Investigating the Impact of AI-Based Conversational Models as Learning Companions Among Second-Year MBBS Students

The methods of medical education are gradually shifting, with increasing interest in alternative methods that support more interactive and student-centered learning. The aim of this study is to evaluate the effectiveness of a structured digital dialog tool designed to aid second-year undergraduate (UG) medical students in understanding selected topics in pathology. A total of 119 participants were enrolled and divided into two groups: one group engaged with the digital learning module, while the other followed a conventional textbook-based study. The modules were carefully created in consultation with subject experts to ensure alignment with curricular standards. After the study period was over, essays, short-answer questions, and multiple-choice tests were used to assess how well the UG students understood the material. The results showed that students who used textbooks performed better on all types of tests. Still, feedback from the digital group showed that they were very satisfied with the tool, with students saying it made the content easier to understand and more interesting. Although the traditional approach led to better academic performance, the digital method offered clear advantages in terms of learner interest and accessibility. The findings support the idea that combining structured digital support with established teaching methods may enhance both motivation and academic success in medical training.