2026 ASEE Annual Conference & Exposition

The recent rapid growth of Generative AI (GenAI) imposes challenges to academic integrity and student engagement, especially in computer programming courses. This issue is alarming for most universities, particularly those at Historically Black Colleges and Universities (HBCUs). HBCU students often face unique psychosocial pressures that can lead to the abuse of AI to complete assignments which hinders the development of foundational computational thinking.
To address these challenges, this study introduces a teaching methodology designed within an introductory programming course. The methodology consists of a two-pronged strategy: 1) transitioning online assessments to proctored paper-based tests to ensure academic integrity and 2) mandating the use of GenAI as a learning tool to engage students for a deeper understanding of class lectures and being well-prepared for tests. Preliminary results indicate ~75% increase in active student engagement in in-class lecture participation that concludes a significant positive shift in learning programming. We also observe a sudden drop (at least 25% decrease) in test performance after shifting to a human proctored in-person test and after two proctored tests, we anticipate that the student performance is being increased gradually (data collection is still ongoing). Based on our findings, this method offers a practical framework for educators to maintain academic rigor while exploiting the pedagogical benefits of AI which is particularly effective in supporting at-risk student populations.