A belief net backbone for student modelling

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

Volumn 1086, Issue , 1996, Pages 596-604

  Reye, Jim ^a  

^a QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER AIDED INSTRUCTION; INTELLIGENT VEHICLE HIGHWAY SYSTEMS;

DYNAMIC EVOLUTION; S STATE; STUDENT MODELING; STUDENT MODELLING;

STUDENTS;

EID: 84949942070     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-61327-7_159     Document Type: Conference Paper

References (8)

1. Collins, A., and Stevens, A.L. (1982) Goals and strategies for inquiry teachers. In Glaser, R. (ed.) Advances in Instructional Psychology (vol. II), 65-119.
2. Corbett, A.T., and Anderson, J.R. (1992) Student modeling and mastery learning in a computer-based programming tutor. In Frasson, C., Gauthier, C. and McCalla, G.I. (eds.) Intelligent Tutoring Systems (ITS’92), 413-420.
3. de Kleer, J., and Williams, B.C. (1987) Diagnosing multiple faults. Artificial Intelligence 32, 97-130.
4. Dean, T., and Kanazawa, K. (1989) A model for reasoning about persistence and causation, Computational Intelligence 5, 142-150.
5. Pearl, J. (1988) Probabilistic, reasoning in intelligent systems: networks of plausible inference. Morgan Kaufmann.
6. Pirolli, R, and Wilson, M. (1992) Measuring learning strategies,and understanding: a research framework. In Frasson, C., Gauthier, C. and McCalla, G.I. (eds.) Intelligent Tutoring Systems (ITS’ 92), 539-558.
7. Shute, V. (1995). SMART evaluation: cognitive diagnosis, mastery learning & remediation. In Greer, J. (ed.) Artificial Intelligence in Education, 1995, 123-130.
8. Villano, M. (1992) Probabilistic student models: bayesian belief networks and knowledge space theory. In Frasson, C., Gauthier, C. and McCalla, G.I. (eds.) Intelligent Tutoring Systems (ITS’92), 491-498