Supporting Research Literacy Using Topic Maps: Building a Mathematics Education Research Ontology

ID: 40680 Type: Virtual Brief Paper
  1. Fei Shu and Emily Sheepy, Concordia University, Montreal, Canada

Abstract: This paper reports on the development of a computational ontology that represents structural and substantive content features, as well as bibliographic information, for research articles published in a Canadian journal of mathematics education. The ontology feeds into a Topic Maps associative index that facilitates search of these text resources. The resulting database is designed for use by learners and researchers in a higher education context. The paper discusses Topic Map associative indices as educational tools; presents a potential application of such tools to increasing research literacy in university students; and provides an overview of the process of ontology creation for articles in the domain of mathematics education research.

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