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Between Tool and Trouble: Student Attitudes Toward AI in Programming Education

Authors
Sergio Rojas-Galeano,
Julian Tejada,
Fernando Marmolejo-Ramos
Date
Publisher
arXiv
This study examines how AI code assistants shape novice programmers experiences during a two-part exam in an introductory programming course. In the first part, students completed a programming task with access to AI support; in the second, they extended their solutions without AI. We collected Likert-scale and open-ended responses from 20 students to evaluate their perceptions and challenges. Findings suggest that AI tools were perceived as helpful for understanding code and increasing confidence, particularly during initial development. However, students reported difficulties transferring knowledge to unaided tasks, revealing possible overreliance and gaps in conceptual understanding. These insights highlight the need for pedagogical strategies that integrate AI meaningfully while reinforcing foundational programming skills.
Study at a glance
  • Question: How do AI tools affect beginner students' experiences and challenges during a programming exam?
  • Setting and data: An introductory programming course; 20 novice programming students.
  • Method: Survey with Likert-scale and open-ended questions following a two-part exam task with and without AI.
Why it matters

AI code assistants present a tension between serving as a learning tool and causing trouble for novice programmers. Evaluating student perceptions and challenges addresses how AI support shapes experiences across tasks completed with AI and extended without it.

Key findings
  • In an introductory programming course with 20 students, AI tools were perceived as helpful for understanding code and boosting confidence during initial development.
  • Students reported difficulties transferring their knowledge to programming tasks completed without AI assistance.
  • Working without AI revealed possible student overreliance on the tools and gaps in their conceptual understanding.

Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.

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