Perceptions of undergraduate health professions students on the utilisation of artificial intelligence tools for teaching, learning and assessment: a cross-sectional questionnaire study at a health sciences university in southern India

Artificial intelligence has quietly moved from the fringes of education into the daily lives of students. It is no longer just a futuristic concept discussed in lecture halls; it is a tool many young people already use to study, write, and solve problems. For students training to become doctors, nurses, and other health professionals, this technology offers a new way to learn complex medical concepts and practice clinical reasoning without risk. However, the speed at which these tools are being adopted has outpaced the formal rules and lessons schools have established. While universities are still figuring out how to teach with artificial intelligence, students are already using it, often on their own, to navigate their coursework. This creates a critical question: do these future health professionals trust the technology, or do they view it with suspicion? Understanding their feelings is essential, because if students do not accept these tools, the potential benefits of faster feedback and personalized learning cannot be realized.

A team of researchers in southern India set out to answer this question by listening directly to the students themselves. They conducted a large survey involving 612 undergraduate students from a single health sciences university. This university was unique because it housed six different health professions under one roof: homeopathy, nursing, physiotherapy, pharmacy, dentistry, and Ayurveda. By studying students from all these different backgrounds in the same place, the researchers could see if a student's specific field of study mattered more than their personal experience with technology. The survey asked students about their past use of artificial intelligence, how they felt about using it for teaching and grading, and what they saw as the biggest benefits and risks.

The results painted a picture of cautious optimism. The students generally held positive views about artificial intelligence in education, but their enthusiasm was tempered by a significant amount of uncertainty. When asked if they agreed with statements like "AI can make lectures more engaging" or "AI can help me understand difficult concepts," the majority said yes. Agreement with these positive statements ranged from about 61 percent to 71 percent. However, a large portion of the students—roughly one-quarter to one-third of the group for every question—chose a neutral answer. They neither agreed nor disagreed. The researchers suggest this neutrality does not mean the students are indifferent; rather, it likely reflects a lack of experience. About half of the students surveyed had never used an artificial intelligence tool for their studies before. Without direct experience, they were hesitant to form a strong opinion, waiting to see how the technology would actually work in their classrooms.

When the students did speak up about what they liked, their answers were practical and focused on understanding. The most common benefit they identified was that artificial intelligence could improve their conceptual understanding and clarity. They saw it as a powerful tool for explaining difficult ideas and clearing up doubts quickly. They also appreciated the speed and convenience of getting information. However, their concerns were equally grounded in reality. The top worry was that relying too much on these tools would cause them to lose their ability to think critically and independently. They also feared that the information provided by the machines might be inaccurate, outdated, or misleading. Interestingly, very few students expressed concern about losing practical clinical skills or the idea that the technology might replace their future jobs, suggesting they viewed these tools primarily as study aids rather than replacements for their professional roles.

One of the most revealing findings was how much a student's specific profession influenced their attitude, more so than their gender or how many years they had been in school. Students studying homeopathy expressed the most favorable views, while those studying nursing and physiotherapy were the most reserved. This difference suggests that the culture and curriculum of a specific program shape how students see technology. For instance, nursing and physiotherapy programs place a heavy emphasis on hands-on, supervised practice and human interaction, areas where current text-based artificial intelligence offers little help. These students may simply be recognizing that the technology is less relevant to their specific training needs. In contrast, the researchers found that a student's personal history of using artificial intelligence did not significantly change their overall attitude once their field of study was taken into account. This challenges the common assumption that simply using a tool more will automatically make a person more comfortable with it; instead, the context of their education matters more.

Perhaps the most fragile point in the students' trust was the idea of using artificial intelligence for grading. While students were willing to accept AI as a helper for learning, they were much less willing to let it judge their performance. When asked if they trusted an artificial intelligence system to evaluate their work fairly in objective tests, agreement dropped to its lowest point, and the number of neutral responses was at its highest. This hesitation highlights a deep-seated concern about fairness and accountability. Students are ready to use these tools to learn, but they are not yet ready to hand over the power of assessment to a machine without clear human oversight.

The study concludes that while future health professionals are open to the idea of artificial intelligence in their education, they are not yet fully convinced. They see the potential for better learning but remain wary of the risks to their critical thinking and the fairness of automated grading. The researchers argue that universities should not wait for students to figure this out on their own. Instead, schools should introduce a shared curriculum that teaches all health profession students how to use these tools wisely, how to verify the information they provide, and where their limits lie. By addressing the uncertainty and building trust through education, institutions can help students move from cautious neutrality to confident, responsible use of the technology that will soon define their careers.