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

Elad Yacobson, Giora Alexandron

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


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.

Original languageEnglish
Title of host publicationResponsive and Sustainable Educational Futures - 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Proceedings
EditorsOlga Viberg, Ioana Jivet, Pedro J. Muñoz-Merino, Maria Perifanou, Tina Papathoma
PublisherSpringer Science and Business Media B.V.
Number of pages15
ISBN (Print)9783031426810
StatePublished - 2023
EventProceedings of the 18th European Conference on Technology Enhanced Learning, ECTEL 2023 - Aveiro, Portugal
Duration: 4 Sep 20238 Sep 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14200 LNCS


ConferenceProceedings of the 18th European Conference on Technology Enhanced Learning, ECTEL 2023

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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