<?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>1317-0570</journal-id>
<journal-title><![CDATA[Telos]]></journal-title>
<abbrev-journal-title><![CDATA[Telos]]></abbrev-journal-title>
<issn>1317-0570</issn>
<publisher>
<publisher-name><![CDATA[Universidad Dr. Rafael Belloso Chacín]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1317-05702025000301003</article-id>
<article-id pub-id-type="doi">10.36390/telos273.20</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[INTELIGENCIA ARTIFICIAL EN LA INVESTIGACIÓN: REPLANTEAMIENTO CRÍTICO DE LA ENSEÑANZA DE LA METODOLOGÍA INVESTIGATIVA]]></article-title>
<article-title xml:lang="en"><![CDATA[Artificial Intelligence in Research: Critical Rethinking of the Teaching of Research Methodology]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cendrós Guasch]]></surname>
<given-names><![CDATA[Jesus]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Privada Dr. Rafael Belloso Chacín  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Venezuela</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2025</year>
</pub-date>
<volume>27</volume>
<numero>3</numero>
<fpage>1003</fpage>
<lpage>1009</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://ve.scielo.org/scielo.php?script=sci_arttext&amp;pid=S1317-05702025000301003&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://ve.scielo.org/scielo.php?script=sci_abstract&amp;pid=S1317-05702025000301003&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://ve.scielo.org/scielo.php?script=sci_pdf&amp;pid=S1317-05702025000301003&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN Este artículo analiza el impacto de la Inteligencia Artificial (IA) en la enseñanza de la metodología de investigación. . Si bien la IA ofrece mejoras notables en eficiencia y escalabilidad en todas las fases de la investigación (revisión literaria, análisis de datos, redacción), el análisis revela riesgos profundos como sesgos algorítmicos, erosión del pensamiento crítico, opacidad de los sistemas ("caja negra") y la potencial marginación de epistemologías no occidentales. Frente a estos desafíos, frente a esto, se rechaza el determinismo tecnológico y se propone una integración centrada en lo humano. La conclusión subraya que el verdadero potencial de la IA no está en reemplazar, sino ahorrar tiempo liberando al investigador de tareas rutinarias para potenciar su labor crítica y creativa. Para ello, se requiere una formación docente en "criticalidad digital", políticas institucionales que alineen los incentivos y un marco ético ampliado que trascienda lo individual para abordar dimensiones estructurales y de gobernanza, asegurando que la tecnología sirva a los valores pedagógicos fundamentales.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT This article provides a critical analysis of the impact of Artificial Intelligence (AI) on teaching research methodology. It identifies a significant gap between high student adoption and low integration by faculty. While AI offers notable gains in efficiency and scalability across all research phases (literature review, data analysis, writing), the analysis reveals profound risks such as algorithmic biases, erosion of critical thinking, opacity of systems ("black box"), and the potential marginalization of non-Western epistemologies.In the face of these challenges, technological determinism is rejected in favor of a human-centered integration. The conclusion emphasizes that AI's true potential lies not in replacement but in freeing the researcher from routine tasks to save time to enhance their critical and creative work. Achieving this requires teacher training in "digital criticality," institutional policies that align incentives, and an expanded ethical framework that transcends the individual to address structural and governance dimensions, ensuring that technology serves fundamental pedagogical values.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Metodología de la Investigación]]></kwd>
<kwd lng="es"><![CDATA[Inteligencia Artificial]]></kwd>
<kwd lng="es"><![CDATA[Sesgo algorítmico]]></kwd>
<kwd lng="es"><![CDATA[Enseñanza]]></kwd>
<kwd lng="es"><![CDATA[impacto IA]]></kwd>
<kwd lng="en"><![CDATA[Research Methodology]]></kwd>
<kwd lng="en"><![CDATA[Artificial Intelligence]]></kwd>
<kwd lng="en"><![CDATA[Algorithmic Bias]]></kwd>
<kwd lng="en"><![CDATA[Teaching]]></kwd>
<kwd lng="en"><![CDATA[IA impact]]></kwd>
</kwd-group>
</article-meta>
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