Analytics of planning behaviours in self-regulated learning: Links with strategy use and prior knowledge

Tongguang Li, Yizhou Fan, Namrata Srivastava, Zijie Zeng, Xinyu Li, Hassan Khosravi, Yi-Shan Tsai, Zachari Swiecki, Dragan Gašević

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

Abstract

A sophisticated grasp of self-regulated learning (SRL) skills has become essential for learners in computer-based learning environment (CBLE). One aspect of SRL is the plan-making process, which, although emphasized in many SRL theoretical frameworks, has attracted little research attention. Few studies have investigated the extent to which learners complied with their planned strategies, and whether making a strategic plan is associated with actual strategy use. Limited studies have examined the role of prior knowledge in predicting planned and actual strategy use. In this study, we developed a CBLE to collect trace data, which were analyzed to investigate learners' plan-making process and its association with planned and actual strategy use. Analysis of prior knowledge and trace data of 202 participants indicated that 1) learners tended to adopt strategies that significantly deviated from their planned strategies, 2) the level of prior knowledge was associated with planned strategies, and 3) neither the act of plan-making nor prior knowledge predicted actual strategy use. These insights bear implications for educators and educational technologists to recognise the dynamic nature of strategy adoption and to devise approaches that inspire students to continually revise and adjust their plans, thereby strengthening SRL.

Original languageEnglish
Title of host publicationLAK 2024 Conference Proceedings - The Fourteenth International Conference on Learning Analytics & Knowledge
EditorsSrecko Joksimovic, Andrew Zamecnik
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages438-449
Number of pages12
ISBN (Electronic)9798400716188
DOIs
Publication statusPublished - 2024
EventInternational Learning Analytics & Knowledge Conference 2024 - Kyoto, Japan
Duration: 18 Mar 202422 Mar 2024
Conference number: 14th
https://dl.acm.org/doi/proceedings/10.1145/3636555 (Conference Proceedings)
https://www.solaresearch.org/events/lak/lak24/
https://ceur-ws.org/Vol-3667/ (LAK 2024 Workshop Proceedings)

Conference

ConferenceInternational Learning Analytics & Knowledge Conference 2024
Abbreviated titleLAK 2024
Country/TerritoryJapan
CityKyoto
Period18/03/2422/03/24
Internet address

Keywords

  • learning analytics
  • learning strategies
  • self-regulated learning
  • strategic planning

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