Evaluating the Performance of Copula-Based Item Response Theory Models for Interpretable Assessment

Authors

  • Eduardo GUZMÁN Departamento de Lenguajes y Ciencias de la Computación, E.T.S. Ingeniería Informática, Universidad de Málaga Author
  • Eva MILLÁN Departamento de Lenguajes y Ciencias de la Computación, E.T.S. Ingeniería Informática, Universidad de Málaga Author

DOI:

https://doi.org/10.58459/icce.2024.4811

Abstract

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.

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Published

2024-11-25

How to Cite

Evaluating the Performance of Copula-Based Item Response Theory Models for Interpretable Assessment . (2024). International Conference on Computers in Education. https://doi.org/10.58459/icce.2024.4811