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Taxonomizing features and methods for identifying at-risk students in computing courses.

Arto HellasPetri IhantolaAndrew PetersenVangel V. AjanovskiMirela GuticaTimo HynninenAntti KnutasJuho LeinonenChris MessomSoohyun Nam Liao
Published in: ITiCSE (2018)
Keyphrases
  • benchmark datasets
  • learning styles
  • feature set
  • distance education
  • e learning
  • feature vectors
  • higher education
  • learning outcomes
  • intelligent tutoring systems