Please use this identifier to cite or link to this item: http://hdl.handle.net/10497/24108
Title: 
Authors: 
Keywords: 
Collaborative inquiry-based learning (CIBL)
Science
Learning analytics
High- and low-performance groups
M-orchestrate app
Collaborative problem-solving
Issue Date: 
2022
Citation: 
Song, Y., Cao, J., Yang, Y., & Looi, C.-K. (2022). Mapping primary students' mobile collaborative inquiry-based learning behaviours in science collaborative problem solving via learning analytics. International Journal of Educational Research, 114, Article 101992. https://doi.org/10.1016/j.ijer.2022.101992
Journal: 
International Journal of Educational Research
Abstract: 
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.
URI: 
ISSN: 
0883-0355
DOI: 
Grant ID: 
General Research Fund (GRF): Ref. 18610817
Dean's Research Fund (Ref. IDS-3 / 7th round)
Funding Agency: 
Research Grants Council, University Grant Committee, Hong Kong
The Education University of Hong Kong
File Permission: 
Embargo_20240601
File Availability: 
With file
Appears in Collections:Journal Articles

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  Until 2024-06-01
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