AI Code Generation Tools - Experience and Perspectives of Computer Science Students

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dc.contributor.advisorPeruma, Anthony
dc.contributor.authorAnderson, Tyler
dc.contributor.departmentComputer Science
dc.date.accessioned2024-12-02T19:36:05Z
dc.date.issued2024
dc.description.degreeM.S.
dc.embargo.liftdate2025-11-26
dc.identifier.urihttps://hdl.handle.net/10125/110031
dc.subjectComputer science
dc.subjectAI
dc.subjectComputer science
dc.subjecteducation
dc.subjectLLM
dc.subjectstudents
dc.subjectsurvey
dc.titleAI Code Generation Tools - Experience and Perspectives of Computer Science Students
dc.typeThesis
dcterms.abstractRecent advancements in large language models (LLMs) and generative artificial intelligence (GenAI) have made significant impacts globally. These AI tools have simplified traditionally strenuous and time-consuming tasks, fostering both optimism and concern regarding their use by students in educational settings. This thesis investigates the usage and perceptions of AI code generation tools, particularly ChatGPT, among computer science (CS) students. We conducted a study involving seventy students from varied academic levels who participated in a 45-minute programming activity with the optional use of ChatGPT assistance. This was followed by an extensive online questionnaire designed to explore the AI code generation tools students use, the frequency of their use, the specific tasks for which they employ these tools, and their underlying motivations. Through comprehensive qualitative and quantitative analysis, we discovered that an overwhelming majority of students are not only familiar with ChatGPT, but also use it for over half their academic work. Students expressed a strong interest in leveraging AI tools to enhance their learning experience, citing benefits such as increased efficiency and deeper understanding of complex concepts. However, they also shared concerns similar to those of their instructors, particularly regarding over-reliance on these tools, difficulty comprehending generated code, and lacking the skills necessary for their future careers. Additionally, we observed a wide range of behaviors in how students use ChatGPT, with most not employing advanced techniques like model priming and prompt engineering strategies. Our findings highlight the need for greater awareness and training in the design and behavior of these tools to maximize the benefits of AI assistance. We discuss the implications of our findings for students, educators, and the industry, suggesting strategies to ensure that the integration of AI code generation tools in educational contexts results in a net positive impact for all stakeholders.
dcterms.extent66 pages
dcterms.languageen
dcterms.publisherUniversity of Hawai'i at Manoa
dcterms.rightsAll UHM dissertations and theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission from the copyright owner.
dcterms.typeText
local.identifier.alturihttp://dissertations.umi.com/hawii:12303

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