Examining and Scaffolding Collective Idea Improvement in Knowledge Building Using Analytics and Meta-Discourse

Abstract

Knowledge Building (KB) engages students in meta-discourse to improve collective ideas. Multiple studies have examined the roles of learning analytical tools in supporting meta-discourse, while this study focused on the supportive roles of the KF-embedded tools. We designed a learning environment that engages meta-discourse among students with the assistance of word cloud and idea-building tools, both of which are embedded in KF. A total of 22 Singapore secondary school students participated in a six-weeks long study to learn photosynthesis in a KB learning environment. We adopted social network, inferential statistical, and semantic analyses. The results show that students' learning gain is correlated with the number of posts in KF. In addition, the Learning Analytics-augmented meta-discourse supported students' KF participation and collective idea improvement. Qualitative analysis showed how students engaged in meta-discourse sessions. The methodological and practical contributions were discussed.