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The State of the Art of Diagnostic Multiparty Eye Tracking in Synchronous Computer-Mediated Collaboration
In recent years, innovative multiparty eye tracking setups have been introduced to synchronously capture eye movements of multiple individuals engaged in computer-mediated collaboration. Despite its great potential for studying cognitive processes within groups, the method was primarily used as an i...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Bern Open Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10690675/ https://www.ncbi.nlm.nih.gov/pubmed/38046524 http://dx.doi.org/10.16910/jemr.16.2.4 |
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author | Reuscher, Tom Frank Toreini, Peyman Maedche, Alexander |
author_facet | Reuscher, Tom Frank Toreini, Peyman Maedche, Alexander |
author_sort | Reuscher, Tom Frank |
collection | PubMed |
description | In recent years, innovative multiparty eye tracking setups have been introduced to synchronously capture eye movements of multiple individuals engaged in computer-mediated collaboration. Despite its great potential for studying cognitive processes within groups, the method was primarily used as an interactive tool to enable and evaluate shared gaze visualizations in remote interaction. We conducted a systematic literature review to provide a comprehensive overview of what to consider when using multiparty eye tracking as a diagnostic method in experiments and how to process the collected data to compute and analyze group-level metrics. By synthesizing our findings in an integrative conceptual framework, we identified fundamental requirements for a meaningful implementation. In addition, we derived several implications for future research, as multiparty eye tracking was mainly used to study the correlation between joint attention and task performance in dyadic interaction. We found multidimensional recurrence quantification analysis, a novel method to quantify group-level dynamics in physiological data, to be a promising procedure for addressing some of the highlighted research gaps. In particular, the computation method enables scholars to investigate more complex cognitive processes within larger groups, as it scales up to multiple data streams. |
format | Online Article Text |
id | pubmed-10690675 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Bern Open Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-106906752023-12-02 The State of the Art of Diagnostic Multiparty Eye Tracking in Synchronous Computer-Mediated Collaboration Reuscher, Tom Frank Toreini, Peyman Maedche, Alexander J Eye Mov Res Research Article In recent years, innovative multiparty eye tracking setups have been introduced to synchronously capture eye movements of multiple individuals engaged in computer-mediated collaboration. Despite its great potential for studying cognitive processes within groups, the method was primarily used as an interactive tool to enable and evaluate shared gaze visualizations in remote interaction. We conducted a systematic literature review to provide a comprehensive overview of what to consider when using multiparty eye tracking as a diagnostic method in experiments and how to process the collected data to compute and analyze group-level metrics. By synthesizing our findings in an integrative conceptual framework, we identified fundamental requirements for a meaningful implementation. In addition, we derived several implications for future research, as multiparty eye tracking was mainly used to study the correlation between joint attention and task performance in dyadic interaction. We found multidimensional recurrence quantification analysis, a novel method to quantify group-level dynamics in physiological data, to be a promising procedure for addressing some of the highlighted research gaps. In particular, the computation method enables scholars to investigate more complex cognitive processes within larger groups, as it scales up to multiple data streams. Bern Open Publishing 2023-06-19 /pmc/articles/PMC10690675/ /pubmed/38046524 http://dx.doi.org/10.16910/jemr.16.2.4 Text en Copyright (©) 2023 Tom Frank Reuscher, Peyman Toreini, Alexander Maedche https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License, ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Research Article Reuscher, Tom Frank Toreini, Peyman Maedche, Alexander The State of the Art of Diagnostic Multiparty Eye Tracking in Synchronous Computer-Mediated Collaboration |
title | The State of the Art of Diagnostic Multiparty Eye Tracking in Synchronous Computer-Mediated Collaboration |
title_full | The State of the Art of Diagnostic Multiparty Eye Tracking in Synchronous Computer-Mediated Collaboration |
title_fullStr | The State of the Art of Diagnostic Multiparty Eye Tracking in Synchronous Computer-Mediated Collaboration |
title_full_unstemmed | The State of the Art of Diagnostic Multiparty Eye Tracking in Synchronous Computer-Mediated Collaboration |
title_short | The State of the Art of Diagnostic Multiparty Eye Tracking in Synchronous Computer-Mediated Collaboration |
title_sort | state of the art of diagnostic multiparty eye tracking in synchronous computer-mediated collaboration |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10690675/ https://www.ncbi.nlm.nih.gov/pubmed/38046524 http://dx.doi.org/10.16910/jemr.16.2.4 |
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