"Give me the code" -- Log Analysis of First-Year CS Students' Interactions With GPT

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Publicat a:arXiv.org (Dec 1, 2024), p. n/a
Autor principal: Alves, Pedro
Altres autors: Bruno Pereira Cipriano
Publicat:
Cornell University Library, arXiv.org
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Accés en línia:Citation/Abstract
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022 |a 2331-8422 
035 |a 3133828887 
045 0 |b d20241201 
100 1 |a Alves, Pedro 
245 1 |a "Give me the code" -- Log Analysis of First-Year CS Students' Interactions With GPT 
260 |b Cornell University Library, arXiv.org  |c Dec 1, 2024 
513 |a Working Paper 
520 3 |a The impact of Large Language Models (LLMs) like GPT-3, GPT-4, and Bard in computer science (CS) education is expected to be profound. Students now have the power to generate code solutions for a wide array of programming assignments. For first-year students, this may be particularly problematic since the foundational skills are still in development and an over-reliance on generative AI tools can hinder their ability to grasp essential programming concepts. This paper analyzes the prompts used by 69 freshmen undergraduate students to solve a certain programming problem within a project assignment, without giving them prior prompt training. We also present the rules of the exercise that motivated the prompts, designed to foster critical thinking skills during the interaction. Despite using unsophisticated prompting techniques, our findings suggest that the majority of students successfully leveraged GPT, incorporating the suggested solutions into their projects. Additionally, half of the students demonstrated the ability to exercise judgment in selecting from multiple GPT-generated solutions, showcasing the development of their critical thinking skills in evaluating AI-generated code. 
653 |a Programming 
653 |a Impact analysis 
653 |a Students 
653 |a Prompt engineering 
653 |a Large language models 
653 |a Artificial intelligence 
653 |a Critical thinking 
653 |a Skills 
653 |a Generative artificial intelligence 
653 |a Undergraduate study 
700 1 |a Bruno Pereira Cipriano 
773 0 |t arXiv.org  |g (Dec 1, 2024), p. n/a 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3133828887/abstract/embedded/ITVB7CEANHELVZIZ?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u http://arxiv.org/abs/2411.17855