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Stephen Macneil

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Assistant Professor

Temple University

United States

Research Interests

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About

Stephen Macneil is an Assistant Professor at Temple University in the United States. His research focuses on the application of large language models in computer science education, particularly in generating learning materials and code explanations. Recent publications include "Experiences from Using Code Explanations Generated by Large Language Models in a Web Software Development E-Book" and "Automatically Generating CS Learning Materials with Large Language Models."

Recent Grants

Grant: Close

NSF Convergence Accelerator Track H: Next Generation Augmentative and Alternative Communication Technology Powered by Artificial Intelligence

Open Date: 2022-12-15

Close Date: 2024-11-30

Grant: Close

REU Site: Research Experiences in Pervasive Computing for Smart Health, Safety, and Well-being

Open Date: 2022-03-01

Close Date: 2025-02-28

Articles (16)

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2026

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2023

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2023

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2022

Collaborators (16)

Jacqueline Smith

Associate Professor, Teaching Stream

University of Toronto

CANADA

Stephen Macneil

Research Interests

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About

Recent Grants

Articles (16)

The Use of a Visual Scene Display for the Acquisition of Manding in Young Children with Complex Communication Needs

Breaking the Programming Language Barrier: Multilingual Prompting to Empower Non-Native English Learners

Exploring Student Reactions to LLM-Generated Feedback on Explain in Plain English Problems

A Plan for an ACM Task Force Working Group into the Ethical and Societal Impacts of Generative AI in Higher Computing Education

"All Roads Lead to ChatGPT": How Generative AI is Eroding Social Interactions and Student Learning Communities

Evaluating the Impact of AI-Generated Visual Explanations on Decision-Making for Image Matching

Exploring Engagement Opportunities for Autistic Children: Using AAC as a Controller in a Wizard-of-Oz Coloring Game

Fostering Responsible AI Use Through Negative Expertise: A Contextualized Autocompletion Quiz

LLM-itation is the Sincerest Form of Data: Generating Synthetic Buggy Code Submissions for Computing Education

Neurodiversity in Computing Education Research: A Systematic Literature Review

Probing the Unknown: Exploring Student Interactions with Probeable Problems at Scale in Introductory Programming

The Role of Generative AI in Software Student CollaborAItion

Preliminary Investigation of Context-Aware Augmentative and Alternative Communication with Automated Just-in-Time Cloze Phrase Response Options for Social Participation from Children on the Autism Spectrum

Using Large Language Models to Automatically Identify Programming Concepts in Code Snippets

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

Automatically Generating CS Learning Materials with Large Language Models

Collaborators (16)

Jacqueline Smith

Petri Ihantola

Natalie Kiesler

Oana Andrei

Alison Clear

Brenna Griffen

Andrew Luxton-Reilly

Samuel Mann

Joao Orvalho

David Smith

Sami Sarsa

Judithe Sheard

Janice Mak

Elizabeth Lorah

Brent N. Reeves

Sheida Raley

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