Using Generative Artificial Intelligence to Conduct a Problem-Solving Workshop

This study presents a pedagogical innovation implemented across five engineering courses, involving a student-led problem preparation workshop enhanced by peer evaluation and Generative Artificial Intelligence (GAI). Students collaboratively designed and solved original problems based on course content, integrating GAI tools to boost creativity, complexity, and critical thinking. Peer review was conducted anonymously using standardized rubric, fostering reflective learning and active engagement. The workshop was voluntary and carried modest weight in course grading, yet participation exceeded 65% in all subjects. Comparative analysis of academic performance revealed significantly higher exam scores among students who participated, especially those who utilized GAI. Survey results further confirmed students’ positive perception of GAI’s utility and their intent to continue using such tools in future academic work. The combined methodology, problem-based learning, peer assessment, and GAI integration, proved to be a scalable and transferable strategy for enhancing student learning outcomes and engagement.