Relationship between models of technology acceptance, artificial intelligence, and information behavior: a systematic literature review
DOI:
https://doi.org/10.15517/3npxt231Keywords:
artificial intelligence, technology acceptance model, information behavior, systematic literature reviewAbstract
Objective: To conduct a systematic literature review (SLR) on technology acceptance models (TAM) regarding the adoption of artificial intelligence (AI) and its relationship with information behavior (IB) in educational settings, consolidating definitions, methods, and research gaps. Methodology: The SRL was divided into two stages: the first was the planning stage, which involved defining the need for the review between 2013 and 2024, selecting keywords in Spanish and English, Boolean operators, the subject area, and the databases DOAJ, Elsevier, and Google Scholar; and the second was the implementation stage, where inclusion and exclusion criteria were applied, and the information was organized into a detailed matrix including author, country, model, definitions, hypotheses, and instruments. Results: Theoretical and empirical findings on models of technology acceptance related to AI, CI, and the complementary methodological relationship among the various models identified. Conclusions: There has been an increase in publications measuring the perceived usefulness and ease of use of AI systems in the classroom; however, there is a need to develop specific measurement instruments for AI, enrich the constructs, and address ethical and cultural dimensions. Finally, the importance of replicable protocols is emphasized to ensure comparability and rigor in future research.
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