Perceived Impact of Artificial Intelligence Usage on Academic Performance Among Undergraduate Health Science Students in Mirpurkhas, Sindh-Pakistan: A Multi-Center Study

Abstract

Background: Many medical and nursing students are increasingly utilizing artificial intelligence tools such as Telemedicine, Jeni.AI, Gemini, and ChatGPT to support both academic and clinical activities. These tools offer rapid responses and can save valuable time. However, there is growing concern that students in cities like Mirpurkhas may become overly reliant on AI, which could potentially compromise the development of critical thinking, problem-solving, and research skills. Methods: A descriptive cross-sectional study was conducted among undergraduate health science students at selected public and private centers in Mirpurkhas. Stratified random sampling was used to recruit a total of 197 participants, and data were collected via Google Forms from January to February 2026. An adapted questionnaire was employed, with minor modifications based on expert review to ensure validity. The collected data were analyzed using SPSS version 27.0, and descriptive statistics were generated for demographic subgroups. Findings: Among the 197 participants, the majority were BSN students (76.1%), aged 18–22 years (67.5%), and enrolled in private institutions (63%). Most students had a CGPA between 3.01–3.50. High perception scores were observed for General Use of AI (3.79 ± 0.40), Future of AI in Education (3.75 ± 0.46), and Impact on Student Skills (3.65 ± 0.48). Effectiveness of AI in Education was rated moderately high (3.49 ± 0.45), while Accuracy and Reliability received a moderate score (2.60 ± 0.50). These findings suggest that students generally find AI tools easy to use; however, they also express concerns about potential erosion of their natural skills and critical thinking. Conclusion: The healthcare undergraduate students demonstrated a high level of acceptance and utilization of artificial intelligence (AI) as a supportive academic tool. While AI use was generally associated with enhanced academic performance, concerns regarding accuracy and potential over-reliance remain. Implementation of structured training programs and clear ethical guidelines is recommended to ensure responsible and effective integration of AI in healthcare academia.

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