PROJECT BASED ASSESSMENT IN THE ERA OF GENERATIVE AI- CHALLENGES AND OPPORTUNITIES

Reference Text
Proceedings of the 20th International CDIO Conference, ESPRIT, Tunis, Tunisia, June 10-13 2024
Year
2024
Abstract

In recent years, generative Artificial Intelligence (GAI) has had a huge impact on education. Students can now prepare complex content with a very low effort, which puts in question the relevance of classic assessment methods. In this paper, we focus on the evaluation of a project-based learning course in a world where the student will benefit from GAI with its various forms of outputs. We explored the challenges of GAI on the project-based learning assessment, and we collected feedback from the course's teachers. Then, we proposed additional criteria in the evaluation grid relating to the use of GAI. We are convinced that we should take advantage of GAI while maintaining the academic integrity and ensuring development of student’s critical skills. We concluded that the assessment grid should include 6 types of criteria which are: integrate AI-specific skills criteria, ethical consideration criteria, providing clear rubrics criteria, collaboration criteria, align with specification criteria, and quality of documentation criteria.