Unpacking Vibe Coding: Help-Seeking Processes in Student-AI Interactions While Programming
arXiv:2604.27134v1 Announce Type: new Abstract: Generative AI is reshaping higher education programming through vibe coding, where students collaborate with AI via natural language rather than writing code line-by-line. We conceptualize this practice as help-seeking, analyzing 19,418 interaction turns from 110 undergraduate students. Using inductive coding and Heterogeneous Transition Network Analysis, we examined interaction sequences to compare top- and low-performing students. Results reveal
Opening excerpt (first ~120 words) tap to expand
Computer Science > Artificial Intelligence arXiv:2604.27134 (cs) [Submitted on 29 Apr 2026] Title:Unpacking Vibe Coding: Help-Seeking Processes in Student-AI Interactions While Programming Authors:Daiana Rinja, Eduardo Araujo Oliveira, Sonsoles López-Pernas, Mohammed Saqr, Marcus Specht, Kamila Misiejuk View a PDF of the paper titled Unpacking Vibe Coding: Help-Seeking Processes in Student-AI Interactions While Programming, by Daiana Rinja and 5 other authors View PDF HTML (experimental) Abstract:Generative AI is reshaping higher education programming through vibe coding, where students collaborate with AI via natural language rather than writing code line-by-line. We conceptualize this practice as help-seeking, analyzing 19,418 interaction turns from 110 undergraduate students.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv.org.
Discussion
0 commentsMore from arXiv.org
