Examining the Usefulness of Quality Scores for Generating Learning Object Recommendations in Repositories of Open Educational Resources
| Autor: | Aldo Gordillo, Daniel López-Fernández, Katrien Verbert |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Technology
Computer science open educational resources Chemistry Multidisciplinary 02 engineering and technology lcsh:Technology lcsh:Chemistry Engineering 0202 electrical engineering electronic engineering information engineering General Materials Science Instrumentation lcsh:QH301-705.5 media_common Fluid Flow and Transfer Processes Physics 05 social sciences General Engineering 050301 education Open educational resources lcsh:QC1-999 Computer Science Applications Chemistry quality Physical Sciences OER 020201 artificial intelligence & image processing media_common.quotation_subject Materials Science Learning object digital repositories Engineering Multidisciplinary Materials Science Multidisciplinary RANKING METRICS Recommender system Physics Applied SYSTEMS Relevance (information retrieval) Quality (business) learning objects Science & Technology lcsh:T Process Chemistry and Technology Hybrid approach Data science MODEL lcsh:Biology (General) lcsh:QD1-999 lcsh:TA1-2040 TEL recommender systems lcsh:Engineering (General). Civil engineering (General) 0503 education lcsh:Physics |
| Zdroj: | Applied Sciences, Vol 10, Iss 4638, p 4638 (2020) Applied Sciences Volume 10 Issue 13 |
| ISSN: | 2076-3417 |
| Popis: | Open educational resources (OER) can contribute to democratize education by providing effective learning experiences with lower costs. Nevertheless, the massive amount of resources currently available in OER repositories makes it difficult for teachers and learners to find relevant and high-quality content, which is hindering OER use and adoption. Recommender systems that use data related to the pedagogical quality of the OER can help to overcome this problem. However, studies analyzing the usefulness of these data for generating OER recommendations are very limited and inconclusive. This article examines the usefulness of using pedagogical quality scores for generating OER recommendations in OER repositories by means of a user study that compares the following four different recommendation approaches: a traditional content-based recommendation technique, a quality-based non-personalized recommendation technique, a hybrid approach that combines the two previous techniques, and random recommendations. This user study involved 53 participants and 400 OER whose quality was evaluated by reviewers using the Learning Object Review Instrument (LORI). The main finding of this study is that pedagogical quality scores can enhance traditional content-based OER recommender systems by allowing them to recommend OER with more quality without detriment to relevance. |
| Databáze: | OpenAIRE |
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