Student perceptions of AI coding assistants in learning
Recorded: Nov. 30, 2025, 1:07 a.m.
| Original | Summarized |
[2507.22900] New Kid in the Classroom: Exploring Student Perceptions of AI Coding Assistants
Skip to main content In just 5 minutes help us improve arXiv: We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. > cs > arXiv:2507.22900 Help | Advanced Search All fields Search open search GO open navigation menu quick links Login Computer Science > Human-Computer Interaction arXiv:2507.22900 (cs) [Submitted on 26 Jun 2025 (v1), last revised 16 Sep 2025 (this version, v4)] Abstract:The arrival of AI coding assistants in educational settings presents a paradigm shift, introducing a "new kid in the classroom" for both students and instructors. Thus, understanding the perceptions of these key actors about this new dynamic is critical. This exploratory study contributes to this area by investigating how these tools are shaping the experiences of novice programmers in an introductory programming course. Through a two-part exam, we investigated student perceptions by first providing access to AI support for a programming task and then requiring an extension of the solution without it. We collected Likert-scale and open-ended responses from 20 students to understand their perceptions on the challenges they faced. Our findings reveal that students perceived AI tools as helpful for grasping code concepts and boosting their confidence during the initial development phase. However, a noticeable difficulty emerged when students were asked to work unaided, pointing to potential overreliance and gaps in foundational knowledge transfer. These insights highlight a critical need for new pedagogical approaches that integrate AI effectively while effectively enhancing core programming skills, rather than impersonating them. Subjects: Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI) Cite as: Focus to learn more arXiv-issued DOI via DataCite Submission history From: Sergio Rojas-Galeano [view email] [v1]
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This research paper, authored by Sergio Rojas-Galeano, investigates student perceptions of artificial intelligence coding assistants within an introductory programming course. The study’s central premise recognizes the introduction of these AI tools as a “new kid in the classroom,” necessitating a detailed examination of how both students and instructors are adapting to this evolving dynamic. The research methodology involved a two-part examination of student performance, initially supporting students’ coding efforts with AI assistance and subsequently requiring them to independently complete the same task. Through this process, data was collected via Likert-scale responses and open-ended feedback, totaling input from twenty students. The core finding highlighted a discernible shift in student attitudes as they progressed through the study. Initially, students perceived the AI tools as supportive resources, primarily assisting in grasping complex code concepts and bolstering their initial confidence levels during the development phase. However, a significant challenge emerged when students were asked to complete the task without AI support. This revealed a pattern of over-reliance on the AI, coupled with noticeable gaps in students’ foundational programming knowledge. The authors argue this suggests a critical need for pedagogical adjustments that effectively integrate AI coding assistants while simultaneously reinforcing core programming skills, rather than simply mimicking or substituting them. The study’s findings underscore the potential pitfalls of relying solely on AI tools to facilitate learning, emphasizing the importance of maintaining a solid grounding in fundamental programming principles. The research contributes to a broader understanding of the changing landscape of education in the age of AI, advocating for a balanced approach that leverages AI’s capabilities to augment, rather than replace, traditional pedagogical methods. |