Trust in Artificial Intelligence Tools and Mathematical Critical Thinking: A Predictive Relationship in University Students

Authors

DOI: https://doi.org/10.6018/rifop.698761
Keywords: artificial intelligence, confidence, skepticism, mathematics, critical thinking

Supporting Agencies

  • proyecto “Iluminando oportunidades interseccionales: aprendizaje para la mejora educativa y laboral del uso de la IA (IAMIGA)” (MEL-14-UGR24), financiado por la Universidad de Granada a través del Vicerrectorado de Investigación y Transferencia.

Abstract

The integration of artificial intelligence (AI) in higher education has generated new opportunities and challenges for fostering critical thinking, particularly in mathematics learning. This study aimed to examine the relationship between confidence and skepticism toward AI, its academic use, and university students’ mathematical critical thinking. A quantitative, descriptive, and cross-sectional design was applied to a sample of 820 Spanish university students. Data were collected through a structured questionnaire and analyzed using Pearson correlations and multiple and hierarchical regressions. The results revealed a positive and significant relationship between confidence in AI and mathematical critical thinking, while skepticism showed a negative but weaker association. No significant interaction effects were found between AI use for learning and confidence, suggesting that perceptual attitudes exert a stronger influence than usage or demographic variables. In conclusion, the findings highlight the need to promote critical digital literacy that combines informed trust and reflective skepticism, guiding higher education toward an ethical, autonomous, and analytical use of AI

Downloads

Download data is not yet available.
Metrics
Views/Downloads
  • Abstract
    21
  • pdf (Español (España))
    0

Author Biographies

Hassan Hossein-Mohand, University of Granada

Hassan Hossein-Mohand holds a degree in Physics from UNED, a Master’s degree in Occupational Risk Prevention from Universidad Francisco de Vitoria, and a PhD in Education from Universidad Autónoma de Madrid (International Mention, Cum Laude). He has developed his professional career at the intersection of formal and non-formal education. He is currently a Professor of Mathematics Education at the University of Granada and a tutor professor at UNED. In addition, he is co-founder of a training centre specialising in language certification and has coordinated initiatives such as the CUID-UNED language centre in Melilla; he is also co-founder of the “Red Tutor” network and its awards for academic excellence.

His research focuses on school failure in mathematics, the socio-affective dimension of mathematics education, youth wellbeing and leisure, socio-educational intervention and the educational uses of artificial intelligence. He has published 18 journal articles, 15 books and 30 book chapters, and participates in regional, national and international research projects on academic performance, curricular innovation and AI governance in education. He has coordinated and promoted collective volumes on youth, time self-regulation, social services, and media and AI literacy, and is involved in several competitive regional, national and international projects, as well as belonging to four research groups on digital education, mathematics education and socio-educational leisure. He has undertaken research stays in Morocco and Colombia, where he develops educational interventions with the University of Cartagena and the District Education Secretariat. He has supervised around 20 Master’s dissertations and 10 Final Degree Projects, and is currently supervising 4 doctoral theses in Spanish universities and 1 international PhD thesis. At the ERIA Chair, where he is Director of the Socio-Affective and Wellbeing Policies Area, his work focuses on the links between youth wellbeing, educational leisure and the responsible use of AI in higher education.

Hossein Hossein Mohand, Universidad de Granada

Hossein Hossein-Mohand holds a degree in Physics from UNED, a Master’s degree in Occupational Risk Prevention from Universidad Francisco de Vitoria, and a PhD in Education from Universidad Autónoma de Madrid (International Mention, Cum Laude). He is a Professor of Mathematics Education at the University of Granada and a tutor professor at UNED. His teaching and research focus on assessment of learning, teacher education and digital competence, media literacy and the pedagogical integration of generative artificial intelligence in mathematics and higher education. He has undertaken research stays in Morocco and Colombia, where he develops educational interventions in collaboration with the University of Cartagena and the District Education Secretariat.

He has published approximately 18 journal articles, 15 books and 30 book chapters, and takes part in regional, national and international research projects on academic performance, curricular innovation and AI governance in education. He has supervised around 20 Master’s dissertations and 10 Final Degree Projects, and is currently supervising 4 doctoral theses in Spanish universities and 1 international PhD thesis. He is Director of the Assessment, Teaching and Learning Outcomes Area at the ERIA Chair – Responsible Employability in AI (UAM–Founderz–Microsoft).

     

Nabil Mohamed-Chemlali, Universidad Nacional de Educación a Distancia, UNED

Nabil Mohamed Chemlali is a secondary-school Mathematics teacher, a researcher in Mathematics Education, and a PhD candidate in Education at UNED. He holds a BSc in Physics from the University of Murcia and has completed two Master’s degrees at the University of Granada: the Official Master’s Degree in Teacher Training for Compulsory Secondary Education and Upper Secondary Education (Bachillerato), Vocational Training and Language Education, and the Official Master’s Degree in Cultural Diversity. His profile bridges classroom practice with research focused on students’ perceptions, academic motivation, and the effects of technology and artificial intelligence on mathematics learning.

He has published 4 articles in international journals and contributed 7 book chapters to academic volumes. His work presents a strong, practice-oriented research profile aimed at understanding recent educational changes and improving mathematics teaching in real-world secondary education settings.

Juan Manuel Trujillo-Torres, Universidad de Granada

Juan Manuel Trujillo Torres holds a Teaching Diploma from the University of Granada, a degree in Pedagogy from UNED (Madrid), a PhD in Educational Sciences from the University of Granada, and an official Master’s degree in New Technologies Applied to Education from the University of Málaga. He has fourteen years of teaching experience in primary and secondary schools, leading projects focused on ICT integration and emerging pedagogies. He is currently a Full Professor (Chair) and Director of the Department of Didactics and School Organization at the University of Granada.

He has authored over 100 articles in international high-impact journals and 95 book chapters published by recognized academic publishers. He has taken part in more than 200 international education conferences, delivering around 180 presentations and communications. He has been awarded two positively evaluated research six-year terms (CNEAI) and has served on approximately 90 doctoral dissertation committees. He has undertaken academic and teaching visits in universities across the UK, the Czech Republic, Portugal, Colombia, Mexico, Italy, Paraguay, Ukraine, and Morocco. He also serves on scientific committees and acts as a reviewer for numerous education journals, has supervised more than 40 master’s theses, and has held several university management and institutional representation roles.

References

Afroogh, S., Akbari, A., Malone, E., Kargar, M., y Alambeigi, H. (2024). Trust in AI: progress, challenges, and future directions. Humanities and Social Sciences Communications, 11(1). https://doi.org/10.1057/s41599-024-04044-8

Darwin, Diyenti Rusdin, Nur Mukminatien, Nunung Suryati, Ekaning Dewanti Laksmi, y Marzuki. (2023). Critical thinking in the AI era: An exploration of EFL students’ perceptions, benefits, and limitations.Cogent Education, 11(1). https://doi.org/10.1080/2331186x.2023.2290342

Đerić, E., Frank, D., y Milković, M. (2025). Trust in Generative AI Tools: A Comparative Study of Higher Education Students, Teachers, and Researchers. Information, 16(7), 622. https://doi.org/10.3390/info16070622

Gonsalves, C. (2024). Generative AI’s Impact on Critical Thinking: Revisiting Bloom’s Taxonomy. Journal of Marketing Education, 0(0). https://doi.org/10.1177/02734753241305980

Hossein-Mohand, H., Hossein Hossein-Mohand, Albanese, V., y Carmen, del. (2025). AI in mathematics education: A bibliometric analysis of global trends and collaborations (2020-2024). Eurasia Journal of Mathematics Science and Technology Education, 21(2), em2576–em2576. https://doi.org/10.29333/ejmste/15915

Hou, C., Zhu, G., y Vidya Sudarshan. (2025). The role of critical thinking on undergraduates’ reliance behaviours on generative AI in problem‐solving. British Journal of Educational Technology, 56(5). https://doi.org/10.1111/bjet.13613

Jiang, W., Li, D., y Liu, C. (2025). Understanding dimensions of trust in AI through quantitative cognition: Implications for human-AI collaboration. PLOS One, 20(7), e0326558. https://doi.org/10.1371/journal.pone.0326558

Laru, J., Celik, I., Jokela, I., y Mäkitalo, K. (2025). The antecedents of pre-service teachers’ AI literacy: perceptions about own AI driven applications, attitude towards AI and knowledge in machine learning. European Journal of Teacher Education, 1-23. https://doi.org/10.1080/02619768.2025.2535623

Li, M., y Manzari, E. (2025). AI utilization in primary mathematics education: a case study from a southwestern Chinese city. Education and Information Technologies, 30, 11717–11750. https://doi.org/10.1007/s10639-025-13315-z

Marín Díaz, G. (2025). Supporting Reflective AI Use in Education: A Fuzzy-Explainable Model for Identifying Cognitive Risk Profiles. Education Sciences, 15(7), 923. https://doi.org/10.3390/educsci15070923

Mavrikis, M., y Margeti, M. (2024). Review of mathematics education in the age of artificial intelligence. Research in Mathematics Education, 1–8. https://doi.org/10.1080/14794802.2024.2389418

Nazaretsky, T., Mejia-Domenzain, P., Swamy, V., Frej, J., y Käser, T. (2025). The critical role of trust in adopting AI-powered educational technology for learning: An instrument for measuring student perceptions. Computers and Education: Artificial Intelligence, 8, 100368. https://doi.org/10.1016/j.caeai.2025.100368

Opesemowo, O. A. G., y Adewuyi, H. O. (2024). A systematic review of artificial intelligence in mathematics education: The emergence of 4IR. Eurasia Journal of Mathematics, Science and Technology Education, 20(7), em2478. https://doi.org/10.29333/ejmste/14762

Rizos, I., y Gkrekas, N. (2025). The impact of LLMs on mathematics education and research at the university. Social Sciences & Humanities Open, 12, 101969. https://doi.org/10.1016/j.ssaho.2025.101969

Seker, O., Kwon, K., y Kocak, O. (2025). Exploring researchers’ artificial intelligence (AI) literacy: The mediating role of digital literacy and data literacy between 21st century skills and AI literacy. Information Development, 0(0). https://doi.org/10.1177/02666669251336368

Viberg, O., Mutlu Cukurova, Feldman-Maggor, Y., Giora Alexandron, Shirai, S., Susumu Kanemune, Wasson, B., Tømte, C., Spikol, D., Milrad, M., Coelho, R., y Kizilcec, R. F. (2024). What Explains Teachers’ Trust in AI in Education Across Six Countries? International Journal of Artificial Intelligence in Education, 35, 1288–1316. https://doi.org/10.1007/s40593-024-00433-x

Wijaya, T. T., Yu, Q., Cao, Y., He, Y., y Frederick. (2024). Latent Profile Analysis of AI Literacy and Trust in Mathematics Teachers and Their Relations with AI Dependency and 21st-Century Skills. Behavioral Sciences, 14(11), 1008–1008. https://doi.org/10.3390/bs14111008

Zhang, W., y Liu, X. (2025). Artificial Intelligence-Generated Content Empowers College Students’ Critical Thinking Skills: What, How, and Why. Education Sciences, 15(8), 977. https://doi.org/10.3390/educsci15080977

Published
30-04-2026
How to Cite
Hossein-Mohand, H., Hossein Mohand, H., Mohamed-Chemlali, N., & Trujillo-Torres, J. M. (2026). Trust in Artificial Intelligence Tools and Mathematical Critical Thinking: A Predictive Relationship in University Students. Revista Interuniversitaria De Formación Del Profesorado, 40(1), 15–27. https://doi.org/10.6018/rifop.698761
Issue
Vol. 40 No. 1 (2026): Uso responsable de la inteligencia artificial. Aprendizaje, formación y empleabilidad
Section
Artículos

Copyright (c) 2026 Revista Interuniversitaria de Formación del Profesorado

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 Unported License.

La Revista Interuniversitaria de Formación del Profesorado (RIFOP), con ISSN impreso 0213-8646 e ISSN electrónico 2530-3791, se adhiere a los avisos de derechos de autor propuestos por Creative Commons.

Derechos de autor

Los artículos publicados en la revista están sujetos a las siguientes condiciones:

  1. La Asociación Universitaria de Formación del Profesorado (AUFOP) es la editora de RIFOP y posee los derechos de autor de los artículos publicados en ella. Se permite la reutilización de estos bajo la licencia de uso indicada en el punto 2.

© Asociación Universitaria de Formación del Profesorado (AUFOP)

  1. Los artículos se publican en versión electrónica bajo la licencia Creative Commons Reconocimiento-NoComercial-SinObraDerivada 3.0 España (texto legal). Los artículos pueden copiarse, utilizarse, difundirse, transmitirse y exhibirse públicamente siempre que: i) se cite la autoría y la fuente original de publicación (revista, editores y URL del artículo); ii) no se utilizan con fines comerciales; iii) se menciona la existencia y las especificaciones de la licencia de uso.
  2. Condiciones de autoarchivo. Se permite y se anima a los autores a difundir versiones electrónicas preimpresas (versiones previas a la revisión por pares) y/o postimpresas (versiones revisadas y aceptadas para su publicación) de sus artículos antes de su publicación, ya que esto favorece su rápida circulación y difusión, y supone un posible aumento de citas y alcance dentro de la comunidad académica.

Declaración de privacidad

Los nombres y direcciones de correo electrónico incorporados a esta revista se utilizarán únicamente para los fines declarados de la revista y no estarán disponibles para ningún otro fin ni para terceros.