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Artificial Intelligence in Higher Education: Predictive Analysis of Attitudes and Dependency Among Ecuadorian University Students

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  • Carla Mendoza Arce

    (Business Administration Program, Faculty of Social Sciences, Commercial Education and Law, Universidad Estatal de Milagro, Milagro 091050, Ecuador)

  • Jaime Camacho Gavilanes

    (Business Administration Program, Faculty of Social Sciences, Commercial Education and Law, Universidad Estatal de Milagro, Milagro 091050, Ecuador)

  • Edgar Mendoza Arce

    (Business Administration Program, Faculty of Social Sciences, Commercial Education and Law, Universidad Estatal de Milagro, Milagro 091050, Ecuador)

  • Edgar Mendoza Haro

    (Business Administration Program, Faculty of Social Sciences, Commercial Education and Law, Universidad Estatal de Milagro, Milagro 091050, Ecuador)

  • Diego Bonilla-Jurado

    (Centro de Innovación y Transferencia Tecnologica, Instituto Superior Tecnológico España, Ambato 180103, Ecuador)

Abstract

This study examines the relationship between attitudes toward artificial intelligence (AI) and AI dependency among Ecuadorian university students. A cross-sectional design was used, applying two validated instruments: the Artificial Intelligence Dependence Scale (DAI) and the General Attitudes Toward Artificial Intelligence Scale (GAAIS), with a sample of 540 students. Structural equation modeling (SEM) assessed how both positive and negative attitudes predict dependency levels. Results indicate a moderate level of AI dependency and an ambivalent attitudinal profile. Both attitudinal dimensions significantly predicted dependency, suggesting dual-use behaviors shaped by perceived utility and ethical concerns. Urban students reported higher dependency and greater sensitivity to AI-related risks, highlighting digital inequalities. Although the SEM model showed adequate comparative fit (CFI = 0.976; TLI = 0.973), residual indicators (RMSEA = 0.075) suggest further refinement is needed. This study contributes to underexplored Latin American contexts and emphasizes the need for equity-driven digital literacy strategies in higher education. Findings support pedagogical frameworks promoting critical thinking, ethical reasoning, and responsible AI use. The study aligns with Sustainable Development Goals 4 (Quality Education) and 10 (Reduced Inequalities), reinforcing the importance of inclusive, learner-centered approaches to AI integration.

Suggested Citation

  • Carla Mendoza Arce & Jaime Camacho Gavilanes & Edgar Mendoza Arce & Edgar Mendoza Haro & Diego Bonilla-Jurado, 2025. "Artificial Intelligence in Higher Education: Predictive Analysis of Attitudes and Dependency Among Ecuadorian University Students," Sustainability, MDPI, vol. 17(17), pages 1-13, August.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:17:p:7741-:d:1736647
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    References listed on IDEAS

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    1. Bilal Ibrahim Zakarneh & Fahad Aljabr & Nidal Al Said & Mohamed Jlassi, 2025. "Assessing Pedagogical Strategies Integrating ChatGPT in English Language Teaching: A Structural Equation Modelling-Based Study," World Journal of English Language, Sciedu Press, vol. 15(3), pages 364-364, May.
    2. Ines Djokic & Nikola Milicevic & Nenad Djokic & Borka Malcic & Branimir Kalas, 2024. "Students’ Perceptions of the Use of Artificial Intelligence in Educational Service," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(65), pages 294-294, February.
    3. Sara Sáez-Velasco & Mario Alaguero-Rodríguez & Sonia Rodríguez-Cano & Vanesa Delgado-Benito, 2025. "Students’ Attitudes Towards AI and How They Perceive the Effectiveness of AI in Designing Video Games," Sustainability, MDPI, vol. 17(7), pages 1-13, March.
    4. Liangyong Xue & Abdullah Mat Rashid & Sha Ouyang, 2024. "The Unified Theory of Acceptance and Use of Technology (UTAUT) in Higher Education: A Systematic Review," SAGE Open, , vol. 14(1), pages 21582440241, February.
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