<?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>2026-07-16T01:16:04Z</responseDate><request verb="GetRecord" identifier="oai:riubu.ubu.es:10259/11912" metadataPrefix="marc">https://riubu.ubu.es/oai/request</request><GetRecord><record><header><identifier>oai:riubu.ubu.es:10259/11912</identifier><datestamp>2026-07-14T00:05:28Z</datestamp><setSpec>com_10259_9401</setSpec><setSpec>com_10259_5087</setSpec><setSpec>com_10259_2728</setSpec><setSpec>col_10259_9403</setSpec></header><metadata><record xmlns="http://www.loc.gov/MARC21/slim" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dcterms="http://purl.org/dc/terms/" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
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<subfield code="a">Martínez Mora, Sara</subfield>
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<subfield code="a">Morales Balbás, Samuel</subfield>
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<subfield code="a">Sanz Palacios, Teresa</subfield>
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<subfield code="a">Urizarna Sánchez, Alba</subfield>
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<subfield code="c">2026-05-18</subfield>
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<subfield code="a">This study analyses the multimodal evaluation of cognitive load in complex visuomotor &#xd;
test, specifically focusing on implicit bias within human-IA interaction in the context of &#xd;
Industry 5.0. The research aims to understand how unconscious prejudices, measured &#xd;
through the Implicit Association Test (IAT or TAI, Spanish version), modulate user &#xd;
experience and how intelligent systems can act as emotional regulators. Using a multiple &#xd;
single case experimental design (n=3) three female university students aged 20 were &#xd;
evaluated. The methodology integrated subjective measures via NASA-TLX, &#xd;
physiological responses using Galvanic Skin Response (GSR) and &#xd;
electroencephalography (EEG), and visual behaviour through eye-tracking technology. &#xd;
In addition, a conversational chatbot named EsencIA was developed to provide &#xd;
psychological support based on cognitive-behavioural therapy for participants &#xd;
experiencing high frustration. Results indicate that participants perceive the TAI as a &#xd;
demanding task with medium-high mental load, where the temporal demand and effort &#xd;
are prominent. Quantitative data show a correlation between the intensity of implicit bias &#xd;
and visual exploration patterns, suggesting that more consolidated biases require greater &#xd;
cognitive supervision and increased saccadic movements. These findings highlight the &#xd;
importance of integrating multimodal metrics to understand cognitive and emotional &#xd;
processing, confirming the potential of IA as a support tool in high-demand environment &#xd;
to mitigate stress and improve user interaction.</subfield>
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<subfield code="a">https://hdl.handle.net/10259/11912</subfield>
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<subfield code="a">Industria 5.0</subfield>
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<subfield code="a">TAI</subfield>
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<subfield code="a">Eye-tracking</subfield>
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<subfield code="a">Chatbot</subfield>
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<subfield code="a">Carga cognitiva</subfield>
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<subfield code="a">Apoyo emocional</subfield>
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<subfield code="a">Evaluación multimodal de la carga cognitiva en el desempeño  de tareas visomotoras complejas: un estudio sobre el sesgo  implícito en la interacción humano-ia</subfield>
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