AI Innovations(Day 1)

AI Innovations(Day 1)

Agenda & Resources

Day 1, February 26, 2024

Session 1: 9.00 am - 10.30 am




9:00 am - 9:05 am

Welcome remarks, Travel Scholarship winner announcements

Muktha Ananda, Google

Simon Woodhead, EEDI

9:05 am - 9:35 am

Invited Speaker

Introduction: Muktha Ananda, Google

Vered Shwartz, University of British Columbia;

Large Language Models in Education: Challenges and Opportunities

Abstract: Large language models (LLMs) like ChatGPT have become popular, reaching millions of users across the globe. The diverse range of capabilities of LLMs, from conversing and crafting fluent essays, to coding and composing poetry, holds great promise for a variety of fields, including education. In this talk, we will explore how LLMs may be used to enhance rather than degrade teaching and learning. We will then discuss some limitations and risks of using LLMs in general and in educational setups in particular.

9:35 am - 10:30 am

Contributed Talks

Moderator: Debshila Basu Mallick, OpenStax-Rice University

  1. Day 1 Best paper runner-up: Using Large Language Models for Student-Code Guided Test Case Generation in Computer Science Education [paper] [slide]
  2. Explaining Code Examples in Introductory Programming Courses: LLM vs Humans [paper] [slide]
  3. Using Large Language Models to Assess Tutors' Performance in Reacting to Students Making Math Errors[paper] [slide]
  4. Improving Assessment of Tutoring Practices using Retrieval-Augmented Generation[paper] [slide]
  5. Learning to Compare Hints: Combining Insights from Student Logs and Large Language Models[paper] [slide]
  6. AI-Augmented Advising: AI-Augmented Advising: A Comparative Study of ChatGPT-4 and Advisor-based Major Recommendations[paper] [slide]

10.30 am - 11.00 am: Posters & Break[1] 

Session 2: 11.00 am - 12.30 pm

11:00 - 11:45 am


Gary Marcus, Professor Emeritus, NYU;

Introduction: Simon Woodhead, EEDI

11:45 - 12:30 pm

Poster Session


12.30 pm - 2.00 pm:  Lunch (on your own, not provided)

Session 3: 2.00 pm - 3.30 pm

2:00 pm - 2:30 pm

Contributed Talks

Moderator: Muktha Ananda

  1. Challenges and Opportunities of Moderating Usage of Large Language Models in Education[paper] [slide]
  2. Day 1 Best paper: Concept Prerequisite Relation Prediction by Using Permutation-Equivariant Directed Graph Neural Networks [paper] [slide]
  3. The Impact of Student-AI Collaborative Feedback Generation on Learning Outcomes[paper] [slide]

2:30 pm - 3:30 pm

Mathematical Reasoning Competition

Moderators: Mr. Tian Mi, TAL Education Group 

Prof. Zitao Liu, Guangdong Institute of Smart Education, Jinan University

3.30 pm - 4.00 pm: Posters & Break1 

Session 4: 4.00 pm - 5.00 pm

4:00 pm - 4:55 pm

AI4Ed Vision 2034: Prioritizing Use Cases for Equitable Impact

Moderator: Jeremy Roschelle, Digital Promise

Speakers: Pat Yongpradit,,

Kinnis Gosha, Morehouse College

Muhammad Abdul-Mageed, University of British Columbia

Karen DSouza, Purdue University

Mohi Reza, University of Toronto

4:55 pm - 5:00 pm

Day 1 closing remarks

Debshila Basu Mallick, OpenStax-Rice U

Collaborating Organizations

Collaborating Organizations