The influence of learning motivation and procrastination on ChatGPT dependence

Authors

DOI:

https://doi.org/10.5944/ried.45497

Keywords:

motivation, dependence, ChatGPT, procrastination, artificial intelligence, higher education

Abstract

In a short period of time, generative artificial intelligences such as ChatGPT have become a widely used support tool for students' learning processes, altering how many approach academic tasks. Their immediacy and accessibility make them attractive alternatives to traditional study resources, to the extent that some students may have even developed a certain degree of dependence on these tools. The present study investigates the impact of learning motivation and procrastination on ChatGPT dependence. A total of 467 university students from the field of education participated by completing a series of validated scales measuring different types of motivation defined in Self-Determination Theory (extrinsic motivation, intrinsic motivation, and amotivation), procrastination, and ChatGPT dependence. The indirect effects of the mediation analyses revealed that students with lower levels of intrinsic motivation (β = -.076; LL = -.121; UL = -.037) and higher levels of amotivation (β = .090; LL = .041; UL = .144) were more likely to procrastinate frequently, with procrastination emerging as a significant factor contributing to greater ChatGPT dependence. Similarly, results indicated that students with high extrinsic motivation (without procrastination serving as a mediator) were more prone to develop greater dependence on ChatGPT (β = .122; p = .022). These findings highlight the importance of implementing strategies that foster intrinsic motivation and self-regulation, helping students use generative AI-based tools appropriately while developing essential competencies that could be at risk from excessive use of these tools, such as critical thinking and problem-solving.

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Author Biographies

Héctor Galindo-Domínguez, Universidad del País Vasco, UPV/EHU (Spain)

PhD in Education with Cum Laude distinction (University of Deusto), holding master’s degrees in Educational Innovation (UNED) and School Bullying (San Jorge University), and a bachelor’s degree in Primary Education (UPV/EHU). Assistant Professor at the University of the Basque Country (UPV/EHU), researcher in educational methodologies and technologies, well-being, and critical thinking, with experience as a Primary Education teacher.

Martín Sainz-de-la-Maza, Universidad del País Vasco, UPV/EHU (Spain)

Graduate in Psychology and PhD from the University of the Basque Country (UPV/EHU), with master’s degrees in Social Psychology and Social Sciences. Lecturer in Developmental and Educational Psychology (UPV/EHU) and collaborator in research projects on risk practices. Has presented work at national and international conferences on education and social sciences.

Lucía Campo, Universidad del País Vasco, UPV/EHU (Spain)

PhD in Education (University of Deusto), with degrees in Psychology and Psychopedagogy, and a Master’s in Innovation and Competencies. Assistant Professor at the University of the Basque Country (UPV/EHU), with experience as a university lecturer, educational planning advisor, and special education teacher. Her research focuses on teaching competencies, critical thinking, assessment, and the use of technologies in education.

Daniel Losada-Iglesias, Universidad del País Vasco, UPV/EHU (Spain)

PhD in Psychodidactics, with degrees in Psychopedagogy and Primary Education. Full Professor at the University of the Basque Country (UPV/EHU), specializing in Educational Technology and Teacher Training. Author of over 50 publications, with three teaching periods and two research periods officially recognized, leadership experience, and member of the Editorial Board of the Latin American Journal of Educational Technology.

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Published

2026-01-02

How to Cite

Galindo-Domínguez, H., Sainz-de-la-Maza, M., Campo, L., & Losada-Iglesias, D. (2026). The influence of learning motivation and procrastination on ChatGPT dependence. RIED-Revista Iberoamericana de Educación a Distancia, 29(1), 217–240. https://doi.org/10.5944/ried.45497

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