Cited By
View all- MilláN EDescalçO LCastillo GOliveira PDiogo S(2013)Using Bayesian networks to improve knowledge assessmentComputers & Education10.1016/j.compedu.2012.06.01260:1(436-447)Online publication date: 1-Jan-2013
Computerized evaluation and diagnosis of student's knowledge based on Bayesian networks
Authors: 
Gladys Castillo, Luís Descalço, Sandra Diogo, Eva Millán, Paula Oliveira, Batel AnjoAuthors Info & Claims
Abstract
In this paper, we describe the integration and evaluation of an existing generic Bayesian student model into an existing computerized testing system within the Projecto Matemática Ensino (PmatE) of the University of Aveiro. The Bayesian student model had previously been evaluated with simulated students, but a real application was still needed. The testing system in PmatE is based in the use of Learning Objects (LO), which are question generators which essentially consist of some parameterized text and sets of parameterized "true/false" questions (at least four). These LO together with the experience of PmatE in using computerized tests with students, gives us ideal conditions for testing the described Bayesian student model with real students.
References
[1]
Projecto Matemática Ensino (PmatE), http://pmate2.ua.pt/pmate/
[2]
Sousa, J., Batel, A., Orlando, R.: SA3C- Platform of Evaluation System and Computer Assisted Learning. WEAS Transactions on Advances in Engineering Education 2, 1-6 (2005)
[3]
Pinto, J.S., Oliveira, M.P., Anjo, A.B., Vieira, S.I., Isidro, R.O., Silva, M.H.: TDmat-mathematics diagnosis evaluation test for engineering sciences students. International Journal of Mathematical Education in Science and Technology 38(3), 283-299 (2007)
[4]
Millán, E., Pérez de la Cruz, J.-L.: A Bayesian Diagnostic Algorithm for Student Modeling. User Modeling and User-Adapted Interaction 12, 281-330 (2002)
[5]
Millán, E., Pérez de la Cruz, J.-L., García, F.: Dynamic versus Static Student Models Based on Bayesian Networks: An Empirical Study. In: Palade, V., Howlett, R.J., Jain, L. (eds.) KES 2003. LNCS, vol. 2774, pp. 1337-1344. Springer, Heidelberg (2003)
[6]
SMILE and GENIE, http://genie.sis.pitt.edu/
[7]
Carmona, C., Millan, E., Pérez-de-la-Cruz, J.-L., Trella, M., Conejo, R.: Introducing pre-requisite relations in a multi-layered Bayesian student model. In: Ardissono, L., Brna, P., Mitrović, A. (eds.) UM 2005. LNCS (LNAI), vol. 3538, pp. 347-356. Springer, Heidelberg (2005)
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Published In
September 2010
652 pages
ISBN:3642160190
Sponsors
- Universidad Internacional de la Rioja
- Springer-Verlag
- University of Leeds
- imc AG
- Atos Origin
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 28 September 2010
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View all- MilláN EDescalçO LCastillo GOliveira PDiogo S(2013)Using Bayesian networks to improve knowledge assessmentComputers & Education10.1016/j.compedu.2012.06.01260:1(436-447)Online publication date: 1-Jan-2013