Using data-driven discovery of better student models to improve student learning

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

Volumn 7926 LNAI, Issue , 2013, Pages 421-430

  Koedinger, Kenneth R ^a   Stamper, John C ^a   McLaughlin, Elizabeth A ^a   Nixon, Tristan ^b  

^a Carnegie Mellon University   (United States)

^b Carnegie Learning Inc   (United States)

Author keywords

Cognitive modeling; Data mining; Machine learning

Indexed keywords

ARTIFICIAL INTELLIGENCE; CURRICULA; DATA MINING; EDUCATION COMPUTING; LEARNING SYSTEMS;

ACCURATE PREDICTION; COGNITIVE MODEL; DATA DRIVEN; PROBLEM DECOMPOSITION; STATISTICAL ALGORITHM; STUDENT LEARNING; STUDENT MODELS;

STUDENTS;

EID: 84880011040     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-39112-5_43     Document Type: Conference Paper

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