Which algorithms suit which learning environments? A comparative study of recommender systems in TEL

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

Volumn 9891 LNCS, Issue , 2016, Pages 124-138

  Kopeinik, Simone ^a   Kowald, Dominik ^a   Lex, Elisabeth ^a  

^a GRAZ UNIVERSITY OF TECHNOLOGY   (Austria)

Author keywords

ACT R; Offline study; Recommender systems; Resource recommendation; SUSTAIN; Tag recommendation; Technology enhanced learning; TEL

Indexed keywords

COLLABORATIVE FILTERING; COMPUTER AIDED INSTRUCTION; ENGINEERING EDUCATION; RECOMMENDER SYSTEMS;

ACT-R; OFF-LINE STUDIES; RESOURCE RECOMMENDATION; SUSTAIN; TAG RECOMMENDATIONS; TECHNOLOGY ENHANCED LEARNING;

LEARNING ALGORITHMS;

EID: 84988515310     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-45153-4_10     Document Type: Conference Paper

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