Search Results for author: Charles Koutcheme

Found 3 papers, 2 papers with code

Open Source Language Models Can Provide Feedback: Evaluating LLMs' Ability to Help Students Using GPT-4-As-A-Judge

1 code implementation8 May 2024 Charles Koutcheme, Nicola Dainese, Sami Sarsa, Arto Hellas, Juho Leinonen, Paul Denny

Inspired by recent work that has utilised very powerful LLMs, such as GPT-4, to evaluate the outputs produced by less powerful models, we conduct an automated analysis of the quality of the feedback produced by several open source models using a dataset from an introductory programming course.

Benchmarking Educational Program Repair

1 code implementation8 May 2024 Charles Koutcheme, Nicola Dainese, Sami Sarsa, Juho Leinonen, Arto Hellas, Paul Denny

The emergence of large language models (LLMs) has sparked enormous interest due to their potential application across a range of educational tasks.

Benchmarking Program Repair

Exploring the Responses of Large Language Models to Beginner Programmers' Help Requests

no code implementations9 Jun 2023 Arto Hellas, Juho Leinonen, Sami Sarsa, Charles Koutcheme, Lilja Kujanpää, Juha Sorva

At the same time, the results highlight the unreliability of LLMs: LLMs make some of the same mistakes that students do, perhaps especially when formatting output as required by automated assessment systems.

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