Information Technology Reference
In-Depth Information
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
from http://www.warwick.ac.uk/go/cap/resources/eguides .
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,
from http://www.ncsu.edu/felder-public/ILSdir/styles.htm .
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.
Search WWH ::




Custom Search