References - Advances in Personalized Web-Based Education - page 151

Markham, S., Ceddia, J., Sheard, J., Burvill, C., Weir, J., Field, B. et al. (2003). Applying
agent technology to evaluation tasks in e-learning environments. In Exploring Educational
Technologies Conference (pp. 16-17).
Martin, B. (1999). Constraint-based student modeling: Representing student knowledge. In
Proceedings of the 3rd New Zealand Computer Science Research Students' Conference ,
Hamilton NZ (pp. 22-29).
Martins, A. C., Faria, L., Vaz de Carvalho, C., & Carrapatoso, E. (2008). User modeling in adap-
tive hypermedia educational systems. Educational Technology and Society, 11 (1), 194-207.
Mayo, M. J. (2001). Bayesian student modelling and decision-theoretic selection of tuto-
rial actions in intelligent tutoring systems. Ph.D. Thesis . Retrieved June 29, 2012, from
http://www.cosc.canterbury.ac.nz/research/reports/PhdTheses/2001/phd_0102.pdf .
McGill, T. J., & Volet, S. E. (1997). A conceptual framework for analyzing students' knowledge
of programming. Journal of Research on Computing in Education, 29 (3), 276-297.
Mendel, J. M. (2001). Uncertain rule-based fuzzy logic systems: Introduction and new directions .
Upper Saddle River, NJ: Prentice-Hall.
Mendel, J. M. (2007). Advances in type-2 fuzzy sets and systems. Information Sciences, 177 (1),
84-110.
Miao, Y., & Liu, Z. Q. (2000). On causal inference in fuzzy cognitive maps. IEEE Transactions
on Fuzzy Systems, 8 (1), 107-119.
Michaud, L. N., & McCoy, K. F. (2004). Empirical derivation of a sequence of user stereotypes
for language learning. User Modelling and User-Adapted Interaction, 14 , 317-350.
Millán, E., & Perez de la Cruz, J.-L. (2002). A bayesian diagnostic algorithm for student model-
ing. User Modelling and User-Adapted Interaction, 12 (2/3), 281-330.
Millán, E., Loboda, T., & Pérez-de-la-Cruz, J. L. (2010). Bayesian networks for student model
engineering. Computers and Education, 55 (4), 1663-1683.
Mitrovic, A. (2003). An intelligent SQL tutor on the web. International Journal of Artificial
Intelligence in Education, 13 (2-4), 173-197.
Mitrovic, A., and Martin, B. (2006). Evaluating the effects of open student models on learning. In
Proceedings of the 2nd International Conference on Adaptive Hypermedia and Adaptive Web-
Based Systems (pp. 296-305).
Mitrovic, A., Marting, B., & Mayo, M. (2002). Using Evaluation to Shape ITS Design: Results
and Experiences with SQL-Tutor. User Modelling and User-Adapted Interaction , 12 (2/3),
243-279.
Mitrovic, A., Martin, B., & Suraweera, P. (2007). Intelligent tutors for all: Constraint-based
approach. IEEE Intelligent Systems, 22 (4), 38-45.
Mitrovic, A., Mayo, M., Suraweera, P., & Martin, B. (2001). Constraint-based tutors: A suc-
cess story. In Proceedings of 14th International Conference on Industrial and Engineering
Applications of Artificial Intelligence and Expert Systems (IEA/AIE-2001) , Budapest
(pp. 931-940).
Mizumoto, M., & Tanaka, K. (1976). Some properties of fuzzy sets of type 2. Information and
Control, 31 (4), 312-340.
Moridis, C. N., & Economides, A. A. (2009). Prediction of student's mood during an online test using
formula-based and neural network-based method. Computers and Education, 53 , 644-652.
Mulwa, C., Lawless, S., Sharp, M., & Wade, V. (2011). The evaluation of adaptive and personal-
ized information retrieval systems: A review. International Journal of Knowledge and Web
Intelligence, 2 (2/3), 138-156.
Muñoz, K., Mc Kevitt, P., Lunney, T., Noguez, J., & Neri, L. (2010). PlayPhysics: An emotional
game learning environment for teaching physics. In Proceedings of the 4th International
Conference on Knowledge Science, Engineering and Management (KSEM' 10) , Belfast,
Northern Ireland, UK (pp. 400-411).
Muñoz, K., Mc Kevitt, P., Lunney, T., Noguez, J., & Neri, L. (2011). An emotional student model
for game-play adaptation. Entertainment Computing, 2 (2), 133-141.
Nguyen, L., & Do, P. (2008). Learner model in adaptive learning. In Proceedings of World
Academy of Scıence, Engıneerıng and Technology (pp. 396-401).