A neuro-fuzzy approach in student modeling

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2702, Issue , 2003, Pages 337-341

  Stathacopoulou, Regina ^a   Grigoriadou, Maria ^a   Magoulas, George D ^b   Mitropoulos, Denis ^a  

^a UNIVERSITY OF ATHENS   (Greece)

^b BRUNEL UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; EDUCATION; KNOWLEDGE REPRESENTATION; LINGUISTICS; MATHEMATICAL MODELS; NEURAL NETWORKS; PROBABILITY DISTRIBUTIONS; STUDENTS; VECTORS; COMPUTER AIDED INSTRUCTION; FUZZY LOGIC; TEACHING;

MEMBERSHIP DEGREES; NEURO-FUZZY APPROACH; STUDENT MODELING; EXPLORATORY LEARNING; FUZZY EVIDENCES; FUZZY MODELING; OBSERVABLE BEHAVIOR; STUDENT DIAGNOSIS; STUDENT KNOWLEDGE;

FUZZY SETS; FUZZY INFERENCE;

EID: 8344251855     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/3-540-44963-9_46     Document Type: Conference Paper

References (13)

1. Arons A. B. (1990) A guide to introductory physics teaching. Washington : John Wiley & Sons, Inc.
2. Brown J. S., Collins A., Duguid P. (1989) Situated cognition and the culture of learning. Educational researcher 18 32-34.
3. Driver R. (1983) The pupil as a scientist? Milton Keynes: Open University Press.
4. Grigoriadou M., Mitropoulos D., Samarakou M., Solomonidou C., Stavridou E. (1999). Methodology for the Design of Educational Software in Mathematics and Physics for Secondary Education. Computer Based Learning in Science, Conf. Proc. 1999 pB3.
5. Hawkes, L. W., Derry, S. J. & Rundensteiner. E. A. (1990) Individualized tutoring using an intelligent fuzzy temporal relational database. International Journal of Man-Machines Studies, 33,pp 409-429
6. Jameson A.,(1996) Numerical Uncertainty Management In User and Student Modeling: An Overview of Systems and Issues. User Modeling and User-Adapted Interaction, 5, p. 193-251.
7. Magoulas G.D., Vrahatis M.N., and Androulakis G.S. (1997). Effective back-propagation training with variable stepsize. Neural Networks, 10, pp. 69-82.
8. Mitchell T. M. Machine learning (1997), McGraw-Hill, cp.4, pp. 81-117.
9. Posey C. L., Hawkes L. W. (1996). Neural Networks Applied to Knowledge Acquisition in the Student Model. Information Science 88, p. 275-298.
10. Vanlehn K., Niu Z. (2001). Bayesian student modeling, user interfaces and feedback: A sensitivity analysis. Inter. Journal of Artificial Intelligence in Education 12 154-184.
11. Vosniadou S. (1994) From cognitive theory to educational technology. In: Vosniadou S., De Corte E., Mandl H. (Ed), Technology-Based Learning Environments, Psychological and Educational Foundations. NATO ASI Series. F, vol. 137, 11-17. Berlin: Springer-Verlag.
12. Yasdi R.(2000). A Litetature Syrvey on Applications of Neural Networks for Human-Computer Interaction. Neural Computing & Applications, 9, p.245-258.
13. Zadeh L.A.(1989). Knowledge Representation in Fuzzy Logic. In Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems Advances in Fuzzy Systems-Application and Theory, Vol 6. Editors G.J. Klir & B.Yuan.