A Hybrid Assessment Approach to AI-Enhanced Challenge-Based Learning in Engineering Education

This paper introduces a hybrid assessment approach integrating Generative AI (GenAI), specifically ChatGPT, into challenge-based engineering education. Students iteratively defined problem statements, brainstormed solutions, and presented their work, receiving feedback through rubric-based GenAI assessments of ChatGPT interactions and direct faculty evaluation. While ChatGPT positively influenced student performance and intellectual engagement, it amplified existing differences in motivation, prior knowledge, skills, and team dynamics, underscoring the importance of comprehensive, human-centered pedagogical approaches. Compared to previous iterations, this approach facilitated robust hypothesis validation and meaningful student reflection on AI usage. Contrary to concerns about reduced effort, most teams leveraged ChatGPT for deeper exploration and critical thinking, resulting in more confident presentations and higher-quality content. These findings reinforce evidence that explicit GenAI adoption, with guided faculty oversight, supports design-thinking strategies, enhances student engagement, and maintains academic integrity. Continued methodological refinement and further empirical research remain essential to maximize GenAI's educational benefits in challenge-based engineering education.