EAAI-21: The 11th Symposium on Educational Advances in Artificial Intelligence

A Virtual Conference    (Collocated with AAAI-21)
Feb. 6-7, 2021

Sponsored by the Association for the Advancement of Artificial Intelligence



Program Schedule

Saturday, February 6, 2021

9:30am - 5:15pm EST

[9:30-10:45am] 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).

[10:45 - 11:00] Welcome
Lisa Torrey - St. Lawrence University
Michael Guerzhoy - Princeton University

[11:00 - 11:45] Main Track

[11:45 - 12:45] Main Track

[12:45 - 3:00] Gin Rummy Undergraduate Research Challenge

[3:00 - 3:45] Main Track

[3:45 - 4:30] Main Track

[4:30 - 5:15] Main Track

Sunday, February 7, 2021

10:00am - 6:00pm EST

[10:00 - 11:15] Teaching Online and Blended AI Courses
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.

[11:15 - 12:15] Demos, Software Tools, and Activities for Teaching AI in K-12

[12:15 - 1:15] Demos, Software Tools, and Activities for Teaching AI in K-12

[1:15 - 3:00] Gin Rummy Undergraduate Research Challenge

[3:00 - 3:45] Model AI Assignments

[3:45 - 4:30] Model AI Assignments

[4:30 - 5:15] Model AI Assignments

[5:15 - 6:00] 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.


Main Track

The main track invites a broad range of papers on teaching AI and teaching with AI. Submissions may be framed as research papers or as experience reports. Potential topics include:

Special Track: Demos, Software Tools, and Activities for Teaching AI in K-12

Chairs: Dave Touretzky (Carnegie Mellon) and Christina Gardner-McCune (University of Florida)

This special track invites papers on the development and use of resources to support K-12 AI education. Examples include online demos, software tools, and structured activities. Our goal is to make resources available for K-12 teachers to use in the classroom to engage students in learning about AI technologies. Papers should include the following: description of the resource; target age group; setup and resources needed; AI concepts addressed; expected learning outcomes; and (if possible) implementation results. Online demos and software tools should be accompanied by brief video walk-throughs.

Special Track: Gin Rummy Undergraduate Research Challenge

Chair: Todd Neller (Gettysburg College)

This special track invites papers addressing the Gin Rummy Undergraduate Research Challenge (http://cs.gettysburg.edu/~tneller/games/ginrummy/eaai). The object of this challenge is to develop a competitive and efficient Gin Rummy player. The broader purpose of EAAI undergraduate research challenges is to encourage faculty-mentored undergraduate students to experience the full life-cycle of AI research.

Submissions should be framed as research papers, with at least one undergraduate author and at least one faculty author, reporting on a player that has been submitted to the tournament.

Special Track: Model AI Assignments Session

Chair: Todd Neller, Gettysburg College

This special track invites assignments for AI classes. Good assignments take a lot of work to design. If an assignment you have developed may be useful to other AI educators, this track provides an opportunity to share it. Model AI Assignments are kept in a public online archive.

This track has special submission instructions (http://modelai.gettysburg.edu).

Submission Content and Formatting

All submissions must be anonymous for double-blind review.

Except for Model AI Assignments, which have their own format, papers should be:

EAAI-21 will not consider any paper that, at the time of submission, is under review for or has already been published or accepted for publication in a refereed journal or conference. Once submitted to EAAI-21, papers may not be submitted to another refereed journal or conference during the review period. These restrictions do not apply to unrefereed forums or workshops without archival proceedings.


Program co-Chairs

Organizing Committee

K12 Track Chairs

Program Committee

The following links are to various material on AAAI-21 and EAAI-21.