Informing authoring best practices through an analysis of pedagogical content and student behavior

Abstract

Among other factors, student behavior during learning activities is affected by the pedagogical content they are interacting with. In this paper, we analyze this effect in the context of a problem-solving based online Physics course. We use a representation of the content in terms of its position, composition and visual layout to identify eight content types that correspond to problem solving sub-tasks. Canonical examples as well as a sequence model of these tasks are presented. Student behaviors, measured in terms of activity, help-requests, mistakes and time on task, are compared across each content type. Students request more help while working through complex computational tasks and make more mistakes on tasks that apply conceptual knowledge. We discuss how these findings can inform the design of pedagogical content and authoring tools.