Uptake and Application of Artificial Intelligence by Lecturers and Students of Kenya Medical Training College

Background: The rapid growth of Artificial Intelligence (AI) is revolutionizing healthcare delivery and health professional education by supporting personalized, technology-driven learning approaches. However, little is known on the uptake and application of AI in middle-level health professional training institutions in Kenya. Kenya Medical Training College (KMTC) is the largest public middle-level health professional training institution which plays a critical role in producing human resource for health. Understanding the extent to which AI is utilized within KMTC is therefore essential for informing institutional policies and strategies for embedding AI technology into health professional education.
Methods: A cross-sectional study was conducted between November 2024 and November 2025 across eight randomly selected KMTC campuses. Multistage sampling technique was employed. Data was collected using structured electronic questionnaires. A total of 581 respondents participated, representing a 97% response rate. Data were analyzed using SPSS to generate descriptive statistics and associations.
Results: Overall, 76.3% of students reported using AI during their studies, while 56.3% of lecturers had used AI to support teaching and learning activities. ChatGPT was the most commonly used AI tool (66.3%). Among students, AI use was significantly associated with course of study (χ² = 66.79, p < 0.001), age group (χ² = 12.83, p < 0.046), year of study (χ² = 10.96, p < 0.004), and level of training (χ² = 6.58, p < 0.037). Among lecturers, AI use was significantly associated with level of education (χ² = 13.23, p < 0.039). Major challenges included limited internet access (students 52.5%), limited technical capacity (lecturers 31.3%), and inadequate knowledge of AI tools. Notably, 66.1% of students believed AI will become increasingly important in future medical practice.
Discussion: AI uptake within KMTC setting is growing however variations exists reflecting differences in digital literacy, internet access, and exposure to digital tools across programs and campuses. Limited infrastructure and low technical capacity appears to impede integration of AI into teaching and learning. Strengthening digital infrastructure, building faculty and student capacity in responsible AI use, and developing institutional policies and guidelines could facilitate more effective adoption.

Artificial intelligence, uptake, application

1. Dwivedi YK, Kshetri N, Hughes L, Slade EL, Jeyaraj A, Kar AK, et al. “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice, and policy. Int J Inf Manage. 2023;71:102642. doi:10.1016/j.ijinfomgt.2023.102642. [Google Scholar] [Crossref]

2. Modiba F, Berg A, Mago S. Opportunities and challenges of generative artificial intelligence supporting research in African classrooms. S Afr J High Educ. 2025;38(3). doi:10.20853/39-3-6272. [Google Scholar] [Crossref]

3. Han ER, Yeo S, Kim MJ, Lee YH, Park KH, Roh H. Medical education trends for future physicians in the era of advanced technology and artificial intelligence: An integrative review. BMC Med Educ. 2019;19(1):1–15. doi:10.1186/s12909-019-1537-0. [Google Scholar] [Crossref]

4. Oke A, Fernandes F. Innovations in teaching and learning: Exploring the perceptions of the education sector on the 4th industrial revolution (4IR). J Open Innov Technol Mark Complex. 2020;6(3):57. doi:10.3390/joitmc6030057. [Google Scholar] [Crossref]

5. Narayanan S, Ramakrishnan R, Durairaj E, Das A. Artificial intelligence revolutionizing the field of medical education. Cureus. 2023;15(11):e49604. doi:10.7759/cureus.49604. [Google Scholar] [Crossref]

6. Morris Gordon M, Daniel M, Ajiboye A, Uraiby H, Xu NY, Bartlett R, et al. A scoping review of artificial intelligence in medical education: BEME Guide No. 84. Med Teach. 2024;46(4):446–470. doi:10.1080/0142159X.2024.2314198. [Google Scholar] [Crossref]

7. Matere A. Effectiveness of artificial intelligence tools in teaching and learning in higher education institutions in Kenya. J Kenya Natl Comm UNESCO. 2024;5(1). doi:10.62049/jkncu.v5i1.177. [Google Scholar] [Crossref]

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