2026 ASEE Annual Conference & Exposition

Developing effective strategies to support student learning and computational proficiency in introductory programming courses has long posed a challenge. Prior research underscores the importance of program comprehension and the ability to clearly articulate one’s understanding as foundational to developing programming skills. These competencies are crucial not only for success as students progress through a computing curriculum but also for their long-term professional growth.

The rapid emergence and increasing accessibility of generative artificial intelligence (GenAI) tools introduce new complexities for educators and learners alike. While these tools allow students to use large language model (LLM)-based queries to generate functional programming solutions with minimal effort, they also raise concerns about overreliance, which may hinder students’ ability to independently construct and comprehend computational solutions. As GenAI tools become more pervasive in educational settings, it is essential to ensure that students continue to develop and retain proficient computational understanding rather than circumventing it through automated assistance.

This case study examines an instructional intervention implemented in an introductory programming course at a minority-serving institution (MSI) in the Mid-Atlantic United States during the Fall 2024 semester. The intervention integrated the use of the GenAI tool, ChatGPT, within selected take-home assignments and required students to participate in structured code reviews and verbal think-aloud activities. The objective was to assess students’ ability to apply their programming skills and concepts while having direct access to a GenAI tool. This approach also encouraged students to articulate their understanding/comprehension of programming concepts and explain the reasoning behind their code. Additionally, the study aimed to provide initial insight on whether students could continue to develop and showcase their programming skills without becoming overreliant on GenAI tools.

A mixed methods approach was used to evaluate student performance on these selected assignments, while observing their experiences with ChatGPT. Findings indicated that most students demonstrated proficiency in interpreting code and articulating their solutions, both in writing and verbally, even while using ChatGPT. Students also reported that ChatGPT aided their understanding of programming concepts and supported their development of essential skills in code review and evaluation. This study examines how such interventions can support students’ development of program comprehension skills in a GenAI-enabled learning environment, providing insights for educators aiming to adapt instruction while maintaining rigor and depth in foundational computing education.