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Home / Conferences / AAAI Conference on Artificial Intelligence / AAAI 2021 Conference /

The Eleventh Symposium on Educational Advances in Artificial Intelligence (EAAI-21)

January 29, 2023

Saturday – Sunday, February 6-7

External Link: https://pages.mtu.edu/~lebrown/eaai/

EAAI-21 provides a venue for researchers and educators to discuss issues and share resources related to teaching AI and using AI in education. Contributions address K-12, undergraduate, and post-graduate education. The program comprises the 2021 Outstanding Educator Award Lecture by Michael Wooldridge, a panel on Teaching Online and Blended AI Courses, a main track, a special track on Demos, Software Tools, and Activities for Teaching AI in K-12, a special track on Model AI Assignments, and the EAAI-21 Gin Rummy Undergraduate Research Challenge.

EAAI-21 is open to all registered AAAI-21 attendees. The full EAAI-21 schedule is included below.

AAAI gratefully acknowledges a generous grant from AI Journal, which helped make this program possible.

Lisa Torrey and Michael Guerzhoy
EAAI-21 Cochairs


EAAI-21 Program Schedule

Saturday, February 6, 2021
6:30am – 2:15pm PST


[6:30-7:45am] Talking to the Public about AI
Michael Wooldridge – University of Oxford and Alan Turing Institute, London

Since everything went crazy in AI, around 2012, I, like many other members of our community, have frequently found myself put in the position of having to talk about our field to a non-specialist audience. I’ve been interviewed on TV and radio, and spoken to endless university committees, government committees, and industrial conferences. More recently, following the publication of my two popular science books (the Ladybird Expert Guide to AI [2018], and The Road to Conscious Machines [2020]), I’ve even begun speaking at a literary festivals (believe me, I never expected to be doing this as a PhD student studying multiagent systems back in 1989). In this talk, I will relate these experiences, the mistakes I made, and what I learned from them – how our field is perceived, what people fear, hope, and expect from it, and how best to communicate excitement about the very real progress we’ve made recently with a realistic understanding of where we are and where we are going.

Michael Wooldridge is the winner of this year’s Outstanding Educator award. He is a Professor of Computer Science and Head of Department of Computer Science at the University of Oxford, and a programme director for AI at the Alan Turing Institute. He is a Fellow of the ACM, the Association for the Advancement of AI (AAAI), and the European Association for AI (EurAI). From 2014-16, he was President of the European Association for AI, and from 2015-17 he was President of the International Joint Conference on AI (IJCAI). As well as more than 400 technical articles on AI, he has published two popular science introductions to the field: The Ladybird Expert Guide to AI (2018), and The Road to Conscious Machines (Pelican, 2020).


[7:45 – 8:00] Welcome
Lisa Torrey – St. Lawrence University
Michael Guerzhoy – Princeton University


[8:00 – 8:45] Main Track

Applied Machine Learning for Games: A Graduate School Course
Yilei Zeng, Aayush Shah, Jameson Thai, Michael Zyda

Designing a Hybrid AI Residency
Felipe Leno Da Silva, Silvio Stanzani, Jefferson Coelho, Jorge Mondadori, Muriel Mazzetto, Felipe Sanches Couto, Raphael Cobe


[8:45 – 9:45] Main Track

AI-Infused Collaborative Inquiry in Upper Elementary School: A Game-Based Learning Approach
Seung Lee, Bradford Mott, Anne Ottenbreit-Leftwich, Adam Scribner, Sandra Taylor, Kyungjin Park, Jonathan Rowe, Krista Glazewski, Cindy E. Hmelo-Silver, James Lester

Introduction to Machine Learning with Robots and Playful Learning
Viktoriya Olari, Kostadin Cvejoski, Øyvind Eide

Learning Artificial Intelligence: Insights into How Youth Encounter and Build Understanding of AI Concepts
Eric Greenwald, Maxyn Leitner, Ning Wang


[9:45 – 12:00] Gin Rummy Undergraduate Research Challenge

Extracting Learned Discard and Knocking Strategies from a Gin Rummy Bot
Benjamin Goldstein, Jean Astudillo Guerra, Emily Haigh, Bryan Cruz Ulloa, Jeremy Blum

A Heuristic Evaluation Function for Hand Strength Estimation in Gin Rummy
Aqib Ahmed, Joshua Leppo, Michal Lesniewski, Riken Patel, Jonathan Perez, Jeremy J. Blum

Estimating Card Fitness for Discard in Gin Rummy
Jacob Gallucci, Richard Bowser, Sarah Kettell, Christian Overton

A Deterministic Neural Network Approach to Playing Gin Rummy
Viet Dung Nguyen, Dung Doan, Todd W. Neller

A Data-Driven Approach for Gin Rummy Hand Evaluation
Sang T. Truong, Todd W. Neller

Opponent Hand Estimation in the Game of Gin Rummy
Peter E. Francis, Hoang Anh Just, Todd W. Neller

Knocking in the Game of Gin Rummy
Ryzeson C. Maravich, Taylor C. Neller, Todd W. Neller


[12:00 – 12:45] Main Track

Visualizing NLP in Undergraduate Students’ Learning about Natural Language
Cecilia Ovesdotter Alm, Alex Hedges

Deep Discourse Analysis for Generating Personalized Feedback in Intelligent Tutor Systems
Matt Grenander, Robert Belfer, Ekaterina Kochmar, Iulian V. Serban, François St-Hilaire, Jackie C. K. Cheung


[12:45 – 1:30] Main Track

Educational Question Mining At Scale: Prediction, Analysis and Personalization
Zichao Wang, Sebastian Tschiatschek, Simon Woodhead, José Miguel Hernández-Lobato, Simon Peyton Jones, Richard G. Baraniuk, Cheng Zhang

Student Knowledge Prediction for Teacher-Student Interaction
Seonghun Kim, Woojin Kim, Yeonju Jang, Seongyune Choi, Heeseok Jung, Hyeoncheol Kim


[1:30 – 2:15] Main Track

Why and What to Teach: AI Curriculum for Elementary School
Seonghun Kim, Yeonju Jang, Woojin Kim, Seongyune Choi, Heeseok Jung, Soohwan Kim, Hyeoncheol Kim

Teacher Perspectives on How To Train Your Robot: A Middle School AI and Ethics Curriculum
Randi Williams, Stephen P. Kaputsos, Cynthia Breazeal


Sunday, February 7, 2021
7:00am – 3:00pm PST


[7:00 – 8:15] Teaching Online and Blended AI Courses

Panelists: Ashok Goel – Georgia Institute of Technology
Ansaf Salleb-Aouissi – Columbia University
Mehran Sehami – Stanford University

This panel is composed of AI faculty with experience teaching online and blended classes. Many of us found ourselves teaching AI courses online for the first time last year, and even after COVID-19 subsides, higher education is likely to retain online components. How will we make the most of this challenge (and opportunity)? How do we engage and bond with students online? What are the best tools for AI courses? In a blended model, which components of a course can be done best online and which are best in person? Panelists will share what they’ve learned on these topics and more.

Ashok Goel is a Professor in the School of Interactive Computing at Georgia Institute of Technology and the Chief Scientist with Georgia Tech’s Center for 21st Century Universities. In 2014, he co-developed a Udacity course on Knowledge-Based AI; in 2016, his research laboratory developed Jill Watson, a virtual teaching assistant for automatically answering questions in online classes; and in 2019, he co-edited a volume on Blended Learning published by MIT Press. Ashok received AAAI’s Outstanding AI Educator Award in 2019, and the University System of Georgia’s Hall of Fame Faculty Award for Scholarship of Teaching and Learning in 2020.

Ansaf Salleb-Aouissi is a senior lecturer in computer science with specific interests in machine learning and AI applications, including education and healthcare. She has published in top quality venues including JMLR, TPAMI, AAAI, ECML, PKDD, COLT, IJCAI, ECAI, CHILL, and AISTAT. She also has a genuine interest in education and teaching, particularly on how to translate complex topics and break up abstract concepts into a form understandable and engaging to students. Recently, she has been working on building education tools for auto-grading and self-learning to provide additional support to her students in computer science and discrete mathematics. Her EdX course on Artificial Intelligence has attracted over a quarter million learners from all over the world since 2017.

Mehran Sahami is the James and Ellenor Chesebrough Professor in Engineering and Associate Chair for Education in the Computer Science department at Stanford University. He is also the Robert and Ruth Halperin University Fellow in Undergraduate Education. He served as co-chair of the ACM/IEEE-CS joint task force on Computer Science Curricula 2013, is Past Chair of the ACM Education Board, and was appointed by the Governor of California to the state’s Computer Science Strategic Implementation Plan Advisory Panel.


[8:15 – 9:15] Demos, Software Tools, and Activities for Teaching AI in K-12

Web-Based Platform for K-12 AI Education in China
Chao Wu, Yan Li, Junxiang Li, Qiongdan Zhang, Fei Wu

PoseBlocks: A Toolkit for Creating (and Dancing) with AI
Brian Jordan, Nisha Devasia, Jenna Hong, Randi Williams, Cynthia Breazeal

Teaching Tech to Talk: K-12 Conversational Artificial Intelligence Literacy Curriculum and Development Tools
Jessica Van Brummelen, Tommy Heng, Viktoriya Tabunshchyk


[9:15 – 10:15] Demos, Software Tools, and Activities for Teaching AI in K-12

GANs Unplugged
Patrick Virtue

What are GANs?: Introducing Generative Adversarial Networks to Middle School Students
Safinah Ali, Daniella DiPaola, Cynthia Breazeal

The Contour to Classification game
Irene Lee, Safinah Ali


[10:15 – 12:00] Gin Rummy Undergraduate Research Challenge

Heisenbot: A Rule-Based Game Agent for Gin Rummy
Matthew Eicholtz, Savanna Moss, Matthew Traino, Christian Roberson

A Highly-Parameterized Ensemble to Play Gin Rummy
Masayuki Nagai, Kavya Shrivastava, Kien Ta, Steven Bogaerts, Chad Byers

Random Forests for Opponent Hand Estimation in Gin Rummy
Anthony Hein, May Jiang, Vydhourie Thiyageswaran, Michael Guerzhoy

Evaluating Gin Rummy Hands Using Opponent Modeling and Myopic Meld Distance
Phoebe Goldman, Corey R. Knutson, Ryan Mahtab, Jack Maloney, Joseph B. Mueller, Richard G. Freedman

Opponent Hand Estimation in Gin Rummy Using Deep Neural Networks and Heuristic Strategies
Bhaskar Mishra, Ashish Aggarwal

Modeling Expert Knowledge in a Heuristic-Based Gin Rummy Agent
Sarah Larkin, William Collicott, Jason Hiebel


[12:00 – 12:45] Model AI Assignments

“Unplugged” Semantic Networks and Knowledge Representations
Duri Long, Jonathan Moon, Brian Magerko

Introducing AI Worksheet Activity
Duri Long, Jonathan Moon, Brian Magerko


[12:45 – 1:30] Model AI Assignments

Rush Hour: Designing and Comparing Heuristics for a Children’s Puzzle
John Maraist

Using Markov Chain Text Generators to Facilitate Found Poetry Creation
Alex Leto, Toni Lefton, Tom Williams


[1:30 – 2:15] Model AI Assignments

ScalarFlow: Implementing Reverse Mode Automatic Differentiation
Nathan Sprague

Text Denoising Autoencoder for News Headlines
Lisa Zhang, Pouria Fewzee


[2:15 – 3:00] Community Meeting

All attendees are invited to join us for an informal community meeting at the end of EAAI-21, where we’ll socialize and share ideas for next year’s symposium.

Categories: 2021, aaai

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