Analyse qualitative des facteurs méta-individuels de l’acceptation et de l’utilisation de l’intelligence artificielle dans le contexte éducatif d’Agadir

Abstract

This research contextualizes, within teaching practice in Agadir, a model of meta-individual factors of technology acceptance, applied to artificial intelligence. Sixteen semi-structured interviews, conducted from December 2024 to January 2025 with teachers and practitioners, were transcribed and processed using NVivo 12 software according to two levels of analysis: lexical and thematic. The lexical analysis remains descriptive; the retention of factors relies on directed thematic analysis. Technology-work fit and infrastructure complexity appear associated with acceptance across all sixteen participants. Social influence, cited by six participants, is retained with caution. Managerial support, mentioned by ten participants, is formulated as a proposed moderator of the relationship between acceptance and use. Age and experience are proposed as moderators to be tested. The study distinguishes acceptance from use and calls for confirmatory validation before any generalization.

However, these findings, being exploratory in nature and derived from a directed qualitative analysis, should be interpreted with caution. They open avenues for future research aimed at testing and, where appropriate, generalizing the revised model.