Artificial Intelligence and Didactics: Insights for teaching Latin

The article examines the integration of artificial intelligence (AI) into the didactics of Latin, framing AI as a transformative epistemic mediator rather than a mere technological adjunct. In the evolving digital landscape, AI is reshaping educational processes by influencing how knowledge is accessed, structured, and interpreted. The study critically explores four key areas—adaptive learning, gamification, assisted translation, and digital resources—demonstrating how AI can enhance pedagogical personalization, engagement, and inclusive learning experiences. Special attention is given to the challenges posed by algorithmic opacity, teacher mediation, and the ethical tensions surrounding automation in educational settings. The Latin language, understood as a symbolic and logical construct, is presented as uniquely suited to benefit from AI-enhanced learning environments, which can support complex interpretive practices. When implemented within a coherent pedagogical framework, critically and ethically, AI has the potential to revitalize classical language teaching, enhance students’ interpretive skills and metalinguistic skills, foster both critical literacy and meaningful interaction with classical texts. Ultimately, this contribution argues for a humanistic and ethically grounded approach on AI integration in education: Latin and AI together offer new avenues for promoting critical thinking and cultural awareness in education, reaffirming the relevance of classical studies in the digital age. Keywords: Artificial Intelligence; Inclusion; Teacher Education; Latin Didactics; Inclusive Technologies.

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Publication Details

Journal
Athens Journal of Education
Published
2026-10-31
DOI
https://doi.org/10.30958/aje.13-4-7
Primary Topic
Artificial Intelligence in Education
Type
article
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0.00
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article

Artificial Intelligence and Didactics: Insights for teaching Latin

Michele Domenico Todino, Iolanda Zollo, Rita Colace
Athens Journal of Education
Artificial Intelligence in Education
article

Artificial Intelligence and Didactics: Insights for teaching Latin

Michele Domenico Todino, Iolanda Zollo, Rita Colace
article en

Abstract

The article examines the integration of artificial intelligence (AI) into the didactics of Latin, framing AI as a transformative epistemic mediator rather than a mere technological adjunct. In the evolving digital landscape, AI is reshaping educational processes by influencing how knowledge is accessed, structured, and interpreted. The study critically explores four key areas—adaptive learning, gamification, assisted translation, and digital resources—demonstrating how AI can enhance pedagogical personalization, engagement, and inclusive learning experiences. Special attention is given to the challenges posed by algorithmic opacity, teacher mediation, and the ethical tensions surrounding automation in educational settings. The Latin language, understood as a symbolic and logical construct, is presented as uniquely suited to benefit from AI-enhanced learning environments, which can support complex interpretive practices. When implemented within a coherent pedagogical framework, critically and ethically, AI has the potential to revitalize classical language teaching, enhance students’ interpretive skills and metalinguistic skills, foster both critical literacy and meaningful interaction with classical texts. Ultimately, this contribution argues for a humanistic and ethically grounded approach on AI integration in education: Latin and AI together offer new avenues for promoting critical thinking and cultural awareness in education, reaffirming the relevance of classical studies in the digital age. Keywords: Artificial Intelligence; Inclusion; Teacher Education; Latin Didactics; Inclusive Technologies.

Athens Journal of EducationVol. 13(4)
Openalex Percentile: Top 6%
Artificial Intelligence in Education
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Artificial Intelligence and Didactics: Insights for teaching Latin — Michele Domenico Todino, Iolanda Zollo, et al. · Athens Journal of Education (2026) | TGRS Research Map | TGRS