Recommending Is Reflecting: A Surprising Benefit of Social Recommender Systems for Teachers

Elad Yacobson, Giora Alexandron

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

Abstract

Social recommender systems for teachers are based on evaluative feedback that teachers provide regarding learning resources (LRs) they used. These systems can greatly enhance the efficiency of locating quality digital learning resources by teachers. Previous studies on social recommender systems were based on the view that the act of providing feedback has no direct merit for the recommending teacher. We challenge this viewpoint, hypothesizing that writing a review about an LR would necessitate teachers to revisit and critically evaluate their teaching experiences with it, thus promoting reflective thinking. To investigate this hypothesis, we applied a verbal analysis protocol to measure the level of reflective thinking within 394 reviews of LRs provided by teachers. Our findings reveal that writing feedback on LRs indeed promotes reflective thinking, although the depth and content of the reflection are somewhat limited.

Original languageEnglish
Title of host publicationTechnology Enhanced Learning for Inclusive and Equitable Quality Education
Subtitle of host publication19th European Conference on Technology Enhanced Learning, EC-TEL 2024, Proceedings
EditorsRafael Ferreira Mello, Nikol Rummel, Ioana Jivet, Gerti Pishtari, José A. Ruipérez Valiente
PublisherSpringer Science and Business Media B.V.
Pages195-200
Number of pages6
ISBN (Print)9783031723117
DOIs
StatePublished Online - 13 Sep 2024
Event19th European Conference on Technology Enhanced Learning, EC-TEL 2024 - Krems, Austria
Duration: 16 Sep 202420 Sep 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume15160 LNCS

Conference

Conference19th European Conference on Technology Enhanced Learning, EC-TEL 2024
Country/TerritoryAustria
CityKrems
Period16/09/2420/09/24

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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