Impact of generative artificial intelligence on the decision-making of university students in the health sciences: A transversal study

Darwin Marcelo Varela Lascano, Tania Lisbeth Chicaiza Zambrano, Eduardo Xavier Macías Collahuazo and Yordan Ernesto Calero Ocaña

Data and Metadata, 2025, vol. 4, 1017

Abstract: Advanced AI systems, such as those in their generative phase, cause uncertainty among higher education students about their functionality and the academic level they may have when interacting with IAGs such as ChatGPT. The study aimed to examine how interaction with AI tools, such as generative language models, influences students' ability to select learning strategies, manage academic resources, and make informed decisions during their professional training. A quantitative, descriptive, non-experimental approach was used. The initial population was 500 students from the Faculty of Medicine of two recognized higher education institutions in Ecuador, after applying certain inclusion criteria through random convenience sampling. The results showed that generative artificial intelligence significantly influences the academic decision-making of medical students, with scalability and efficiency standing out as key factors. In contrast, user satisfaction showed an inverse relationship, and institutional integration was not a determining factor. It is concluded that the impact of these tools depends on their strategic functionality rather than their superficial perception.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:dbk:datame:v:4:y:2025:i::p:1017:id:1056294dm20251017

DOI: 10.56294/dm20251017

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