of a new selection procedure based on machine learning (ML) and virtual reality (VR). Specifically, decision-making behaviours and eye-gaze patterns were used to classify individuals based on their leadership styles while immersed in virtual enviro...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-05-01
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| Series: | Frontiers in Psychology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyg.2022.864266/full |
| _version_ | 1811232916429078528 |
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| author | Elena Parra Aitana García Delgado Lucía Amalia Carrasco-Ribelles Lucía Amalia Carrasco-Ribelles Irene Alice Chicchi Giglioli Javier Marín-Morales Cristina Giglio Mariano Alcañiz Raya |
| author_facet | Elena Parra Aitana García Delgado Lucía Amalia Carrasco-Ribelles Lucía Amalia Carrasco-Ribelles Irene Alice Chicchi Giglioli Javier Marín-Morales Cristina Giglio Mariano Alcañiz Raya |
| author_sort | Elena Parra |
| collection | DOAJ |
| description | The aim of this study was to evaluate the viability of a new selection procedure based on machine learning (ML) and virtual reality (VR). Specifically, decision-making behaviours and eye-gaze patterns were used to classify individuals based on their leadership styles while immersed in virtual environments that represented social workplace situations. The virtual environments were designed using an evidence-centred design approach. Interaction and gaze patterns were recorded in 83 subjects, who were classified as having either high or low leadership style, which was assessed using the Multifactor leadership questionnaire. A ML model that combined behaviour outputs and eye-gaze patterns was developed to predict subjects’ leadership styles (high vs low). The results indicated that the different styles could be differentiated by eye-gaze patterns and behaviours carried out during immersive VR. Eye-tracking measures contributed more significantly to this differentiation than behavioural metrics. Although the results should be taken with caution as the small sample does not allow generalization of the data, this study illustrates the potential for a future research roadmap that combines VR, implicit measures, and ML for personnel selection. |
| first_indexed | 2024-04-12T11:12:20Z |
| format | Article |
| id | doaj.art-8e88084805f441268efa141608a266dd |
| institution | Directory Open Access Journal |
| issn | 1664-1078 |
| language | English |
| last_indexed | 2024-04-12T11:12:20Z |
| publishDate | 2022-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychology |
| spelling | doaj.art-8e88084805f441268efa141608a266dd2022-12-22T03:35:35ZengFrontiers Media S.A.Frontiers in Psychology1664-10782022-05-011310.3389/fpsyg.2022.864266864266Combining Virtual Reality and Machine Learning for Leadership Styles RecognitionElena Parra0Aitana García Delgado1Lucía Amalia Carrasco-Ribelles2Lucía Amalia Carrasco-Ribelles3Irene Alice Chicchi Giglioli4Javier Marín-Morales5Cristina Giglio6Mariano Alcañiz Raya7Institute for Research and Innovation in Bioengineering, Polytechnic University of Valencia, Valencia, SpainInstitute for Research and Innovation in Bioengineering, Polytechnic University of Valencia, Valencia, SpainInstitute for Research and Innovation in Bioengineering, Polytechnic University of Valencia, Valencia, SpainFundació Institut Universitari per a la Recerca a l’Atenció Primària de Salut Jordi Gol i Gurina, Cornellà de Llobregat, SpainInstitute for Research and Innovation in Bioengineering, Polytechnic University of Valencia, Valencia, SpainInstitute for Research and Innovation in Bioengineering, Polytechnic University of Valencia, Valencia, SpainInstitute for Research and Innovation in Bioengineering, Polytechnic University of Valencia, Valencia, SpainInstitute for Research and Innovation in Bioengineering, Polytechnic University of Valencia, Valencia, SpainThe aim of this study was to evaluate the viability of a new selection procedure based on machine learning (ML) and virtual reality (VR). Specifically, decision-making behaviours and eye-gaze patterns were used to classify individuals based on their leadership styles while immersed in virtual environments that represented social workplace situations. The virtual environments were designed using an evidence-centred design approach. Interaction and gaze patterns were recorded in 83 subjects, who were classified as having either high or low leadership style, which was assessed using the Multifactor leadership questionnaire. A ML model that combined behaviour outputs and eye-gaze patterns was developed to predict subjects’ leadership styles (high vs low). The results indicated that the different styles could be differentiated by eye-gaze patterns and behaviours carried out during immersive VR. Eye-tracking measures contributed more significantly to this differentiation than behavioural metrics. Although the results should be taken with caution as the small sample does not allow generalization of the data, this study illustrates the potential for a future research roadmap that combines VR, implicit measures, and ML for personnel selection.https://www.frontiersin.org/articles/10.3389/fpsyg.2022.864266/fullleadership style recognitionvirtual realityeye-trackingmachine learningleadership |
| spellingShingle | Elena Parra Aitana García Delgado Lucía Amalia Carrasco-Ribelles Lucía Amalia Carrasco-Ribelles Irene Alice Chicchi Giglioli Javier Marín-Morales Cristina Giglio Mariano Alcañiz Raya Combining Virtual Reality and Machine Learning for Leadership Styles Recognition Frontiers in Psychology leadership style recognition virtual reality eye-tracking machine learning leadership |
| title | Combining Virtual Reality and Machine Learning for Leadership Styles Recognition |
| title_full | Combining Virtual Reality and Machine Learning for Leadership Styles Recognition |
| title_fullStr | Combining Virtual Reality and Machine Learning for Leadership Styles Recognition |
| title_full_unstemmed | Combining Virtual Reality and Machine Learning for Leadership Styles Recognition |
| title_short | Combining Virtual Reality and Machine Learning for Leadership Styles Recognition |
| title_sort | combining virtual reality and machine learning for leadership styles recognition |
| topic | leadership style recognition virtual reality eye-tracking machine learning leadership |
| url | https://www.frontiersin.org/articles/10.3389/fpsyg.2022.864266/full |
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