A learning analytic approach to unveiling self-regulatory processes in learning tactics

Yizhou Fan, John Saint, Shaveen Singh, Jelena Jovanovic, Dragan Gašević

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

Investigation of learning tactics and strategies has received increasing attention by the Learning Analytics (LA) community. While previous research efforts have made notable contributions towards identifying and understanding learning tactics from trace data in various blended and online learning settings, there is still a need to deepen our understanding about learning processes that are activated during the enactment of distinct learning tactics. In order to fill this gap, we propose a learning analytic approach to unveiling and comparing self-regulatory processes in learning tactics detected from trace data. Following this approach, we detected four learning tactics (Reading with Quiz Tactic, Assessment and Interaction Tactic, Short Login and Interact Tactic and Focus on Quiz Tactic) as used by 728 learners in an undergrad course. We then theorised and detected five micro-level processes of self-regulated learning (SRL) through an analysis of trace data. We analysed how these micro-level SRL processes were activated during enactment of the four learning tactics in terms of their frequency of occurrence and temporal sequencing. We found significant differences across the four tactics regarding the five micro-level SRL processes based on multivariate analysis of variance and comparison of process models. In summary, the proposed LA approach allows for meaningful interpretation and distinction of learning tactics in terms of the underlying SRL processes. More importantly, this approach shows the potential to overcome the limitations in the interpretation of LA results which stem from the context-specific nature of learning. Specifically, the study has demonstrated how the interpretation of LA results and recommendation of pedagogical interventions can also be provided at the level of learning processes rather than only in terms of a specific course design.

Original languageEnglish
Title of host publicationLAK21 Conference Proceedings - The Impact we Make: The contributions of learning analytics to learning
Subtitle of host publicationThe Eleventh International Conference on Learning Analytics & Knowledge
EditorsMaren Scheffel, Nia Dowell, Srecko Joksimovic, George Siemens
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages184-195
Number of pages12
ISBN (Electronic)9781450389358
DOIs
Publication statusPublished - 2021
EventInternational Learning Analytics & Knowledge Conference 2021 - Online, Irvine, United States of America
Duration: 12 Apr 202116 Apr 2021
Conference number: 11th
https://www.solaresearch.org/events/lak/lak21/
https://dl.acm.org/doi/proceedings/10.1145/3448139 (Proceedings)

Conference

ConferenceInternational Learning Analytics & Knowledge Conference 2021
Abbreviated titleLAK 2021
CountryUnited States of America
CityIrvine
Period12/04/2116/04/21
Internet address

Keywords

  • Learning analytics
  • Learning tactic
  • Process model
  • Self-regulated learning

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