195 citations · 268 across the 7 of their papers we have counts for
8 papers
Generative AI in Computing Education: Perspectives of Students and Instructors
Cynthia Zastudil, Magdalena Rogalska, Christine Kapp +2
Generative models are now capable of producing natural language text that is, in some cases, comparable in quality to the text produced by people. In the computing education contex…
Memory Sandbox: Transparent and Interactive Memory Management for Conversational Agents
Ziheng Huang, Sebastian Gutierrez, Hemanth Kamana +1
The recent advent of large language models (LLM) has resulted in high-performing conversational agents such as chatGPT. These agents must remember key information from an ongoing c…
Prompt Middleware: Mapping Prompts for Large Language Models to UI Affordances
Stephen MacNeil, Andrew Tran, Joanne Kim +3
To help users do complex work, researchers have developed techniques to integrate AI and human intelligence into user interfaces (UIs). With the recent introduction of large langua…
Freeform Templates: Combining Freeform Curation with Structured Templates
Stephen MacNeil, Ziheng Huang, Kenneth Chen +4
Online whiteboards are becoming a popular way to facilitate collaborative design work, providing a free-form environment to curate ideas. However, as templates are increasingly bei…
Comparing Code Explanations Created by Students and Large Language Models
Juho Leinonen, Paul Denny, Stephen MacNeil +5
Reasoning about code and explaining its purpose are fundamental skills for computer scientists. There has been extensive research in the field of computing education on the relatio…
Fluid Transformers and Creative Analogies: Exploring Large Language Models' Capacity for Augmenting Cross-Domain Analogical Creativity
Zijian Ding, Arvind Srinivasan, Stephen MacNeil +1
Cross-domain analogical reasoning is a core creative ability that can be challenging for humans. Recent work has shown some proofs-of concept of Large language Models' (LLMs) abili…
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…
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…