Catalyst for co-construction: the role of AI-directed speech recognition technology in the self-organization of knowledge

This study examines how AI-directed speech recognition technology (generating real-time word clouds from oral discussions) scaffolds knowledge co-construction among pre-service teachers in a science education context, analyzing the process through social system self-organization theory. The research investigates how visual artifacts from speech recognition trigger self-organization characteristics like increased information exchange, far-from-equilibrium states, and crystallization of group thinking.

The purpose of this study was to analyze knowledge co-construction as a self-organization process and the role of technology as its catalyst. Novel AI-directed speech recognition technology and the artifacts it generates were deployed to scaffold the knowledge co-construction process in two groups of pre-service teachers in a science education context. Throughout the lesson, the focus of the learning tasks was on pedagogical content knowledge and students' preconceptions. Analysis was conducted

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