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

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