Modeling of the adoption of artificial intelligence tools in higher education: a TAM -based approach
DOI:
https://doi.org/10.5281/zenodo.17653760Keywords:
artificial intelligence, higher education, technology adoption, perceived usefulnessAbstract
Introduction: artificial intelligence (AI) has emerged as one of the most transformative technologies in higher education, providing tools that facilitate personalized learning and optimize academic and administrative processes; however, its adoption depends on individual and organizational factors. Objective: to analyze the influence of perceived usefulness, ease of use, attitude, and intention to use on the adoption of AI tools among university students through the Technology Acceptance Model (TAM). Method: a quantitative descriptive-correlational approach was employed, applying a validated questionnaire to 55 students with prior experience in AI, and the data were processed using Pearson correlations and multiple regression analysis. Results: intention to use was identified as the most relevant predictor of actual use (β = 0.679, p < 0.001), followed by perceived usefulness (β = 0.374, p = 0.024), while ease of use had no significant impact, and attitude showed an inconclusive negative relationship. Conclusion: the TAM model proved pertinent in explaining the adoption of AI tools in higher education, highlighting that perceived usefulness and intention to use are the determining factors to ensure effective implementation of these technologies.
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