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Conati, C., & Maclaren, H. (2009). Empirically building and evaluating a probabilistic model of
user affect.
User Modeling and User-Adapted Interaction,
19
(3), 267-303.
Conati, C., & Zhou, X. (2002). Modeling students' emotions from cognitive appraisal in edu-
cational games. In
Proceedings of the 6th International Conference on Intelligent Tutoring
Systems
, Biarritz, France and San Sebastian, Spain (pp. 944-954).
Conati, C., Gertner, A., & Vanlehn, K. (2002). Using bayesian networks to manage uncertainty in
student modeling.
User Modeling and User-Adapted Interaction,
12
(4), 371-417.
Craiger, J. P., Goodman, D. F., Weiss, R. J., & Butler, A. (1996). Modeling organizational behav-
ior with fuzzy cognitive maps.
Journal of Computational Intelligence and Organizations,
1
,
120-123.
Crockett, K., Latham, A., McLean, D., & O'Shea, J. (2013). A fuzzy model for predicting
learning styles using behavioral cues in an conversational intelligent tutoring system. In
Proceedings of the b2013 International Conference on Fuzzy Systems
(pp. 1-8). India:
Hyderabad International Convention Center (HICC).
de Raadt, M. (2007). A review of Australasian investigations into problem solving and the novice
programmer.
Computer Science Education,
17
(3), 201-213.
Del Missier, F., & Ricci, F. (2003). Understanding recommender systems: Experimental evalua-
tion challenges. In
Proceedings of the Second Workshop on Empirical Evaluation of Adaptive
Systems
, Pittsburgh (pp. 31-40).
Dempster, J. (2004). Evaluating e-learning developments: An overview. Retrieved July 23, 2008
Desmarais, M. C., & Baker, R. S. (2012). A review of recent advances in learner and skill modeling
in intelligent learning environments.
User Modeling and User-Adapted Interaction,
22
(1-2),
9-38.
Devedzic, V. (2006).
Semantic web and education (Monograph)
. Berlin Heidelberg, New York:
Springer.
Dodds, P., & Fletcher, J. (2004). Opportunities for new ''smart'' learning environments enabled
by next-generation web capabilities.
Journal of Educational Multimedia and Hypermedia,
13
(4), 391-404.
Dolog, P., Henze, N., Nejdl, W., & Sintek, M. (2004). The personal reader: Personalizing and
enriching learning resources using semantic web technologies. In
Proceedings of the 3rd
International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
,
Eindhoven, Netherlands (pp. 85-94).
Drigas, A., Argyri, K., & Vrettaros, J. (2009). Decade review (1999-2009): Artificial intelligence
techniques in student modeling. In
Proceedings of the 2nd World Summit on the Knowledge
Society (WSKS 2009)
, Chania, Crete, Greece (pp. 552-564).
Durrani, S., & Durrani, D. S. (2010). Intelligent tutoring systems and cognitive abilities. In
Proceedings of Graduate Colloquium on Computer Sciences (GCCS), Department of
Computer Science
(p. 1). FAST-NU Lahore.
Echauz, J. R., & Vachtsevanos, G. J. (1995). Fuzzy grading system.
IEEE Transactions on
Education,
38
(2), 158-165.
Faraco, R. A., Rosatelli, M. C., & Gauthier, F. A. O. (2004). An approach of student modeling in a
learning companion system. In
Proceedings of the IX IBERAMIA
, Puebla, Mexico (pp. 891-900).
Felder, R. M., & Silverman, L. K. (1988). Learning and teaching styles.
Engineering Education,
78
(7), 674-681.
Felder, R. M., & Soloman, B. A. (2003). Learning styles and strategies. Retrieved June 28, 2012,
Flavell, J. H. (1976) Metacognitive aspects of problem solving. In L. B. Resnick (Ed.),
The
nature of intelligence
(pp 231-236). Hillsdale: Erlbaum.
Gaudioso, E., Montero, M., & Hernandez-del-Olmo, F. (2012). Supporting teachers in adap-
tive educational system through predictive models: A proof of concept.
Expert Systems with
Applications,
39
(1), 621-625.
Gena, C. (2005). Methods and techniques for the evaluation of user-adaptive systems.
The knowl-
edge Engineering Review,
20
(1), 1-37.
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