Keywords

Generative Artificial Intelligence, Human-computer Interaction, AI Literacy, Ethics in Education, Teacher Resistance, Student Resistance

Abstract

The expansion of generative artificial intelligence in education has renewed debate about its pedagogical value, ethical risks, and the new forms of mediation emerging among teachers, students, and technologies. The problem guiding this study lies in the fact that these forms of mediation, increasingly present in higher education, are not fully explained by frameworks for technology integration developed for non-conversational digital environments. In this context, the study examines how students and graduates of postgraduate education programs perceive the potential of language models such as ChatGPT, Claude, and Gemini to support meaningful learning, and whether these perceptions call for a reconsideration of TPACK and SAMR. The research follows a qualitative, interpretive methodology based on theoretical thematic analysis. Data collection involved open-ended questionnaires (N=50) and semi-structured interviews (N=10) conducted with participants affiliated with two universities in Israel and Argentina. Three core themes emerged: (1) Production, where generative AI supports information retrieval and writing; (2) Interaction, where participants perceive it as a cognitive and dialogic support; and (3) Ethics and Resistance, where concerns arise regarding dependency, authenticity, fairness, and pedagogical responsibility. The study’s originality lies in articulating empirical evidence with a human-computer interaction perspective in order to provide conceptual and pedagogical criteria relevant to teaching, AI literacy, and institutional guidance.

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Received: 2026-03-02 | Reviewed: 2026-03-18 | Accepted: 2026-03-25 | Online First: 2026-07-17 | Published: 2026-07-19

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Marcelo I. Dorfsman. (2026). Reframing Traditional Models of Educational Technology in the AI Generative Era. Comunicar, 34(86). 10.5281/zenodo.21421393

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