Educational Web Mining to Support Teachers' Self-Regulated Learning in Planning Technological Integration in the Classroom

• In Event: Poster Session 3
  In Poster Session: Exploring the Current Landscape of Technology, Instruction, Cognition, and Learning

Abstract

This study aims to support teacher professional development by leveraging the affordances of vast networks of pedagogical resources. We demonstrate the use of educational web mining techniques, including automated text extraction, pre-processing, and community detection algorithms to derive the semantic relationships inherent to networks of online resources. The method is applied to a database of 32,729 educational blogs in order to derive a model in relation to the subject matter area of mathematics. The results provide evidence for the internal validity of the network structure. We discuss the implications of the network-based approach to learner modeling in the context of nBrowser, an intelligent web browser designed as a metacognitive tool to foster self-regulated learning skills in pre-service teachers.

Authors

• Eric G. Poitras, University of Utah

• Negar Fazeli, University of Utah