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dc.contributor.authorEstivill-Castro, Vladimir
dc.contributor.authorLimongelli, Carla
dc.contributor.authorLombardi, Matteo
dc.contributor.authorMarani, Alessandro
dc.date.accessioned2017-11-29T23:29:25Z
dc.date.available2017-11-29T23:29:25Z
dc.date.issued2016
dc.identifier.isbn9781450342902
dc.identifier.doi10.1145/2911451.2914670
dc.identifier.urihttp://hdl.handle.net/10072/123852
dc.description.abstractIn the Technology Enhanced Learning (TEL) community, the problem of conducting reproducible evaluations of recommender systems is still open, due to the lack of exhaustive benchmarks. The few public datasets available in TEL have limitations, being mostly small and local. Recently, Massive Open Online Courses (MOOC) are attracting many studies in TEL, mainly because of the huge amount of data for these courses and their potential for many applications in TEL. This paper presents DAJEE, a dataset built from the crawling of MOOCs hosted on the Coursera platform. DAJEE offers information on the usage of more than 20,000 resources in 407 courses by 484 instructors, with a conjunction of different educational entities in order to store the courses' structure and the instructors' teaching experiences.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherAssociation for Computing Machinery (ACM)
dc.publisher.placeUnited States
dc.relation.ispartofconferencename39th International ACM SIGIR conference on Research and Development in Information Retrieval
dc.relation.ispartofconferencetitleSIGIR'16: PROCEEDINGS OF THE 39TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL
dc.relation.ispartofdatefrom2016-07-17
dc.relation.ispartofdateto2016-07-21
dc.relation.ispartoflocationPisa, ITALY
dc.relation.ispartofpagefrom681
dc.relation.ispartofpagefrom4 pages
dc.relation.ispartofpageto684
dc.relation.ispartofpageto4 pages
dc.subject.fieldofresearchInformation Systems not elsewhere classified
dc.subject.fieldofresearchcode080699
dc.titleDAJEE: A dataset of joint educational entities for information retrieval in technology enhanced learning
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.hasfulltextNo Full Text
gro.griffith.authorEstivill-Castro, Vladimir
gro.griffith.authorLombardi, Matteo
gro.griffith.authorMarani, Alessandro


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