The widespread emergence of generative artificial intelligence (GAI) has prompted growing interest in understanding the factors that drive its adoption in academic contexts. This study explores the behavioral intention of Peruvian university students to use GAI tools in their educational activities by applying the technology acceptance model (TAM) through partial least squares structural equation modeling (PLS-SEM). A total of 350 valid responses were collected from students at the Universidad Nacional Agraria La Molina. The model demonstrated strong reliability and validity, with key constructs such as perceived usefulness and attitude toward use explaining 12% and 9% of the variance in intention, respectively. Notably, behavioral intention significantly predicted actual use, accounting for 58.8% of the variance. To address concerns of common method bias, statistical controls were implemented. The results underscore the importance of designing user-friendly and pedagogically relevant GAI tools because ease of use was found to strongly influence perceived usefulness and attitudes. This study contributes to the literature by validating a TAM-based model in the Latin American higher education context and identifying actionable variables that institutions can leverage to foster ethical and effective adoption of GAI. It also highlights students’ current reliance on tools such as ChatGPT® and ChatPDF® for information retrieval and summarization. These findings support the development of informed policies and training initiatives to guide the responsible integration of AI in academic environments.
The widespread emergence of generative artificial intelligence (GAI) has prompted growing interest in understanding the factors that drive its adoption in academic contexts. This study explores the behavioral intention of Peruvian university students to use GAI tools in their educational activities by applying the technology acceptance model (TAM) through partial least squares structural equation modeling (PLS-SEM). A total of 350 valid responses were collected from students at the Universidad Nacional Agraria La Molina. The model demonstrated strong reliability and validity, with key constructs such as perceived usefulness and attitude toward use explaining 12% and 9% of the variance in intention, respectively. Notably, behavioral intention significantly predicted actual use, accounting for 58.8% of the variance. To address concerns of common method bias, statistical controls were implemented. The results underscore the importance of designing user-friendly and pedagogically relevant GAI tools because ease of use was found to strongly influence perceived usefulness and attitudes. This study contributes to the literature by validating a TAM-based model in the Latin American higher education context and identifying actionable variables that institutions can leverage to foster ethical and effective adoption of GAI. It also highlights students’ current reliance on tools such as ChatGPT® and ChatPDF® for information retrieval and summarization. These findings support the development of informed policies and training initiatives to guide the responsible integration of AI in academic environments. Read More
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