<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-05-27T04:42:57Z</responseDate><request verb="GetRecord" identifier="oai:riuma.uma.es:10630/35507" metadataPrefix="mods">https://riuma.uma.es/rest/oai/request</request><GetRecord><record><header><identifier>oai:riuma.uma.es:10630/35507</identifier><datestamp>2026-02-03T12:03:51Z</datestamp><setSpec>com_10630_2254</setSpec><setSpec>col_10630_37959</setSpec></header><metadata><mods:mods xmlns:doc="http://www.lyncode.com/xoai" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
   <mods:name>
      <mods:namePart>Guzmán-de-los-Riscos, Eduardo Francisco</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>Millán-Valldeperas, Eva</mods:namePart>
   </mods:name>
   <mods:extension>
      <mods:dateAvailable encoding="iso8601">2024-12-04T11:15:56Z</mods:dateAvailable>
   </mods:extension>
   <mods:extension>
      <mods:dateAccessioned encoding="iso8601">2024-12-04T11:15:56Z</mods:dateAccessioned>
   </mods:extension>
   <mods:originInfo>
      <mods:dateIssued encoding="iso8601">2024</mods:dateIssued>
   </mods:originInfo>
   <mods:identifier type="citation">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.</mods:identifier>
   <mods:identifier type="uri">https://hdl.handle.net/10630/35507</mods:identifier>
   <mods: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&#xd;
school teachers. The results show that both methods can be used to obtain reliable estimations of students’ knowledge.</mods:abstract>
   <mods:language>
      <mods:languageTerm>eng</mods:languageTerm>
   </mods:language>
   <mods:accessCondition type="useAndReproduction">http://creativecommons.org/licenses/by-nc-sa/4.0/</mods:accessCondition>
   <mods:accessCondition type="useAndReproduction">open access</mods:accessCondition>
   <mods:accessCondition type="useAndReproduction">Atribución-NoComercial-CompartirIgual 4.0 Internacional</mods:accessCondition>
   <mods:subject>
      <mods:topic>Estudiantes universitarios - Evaluación</mods:topic>
   </mods:subject>
   <mods:subject>
      <mods:topic>Modelos matemáticos</mods:topic>
   </mods:subject>
   <mods:titleInfo>
      <mods:title>Evaluating the Performance of Copula-Based Item Response Theory Models for Interpretable Assessment</mods:title>
   </mods:titleInfo>
   <mods:genre>conference output</mods:genre>
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