{"slug": "computer-science-achievement-and-writing-skills-predict-vibe-coding-proficiency", "title": "Computer Science Achievement and Writing Skills Predict Vibe Coding Proficiency", "summary": "A preregistered study of 100 tertiary-level students found that computer science achievement and writing skills are significant predictors of proficiency in LLM-driven 'vibe coding', with CS achievement remaining significant after controlling for domain-general cognitive skills. The study, submitted to arXiv on 14 Mar 2026, used tasks curated by eight experts and a purpose-built environment mirroring commercial tools, informing tool and curriculum design.", "body_md": "# Computer Science > Human-Computer Interaction\n\n  [Submitted on 14 Mar 2026]\n\n# Title:Computer Science Achievement and Writing Skills Predict Vibe Coding Proficiency\n\n[View PDF](/pdf/2603.14133)\n\n[HTML (experimental)](https://arxiv.org/html/2603.14133v1)\n\nAbstract:Many software development platforms now support LLM-driven programming, or \"vibe coding\", a technique that allows one to specify programs in natural language and iterate from observed behavior, all without directly editing source code. While its adoption is accelerating, little is known about which skills best predict success in this workflow. We report a preregistered cross-sectional study with tertiary-level students (N = 100) who completed measures of computer-science achievement, domain-general cognitive skills, written-communication proficiency, and a vibe-coding assessment. Tasks were curated via an eight-expert consensus process and executed in a purpose-built, vibe-coding environment that mirrors commercial tools while enabling controlled evaluation. We find that both writing skill and CS achievement are significant predictors of vibe-coding performance, and that CS achievement remains a significant predictor after controlling for domain-general cognitive skills. The results may inform tool and curriculum design, including when to emphasize prompt-writing versus CS fundamentals to support future software creators.\n    \n\n## Submission history\n\nFrom: Sverrir Thorgeirsson [\n[view email](/show-email/d53808d9/2603.14133)]\n\n**[v1]** Sat, 14 Mar 2026 21:42:22 UTC (2,504 KB)\n\n### References & Citations\n\nLoading...\n\n# Bibliographic and Citation Tools\n\nBibliographic Explorer \n\n*(*[What is the Explorer?](https://info.arxiv.org/labs/showcase.html#arxiv-bibliographic-explorer))\nConnected Papers \n\n*(*[What is Connected Papers?](https://www.connectedpapers.com/about))\nLitmaps \n\n*(*[What is Litmaps?](https://www.litmaps.co/))\nscite Smart Citations \n\n*(*[What are Smart Citations?](https://www.scite.ai/))\n# Code, Data and Media Associated with this Article\n\nalphaXiv \n\n*(*[What is alphaXiv?](https://alphaxiv.org/))\nCatalyzeX Code Finder for Papers \n\n*(*[What is CatalyzeX?](https://www.catalyzex.com))\nDagsHub \n\n*(*[What is DagsHub?](https://dagshub.com/))\nGotit.pub \n\n*(*[What is GotitPub?](http://gotit.pub/faq))\nHugging Face \n\n*(*[What is Huggingface?](https://huggingface.co/huggingface))\nScienceCast \n\n*(*[What is ScienceCast?](https://sciencecast.org/welcome))\n# Demos\n\n# Recommenders and Search Tools\n\nInfluence Flower \n\n*(*[What are Influence Flowers?](https://influencemap.cmlab.dev/))\nCORE Recommender \n\n*(*[What is CORE?](https://core.ac.uk/services/recommender))\n# arXivLabs: experimental projects with community collaborators\n\narXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.\n\nBoth individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.\n\nHave an idea for a project that will add value for arXiv's community? [**Learn more about arXivLabs**](https://info.arxiv.org/labs/index.html).", "url": "https://wpnews.pro/news/computer-science-achievement-and-writing-skills-predict-vibe-coding-proficiency", "canonical_source": "https://arxiv.org/abs/2603.14133", "published_at": "2026-09-07 08:29:30+00:00", "updated_at": "2026-09-07 08:56:56.704106+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-research", "ai-tools"], "entities": ["arXiv", "Sverrir Thorgeirsson"], "alternates": {"html": "https://wpnews.pro/news/computer-science-achievement-and-writing-skills-predict-vibe-coding-proficiency", "markdown": "https://wpnews.pro/news/computer-science-achievement-and-writing-skills-predict-vibe-coding-proficiency.md", "text": "https://wpnews.pro/news/computer-science-achievement-and-writing-skills-predict-vibe-coding-proficiency.txt", "jsonld": "https://wpnews.pro/news/computer-science-achievement-and-writing-skills-predict-vibe-coding-proficiency.jsonld"}}