Effects of internal and external conditions on strategies of self-regulated learning: a learning analytics study

Namrata Srivastava, Yizhou Fan, Mladen Rakovic, Shaveen Singh, Jelena Jovanovic, Joep Van Der Graaf, Lyn Lim, Surya Surendrannair, Jonathan Kilgour, Inge Molenaar, Maria Bannert, Johanna Moore, Dragan Gasevic

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

1 Citation (Scopus)

Abstract

Self-regulated learning (SRL) skills are essential for successful learning in a technology-enhanced learning environment. Learning Analytics techniques have shown a great potential in identifying and exploring SRL strategies from trace data in various learning environments. However, these strategies have been mainly identified through analysis of sequences of learning actions, and thus interpretation of the strategies is heavily task and context dependent. Further, little research has been done on the association of SRL strategies with different influencing factors or conditions. To address these gaps, we propose an analytic method for detecting SRL strategies from theoretically supported SRL processes and applied the method to a dataset collected from a multi-source writing task. The detected SRL strategies were explored in terms of their association with the learning outcome, internal conditions (prior-knowledge, metacognitive knowledge and motivation) and external conditions (scaffolding). The study results showed our analytic method successfully identified three theoretically meaningful SRL strategies. The study results revealed small effect size in the association between the internal conditions and the identified SRL strategies, but revealed a moderate effect size in the association between external conditions and the SRL strategy use.

Original languageEnglish
Title of host publicationLAK22 Conference Proceedings
EditorsAlyssa Friend Wise, Roberto Martinez-Maldonado, Isabel Hilliger
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages392-403
Number of pages12
ISBN (Electronic)9781450395731
DOIs
Publication statusPublished - 2022
EventInternational Conference on Learning Analytics and Knowledge 2022: Learning Analytics for Transition, Disruption and Social Change - Online, United States of America
Duration: 21 Mar 202225 Mar 2022
Conference number: 12th
https://dl.acm.org/doi/proceedings/10.1145/3506860 (Proceedings)

Conference

ConferenceInternational Conference on Learning Analytics and Knowledge 2022
Abbreviated titleLAK 2022
Country/TerritoryUnited States of America
Period21/03/2225/03/22
Internet address

Keywords

  • Learning analytics
  • Scaffolding
  • Self-regulated learning
  • SRL strategies

Cite this