How Do Teachers Search for Learning Resources? A Mixed Method Field Study

Abstract

Teachers using Open Educational Resource (OER) repositories face the challenge of searching and selecting learning resources (LRs) that match their pedagogical goals and teaching preferences. However, teachers are often overwhelmed by the multitude of LRs in such repositories. One way of aiding teachers is providing them with search mechanisms that rely on semantic information describing different properties of the materials, and peer-generated reviews and feedback (‘social recommendations’). Previous studies of teachers’ search and select strategies in such systems were usually conducted in controlled settings, limiting their generalization to real-life contexts. The literature also lacks systematic evaluations of the usefulness of semantic information and social recommendations to teachers’ search processes. To address these gaps, we conducted a study with physics teachers who use a nation-wide blended-learning environment containing an OER repository and social network features. We applied a mixed-method approach, first interviewing teachers and observing them performing authentic search tasks, and then triangulating these findings with quantitative analysis of log files containing data about teacher interaction with the learning environment. Our findings demonstrate the value that teachers ascribe to social-based information, especially from peers who are perceived as credible or like-minded, when searching and selecting LRs. We discuss possible implications for stake-holders and designers of OER repositories for blended instruction in K-12 environments.

The work of EY was partially supported by the Israeli Council for Higher Education via the Weizmann Data Science Research Center. GA’s research was generously supported by the Estate of Emile Mimran and by the Maurice and Vivienne Wohl Biology Endowment. The authors wish to thank Dr. Moriah Ariely for her assistance with the qualitative part of this research.