Dynamic Network Analysis of Knowledge-Building Discourse
Knowledge Building (KB) as a pedagogy requires sustained effort from a learner community to improve its ideas. KB discourse that mediates such efforts is conceptualized as an interactive, dynamic system involving epistemic agents (e.g., learners), knowledge objects and sociocognitive practices – with the relationships among them explicated by a set of pedagogical principles (Scardamalia, 2002). So far, much work has committed to the extraction of analytical measures for understanding various aspects of KB discourse. In this talk, Dr. Chen will present an early effort of applying dynamic network analysis (DNA) to develop a more holistic understanding of KB discourse.
Dr. Bodong Chen is an assistant professor in Learning Technologies at the University of Minnesota. His research sits at the intersection of learning sciences, online learning and learning analytics. He designs CSCL environments to foster higher-order competencies, analyzes learning experiences in MOOCs and develops analytics to facilitate reflective engagement in educational discourse. His new NSF project looks for ways to transform scientific discourse in high school classrooms with the broader cyberspace.