Evaluating Recommender Systems for Technology Enhanced Learning: A Quantitative Survey

Autor/inn/en	Erdt, Mojisola; Fernandez, Alejandro; Rensing, Christoph
Titel	Evaluating Recommender Systems for Technology Enhanced Learning: A Quantitative Survey
Quelle	In: IEEE Transactions on Learning Technologies, 8 (2015) 4, S.326-344 (19 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1939-1382
DOI	10.1109/TLT.2015.2438867
Schlagwörter	Technology Uses in Education; Evaluation Methods; Statistical Analysis; Surveys; Information Systems; Evaluation Needs; Evaluation Problems + Suchen Sie Ihr Suchwort? Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Statistische Analyse; Survey; Umfrage; Befragung
Abstract	The increasing number of publications on recommender systems for Technology Enhanced Learning (TEL) evidence a growing interest in their development and deployment. In order to support learning, recommender systems for TEL need to consider specific requirements, which differ from the requirements for recommender systems in other domains like e-commerce. Consequently, these particular requirements motivate the incorporation of specific goals and methods in the evaluation process for TEL recommender systems. In this article, the diverse evaluation methods that have been applied to evaluate TEL recommender systems are investigated. A total of 235 articles are selected from major conferences, workshops, journals, and books where relevant work have been published between 2000 and 2014. These articles are quantitatively analysed and classified according to the following criteria: type of evaluation methodology, subject of evaluation, and effects measured by the evaluation. Results from the survey suggest that there is a growing awareness in the research community of the necessity for more elaborate evaluations. At the same time, there is still substantial potential for further improvements. This survey highlights trends and discusses strengths and shortcomings of the evaluation of TEL recommender systems thus far, thereby aiming to stimulate researchers to contemplate novel evaluation approaches. (As Provided).
Anmerkungen	Institute of Electrical and Electronics Engineers, Inc. 445 Hoes Lane, Piscataway, NJ 08854. Tel: 732-981-0060; Web site: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4620076
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01