Students' sense-making of personalised feedback based on learning analytics

Lim, L-A; Dawson, S; Gasevic, D; Joksimovic, S; Fudge, A; Pardo, A; Gentili, S

Students' sense-making of personalised feedback based on learning analytics

Lim, L-A Dawson, S Gasevic, D Joksimovic, S Fudge, A Pardo, A Gentili, S

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Publisher:: AUSTRALASIAN SOC COMPUTERS LEARNING TERTIARY EDUCATION-ASCILITE
Publication Type:: Journal Article
Citation:: AUSTRALASIAN JOURNAL OF EDUCATIONAL TECHNOLOGY, 2020, 36, (6), pp. 15-33
Issue Date:: 2020-01-01

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Field	Value	Language
dc.contributor.author	Lim, L-A
dc.contributor.author	Dawson, S
dc.contributor.author	Gasevic, D
dc.contributor.author	Joksimovic, S
dc.contributor.author	Fudge, A
dc.contributor.author	Pardo, A
dc.contributor.author	Gentili, S
dc.date.accessioned	2021-03-31T02:24:11Z
dc.date.available	2021-03-31T02:24:11Z
dc.date.issued	2020-01-01
dc.identifier.citation	AUSTRALASIAN JOURNAL OF EDUCATIONAL TECHNOLOGY, 2020, 36, (6), pp. 15-33
dc.identifier.issn	1449-3098
dc.identifier.issn	1449-5554
dc.identifier.uri	http://hdl.handle.net/10453/147716
dc.description.abstract	<jats:p>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. Implications for practice or policy: Personalised feedback based on learning analytics should be informed by an understanding of students’ self-regulated learning. Instructors implementing personalised feedback should align this closely with the course curriculum. Instructors implementing personalised feedback in their courses should consider the relational element of feedback by using a positive tone. Personalised feedback can be further enhanced by increasing the dialogic element and by including more information about learning strategies. </jats:p>
dc.language	English
dc.publisher	AUSTRALASIAN SOC COMPUTERS LEARNING TERTIARY EDUCATION-ASCILITE
dc.relation.ispartof	AUSTRALASIAN JOURNAL OF EDUCATIONAL TECHNOLOGY
dc.relation.isbasedon	10.14742/ajet.6370
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0906 Electrical and Electronic Engineering, 1302 Curriculum and Pedagogy, 1303 Specialist Studies in Education
dc.subject.classification	Education
dc.title	Students' sense-making of personalised feedback based on learning analytics
dc.type	Journal Article
utslib.citation.volume	36
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	1302 Curriculum and Pedagogy
utslib.for	1303 Specialist Studies in Education
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	1302 Curriculum and Pedagogy
utslib.for	1303 Specialist Studies in Education
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (Teaching and Learning)
utslib.copyright.status	open_access	*
dc.date.updated	2021-03-31T02:24:10Z
pubs.issue	6
pubs.publication-status	Published
pubs.volume	36
utslib.citation.issue	6

Abstract:

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. Implications for practice or policy: Personalised feedback based on learning analytics should be informed by an understanding of students’ self-regulated learning. Instructors implementing personalised feedback should align this closely with the course curriculum. Instructors implementing personalised feedback in their courses should consider the relational element of feedback by using a positive tone. Personalised feedback can be further enhanced by increasing the dialogic element and by including more information about learning strategies.

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http://hdl.handle.net/10453/147716