Artificial Intelligence-Powered Learning Technologies in Pharmacy Education: Knowledge, Attitudes, and Practices of Undergraduate Pharmacy Students
Objectives Artificial intelligence (AI) is increasingly integrated into health professions education, including pharmacy training. Understanding students’ knowledge, attitudes, and practices (KAP) toward AI-powered learning tools is essential for effective curricular integration. Materials and Methods A descriptive cross-sectional study was conducted among undergraduate pharmacy students at a Nigerian university during the 2024/2025 academic session from August 2025 to November 2025. Data were collected using a validated self-administered questionnaire adapted from previous studies. KAP scores were categorised using modified Bloom’s cut-offs. Descriptive statistics, Spearman’s correlation, and multivariable logistic regression were applied. Results A total of 456 students participated (response rate: 81.3%), with a median age of 23 years (IQR: 20–25). Overall, 69.7% demonstrated good knowledge, 72.4% showed positive attitudes, and 50.4% exhibited good practices regarding AI-powered learning tools. Knowledge showed a weak but statistically significant positive correlation with attitude (Spearman’s rho = 0.248, p < 0.001). Year of study was the only significant predictor of poor knowledge, with second-year students more likely and fifth-year students less likely to have poor knowledge. Conclusion Pharmacy students demonstrated generally modest engagement with AI-powered learning tools despite limited formal training. Integrating structured AI education into pharmacy curricula may enhance students’ knowledge and promote responsible use.
Authors
- Roland Nnaemeka Okoro (ORCID: https://orcid.org/0000-0002-6391-5000)
- Steward Mudenda
- Abdullahi Musa Garba
Institutions
- University of Zambia (ZM)
- University of Maiduguri (NG)
Publication Details
- Journal
- Science and Technology Nexus
- Published
- 2026-05-12
- DOI
- https://doi.org/10.25259/stn_5_2026
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00