An Assessment of Idea Emergence in Subject-Matter Collaborative Learning

Abstract

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Idea emergence is critical in learning as knowledge creation. Although recent advancements make it possible to detect emergent ideas and evaluate how students engage in knowledge creation in collaborative learning contexts, the relationship between the learning processes and final conceptual understanding has not been well-studied. One confounding factor is how much students engage in their study topic during collaboration. In this study, therefore, we propose a new procedure for evaluating idea emergence in the context of jigsaw instruction by combining a socio-semantic network analysis of discourse and a text-mining algorithm, “the term-frequency.” This procedure was used to evaluate how high-school learners engaged in their social process of knowledge creation as well as how much they discuss their study topics, the human immune system. Results showed that the weight of priority on a study topic did not significantly differ in both high and low conceptual understanding groups, but high conceptual understanding groups were more engaged in sharing and discussing ideas in the early stage of their collaboration. It is suggested that students' recognition of the study topic was not different depending on the levels of their conceptual understanding in a well-structured collaborative learning context such as jigsaw instruction. However, what matters is how students discuss their ideas through collaborative discourse.

Keywords

• assessment
• idea emergence
• subject-matter
• collaborative learning
• socio-semantic network analysis
• text-mining algorithm