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Investigating the Impact of Artificial Intelligence Tools on Students’ Academic Achievement
KTH, School of Electrical Engineering and Computer Science (EECS).
KTH, School of Electrical Engineering and Computer Science (EECS).
2024 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Undersökning av Artificiell Intelligens-Verktygs Påverkan på Students Akademiska Prestationer (Swedish)
Abstract [en]

In a short time, the world has been introduced to AI tools that once were thought fringe tools have shown remarkable capacity for solving generic problems and generating solutions. OpenAI has released Codex which has already been shown to outperform most first-year students on typical programming assignments in introductory courses in programming. This thesis explores the student attitudes toward leveraging AI tools in their academic studies and the usefulness and frequency they use them. The thesis also explores the academic achievements of first-year students at KTH for the introductory programming course for the course offerings of 2021 and 2023 using static analysis tools. The study shows that students from 2023 are more likely to find AI tools more useful on average than in 2021, and they are using AI tools more frequently. It is shown that the students from 2023 achieved a higher code quality in the introductory course in programming compared to the students from 2021 according to the static analysis with a statistical significance (p-value < 0.05).

Abstract [sv]

På kort tid har världen introducerats till AI verktyg, som först använts till specifika lösningar i periferin till att anses ha en anmärkningsvärd kapacitet för att lösa generella problem och generera lösningar. OpenAI har lanserat Codex vilket redan har visats prestera bättre än första års studenter på typiska uppgifter i introduktionskurser till programmering. Denna uppsats utforskar studenters attityder till att använda AI-verktyg i sina studier, deras uppskattning av användbarhet och hur ofta de använder verktygen. Uppsatsen analyserar också första-års studenters prestation i introduktionskursen i programming på KTH för kursomgångarna som gavs 2021 och 2023, genom statisk programanalys. Studien visar att studenter från 2023 är mer benägna att anse att AI-verktyg är mer användbara i genomsnitt än studenter från 2021, och använder dessa dessutom mer frekvent. Vidare visar studien att studenter från år 2023 har ett högre mått av kodkvalitet i introduktionskursen i programmering i jämförelse med studenter från 2021 genom statisk programanalys med en statistisk signifikans (p-värde < 0.05).

Place, publisher, year, edition, pages
2024. , p. 38
Series
TRITA-EECS-EX ; 2024:386
Keywords [en]
Artificial Intelligence, Academic Achievement, Code Quality, ChatGPT, GitHub Copilot, Educational Technology, SonarQube, Programming Education
Keywords [sv]
Artificiell Intelligens, Akademiska Prestationer, Kodkvalitet, ChatGPT, GitHub Copilot, Utbildningsteknologi, SonarQube, Programmeringsutbildning
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-351181OAI: oai:DiVA.org:kth-351181DiVA, id: diva2:1886541
Supervisors
Examiners
Available from: 2024-08-30 Created: 2024-08-02 Last updated: 2024-08-30Bibliographically approved

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