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Evaluating Contextually Personalized Programming Exercises Created with Generative AI

Publiceringsår

2024

Upphovspersoner

Logacheva, Evanfiya; Hellas, Arto; Prather, James; Sarsa, Sami; Leinonen, Juho

Abstrakt

Programming skills are typically developed through completing various hands-on exercises. Such programming problems can be contextualized to students’ interests and cultural backgrounds. Prior research in educational psychology has demonstrated that context personalization of exercises stimulates learners’ situational interests and positively affects their engagement. However, creating a varied and comprehensive set of programming exercises for students to practice on is a time-consuming and laborious task for computer science educators. Previous studies have shown that large language models can generate conceptually and contextually relevant programming exercises. Thus, they offer a possibility to automatically produce personalized programming problems to fit students’ interests and needs. This article reports on a user study conducted in an elective introductory programming course that included contextually personalized programming exercises created with GPT-4. The quality of the exercises was evaluated by both the students and the authors. Additionally, this work investigated student attitudes towards the created exercises and their engagement with the system. The results demonstrate that the quality of exercises generated with GPT-4 was generally high. What is more, the course participants found them engaging and useful. This suggests that AI-generated programming problems can be a worthwhile addition to introductory programming courses, as they provide students with a practically unlimited pool of practice material tailored to their personal interests and educational needs.
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Organisationer och upphovspersoner

Aalto-universitetet

Hellas Arto

Logacheva Evanfiya Orcid -palvelun logo

Leinonen Juho Orcid -palvelun logo

Publikationstyp

Publikationsform

Artikel

Moderpublikationens typ

Konferens

Artikelstyp

Annan artikel

Målgrupp

Vetenskaplig

Kollegialt utvärderad

Kollegialt utvärderad

UKM:s publikationstyp

A4 Artikel i en konferenspublikation

Publikationskanalens uppgifter

Moderpublikationens redaktörer

Denny, Paul; Porter, Leo; Hamilton, Margaret; Morrison, Briana

Förläggare

ACM

Volym

1

Sidor

95-113

Publikationsforum

5098

Publikationsforumsnivå

1

Öppen tillgång

Öppen tillgänglighet i förläggarens tjänst

Ja

Öppen tillgång till publikationskanalen

Helt öppen publikationskanal

Parallellsparad

Ja

Övriga uppgifter

Vetenskapsområden

Data- och informationsvetenskap

Nyckelord

[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Förlagets internationalitet

Internationell

Språk

engelska

Internationell sampublikation

Ja

Sampublikation med ett företag

Nej

DOI

10.1145/3632620.3671103

Publikationen ingår i undervisnings- och kulturministeriets datainsamling

Ja