Supporting the Discoverability of Open Educational Resources

Autor/inn/en	Cortinovis, Renato; Mikroyannidis, Alexander; Domingue, John; Mulholland, Paul; Farrow, Robert
Titel	Supporting the Discoverability of Open Educational Resources
Quelle	In: Education and Information Technologies, 24 (2019) 5, S.3129-3161 (33 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Cortinovis, Renato)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1360-2357
DOI	10.1007/s10639-019-09921-3
Schlagwörter	Open Educational Resources; Secondary Education; Secondary School Teachers; Discovery Processes; Taxonomy; Search Strategies + Suchen Sie Ihr Suchwort? Sekundarbereich; Taxonomie; Suchstrategie
Abstract	Open Educational Resources (OERs), now available in large numbers, have a considerable potential to improve many aspects of society, yet one of the factors limiting this positive impact is the difficulty to discover them. This study investigates and proposes strategies to better support educators in discovering OERs, mainly focusing on secondary education. The literature suggests that the effectiveness of existing search systems could be improved by supporting high-level and domain-oriented tasks. Hence a preliminary taxonomy of discovery-related tasks was developed, based on the analysis of the literature, interpreted through Information Foraging Theory. This taxonomy was empirically evaluated with a few experienced educators, to preliminary identify an interesting class of Query By Examples (QBE) expansion by similarity tasks, which avoids the need to decompose natural high-level tasks in a complex sequence of sub-tasks. Following the Design Science Research methodology, three prototypes to support as well as to refine those tasks were iteratively designed, implemented, and evaluated involving an increasing number of educators in usability oriented studies. The resulting high-level and domain-oriented blended search/recommendation strategy, transparently replicates Google searches in specialized networks, and identifies similar resources with a QBE strategy. It makes use of a domain-oriented similarity metric based on shared schema.org/LRMI alignments to educational frameworks, and clusters results in expandable classes of comparable degree of similarity. The summative evaluation shows that educators appreciate this exploratory-oriented strategy because -- balancing similarity and diversity -- it supports their high-level tasks, such as lesson planning and personalization of education. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01