Marian Sauter, Tobias Wagner, Teresa Hirzle, Bao Xin Lin, Enrico Rukzio, Anke Huckauf
{"title":"屏幕背后:探索眼动可视化优化在线教学","authors":"Marian Sauter, Tobias Wagner, Teresa Hirzle, Bao Xin Lin, Enrico Rukzio, Anke Huckauf","doi":"10.1145/3603555.3603560","DOIUrl":null,"url":null,"abstract":"The effective delivery of e-learning depends on the continuous monitoring and management of student attention. While instructors in traditional classroom settings can easily assess crowd attention through gaze cues, these cues are largely unavailable in online learning environments. To address this challenge and highlight the significance of our study, we collected eye movement data from twenty students and developed four visualization methods: (a) a heat map, (b) an ellipse map, (c) two moving bars, and (d) a vertical bar, which were overlaid on 13 instructional videos. Our results revealed unexpected preferences among the instructors. Contrary to expectations, they did not prefer the established heat map and vertical bar for live online instruction. Instead, they chose the less intrusive ellipse visualization. Nevertheless, the heat map remained the preferred choice for retrospective analysis due to its more detailed information. Importantly, all visualizations were found to be useful and to help restore emotional connections in online learning. In conclusion, our innovative visualizations of crowd attention show considerable potential for a wide range of applications, extending beyond e-learning to all online presentations and retrospective analyses. The significant results of our study underscore the critical role these visualizations will play in enhancing both the effectiveness and emotional connectedness of future e-learning experiences, thereby facilitating the educational landscape.","PeriodicalId":132553,"journal":{"name":"Proceedings of Mensch und Computer 2023","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Behind the Screens: Exploring Eye Movement Visualization to Optimize Online Teaching and Learning\",\"authors\":\"Marian Sauter, Tobias Wagner, Teresa Hirzle, Bao Xin Lin, Enrico Rukzio, Anke Huckauf\",\"doi\":\"10.1145/3603555.3603560\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The effective delivery of e-learning depends on the continuous monitoring and management of student attention. While instructors in traditional classroom settings can easily assess crowd attention through gaze cues, these cues are largely unavailable in online learning environments. To address this challenge and highlight the significance of our study, we collected eye movement data from twenty students and developed four visualization methods: (a) a heat map, (b) an ellipse map, (c) two moving bars, and (d) a vertical bar, which were overlaid on 13 instructional videos. Our results revealed unexpected preferences among the instructors. Contrary to expectations, they did not prefer the established heat map and vertical bar for live online instruction. Instead, they chose the less intrusive ellipse visualization. Nevertheless, the heat map remained the preferred choice for retrospective analysis due to its more detailed information. Importantly, all visualizations were found to be useful and to help restore emotional connections in online learning. In conclusion, our innovative visualizations of crowd attention show considerable potential for a wide range of applications, extending beyond e-learning to all online presentations and retrospective analyses. The significant results of our study underscore the critical role these visualizations will play in enhancing both the effectiveness and emotional connectedness of future e-learning experiences, thereby facilitating the educational landscape.\",\"PeriodicalId\":132553,\"journal\":{\"name\":\"Proceedings of Mensch und Computer 2023\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of Mensch und Computer 2023\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3603555.3603560\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of Mensch und Computer 2023","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3603555.3603560","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Behind the Screens: Exploring Eye Movement Visualization to Optimize Online Teaching and Learning
The effective delivery of e-learning depends on the continuous monitoring and management of student attention. While instructors in traditional classroom settings can easily assess crowd attention through gaze cues, these cues are largely unavailable in online learning environments. To address this challenge and highlight the significance of our study, we collected eye movement data from twenty students and developed four visualization methods: (a) a heat map, (b) an ellipse map, (c) two moving bars, and (d) a vertical bar, which were overlaid on 13 instructional videos. Our results revealed unexpected preferences among the instructors. Contrary to expectations, they did not prefer the established heat map and vertical bar for live online instruction. Instead, they chose the less intrusive ellipse visualization. Nevertheless, the heat map remained the preferred choice for retrospective analysis due to its more detailed information. Importantly, all visualizations were found to be useful and to help restore emotional connections in online learning. In conclusion, our innovative visualizations of crowd attention show considerable potential for a wide range of applications, extending beyond e-learning to all online presentations and retrospective analyses. The significant results of our study underscore the critical role these visualizations will play in enhancing both the effectiveness and emotional connectedness of future e-learning experiences, thereby facilitating the educational landscape.