Neuroeducation and artificial intelligence: innovative strategies to strengthen teaching and learning processes in Basic General Education

The integration of artificial intelligence (AI) tools into basic general education creates new possibilities for differentiated teaching, while neuroeducation contributes evidence on attention, memory, motivation, self-regulation, and learning. This documentary review aimed to examine pedagogical strategies derived from both fields and assess their opportunities and limitations in school teaching and learning. A targeted search of academic literature published between January 2020 and August 31, 2026 was conducted using thematic relevance, editorial traceability, and educational applicability criteria. PRISMA 2020 guidance informed transparent reporting of the selection process, without claiming an undocumented exhaustive quantitative flow. The synthesis drew on 16 verified academic publications and four methodological or institutional sources. Findings were organized into four dimensions: neuroeducational principles, AI-supported personalization, teacher competencies, and ethical implementation conditions. Reviewed studies suggest opportunities for differentiated feedback, graduated tasks, active learning, and lesson planning. However, they also identify persistent neuromyths, variable accuracy of generative outputs, children’s data privacy risks, and unequal access to digital infrastructure. The review concludes that combining neuroeducation and AI can be pedagogically relevant when AI remains a supervised support tool, measurable learning outcomes are assessed, and technological personalization is not confused with neurocognitive diagnosis. Teacher judgment, inclusion, and evidence-based instructional design should guide implementation.

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Publication Details

Journal
Sage Sphere in Artificial Intelligence
Published
2026-11-11
DOI
https://doi.org/10.63688/hn001w30
Primary Topic
Artificial Intelligence in Education
Type
article
Field-Weighted Citation Impact
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article

Neuroeducation and artificial intelligence: innovative strategies to strengthen teaching and learning processes in Basic General Education

Fabiana Nairoby Moncayo Quirola, Emely Jamilet Cárdenas Posligua, Derian Santiago Mendoza Zambrano, Jessica Vivian Quirola Mera et al.
Sage Sphere in Artificial Intelligence
Artificial Intelligence in Education
article

Neuroeducation and artificial intelligence: innovative strategies to strengthen teaching and learning processes in Basic General Education

Fabiana Nairoby Moncayo Quirola, Emely Jamilet Cárdenas Posligua, Derian Santiago Mendoza Zambrano, Jessica Vivian Quirola Mera, Virginia Yamilet Mendoza Loor
article en

Abstract

The integration of artificial intelligence (AI) tools into basic general education creates new possibilities for differentiated teaching, while neuroeducation contributes evidence on attention, memory, motivation, self-regulation, and learning. This documentary review aimed to examine pedagogical strategies derived from both fields and assess their opportunities and limitations in school teaching and learning. A targeted search of academic literature published between January 2020 and August 31, 2026 was conducted using thematic relevance, editorial traceability, and educational applicability criteria. PRISMA 2020 guidance informed transparent reporting of the selection process, without claiming an undocumented exhaustive quantitative flow. The synthesis drew on 16 verified academic publications and four methodological or institutional sources. Findings were organized into four dimensions: neuroeducational principles, AI-supported personalization, teacher competencies, and ethical implementation conditions. Reviewed studies suggest opportunities for differentiated feedback, graduated tasks, active learning, and lesson planning. However, they also identify persistent neuromyths, variable accuracy of generative outputs, children’s data privacy risks, and unequal access to digital infrastructure. The review concludes that combining neuroeducation and AI can be pedagogically relevant when AI remains a supervised support tool, measurable learning outcomes are assessed, and technological personalization is not confused with neurocognitive diagnosis. Teacher judgment, inclusion, and evidence-based instructional design should guide implementation.

Sage Sphere in Artificial IntelligenceVol. 4(1)
Artificial Intelligence in Education
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