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oai:riuma.uma.es:10630/355072026-02-03T12:03:51Zcom_10630_2254col_10630_37959

Evaluating the Performance of Copula-Based Item Response Theory Models for Interpretable Assessment Guzmán-de-los-Riscos, Eduardo Francisco Millán-Valldeperas, Eva Estudiantes universitarios - Evaluación Modelos matemáticos 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 primary school teachers. The results show that both methods can be used to obtain reliable estimations of students’ knowledge. 2024-12-04T11:15:56Z 2024-12-04T11:15:56Z 2024 2024 conference output 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. https://hdl.handle.net/10630/35507 eng 32nd International Conference on Computers in Education, ICCE 2024 Manila, Philipphines 25-29 November, 2024 http://creativecommons.org/licenses/by-nc-sa/4.0/ open access Atribución-NoComercial-CompartirIgual 4.0 Internacional