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20212026
most citedAutomatic Generation of Programming Exercises and Code Explanations using Large Language Models

473 citations · 2.3k across the 48 of their papers we have counts for

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Showing 2022Show all

7 papers · 1 filter

cs.CY2022★ 43 cited

Automatically Generating CS Learning Materials with Large Language Models

Stephen MacNeil, Andrew Tran, Juho Leinonen +5

Recent breakthroughs in Large Language Models (LLMs), such as GPT-3 and Codex, now enable software developers to generate code based on a natural language prompt. Within computer s…

cs.HC2022★ 37 cited

Programming Is Hard -- Or at Least It Used to Be: Educational Opportunities And Challenges of AI Code Generation

Brett A. Becker, Paul Denny, James Finnie-Ansley +3

The introductory programming sequence has been the focus of much research in computing education. The recent advent of several viable and freely-available AI-driven code generation…

cs.HC2022★ 18 cited

Robosourcing Educational Resources -- Leveraging Large Language Models for Learnersourcing

Paul Denny, Sami Sarsa, Arto Hellas +1

In this article, we introduce and evaluate the concept of robosourcing for creating educational content. Robosourcing lies in the intersection of crowdsourcing and large language m…

cs.SE2022★ 3 cited

Experiences from Using Code Explanations Generated by Large Language Models in a Web Software Development E-Book

Stephen MacNeil, Andrew Tran, Arto Hellas +5

Advances in natural language processing have resulted in large language models (LLMs) that are capable of generating understandable and sensible written text. Recent versions of th…

cs.HC2022★ 14 cited

Conversing with Copilot: Exploring Prompt Engineering for Solving CS1 Problems Using Natural Language

Paul Denny, Viraj Kumar, Nasser Giacaman

GitHub Copilot is an artificial intelligence model for automatically generating source code from natural language problem descriptions. Since June 2022, Copilot has officially been…

cs.HC2022★ 228 cited

Using Large Language Models to Enhance Programming Error Messages

Juho Leinonen, Arto Hellas, Sami Sarsa +4

A key part of learning to program is learning to understand programming error messages. They can be hard to interpret and identifying the cause of errors can be time-consuming. One…

cs.SE2022★ 473 cited

Automatic Generation of Programming Exercises and Code Explanations using Large Language Models

Sami Sarsa, Paul Denny, Arto Hellas +1

This article explores the natural language generation capabilities of large language models with application to the production of two types of learning resources common in programm…