A machine learning framework for an expert tutor construction
College of Computer Studies
Proceedings - International Conference on Computers in Education, ICCE 2002
This paper discusses a machine learning framework that uses extraction, classification, and generalization techniques to classify students according to their cognitive and behavioral learning patterns and to categorize tutoring strategies of expert human tutors. A great deal of the discussion focuses on the use of reinforcement learning techniques, specifically the ?-greedy and temporal difference TD(0) methods in deriving tutoring policies over a class of students. Future works will deal on incremental learning and modification of learned policies while the tutor performs on-line in real-time, and extracting and learning the way expert tutors execute their tutoring activities. © 2002 IEEE.
Digitial Object Identifier (DOI)
Legaspi, R. S., & Sison, R. C. (2002). A machine learning framework for an expert tutor construction. Proceedings - International Conference on Computers in Education, ICCE 2002, 670-674. https://doi.org/10.1109/CIE.2002.1186038
Intelligent tutoring systems; Expert systems (Computer science)