Journal
INTERNATIONAL JOURNAL OF EDUCATIONAL RESEARCH
Volume 114, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.ijer.2022.101992
Keywords
Collaborative inquiry-based learning (CIBL); Science; Learning analytics; High; and low-performance groups; M-orchestrate app; collaborative problem-solving
Categories
Funding
- Research Grants Council, University Grant Committee, Hong Kong [18610817]
- Education University of Hong Kong [IDS-3 / 7th round]
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This study examines how primary students conducted collaborative inquiry-based learning activities supported by a mobile app during the COVID-19 pandemic. Using learning analytics, the researchers analyzed the behaviors of different groups and identified common and different features. The findings can inform teachers in refining their teaching design and researchers in developing scaffolding tools to enhance students' collaborative problem-solving skills.
This article reports on a study focusing on understanding how primary students conducted collaborative inquiry-based learning (CIBL) supported by a mobile app during the COVID-19 pandemic when all lessons were conducted online. Learning analytics (LA) were used to map students' behaviours in CIBL activities. One class with 35 students in Grade 4 participated in this study. Log data was collected and analysed using learning analytics with process mining techniques to understand groups' CIBL behaviours in a mobile learning environment. The findings revealed high- and low-performance groups' common and different features of CIBL behaviours. The research findings can help inform both teachers of making pedagogical refinement in the CIBL activity design, and researchers of developing scaffolding tools at different phases of CIBL on the mobile learning app to enhance students' collaborative problem-solving skills.
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