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Peer-reviewedCC BY-NC-NDJournal of education and health promotion

Motivation to learn artificial intelligence applications and mental well-being in university students: A cross-sectional study.

  • Afaf Abdelah Othman1
  • Huda Saleh Abdul Rahman Al-Shimeimri2
  • Wafaa Mohamed Ibrahim El Bana3
  • Abdelrahim Fathy Ismail4
4 affiliations
  1. 1Department of Education and Psychology, Faculty of Education, Najran University, Saudi Arabia.
  2. 2Department of Psychology, Faculty of Education, Umm Al-Qura University, Saudi Arabia.
  3. 3Applied College, Applied Business Administration, Najran University, Saudi Arabia.
  4. 4Curriculum and Instruction Department, Faculty of Education, King Faisal University, Al Ahsa 31982, Saudi Arabia.
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Abstract

Background

Artificial intelligence (AI) is increasingly integrated into higher education, while students' mental well-being has become a critical concern. The relationship between AI learning motivation and mental well-being was investigated.Materials and methods

A cross-sectional correlational study was conducted among 195 students at the Faculty of Education, Najran University, Saudi Arabia, during the first semester of 2025-2026. Data were collected using the motivation to learn AI applications scale and a researchers-developed mental well-being scale (Cronbach's α = 0.792). Data were analyzed using Statistical Package for the Social Sciences version 26 with Pearson correlation, independent samples t-test, and linear regression (P ≤ 0.050).Results

Motivation to learn AI applications showed a significant positive correlation with mental well-being (r = 0.458, P < 0.001). Students with higher motivation reported significantly higher mental well-being (P < 0.001). Female students showed higher motivation (P = 0.007), while no significant gender differences were found in mental well-being (P = 0.421). Motivation significantly predicted mental well-being (β = 0.233, R ² = 0.184, P < 0.001).Conclusion

Motivation to learn AI applications was positively associated with students' mental well-being and explained a modest proportion of its variance.

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Cite

BibTeXRIS
BibTeX
@article{othman2026motivation,
  title = {{Motivation to learn artificial intelligence applications and mental well-being in university students: A cross-sectional study.}},
  author = {Afaf Abdelah Othman and Huda Saleh Abdul Rahman Al-Shimeimri and Wafaa Mohamed Ibrahim El Bana and Abdelrahim Fathy Ismail},
  journal = {Journal of education and health promotion},
  year = {2026},
  month = sep,
  doi = {10.4103/jehp.jehp_261_26},
  url = {https://europepmc.org/article/MED/42924303},
  note = {CC BY-NC-ND},
}
RIS
TY  - JOUR
TI  - Motivation to learn artificial intelligence applications and mental well-being in university students: A cross-sectional study.
AU  - Afaf Abdelah Othman
AU  - Huda Saleh Abdul Rahman Al-Shimeimri
AU  - Wafaa Mohamed Ibrahim El Bana
AU  - Abdelrahim Fathy Ismail
PY  - 2026
DA  - 2026/09/30
JO  - Journal of education and health promotion
DO  - 10.4103/jehp.jehp_261_26
UR  - https://europepmc.org/article/MED/42924303
AB  - Background  Artificial intelligence (AI) is increasingly integrated into higher education, while students' mental well-being has become a critical concern. The relationship between AI learning motivation and mental well-being was investigated.Materials and methods  A cross-sectional correlational study was conducted among 195 students at the Faculty of Education, Najran University, Saudi Arabia, during the first semester of 2025-2026. Data were collected using the motivation to learn AI applications scale and a researchers-developed mental well-being scale (Cronbach's α = 0.792). Data were analyzed using Statistical Package for the Social Sciences version 26 with Pearson correlation, independent samples t-test, and linear regression (P ≤ 0.050).Results  Motivation to learn AI applications showed a significant positive correlation with mental well-being (r = 0.458, P < 0.001). Students with higher motivation reported significantly higher mental well-being (P < 0.001). Female students showed higher motivation (P = 0.007), while no significant gender differences were found in mental well-being (P = 0.421). Motivation significantly predicted mental well-being (β = 0.233, R ² = 0.184, P < 0.001).Conclusion  Motivation to learn AI applications was positively associated with students' mental well-being and explained a modest proportion of its variance.
SN  - 2277-9531
SN  - 2319-6440
ER  -