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Which factors matter in data-driven peer learning: Social intimacy, proficiency gaps, or selection autonomy?
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DOI：10.1016/j.caeo.2026.100402.png)
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Abstract
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• We implemented a data-driven peer learning system in a real-world higher education course. • Data-driven pairing reduced friendship-driven bias and created pairs with larger proficiency gaps. • Larger proficiency gaps reduced rereading effort in data-driven peer learning, suggesting higher task efficiency. • Learning gains and writing improvements did not differ significantly across conditions. • The study identified proficiency gap and partner-selection autonomy as key factors shaping online peer learning processes.
Keywords:
Peer learning
Social intimacy
Data-driven system
Partner selection
Learner autonomy
Knowledge gap
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