Abstract
Background: Investigating the effectiveness of AI in developing personalized learning pathways for students involves exploring how AI can tailor educational content to meet individual needs. By analyzing students' learning patterns, strengths, and weaknesses, AI can recommend customized resources and learning strategies. This approach can improve engagement and learning outcomes by providing targeted support. Additionally, the investigation should assess how well AI adapts to diverse learning styles and paces. Understanding these factors is crucial to determining AI's role in enhancing personalized education. This study conducted at King Edward Medical College investigates the effectiveness of AI in developing personalized learning pathways for students. Objectives: To analyze the effectiveness of AI in developing personalized learning pathways benefitting medical students. Methods: A cross-sectional study was carried out using an online questionnaire which was filled by 91 students. It consisted of demographical data, rate of utilization of AI, and effects of usage of outcomes of AI on learning methods. The results were analyzed using SPSS version 24. Chi-Square test was applied considering a p -value of <0.05 as significant. Results: 91 students filled out the online questionnaire. 51 percent of the students found AI effective for assisting personalized learning of the student. Out of the 91 students, 74 percent of the students faced difficulty with traditional learning methods which showed the need to integrate AI into personalized learning. 47 percent of students use AI for choosing orientation and growing professionally.52 percent of students use AI for decision making and 74 percent of students feel that AI will improve their patient-centered care. Conclusion: Our study explores the effectiveness of artificial intelligence in developing personalized learning pathways and how medical students can benefit from it and improve their academics as well as their diagnostic abilities.