Dialogic knowledge building in learning communities

In modern education, there has been an increasing emphasis on creative thinking, collaborative problem-solving and critical discussion. In this chapter, I argue that learning communities foster these skills and thus provide a strong foundation for deep learning; i.e. learning that is based on deep reasoning and active knowledge building as defined by Krathwohl (2002), Chi and Ohlsson (2005) and Sfard (2001). Furthermore, learning communities cater to the learner’s main psychological needs for autonomy, competence and relatedness (ACR) (Deci and Ryan 1985). This is important, since ACR fulfillment facilitates deep learning by providing the ground for active knowledge building in the teaching and learning interaction. An analysis of an authentic teaching and learning interaction, in which a student is taught about an electric circuit, shows how the teacher facilitates deep learning through selected communicative means; e.g. questions that scaffold deep reasoning along higher cognitive processes like ‘evaluating’ and ‘creating’. An in-depth analysis of selected sequences in the interaction leads to a communicative model for deep learning, which I call ‘Dialogic Knowledge Building’ (DKB). DKB revolves around question-answer sequences that promote the learner’s re-representation of knowledge in terms of complex conceptualizations.

• Affiliations: 1: A*STAR, Institute of High Performance Computing, Singapore