473 citations · 1.2k across the 39 of their papers we have counts for
6 papers · 1 filter
Synthesizing Research on Programmers' Mental Models of Programs, Tasks and Concepts -- a Systematic Literature Review
Ava Heinonen, Bettina Lehtelä, Arto Hellas +1
Programmers' mental models represent their knowledge and understanding of programs, programming concepts, and programming in general. They guide programmers' work and influence the…
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…
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…
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…
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…
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…