65.063 - Theory-Driven Design of Online Learning Systems, Data Structures, and Analytic Techniques

Session Type: Symposium

Abstract

Online systems have much potential to transform educational practice by personalizing learning, bringing together students from geographically distant locations, and delivering just-in-time feedback to students and teachers. Recent years have brought an explosion of research using online platforms as these learning environments enable fine-grained data collection and allow testing of which learning opportunities work best for which learners. As the number of systems increase, so does the challenge of building theoretically coherent practice and research. The session brings together a diverse set of researchers to discuss: What assumptions about cognition and motivation are embedded in the design of online systems? What data are captured and how can these different types of data shed light on student learning and engagement?

Sub Unit

• SIG-Online Teaching and Learning

Chair

• Jodi Davenport, WestEd

Papers

• Learning Fractions by Splitting: Using Learning Analytics to Illuminate the Development of Mathematical Understanding - Taylor Martin, O'Reilly Media; Carmen Petrick Smith

• Fostering Online Disciplinary Engagement, Knowledge, and Achievement With Participatory Learning and Assessment - Daniel T. Hickey, Indiana University

• Practical and Scientific Benefits of Experiment-Guided Instructional Design of MOOClets and Educational Modules - Joseph Jay Williams, Stanford University; Jascha Sohl-Dickstein; Neil T. Heffernan, Worcester Polytechnic Institute; Candace Thille, Stanford University; John Mitchell

• Investigating Chemistry Learning Using Virtual Lab Activities in Real Classrooms - Jodi Davenport, WestEd; Anna Rafferty, University of California - Berkeley; Michael Karabinos, Carnegie Mellon University; David Yaron, Carnegie Mellon University

Discussant

• Cindy E. Hmelo-Silver, Indiana University