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Automated Next-Step Hint Generation For Introductory Programming Using Large Language Models

dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorKeuning, Hieke
dc.contributor.authorRoest, Lianne
dc.date.accessioned2023-09-06T10:08:09Z
dc.date.available2023-09-06T10:08:09Z
dc.date.issued2023
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/45041
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectWith recent advances in their performances, large language models (LLMs) are now more popular than ever. LLMs, such as ChatGPT, possess various skills, such as answering questions, writing essays or solving programming exercises. Recently, these models have become easily accessible, and researchers have expressed concerns regarding their impact on programming education. This work explores how LLMs can contribute to programming education by supporting students with automated next-step hints gen
dc.titleAutomated Next-Step Hint Generation For Introductory Programming Using Large Language Models
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.courseuuComputing Science
dc.thesis.id23568


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