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

Autor: Dragan Gašević, Jelena Jovanovic, Yizhou Fan, Shaveen Singh, John Saint
Rok vydání: 2021
Předmět:
Zdroj: LAK21: 11th International Learning Analytics and Knowledge Conference, pp. 184-195
LAK
LAK21: 11th International Learning Analytics and Knowledge Conference, 184-195. [S.l.] : Association for Computing Machinery (ACM)
STARTPAGE=184;ENDPAGE=195;TITLE=LAK21: 11th International Learning Analytics and Knowledge Conference
Popis: Item does not contain fulltext 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. LAK21: 11th International Learning Analytics and Knowledge Conference (Irvine, CA, USA, 12-16 April, 2021)
Databáze: OpenAIRE