Abstract

Background: ChatGPT developed by OpenAI is a state-of-the art innovation and is leading the field of technology with its massive ability to generate any of information in human like conversational manner. The utility of this Artificial Intelligence (AI) based model is being tested in various domains and usability in education is certainly a topic of sensation. ChatGPT has been successful in clearing competitive medical exams and could possibly emerge as an ideal tool for advancing teaching learning methodologies in medical education once the accuracy in its content can be validated and affirmed. Objective: In this study, we aim to evaluate the performance of ChatGPT Human Anatomy of first MBBS professional Methods: This assessment was carried out using the university examination question paper of Human Anatomy paper 1. The question paper comprised of 2 essay, 10 short notes and 20 Multiple Choice Questions (MCQ). All the questions were entered on ChatGPT one after the other and the responses generated were saved and sent to our evaluation team in the department of anatomy. Result: ChatGPT has provided brief explanations for all the questions. For the Multiple Choice Questions (MCQ), the option along with reasons were given. Out of 20, six answers were incorrect. Although ChatGPT has provided relevant answers for all the questions, there was no diagrammatic representation provided. The feedback from the faculties suggested that there were few incorrect explanations and content should be more elaborate with relations of the structures being explained in detail. Overall ChatGPT has passed the test with total of 56%. Conclusion: From the results of our study, we emphasize that ChatGPT has the potential to be used as an effective learning tool with its humanoid conversation that can create a personalised learning experience. However, the accuracy and dependability of such tools is a cause of concern. Also, due to lack of its ability to produce pictorial illustration, learning and understanding of subjects like anatomy may not be very efficient.

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Data Sharing Statement

Funding