Mohamad El Iskandarani, Jad A. Atweh, Shannon P. D. McGarry, S. L. Riggs, N. Moacdieh
{"title":"Does It MultiMatch? What Scanpath Comparison Tells us About Task Performance in Teams","authors":"Mohamad El Iskandarani, Jad A. Atweh, Shannon P. D. McGarry, S. L. Riggs, N. Moacdieh","doi":"10.1177/15553434231171484","DOIUrl":null,"url":null,"abstract":"Teamwork and collaboration form the cornerstones of organizational performance and success. It is important to understand how the attention allocation of team members is linked to performance. One approach to studying attention allocation in a team context is to compare the scanpath similarity of two people working in teams and to explore the link between scanpath similarity and team performance. In this study, participants were recruited to work in pairs on an unmanned aerial vehicle (UAV) task that included low and high workload conditions. An eye tracker was used to collect the eye movements of both participants in each team. The scanpaths of two teammates were compared in low and high workload conditions using MultiMatch, an established scanpath comparison algorithm. The obtained scanpath similarity values were correlated with performance measures of response time and accuracy. Several MultiMatch measures showed significant strong correlations across multiple dimensions, providing insight into team behavior and attention allocation. The results suggested that the more similar each team member’s scanpath is, the better their performance. Additional research and consideration of experimental variables will be necessary to further understand how best to use MultiMatch for scanpath similarity assessment in complex domains.","PeriodicalId":46342,"journal":{"name":"Journal of Cognitive Engineering and Decision Making","volume":"17 1","pages":"294 - 309"},"PeriodicalIF":2.2000,"publicationDate":"2023-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cognitive Engineering and Decision Making","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/15553434231171484","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 3
Abstract
Teamwork and collaboration form the cornerstones of organizational performance and success. It is important to understand how the attention allocation of team members is linked to performance. One approach to studying attention allocation in a team context is to compare the scanpath similarity of two people working in teams and to explore the link between scanpath similarity and team performance. In this study, participants were recruited to work in pairs on an unmanned aerial vehicle (UAV) task that included low and high workload conditions. An eye tracker was used to collect the eye movements of both participants in each team. The scanpaths of two teammates were compared in low and high workload conditions using MultiMatch, an established scanpath comparison algorithm. The obtained scanpath similarity values were correlated with performance measures of response time and accuracy. Several MultiMatch measures showed significant strong correlations across multiple dimensions, providing insight into team behavior and attention allocation. The results suggested that the more similar each team member’s scanpath is, the better their performance. Additional research and consideration of experimental variables will be necessary to further understand how best to use MultiMatch for scanpath similarity assessment in complex domains.