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Table · dataset · 2026

Data Sheet 1_A readiness-informed design framework for stabilizing collaborative learning in heterogeneous STEM classrooms.zip

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Introduction<p>Collaborative learning is widely used in STEM education, but its effectiveness is often challenged in heterogeneous classrooms where students differ in prior knowledge, technical experience, and readiness for participation.

Description

This study developed and examined a readiness-informed design framework for stabilizing collaborative learning through structured grouping, role-based accountability, and checkpoint-supported feedback.</p>Methods<p>A design-based implementation study with mixed-methods evaluation was conducted in a biomedical engineering Modern Microscopy course.

Two intact course conditions were compared: free grouping and structured heterogeneous grouping. Data included readiness profiles, group reports, practical performance assessments, questionnaire responses, interviews, process records, and scoring reliability analyses.</p>Results<p>Descriptive group-level patterns favored the structured grouping condition in several outcomes, but bootstrap confidence intervals were wide because the effective group-level sample size was small; therefore, these findings were interpreted as design-based evidence rather than as formal evidence of causal effectiveness.

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Qualitative and process evidence indicated that role accountability, guided peer explanation, and checkpointed revision supported broader participation and more explicit evidence-based reasoning among students with different readiness levels.</p>Discussion<p>This study provides a practical and adaptable framework for instructors seeking to organize heterogeneous STEM groups without fixed ability labeling. The findings suggest that collaborative learning stability can be intentionally designed through structured participation mechanisms, offering a low-cost approach for laboratory, project-based, and design-oriented STEM education.</p>

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Microscopy 75%
Provenance · 1 source records, 18 field assertions
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