An Integrated Model of Feedback and Assessment: From fine grained to holistic programmatic review

LAK2023: LAK23: 13th International Learning Analytics and Knowledge Conference(2023)

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摘要
Abstract: Research in learning analytics (LA) has long held a strong interest in improving student self-regulated learning and measuring the impact of feedback on student outcomes. Despite more than a decade of work in this space very little is known around the contextual factors that influence the topics and diversity of feedback and assessment a student encounters during their full program of study. This paper presents research investigating the institutional adoption of a personalized feedback tool. The reported findings illustrate an association between the topics of feedback, student performance, year level of the course and discipline. The results highlight the need for LA research to capture feedback, assessment and learning outcomes over an entire program of study. Herein we propose a more integrated model drawing on contemporary understandings of feedback with current research findings. The goal is to push LA towards addressing more complex teaching and learning processes from a systems lens. The model posed in this paper begins to illustrate where and how LA can address noted deficits in education practice to better understand how feedback and assessment are enacted by instructors and interpreted by students.
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