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Students' sense-making of personalised feedback based on learning analytics
Although technological advances have brought about new opportunities for scaling feedback to students, there remain challenges in how such feedback is presented and interpreted. There is a need to better understand how students make sense of such feedback to adapt self-regulated learning processes....
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Published in: | Australasian Journal of Educational Technology 2020-01, Vol.36 (6), p.15-33 |
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container_title | Australasian Journal of Educational Technology |
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creator | Lim, Lisa-Angelique Dawson, Shane Gaševic, Dragan Joksimovic, Srecko Fudge, Anthea Pardo, Abelardo Gentili, Sheridan |
description | Although technological advances have brought about new opportunities for scaling feedback to students, there remain challenges in how such feedback is presented and interpreted. There is a need to better understand how students make sense of such feedback to adapt self-regulated learning processes. This study examined students' sense-making of learning analytics-based personalised feedback across four courses. Results from a combination of thematic analysis and epistemic network analysis show an association between student perceptions of their personalised feedback and how these map to subsequent self-described self-regulated learning processes. Most notably, the results indicate that personalised feedback, elaborated by personal messages from course instructors, helps students refine or strengthen important forethought processes of goal-setting, as well as to reduce procrastination. The results highlight the need for instructors to increase the dialogic element in personalised feedback in order to reduce defensive reactions from students who hold to their own learning strategies. This approach may prompt reflection on the suitability of students' current learning strategies and achievement of associated learning goals. [Author abstract] |
doi_str_mv | 10.14742/ajet.6370 |
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There is a need to better understand how students make sense of such feedback to adapt self-regulated learning processes. This study examined students' sense-making of learning analytics-based personalised feedback across four courses. Results from a combination of thematic analysis and epistemic network analysis show an association between student perceptions of their personalised feedback and how these map to subsequent self-described self-regulated learning processes. Most notably, the results indicate that personalised feedback, elaborated by personal messages from course instructors, helps students refine or strengthen important forethought processes of goal-setting, as well as to reduce procrastination. The results highlight the need for instructors to increase the dialogic element in personalised feedback in order to reduce defensive reactions from students who hold to their own learning strategies. This approach may prompt reflection on the suitability of students' current learning strategies and achievement of associated learning goals. [Author abstract]</description><identifier>ISSN: 1449-5554</identifier><identifier>ISSN: 1449-3098</identifier><identifier>EISSN: 1449-5554</identifier><identifier>DOI: 10.14742/ajet.6370</identifier><language>eng</language><publisher>Wollongong: Australasian Society for Computers in Learning in Tertiary Education</publisher><subject>Data analysis ; Data Collection ; Dialogs (Language) ; Electronic Mail ; Feedback ; Foreign Countries ; Goal Orientation ; Higher education ; Independent study ; Individualized Instruction ; Interpersonal Communication ; Learning ; Learning Analytics ; Learning Processes ; Learning Strategies ; Network analysis ; Nontraditional Students ; Personalised feedback ; Research Universities ; Self Management ; Student Attitudes ; Student Motivation ; Student perceptions ; Students ; Teacher Student Relationship ; Thematic approach ; Time Management ; Undergraduate Students</subject><ispartof>Australasian Journal of Educational Technology, 2020-01, Vol.36 (6), p.15-33</ispartof><rights>2020. 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subjects | Data analysis Data Collection Dialogs (Language) Electronic Mail Feedback Foreign Countries Goal Orientation Higher education Independent study Individualized Instruction Interpersonal Communication Learning Learning Analytics Learning Processes Learning Strategies Network analysis Nontraditional Students Personalised feedback Research Universities Self Management Student Attitudes Student Motivation Student perceptions Students Teacher Student Relationship Thematic approach Time Management Undergraduate Students |
title | Students' sense-making of personalised feedback based on learning analytics |
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