INTEGRATING RULE BASED CHATBOT IN LEARNING MANAGEMENT SYSTEM OF UNDERGRADUATE STUDENTS

Introduction: E-learning platforms, such as learning management systems (LMS), can enhance teaching learning outcome in medical education. Rule-based chatbots, designed to simulate human-user interaction, can be integrated in LMS. Objectives: The study aimed to study the efcacy of a rule-based chatbot after a teaching-learning session as an effective adjunct teaching tool in preclinical competency based medical education (CBME) curriculum. Material and Methods: The study employed a cross-sectional design to examine the correlation between performance on formative assessments before and after the implementation of a rule-based chatbot in the LMS. The study comprised 110 rst-year medical students. Data collection involved acquiring written responses for formative evaluation about the key subject matter addressed during Physiology lectures. Statistical Data Analysis: A statistical t-test was conducted to analyse students' formative assessment scores before and after deploying a rule-based chatbot in a LMS. Results: The mean values of formative assessment scores obtained after the implementation of rule-based chatbots were signicantly higher than those obtained before the implementation. Conclusion: Overall, the integration of chatbots in learning management systems has shown promising results in improving student engagement and academic performance.