Neuroeducation and Attentional Engagement Analytics in Initial Teacher Education: A Mixed Study

César Antonio Acosta Fernández and Maricruz Paredes Laguna
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César Antonio Acosta Fernández: Benemérita Escuela Normal Veracruzana “Enrique C. Rébsamen”. Xalapa, México.
Maricruz Paredes Laguna: Benemérita Escuela Normal Veracruzana “Enrique C. Rébsamen”. Xalapa, México.

NeuroData, 2026, vol. 3, 172

Abstract: Introduction: The incorporation of neuroeducational approaches, artificial intelligence and augmented reality in initial teacher training represents an alternative to strengthen attention, participation and understanding of scientific content in primary education. Objective: To evaluate the impact of an immersive instructional environment hybridized with artificial intelligence and augmented reality on levels of attentional engagement and conceptual performance. Methodology: A mixed study with an explanatory sequential design was developed. The sample consisted of 202 fourth-grade primary school students, distributed in an experimental group of 105 students and a control group of 97 students. 6 teachers in initial training also participated. The Attentional Engagement Record Card and the Analytical Test of Conceptual Retention were applied, with an overall reliability of Cronbach's alpha of 0.88. Results: The experimental group achieved a sustained behavioral engagement of 88.2%, compared to 43.5% in the control group. In addition, it obtained a final average of 8.9 points in conceptual performance, while the control group reached 6.7 points. The Chi-square test showed statistically significant differences between both groups. Conclusions: Immersive mediation with artificial intelligence and augmented reality favored sustained attention, active participation and conceptual understanding, as long as its application was accompanied by didactic planning and teacher mediation.

Keywords: neuroeducation; attentional engagement; artificial intelligence; augmented reality; initial teacher training. (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:cxn:neurod:v:3:y:2026:id:172

DOI: 10.63688/neurodata2026172

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