{"title":"大规模对话反馈：学习分析设计建议","authors":"Bhagya Maheshi, Wei Dai, Roberto Martinez-Maldonado, Yi-Shan Tsai","doi":"10.1111/jcal.13034","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Feedback is central to formative assessments but aligns with a one-way information transmission perspective obstructing students' effective engagement with feedback. Previous research has shown that a responsive, dialogic feedback process that requires educators and students to engage in ongoing conversations can encourage student active engagement in feedback. However, it is challenging with larger student cohorts. Learning Analytics (LA) provides promising ways to facilitate timely feedback at scale by leveraging large datasets generated during students' learning. However, current LA design and implementation tend to treat feedback as a one-way transmission rather than a two-way process.</p>\n </section>\n \n <section>\n \n <h3> Objectives</h3>\n \n <p>This case study aims to improve LA design and practice to align with dialogic feedback principles by exploring an authentic dialogic feedback practice at scale.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>We explored a dialogic feedback practice of a course having 700 undergraduate students. The case study used quantitative and qualitative analysis methods to investigate what students expect from feedback, how educators respond to students' feedback requests, and how students experience feedback.</p>\n </section>\n \n <section>\n \n <h3> Results and Conclusions</h3>\n \n <p>The results emphasise the need to focus on cognitive, relational and emotional aspects of the feedback process. In aligning LA with dialogic feedback principles, we propose that LA should promote the following objectives: reflection, adaption, personalisation, emotional management, and scaffolding feedback provision.</p>\n </section>\n </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"40 6","pages":"2790-2808"},"PeriodicalIF":5.1000,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jcal.13034","citationCount":"0","resultStr":"{\"title\":\"Dialogic feedback at scale: Recommendations for learning analytics design\",\"authors\":\"Bhagya Maheshi, Wei Dai, Roberto Martinez-Maldonado, Yi-Shan Tsai\",\"doi\":\"10.1111/jcal.13034\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Feedback is central to formative assessments but aligns with a one-way information transmission perspective obstructing students' effective engagement with feedback. Previous research has shown that a responsive, dialogic feedback process that requires educators and students to engage in ongoing conversations can encourage student active engagement in feedback. However, it is challenging with larger student cohorts. Learning Analytics (LA) provides promising ways to facilitate timely feedback at scale by leveraging large datasets generated during students' learning. However, current LA design and implementation tend to treat feedback as a one-way transmission rather than a two-way process.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Objectives</h3>\\n \\n <p>This case study aims to improve LA design and practice to align with dialogic feedback principles by exploring an authentic dialogic feedback practice at scale.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>We explored a dialogic feedback practice of a course having 700 undergraduate students. The case study used quantitative and qualitative analysis methods to investigate what students expect from feedback, how educators respond to students' feedback requests, and how students experience feedback.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results and Conclusions</h3>\\n \\n <p>The results emphasise the need to focus on cognitive, relational and emotional aspects of the feedback process. 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Dialogic feedback at scale: Recommendations for learning analytics design
Background
Feedback is central to formative assessments but aligns with a one-way information transmission perspective obstructing students' effective engagement with feedback. Previous research has shown that a responsive, dialogic feedback process that requires educators and students to engage in ongoing conversations can encourage student active engagement in feedback. However, it is challenging with larger student cohorts. Learning Analytics (LA) provides promising ways to facilitate timely feedback at scale by leveraging large datasets generated during students' learning. However, current LA design and implementation tend to treat feedback as a one-way transmission rather than a two-way process.
Objectives
This case study aims to improve LA design and practice to align with dialogic feedback principles by exploring an authentic dialogic feedback practice at scale.
Methods
We explored a dialogic feedback practice of a course having 700 undergraduate students. The case study used quantitative and qualitative analysis methods to investigate what students expect from feedback, how educators respond to students' feedback requests, and how students experience feedback.
Results and Conclusions
The results emphasise the need to focus on cognitive, relational and emotional aspects of the feedback process. In aligning LA with dialogic feedback principles, we propose that LA should promote the following objectives: reflection, adaption, personalisation, emotional management, and scaffolding feedback provision.
期刊介绍：
The Journal of Computer Assisted Learning is an international peer-reviewed journal which covers the whole range of uses of information and communication technology to support learning and knowledge exchange. It aims to provide a medium for communication among researchers as well as a channel linking researchers, practitioners, and policy makers. JCAL is also a rich source of material for master and PhD students in areas such as educational psychology, the learning sciences, instructional technology, instructional design, collaborative learning, intelligent learning systems, learning analytics, open, distance and networked learning, and educational evaluation and assessment. This is the case for formal (e.g., schools), non-formal (e.g., workplace learning) and informal learning (e.g., museums and libraries) situations and environments. Volumes often include one Special Issue which these provides readers with a broad and in-depth perspective on a specific topic. First published in 1985, JCAL continues to have the aim of making the outcomes of contemporary research and experience accessible. During this period there have been major technological advances offering new opportunities and approaches in the use of a wide range of technologies to support learning and knowledge transfer more generally. There is currently much emphasis on the use of network functionality and the challenges its appropriate uses pose to teachers/tutors working with students locally and at a distance. JCAL welcomes: -Empirical reports, single studies or programmatic series of studies on the use of computers and information technologies in learning and assessment -Critical and original meta-reviews of literature on the use of computers for learning -Empirical studies on the design and development of innovative technology-based systems for learning -Conceptual articles on issues relating to the Aims and Scope
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