Abstract of Invited Speech

Promoting epistemic cognition in knowledge building: Discourse, tools, and analytics
Bodong Chen
University of Minnesota–Twin Cities, USA

Epistemic cognition is about people's thinking about what they know and how they come to know. As a constructivist approach with unique onto-epistemological underpinnings, Knowledge Building (KB; Scardamalia & Bereiter, 2014) is deeply invested in facilitating epistemic cognition of learners. For example, the inculturation of learners into KB's theory-building discourse involves the exploration and development of learners' epistemic views; KB's supporting technology---Knowledge Forum---is built with epistemic scaffolds to promote epistemic diversity in the theory-building discourse. In this talk, I will discuss a line of research that aims to design discourse practices, tools, metrics, and analytics to promote epistemic cognition in KB. In the first study, we designed a "Discourse Moves tool" that visualizes epistemic diversity in a KB community. With this tool, we engaged a second grade class in metadiscourse about their discourse moves and salient concepts. Results indicated second graders' capability in reflecting on their epistemic moves and taking actions to enrich the epistemic diversity of their community. In the second study, I introduce my recent work on applying Network Science techniques to develop network representations of discourse data and derive network-based metrics of epistemic cognition. In this work, I conceptualize theory-building discourse in KB as a dynamic, multidimensional network involving epistemic agents, epistemic moves, ideas, and concepts. Epistemic cognition---of either an individual and a collective---is reflected in "meta-paths" and structural patterns of the multidimensional network. I will introduce nascent network-based metrics of epistemic cognition in KB discourse and discuss plans of developing analytics tools based on these metrics to promote epistemic cognition.

Invited Speaker

Prof. Bodong Chen (University of Minnesota, USA)

Bodong Chen is an Associate Professor at the University of Minnesota–Twin Cities. He holds the Bonnie Westby Huebner Endowed Chair in Education & Technology and is the inaugural Director of the Learning Informatics Lab. His researches sits at the intersection of learning sciences, learning analytics, online learning, and network science. He develops digital learning environments and pedagogical practices for collaborative knowledge building. He also derives graph metrics of knowledge building discourse, applies relational event modeling to examining social dynamics in online discussions, and uses data mining to investigate teacher professional learning in MOOCs. He obtained his BSc from Beijing Normal University (2006), MEd from Peking University (2009), and PhD from the University of Toronto (2014).