Boundary conditions of collaborative learning using worked-examples: joint moderating effects of task-specific prior knowledge and task complexity on transfer performance and cognitive load

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Abstract
When collaborative learning facilitates learning, remains a central question in educational research. Grounded in cognitive load theory, this study examined whether the effectiveness of collaborative, relative to individual, learning from worked-examples is jointly moderated by learners’ experimentally induced task-specific prior knowledge and task complexity. A 2 (task-specific prior knowledge: low vs. high) × 2 (task complexity: low vs. high) × 2 (learning condition: individual vs. collaborative) mixed design was employed, with task complexity as a within-subjects factor. A total of 134 fifth-grade students participated in the study. They studied mathematical worked-examples of varying complexity, either individually or collaboratively, and then completed near-transfer and far-transfer tests as well as cognitive load ratings. Results showed a significant three-way interaction among task-specific prior knowledge, task complexity, and learning condition for near-transfer, indicating that the effect of learning condition depended jointly on learners’ task-specific prior knowledge and task complexity. Specifically, under high task complexity, collaborative learning outperformed individual learning among learners with high task-specific prior knowledge, whereas no stable collaborative advantage was found for learners with low task-specific prior knowledge. For far-transfer, the main effects of task-specific prior knowledge and task complexity were significant, whereas the main effect of learning condition and all interaction effects did not reach statistical significance. Thus, collaborative learning did not show a stable advantage in far-transfer tasks. The cognitive load results provided supportive evidence for understanding the differences in transfer performance: students in the collaborative learning condition reported lower subjective cognitive load than those in the individual learning condition, and high complexity tasks elicited higher cognitive load than low complexity tasks. Overall, the findings suggest that the effectiveness of collaboration in learning from worked-examples is conditional rather than universal. Its benefits depend on the fit between task complexity and learners’ task-specific prior knowledge. The study provides empirical evidence on the boundary conditions of collaborative learning in elementary mathematics instruction through worked examples and contributes to a better understanding of when collaborative learning is most effective.

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