| Vol-3487 urn:nbn:de:0074-3487-1 Copyright © 2023 for the individual papers by the papers' authors. Copyright © 2023 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# AIEDLLM 2023
Empowering Education with LLMs - the Next-Gen Interface and Content Generation 2023

### Proceedings of the Workshop on Empowering Education with LLMs - the Next-Gen Interface and Content Generation 2023
co-located with 24th International Conference on Artificial Intelligence in Education (AIED 2023)

### Tokyo, Japan, July 7, 2023.

Edited by

### Steven Moore *
John Stamper *
Richard Tong **
Chen Cao **
Zitao Liu ***
Xiangen Hu ****
Yu Lu *****
Joleen Liang ******
Hassan Khosravi *******
Paul Denny ********
Anjali Singh *********
Chris Brooks *********

* Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
** Carnegie Learning, Pittsburgh, Pennsylvania, United States
*** Jinan University, Guangdon Province, China
**** University of Memphis, Memphis, Tennessee, United States
***** Beijing Normal University, Beijing, China
****** Squirrel AI Learning, Shanghai, China
******* University of Queensland, St Lucia, Queensland, Austrailia
******** University of Auckland, Auckland, New Zealand
********* University of Michigan, Ann Arbor, Michigan, United States

## Table of Contents

- Preface
  Summary: There were 38 papers submitted for peer-review to this workshop. Out of these, 17 papers were accepted for this volume.

- Prototyping the use of Large Language Models (LLMs) for Adult Learning Content Creation at Scale 3-7
  Daniel Leiker, Sara Finnigan, Ashley Ricker Gyllen, Mutlu Cukurova
- Using LLM (Large Language Model) to Improve Efficiency in Literature Review for Undergraduate Research 8-16
  Shouvik Ahmed Antu, Haiyan Chen, Cindy K. Richards
- Contextualizing Problems to Student Interests at Scale in Intelligent Tutoring System Using Large Language Models 17-25
  Gautam Yadav, Ying-Jui Tseng, Xiaolin Ni
- Deduction under Perturbed Evidence: Probing Student Simulation (Knowledge Tracing) Capabilities of Large Language Models 26-33
  Shashank Sonkar, Richard G. Baraniuk
- A Case Study using Large Language Models to Generate Metadata for Math Questions 34-42
  Katie Bainbridge, Candace Walkington, Armon Ibrahim, Iris Zhong, Debshila Basu Mallick, Julianna Washington, Rich Baraniuk
- An LLM-Powered Adaptive Practicing System 43-52
  Md Rayhan Kabir, Fuhua Lin
- Detecting ChatGPT-Generated Code in a CS1 Course 53-63
  Muntasir Hoq, Yang Shi, Juho Leinonen, Damilola Babalola, Collin Lynch, Bita Akram
- Is AI the better programming partner? Human-Human Pair Programming vs. Human-AI pAIr Programming 64-77
  Qianou Christina Ma, Sherry Tongshuang Wu, Ken Koedinger
- Generative Large Language Models for Dialog-Based Tutoring: An Early Consideration of Opportunities and Concerns 78-88
  Benjamin D. Nye, Dillon Mee, Mark G. Core
- The Unseen A+ Student: Evaluating the Performance and Detectability of Large Language Models in High School Assignments 89-100
  Matyáš Boháček
- Leveraging LLMs for Adaptive Testing and Learning in Taiwan Adaptive Learning Platform (TALP) 101-110
  Bor-Chen Kuo, Frederic T. Y. Chang, Zong-En Bai
- Generating Multiple Choice Questions from a Textbook: LLMs Match Human Performance on Most Metrics 111-128
  Andrew M. Olney
- Language Modeling for Plan Generation in Game-Base Learning Environments 129-138
  Alex Goslen, Yeo Jin Kim, Jonathan Rowe, James Lester
- Harnessing LLMs in Curricular Design: Using GPT-4 to Support Authoring of Learning Objectives 139-150
  Pragnya Sridhar, Aidan Doyle, Arav Agarwal, Christopher Bogart, Jaromir Savelka, Majd Sakr
- Exploring Pre-Service Teachers’ Perceptions of Large Language Models-Generated Hints in Online Mathematics Learning 151-162
  Sai Gattupalli, Will Lee, Danielle Allessio, Danielle Crabtree, Ivon Arroyo, Beverly Woolf
- Rewriting Math Word Problems with Large Language Models 163-172
  Kole Norberg, Husni Almoubayyed, Stephen E. Fancsali, Logan De Ley, Kyle Weldon, April Murphy, Steve Ritter
- On the Application of Large Language Models for Language Teaching and Assessment Technology 173-197
  Andrew Caines, Luca Benedetto, Shiva Taslimipoor, Christopher Davis, Yuan Gao, Øistein Andersen, Zheng Yuan, Mark Elliott, Russell Moore, Christopher Bryant, Marek Rei, Helen Yannakoudakis, Andrew Mullooly, Diane Nicholls, Paula Buttery

2023-08-14: submitted by Steven Moore, metadata incl. bibliographic data published under Creative Commons CC0
2023-09-17: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|