<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>2737-6419</journal-id>
<journal-title><![CDATA[Revista Athenea]]></journal-title>
<abbrev-journal-title><![CDATA[Athenea]]></abbrev-journal-title>
<issn>2737-6419</issn>
<publisher>
<publisher-name><![CDATA[AutanaBooks, con el apoyo institucional de la Universidad Nacional Experimental Politécnica "Antonio José de Sucre", Vicerrectorado Puerto Ordaz, Venezuela]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2737-64192026000100066</article-id>
<article-id pub-id-type="doi">10.47460/athenea.v7i23.134</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Modelos explicables para identificar dificultades en matemáticas universitarias: análisis del dataset MathE]]></article-title>
<article-title xml:lang="en"><![CDATA[Explainable Models for Identifying Difficulties in University Mathematics: Analysis of the MathE Dataset]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Pozo Valdiviezo]]></surname>
<given-names><![CDATA[Eduardo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Tenelanda Cudco]]></surname>
<given-names><![CDATA[Sandra Elizabeth]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Dávalos Villegas]]></surname>
<given-names><![CDATA[Martha Ximena]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ávila Gaibor]]></surname>
<given-names><![CDATA[Gustavo Javier]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Escuela Superior Politécnica de Chimborazo  ]]></institution>
<addr-line><![CDATA[Riobamba ]]></addr-line>
<country>Ecuador</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Nacional de Chimborazo  ]]></institution>
<addr-line><![CDATA[Riobamba ]]></addr-line>
<country>Ecuador</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Escuela Superior Politécnica de Chimborazo  ]]></institution>
<addr-line><![CDATA[Riobamba ]]></addr-line>
<country>Ecuador</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Escuela Superior Politécnica de Chimborazo  ]]></institution>
<addr-line><![CDATA[Riobamba ]]></addr-line>
<country>Ecuador</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2026</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2026</year>
</pub-date>
<volume>7</volume>
<numero>23</numero>
<fpage>66</fpage>
<lpage>76</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://ve.scielo.org/scielo.php?script=sci_arttext&amp;pid=S2737-64192026000100066&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://ve.scielo.org/scielo.php?script=sci_abstract&amp;pid=S2737-64192026000100066&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://ve.scielo.org/scielo.php?script=sci_pdf&amp;pid=S2737-64192026000100066&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen Este estudio aplica un enfoque de analítica del aprendizaje y modelos explicables para identificar contenidos de mayor dificultad en matemáticas universitarias a partir de registros de interacción de una plataforma de práctica y evaluación. Se realizó un análisis cuantitativo secundario del conjunto de datos MathE, considerando variables de contenido (tema, subtema y palabras clave) y contexto (país y nivel). Primero se estimaron tasas de error por tema y subtema y se sintetizaron patrones mediante visualizaciones comparativas. Luego se entrenaron modelos complementarios, una regresión logística por su interpretabilidad y un modelo no lineal de árboles de gradiente para capturar interacciones, validando la generalización con partición por estudiante. La explicabilidad se abordó mediante atribución de contribuciones para interpretar factores asociados al error. Los hallazgos señalan mayores dificultades en contenidos de Diferenciación, Interpretación Funcional y Probabilidad, junto con debilidades transversales de manipulación algebraica, con apoyos adicionales en Métodos Numéricos e Integración.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract This study applies a learning analytics approach and explainable models to identify the most difficult content areas in university mathematics based on interaction records from a practice and assessment platform. A secondary quantitative analysis of the MathE dataset was conducted, considering content variables (topic, subtopic, and keywords) and contextual variables (country and level). First, error rates were estimated by topic and subtopic, and patterns were synthesized through comparative visualizations. Then, complementary models were trained: a logistic regression model for its interpretability and a nonlinear gradient-boosted tree model to capture interactions, validating generalization through student-level partitioning. Explainability was addressed through contribution attribution to interpret factors associated with errors. The findings indicate greater difficulties in Differentiation, Functional Interpretation, and Probability, together with cross-cutting weaknesses in algebraic manipulation, with additional support needs in Numerical Methods and Integration.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[analítica del aprendizaje]]></kwd>
<kwd lng="es"><![CDATA[educación matemática]]></kwd>
<kwd lng="es"><![CDATA[inteligencia artificial explicable]]></kwd>
<kwd lng="es"><![CDATA[orientación didáctica]]></kwd>
<kwd lng="en"><![CDATA[learning analytics]]></kwd>
<kwd lng="en"><![CDATA[mathematics education]]></kwd>
<kwd lng="en"><![CDATA[explainable artificial intelligence]]></kwd>
<kwd lng="en"><![CDATA[instructional guidance]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<label>1</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Viberg]]></surname>
<given-names><![CDATA[O.]]></given-names>
</name>
<name>
<surname><![CDATA[Hatakka]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Bälter]]></surname>
<given-names><![CDATA[O.]]></given-names>
</name>
<name>
<surname><![CDATA[Mavroudi]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The current landscape of learning analytics in higher education]]></article-title>
<source><![CDATA[Comput. Human Behav.]]></source>
<year>2018</year>
<volume>89</volume>
<page-range>98-110</page-range></nlm-citation>
</ref>
<ref id="B2">
<label>2</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Hwang]]></surname>
<given-names><![CDATA[G. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Tu]]></surname>
<given-names><![CDATA[Y. F.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Roles and research trends of artificial intelligence in mathematics education: A bibliometric mapping analysis and systematic review]]></article-title>
<source><![CDATA[Mathematics]]></source>
<year>2021</year>
<volume>9</volume>
<numero>6</numero>
<issue>6</issue>
</nlm-citation>
</ref>
<ref id="B3">
<label>3</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Khosravi]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Explainable artificial intelligence in education]]></article-title>
<source><![CDATA[Computers and Education: Artificial Intelligence]]></source>
<year>2022</year>
<volume>3</volume>
</nlm-citation>
</ref>
<ref id="B4">
<label>4</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Azevedo]]></surname>
<given-names><![CDATA[B. F.]]></given-names>
</name>
<name>
<surname><![CDATA[Pacheco]]></surname>
<given-names><![CDATA[M. F.]]></given-names>
</name>
<name>
<surname><![CDATA[Fernandes]]></surname>
<given-names><![CDATA[F. P.]]></given-names>
</name>
<name>
<surname><![CDATA[Pereira]]></surname>
<given-names><![CDATA[A. I.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Dataset of mathematics learning and assessment of higher education students using the mathe platform]]></article-title>
<source><![CDATA[Data Brief]]></source>
<year>2024</year>
<volume>53</volume>
</nlm-citation>
</ref>
<ref id="B5">
<label>5</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Long]]></surname>
<given-names><![CDATA[P. D.]]></given-names>
</name>
<name>
<surname><![CDATA[Siemens]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Penetrare la nebbia: tecniche di analisi per l&#8217;apprendimento]]></article-title>
<source><![CDATA[Revista Italiana de Tecnología Educativa]]></source>
<year>2014</year>
<volume>22</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>132-7</page-range></nlm-citation>
</ref>
<ref id="B6">
<label>6</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lemay]]></surname>
<given-names><![CDATA[D. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Baek]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Doleck]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Comparison of learning analytics and educational data mining: A topic modeling approach]]></article-title>
<source><![CDATA[Computers and Education: Artificial Intelligence]]></source>
<year>2021</year>
<volume>2</volume>
</nlm-citation>
</ref>
<ref id="B7">
<label>7</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zeileis]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Examining exams using rasch models and assessment of measurement invariance]]></article-title>
<source><![CDATA[Austrian Journal of Statistics]]></source>
<year>2024</year>
<volume>54</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>9-26</page-range></nlm-citation>
</ref>
<ref id="B8">
<label>8</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[Z.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Model building strategy for logistic regression: Purposeful selection]]></article-title>
<source><![CDATA[Ann. Transl. Med.]]></source>
<year>2016</year>
<volume>4</volume>
<numero>6</numero>
<issue>6</issue>
</nlm-citation>
</ref>
<ref id="B9">
<label>9</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lundberg]]></surname>
<given-names><![CDATA[S. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Lee]]></surname>
<given-names><![CDATA[S. I.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A unified approach to interpreting model predictions]]></article-title>
<source><![CDATA[Adv. Neural Inf. Process. Syst.]]></source>
<year>2017</year>
<volume>2017-December</volume>
<page-range>4766-75</page-range></nlm-citation>
</ref>
<ref id="B10">
<label>10</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Bergdahl]]></surname>
<given-names><![CDATA[N.]]></given-names>
</name>
<name>
<surname><![CDATA[Bond]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Sjöberg]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Dougherty]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Oxley]]></surname>
<given-names><![CDATA[E.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Unpacking student engagement in higher education learning analytics: A systematic review]]></article-title>
<source><![CDATA[International Journal of Educational Technology in Higher Education]]></source>
<year>2024</year>
<volume>21</volume>
<numero>1</numero>
<issue>1</issue>
</nlm-citation>
</ref>
<ref id="B11">
<label>11</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Ifenthaler]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Yau]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Yau]]></surname>
<given-names><![CDATA[Y.-K.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Utilising learning analytics to support study success in higher education: A systematic review]]></article-title>
<source><![CDATA[Educational Technology Research and Development]]></source>
<year>2020</year>
<volume>68</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>1961-90</page-range></nlm-citation>
</ref>
<ref id="B12">
<label>12</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Paulsen]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
<name>
<surname><![CDATA[Lindsay]]></surname>
<given-names><![CDATA[E.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Learning analytics dashboards are increasingly becoming about learning and not just analytics - a systematic review]]></article-title>
<source><![CDATA[Education and Information Technologies]]></source>
<year>2024</year>
<volume>29</volume>
<numero>11</numero>
<issue>11</issue>
<page-range>14279-308</page-range></nlm-citation>
</ref>
<ref id="B13">
<label>13</label><nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
<name>
<surname><![CDATA[Guestrin]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
</person-group>
<source><![CDATA[Xgboost: A scalable tree boosting system]]></source>
<year>2016</year>
<volume>13-17-August-2016</volume>
<conf-name><![CDATA[ ACM SIGKDD International Conference on Knowledge Discovery and Data Mining]]></conf-name>
<conf-loc> </conf-loc>
<page-range>785-94</page-range></nlm-citation>
</ref>
<ref id="B14">
<label>14</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lundberg]]></surname>
<given-names><![CDATA[S. M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[From local explanations to global understanding with explainable ai for trees]]></article-title>
<source><![CDATA[Nature Machine Intelligence]]></source>
<year>2020</year>
<volume>2</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>56-67</page-range></nlm-citation>
</ref>
<ref id="B15">
<label>15</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Barredo Arrieta]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Explainable artificial intelligence (xai): Concepts, taxonomies, opportunities and challenges toward responsible ai]]></article-title>
<source><![CDATA[Information Fusion]]></source>
<year>2020</year>
<volume>58</volume>
<page-range>82-115</page-range></nlm-citation>
</ref>
</ref-list>
</back>
</article>
