Search Results for author: Natalie Kiesler

Found 4 papers, 0 papers with code

Feedback-Generation for Programming Exercises With GPT-4

no code implementations7 Mar 2024 Imen Azaiz, Natalie Kiesler, Sven Strickroth

LLMs such as Codex, GPT-3. 5, and GPT 4 have shown promising results in the context of large programming courses, where students can benefit from feedback and hints if provided timely and at scale.

Fault localization

The Robots are Here: Navigating the Generative AI Revolution in Computing Education

no code implementations1 Oct 2023 James Prather, Paul Denny, Juho Leinonen, Brett A. Becker, Ibrahim Albluwi, Michelle Craig, Hieke Keuning, Natalie Kiesler, Tobias Kohn, Andrew Luxton-Reilly, Stephen MacNeil, Andrew Peterson, Raymond Pettit, Brent N. Reeves, Jaromir Savelka

Second, we report the findings of a survey of computing students and instructors from across 20 countries, capturing prevailing attitudes towards LLMs and their use in computing education contexts.

Ethics

Exploring the Potential of Large Language Models to Generate Formative Programming Feedback

no code implementations31 Aug 2023 Natalie Kiesler, Dominic Lohr, Hieke Keuning

Ever since the emergence of large language models (LLMs) and related applications, such as ChatGPT, its performance and error analysis for programming tasks have been subject to research.

Large Language Models in Introductory Programming Education: ChatGPT's Performance and Implications for Assessments

no code implementations15 Aug 2023 Natalie Kiesler, Daniel Schiffner

This paper investigates the performance of the Large Language Models (LLMs) ChatGPT-3. 5 and GPT-4 in solving introductory programming tasks.

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