Using Peer Assessment Leveraging Large Language Models in Software Engineering Education

Abstract

This paper explores the integration of generative AI and large language models into the realm of software engineering education and training, with a specific focus on the transformation of traditional peer assessment methodologies. The motivation stems from the growing demand for innovative educational techniques that can effectively engage and empower learners in mastering Software Engineering principles. The proposed approach involves presenting students with modeling exercises solved by ChatGPT, prompting them to critically evaluate and provide constructive feedback on the generated solutions. By engaging students in a dialogue with the AI model, we aim to foster a dynamic learning environment where learners can articulate their considerations and insights, thereby enhancing their comprehension of software engineering principles, critical thinking and self evaluation skills. Preliminary results from pilot implementations indicate promising outcomes, suggesting that this approach not only enhances the quality of peer feedback but also contributes to a more interactive and engaging educational experience.