Why feedback literacy matters for learning analytics

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Abstract

Learning analytics (LA) provides data-driven feedback that aims to improve learning and inform action. For learners, LA-based feedback may scaffold self-regulated learning skills, which are crucial to learning success. For teachers, LA-based feedback may help the evaluation of teaching effects and the need for interventions. However, the current development of LA has presented problems related to the cognitive, social-affective, and structural dimensions of feedback. In light of this, this position paper argues that attention needs to shift from the design of LA as a feedback product to one that facilitates a process in which both teachers and students play active roles in meaning-making. To this end, implications for feedback literacy in the context of LA are discussed.

Original languageEnglish
Title of host publicationICLS Proceedings, 16th International Conference of the Learning Sciences (ICLS) 2022
EditorsClark Chinn, Edna Tan, Carol Chan, Yael Kali
Place of PublicationGothenburg Sweden
PublisherInternational Society of the Learning Sciences
Pages27-34
Number of pages8
ISBN (Electronic)9781737330653
Publication statusPublished - 2022
EventInternational Conference of the Learning Sciences 2022 - Hiroshima, Japan
Duration: 6 Jun 202210 Jun 2022
Conference number: 16th
https://2022.isls.org/proceedings/ (Proceedings)
https://2022.isls.org (Website)

Publication series

NameProceedings of International Conference of the Learning Sciences, ICLS
PublisherInternational Society of the Learning Science
ISSN (Print)1814-9316

Conference

ConferenceInternational Conference of the Learning Sciences 2022
Abbreviated titleICLS 2022
Country/TerritoryJapan
CityHiroshima
Period6/06/2210/06/22
Internet address

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