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Generative Artificial Intelligence in Health Informatics Education: A Qualitative Exploration of Student Engagement,
Anas Ali Alhur1, Nouf Khalid Al-Kahtani1
1Department of Health Information Management and Technology, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Background:
Generative artificial intelligence (GenAI) is increasingly used in higher education and health sciences education. However, limited qualitative evidence has examined how undergraduate Health Informatics (HI) students in Saudi Arabia engage with GenAI and interpret its educational, cognitive, ethical, and institutional implications.
Aim:
This study aimed to explore HI students' perceptions and self-reported experiences of GenAI use within academic learning contexts in Saudi Arabia.
Methods:
A qualitative study informed by an interpretivist approach and reflexive thematic analysis was conducted across six Saudi public universities offering undergraduate HI programmes. Thirty undergraduate HI students with prior academic experience using GenAI were purposively recruited. Semi-structured interviews were conducted over a two-month period in 2026 using face-to-face and online modalities. Interviews were audio-recorded, transcribed verbatim, anonymized, and analyzed iteratively using Braun and Clarke's reflexive thematic analysis approach with support from ATLAS.ti software.
Results:
Three themes were identified: engagement with GenAI; perceived benefits and limitations; and ethical and institutional considerations. Participants reported using GenAI to summarize materials, understand complex concepts, organize academic tasks, and support assignments. They perceived GenAI as useful for efficiency and comprehension but also described concerns about over-reliance, reduced independent learning, passive acceptance of outputs, plagiarism, lack of source transparency, and unclear institutional policies.
Conclusion:
Undergraduate HI students in Saudi Arabia perceived GenAI as a useful academic support tool, while also identifying cognitive, ethical, and institutional challenges. These exploratory findings reflect perceptions and self-reported experiences rather than objectively measured educational outcomes. Structured AI literacy, clear institutional guidance, and responsible curriculum integration are needed in HI education.
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