{"title":"教师对使用增强现实增强分析法衡量学生脱离课堂情况的看法","authors":"Manjeet Singh, Shaun Bangay, Atul Sajjanhar","doi":"10.3390/mti7120116","DOIUrl":null,"url":null,"abstract":"There are various ways that teachers manage student disengagement levels during their class lessons, and managing disengagement can be both stressful and challenging, especially since each student is unique. Methods and techniques utilised are specific to teachers’ own experience level, subject knowledge, and teaching styles. We report on the techniques and methods teachers utilise to identify, mitigate, and measure student disengagement during class lessons; the paper presents the results of a mixed-methods, multisession study design comprising gathered qualitative and quantitative data to enable a greater understanding. Eight educators who were full-time educators with varying years of experience from three different schools, who taught or had taught English, maths, and science subjects at the primary school level, participated in this study. The study also observed that teachers used three AR applications and collected valuable feedback on their perspectives by using analytics generated by AR applications to help manage student disengagement. A postsession survey tool was used to gather the perceived importance and ranking of the techniques and methods discussed by the teachers during the previous sessions. The results showed that the majority of teachers deemed spending “Time on Tasks” and giving “Feedback/Reflections” most suited for measuring disengagement, and encouraging “Movement” and use of “Technology” emerged as the most favoured for mitigating disengagement. For utilising AR enhanced analytics in mitigating and measuring student disengagement, the data suggested a difference in perspectives based on teachers’ teaching levels, especially concerning conversations and the use of technology devices. The study did not find conclusive evidence of differences based on teachers’ teaching subjects and there was a notable distinction in building positive relationships among English teachers. This leads to the suggestion that subject-specific pedagogy might influence the perceived effectiveness of using AR-generated analytics in mitigating and measuring student disengagement.","PeriodicalId":52297,"journal":{"name":"Multimodal Technologies and Interaction","volume":"16 5","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Teachers’ Perspectives on Using Augmented-Reality-Enhanced Analytics as a Measure of Student Disengagement\",\"authors\":\"Manjeet Singh, Shaun Bangay, Atul Sajjanhar\",\"doi\":\"10.3390/mti7120116\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There are various ways that teachers manage student disengagement levels during their class lessons, and managing disengagement can be both stressful and challenging, especially since each student is unique. Methods and techniques utilised are specific to teachers’ own experience level, subject knowledge, and teaching styles. We report on the techniques and methods teachers utilise to identify, mitigate, and measure student disengagement during class lessons; the paper presents the results of a mixed-methods, multisession study design comprising gathered qualitative and quantitative data to enable a greater understanding. Eight educators who were full-time educators with varying years of experience from three different schools, who taught or had taught English, maths, and science subjects at the primary school level, participated in this study. The study also observed that teachers used three AR applications and collected valuable feedback on their perspectives by using analytics generated by AR applications to help manage student disengagement. A postsession survey tool was used to gather the perceived importance and ranking of the techniques and methods discussed by the teachers during the previous sessions. The results showed that the majority of teachers deemed spending “Time on Tasks” and giving “Feedback/Reflections” most suited for measuring disengagement, and encouraging “Movement” and use of “Technology” emerged as the most favoured for mitigating disengagement. For utilising AR enhanced analytics in mitigating and measuring student disengagement, the data suggested a difference in perspectives based on teachers’ teaching levels, especially concerning conversations and the use of technology devices. The study did not find conclusive evidence of differences based on teachers’ teaching subjects and there was a notable distinction in building positive relationships among English teachers. This leads to the suggestion that subject-specific pedagogy might influence the perceived effectiveness of using AR-generated analytics in mitigating and measuring student disengagement.\",\"PeriodicalId\":52297,\"journal\":{\"name\":\"Multimodal Technologies and Interaction\",\"volume\":\"16 5\",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2023-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Multimodal Technologies and Interaction\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/mti7120116\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Multimodal Technologies and Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/mti7120116","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
摘要
教师在课堂上管理学生脱离课堂的程度有多种方法,管理学生脱离课堂既有压力又有挑战性,特别是因为每个学生都是独一无二的。所使用的方法和技巧与教师自身的经验水平、学科知识和教学风格有关。我们报告了教师在课堂教学中识别、缓解和衡量学生脱离课堂情况的技巧和方法;本文介绍了混合方法、多时段研究设计的结果,包括收集的定性和定量数据,以便加深理解。来自三所不同学校的八位具有不同工作年限的全职教育工作者参与了本研究,他们在小学阶段教授或曾经教授过英语、数学和科学科目。研究还观察到,教师使用了三种 AR 应用程序,并通过使用 AR 应用程序生成的分析数据收集了宝贵的反馈意见,以帮助管理学生的脱离情况。研究使用了课后调查工具,以收集教师对前几节课所讨论的技巧和方法的认知重要性和排名。结果显示,大多数教师认为 "花时间完成任务 "和 "反馈/反思 "最适合用来衡量脱离情况,而鼓励 "运动 "和使用 "技术 "则是最受欢迎的缓解脱离情况的方法。对于利用增强现实技术分析来缓解和衡量学生脱离课堂的情况,数据表明,教师的教学水平不同,其观点也不同,特别是在对话和使用技术设备方面。研究并未发现教师教学科目差异的确凿证据,但英语教师在建立积极关系方面存在明显差异。这就表明,特定学科的教学法可能会影响使用 AR 生成的分析在缓解和衡量学生脱离课堂情况方面的效果。
Teachers’ Perspectives on Using Augmented-Reality-Enhanced Analytics as a Measure of Student Disengagement
There are various ways that teachers manage student disengagement levels during their class lessons, and managing disengagement can be both stressful and challenging, especially since each student is unique. Methods and techniques utilised are specific to teachers’ own experience level, subject knowledge, and teaching styles. We report on the techniques and methods teachers utilise to identify, mitigate, and measure student disengagement during class lessons; the paper presents the results of a mixed-methods, multisession study design comprising gathered qualitative and quantitative data to enable a greater understanding. Eight educators who were full-time educators with varying years of experience from three different schools, who taught or had taught English, maths, and science subjects at the primary school level, participated in this study. The study also observed that teachers used three AR applications and collected valuable feedback on their perspectives by using analytics generated by AR applications to help manage student disengagement. A postsession survey tool was used to gather the perceived importance and ranking of the techniques and methods discussed by the teachers during the previous sessions. The results showed that the majority of teachers deemed spending “Time on Tasks” and giving “Feedback/Reflections” most suited for measuring disengagement, and encouraging “Movement” and use of “Technology” emerged as the most favoured for mitigating disengagement. For utilising AR enhanced analytics in mitigating and measuring student disengagement, the data suggested a difference in perspectives based on teachers’ teaching levels, especially concerning conversations and the use of technology devices. The study did not find conclusive evidence of differences based on teachers’ teaching subjects and there was a notable distinction in building positive relationships among English teachers. This leads to the suggestion that subject-specific pedagogy might influence the perceived effectiveness of using AR-generated analytics in mitigating and measuring student disengagement.