RT Journal Article
T1 Using Bayesian networks to improve knowledge assessment
A1 Millán-Valldeperas, Eva
A1 Descalço, Luis
A1 Castillo, Gladys
A1 Oliveira, Paula
A1 Diogo, Sandra
K1 Toma de desiciones
K1 Estadística bayesiana
AB In this paper, we describe the integration and evaluation of an existing generic Bayesian student model(GBSM) into an existing computerized testing system within the Mathematics Education Project (PmatE -Projecto Matemática Ensino) of the University of Aveiro. This generic Bayesian student model had beenpreviously evaluated with simulated students, but a real application was still missing. In the workpresented here, we have used the GBSM to define Bayesian Student Models (BSMs) for a concretedomain: first degree equations. In order to test the diagnosis capabilities of such BSMs, an evaluationwith 152 students has been performed. Each of the 152 students took both a computerized test withinPMatE and a written exam, both of them designed to measure students’ knowledge in 12 conceptsrelated to first degree equations. The written exam was graded by three experts. Then two BSMs weredeveloped, one for the computer test and another one for the written exam. These BSMs were used toobtain estimations of student’s knowledge on the same 12 concepts, and the inter-rater agreementamong the different measures was computed. Results show a high degree of agreement among the scoresgiven by the experts and also among the diagnosis provided by the BSM in the written exam and expert’saverage, but a low degree of agreement among the diagnosis provided by the BSM in the computer testand expert’s average
PB Elsevier
SN 0360-1315
YR 2013
FD 2013-01
LK http://hdl.handle.net/10630/7068
UL http://hdl.handle.net/10630/7068
LA eng
NO Plan Nacional de I+D+i, Gobierno de España. TIN2009-14179
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026