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How Novice Programmers Use and Experience ChatGPT when Solving Programming Exercises in an Introductory Course

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arxiv 2407.20792 v1 pith:TCFZWQT7 submitted 2024-07-30 cs.AI

classification cs.AI
keywords programmingstudentschatgptintroductorycontextgenairesearchcourse
verification ladder T0 review T1 audit T2 compute T3 formal
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This research paper contributes to the computing education research community's understanding of Generative AI (GenAI) in the context of introductory programming, and specifically, how students utilize related tools, such as ChatGPT. An increased understanding of students' use is mandatory for educators and higher education institutions, as GenAI is here to stay, and its performance is likely to improve rapidly in the near future. Learning about students' use patterns is not only crucial to support their learning, but to develop adequate forms of instruction and assessment. With the rapid advancement of AI, its broad availability, and ubiquitous presence in educational environments, elaborating how AI can enhance learning experiences, especially in courses such as introductory programming is important. To date, most studies have focused on the educator's perspective on GenAI, its performance, characteristics, and limitations. However, the student perspective, and how they actually use GenAI tools in course contexts, has not been subject to a great number of studies. Therefore, this study is guided by the following research questions: (1) What do students report on their use pattern of ChatGPT in the context of introductory programming exercises? and (2) How do students perceive ChatGPT in the context of introductory programming exercises? To address these questions, computing students at a large German university were asked to solve programming tasks with the assistance of ChatGPT as part of their introductory programming course. Students (n=298) provided information regarding the use of ChatGPT, and their evaluation of the tool via an online survey. This research provides a comprehensive evaluation of ChatGPT-3.5's application by novice programmers in a higher education context...

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Cited by 2 Pith papers

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  1. The Effects of GitHub Copilot on Computing Students' Programming Effectiveness, Efficiency, and Processes in Brownfield Programming Tasks

    cs.SE 2025-06 conditional novelty 6.0 of 10

    GitHub Copilot made undergraduate students faster and more test-successful on brownfield programming tasks, and shifted their workflow from manual coding and web search to prompting, reviewing, and integrating AI suggestions.

  2. SPIRAL integration of generative AI in an undergraduate creative media course: effects on self-efficacy and career outcome expectations

    cs.HC 2025-05 conditional novelty 6.0 of 10

    In a Fall 2023 creative media course, a SPIRAL curriculum that delayed generative AI use until after domain skill practice was associated with higher creative media and GenAI use self-efficacy, demystification about A...

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