RT Conference Proceedings
T1 Evaluating the Performance of Copula-Based Item Response Theory Models for Interpretable Assessment
A1 Guzmán-de-los-Riscos, Eduardo Francisco
A1 Millán-Valldeperas, Eva
K1 Estudiantes universitarios - Evaluación
K1 Modelos matemáticos
AB This paper describes a study evaluating the performance of copula-based Item Response Theory in real-world settings. To achieve this, we used a dataset containing information about 152 students who took a test on first-degree equations. This dataset had previously been employed to assess the performance of a Bayesian Network model in diagnosing 12 concepts related to first-degree equations. Both copula-based Item Response Theory and Bayesian Networks are explainable techniques that can be utilized for educational assessment. In this study, we compare the results of both data-driven methods against the actual state of knowledge of the students, which is a hidden variable, estimated using an expert-driven approach that involved averaging three independent assessments made by experienced primaryschool teachers. The results show that both methods can be used to obtain reliable estimations of students’ knowledge.
YR 2024
FD 2024
LK https://hdl.handle.net/10630/35507
UL https://hdl.handle.net/10630/35507
LA eng
NO Guzmán, E., Millán, E. Evaluating the Performance of Copula-Based Item Response Theory Models for Interpretable Assessment. In 32st International Conference on Computers in Education, ICCE 2024 (pp. 55-64). Asia-Pacific Society for Computers in Education.
NO This research has been supported by the Spanish Ministry of Science and Innovation throughthe research project with reference TED2021-129956B-I00.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026