Knowledge, Attitude, and Perception of Medical Students Toward AI-Based Learning: A Cross-Sectional Study.

Abstract

Background: Artificial intelligence (AI) is rapidly transforming healthcare delivery and medical education. Despite its growing global presence, little is known about the knowledge, attitudes, and perceptions (KAP) of medical students in Pakistan regarding AI-based learning. Understanding these factors is essential for guiding curriculum development and preparing future physicians for an AI-driven health system.

Objective: To assess the KAP of medical students in Khyber Pakhtunkhwa (KP), Pakistan, toward AI-based learning.

Methods: A cross-sectional survey was conducted among 392 medical students from multiple medical colleges in KP. A structured, self-administered questionnaire was used to assess KAP toward AI-based learning. Data were analyzed using SPSS version 26, employing descriptive statistics and chi-square tests to examine group differences. Ordinal logistic regression was performed to identify independent predictors, with statistical significance set at p < 0.05. Ethical approval was obtained from the Institutional Review Board of Gomal Medical College, and informed consent was obtained from all participants.

Results: Of the 392 participants, most demonstrated moderate knowledge (62.8%) regarding AI-based learning, whereas only 30.4% achieved high knowledge scores. Significant variation was observed across academic years, with senior students demonstrating greater knowledge than preclinical students (p < 0.05). In contrast, attitudes and perceptions were largely positive across all years, with nearly three-quarters (74.8%) of students expressing favorable views toward AI. Only 0.8% reported negative attitudes. These findings suggest that enthusiasm for AI is high, but comprehensive understanding remains limited.

Conclusion: Medical students in KP exhibit strong enthusiasm and positive perceptions toward AI-based learning, yet their knowledge remains modest and uneven across training levels. This mismatch highlights the urgent need for structured AI education in undergraduate curricula. Incorporating formal training, workshops, and faculty development programs can bridge this gap and better prepare future physicians to responsibly integrate AI into clinical practice.