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Case study: Using LLMs to assist with solving programming homework assignments

dc.contributor.authorDeriyeva, Alina
dc.contributor.authorDannath, Jesper
dc.contributor.authorPaaßen, Benjamin
dc.contributor.editorKiesler, Natalie
dc.contributor.editorSchulz, Sandra
dc.date.accessioned2024-10-21T10:40:34Z
dc.date.available2024-10-21T10:40:34Z
dc.date.issued2024
dc.description.abstractNowadays, students have the option of using LLMs for assistance in solving homework assignments. Moreover, most LLMs, like ChatGPT, are also trained on large sets of source code and thus can be used to assist in programming exercises. In this paper, we present a case study based on data collected over the course of 1.5 semesters, where students of three programming-related courses were explicitly permitted to use such models while solving homework assignments. In a qualitative evaluation, we observe that there might be a difference between targeted requests for an answer to specific questions and requests for a complete solution from an LLM. Particularly, targeted requests might be pedagogical feasible and enhance the learning experience. Additionally, we discuss the potential of LLM applications in programming education, with a focus on the intermediate level and beyond.en
dc.identifier.doi10.18420/delfi2024-ws-23
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/45038
dc.language.isoen
dc.pubPlaceBonn
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofProceedings of DELFI Workshops 2024
dc.relation.ispartofseriesDELFI
dc.subjectProgramming Education
dc.subjectLLM
dc.titleCase study: Using LLMs to assist with solving programming homework assignmentsen
dc.typeText/Conference Paper
mci.conference.date09.-11. September 2024
mci.conference.locationFulda
mci.conference.sessiontitleDELFI: Workshop
mci.document.qualitydigidoc
mci.reference.pages174-180

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