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 ](http://www.aaai.org/)



  • Abstract submission due: September 1, 2020 11:59pm UTC-12
  • Paper submission deadline: September 9, 2020 11:59pm UTC-12
  • Notification date: November 13, 2020
  • Camera-ready copy due to AAAI: December 18, 2020
  • Symposium dates: February 6-7, 2021

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:

  • The design of an AI curriculum, course, or module.
  • The development or use of a tool or resource to teach AI.
  • The impact of a pedagogical or mentoring technique on AI students.
  • The use of AI to facilitate teaching or to enhance learning.

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

  • Nate Derbinsky, Northeastern University (n.derbinsky@northeastern.edu)
  • Laura Brown, Michigan Technological University (lebrown@mtu.edu)
  • Zachary Dodds, Harvey Mudd College (dodds@cs.hmc.edu)
  • Susan Imberman, CUNY College of Staten Island (susan.imberman@csi.cuny.edu)
  • Todd Neller, Gettysburg College (tneller@gettysburg.edu)

K12 Track Chairs

  • Christina Gardner-McCune, University of Florida (gmccune@ufl.edu)
  • Dave Touretzky, Carnegie Mellon University (dst@cs.cmu.edu)

Program Committee

  • Adam Smith, UC Santa Cruz
  • Alexis Cobo, Pine Crest School
  • Alla Rozovskaya, City University of New York
  • Ameet Soni, Swarthmore College
  • Amelie Marian, Rutgers University
  • Amos Azaria, Ariel University
  • Ananya Christman, Middlebury College
  • Andreas Martin, FHNW University of Applied Sciences and Arts
  • Anna Rafferty, Carleton College
  • Ansaf Salleb-Aouissi, Columbia University
  • Ashish Aggarwal, University of Florida
  • Bita Akram, North Carolina State University
  • Brian O'Neill, Western New England University
  • Cecilia Ovesdotter Alm, Rochester Institute of Technology
  • Chris Brooks, University of San Francisco
  • Claudio Gallicchio, University of Pisa
  • Dave Kauchak, Pomona College
  • David Lockett, ORAU/NASA
  • David Poole, The University of British Columbia
  • Debra Burhans, Canisius College
  • Devika Subramanian, Rice University
  • Doug Turnbull, Ithaca College
  • Ehi Nosakhare, Microsoft
  • Eric Eaton, University of Pennsylvania
  • Erin Talvitie, Harvey Mudd College
  • Felipe Leno da Silva, Advanced Institute for AI
  • Francesca Spezzano, Boise State University
  • Fredrik Heintz, Linköping University
  • George Thomas, University of Wisconsin Oshkosh
  • Giulia Toti, University of Houston
  • Giuseppe Carenini, The University of British Columbia
  • Hadi Hosseini, Pennsylvania State University
  • Haym Hirsh, Cornell University
  • Hyeoncheol Kim, Korea University
  • James Glenn, Yale University
  • James Marshall, Sarah Lawrence College
  • Jared Amalong, Sacramento County Office of Education
  • Jason Hiebel, Michigan Technological University
  • Jeffrey Pfaffmann, Lafayette College
  • Jeremy Blum, Pennsylvania State University
  • Jessie Walker, STEM Resources
  • Jia Tao, Lafayette College
  • Jim Boerkoel, Harvey Mudd College
  • Jimmy Lee, The Chinese University of Hong Kong
  • John Anderson, University of Manitoba
  • John Chapin, Loudoun County Public Schools
  • Joseph Osborn, Pomona College
  • Joshua Eckroth, Stetson University
  • Joyce Williams, National Geospatial Intelligence Agency
  • Joydeep Biswas, University of Texas Austin
  • Justin Li, Occidental College
  • Kelly Powers, Cornell Tech
  • Laney Strange, Northeastern University
  • Lars Kotthoff, University of Wyoming
  • Laura Brown, Michigan Technological University
  • Lisa Meeden, Swarthmore College
  • Lisa Zhang, University of Toronto
  • Maria Gini, University of Minnesota
  • Marie desJardins, Simmons University
  • Mark Miller, Learningtech.org
  • Matthew Eicholtz, Florida Southern College
  • Matthew Taylor, Washington State University
  • Mehran Sahami, Stanford University
  • Mei Si, Rensselaer Polytechnic Institute
  • Michael Wollowski, Rose-Hulman Institute of Technology
  • Nancy Green, University of North Carolina Greensboro
  • Narges Norouzi, UC Santa Cruz
  • Nate Derbinsky, Northeastern University
  • Panagiotis Karras, Aarhus University
  • Qian Yang, Duke University
  • Radu Paul Mihail, Valdosta State University
  • Raghuram Ramanujan, Davidson College
  • Raja Sooriamurthi, Carnegie Mellon University
  • Rajiv Ratn Shah, IIIT Delhi
  • Rania Hodhod, Columbus State University
  • Richard Freedman, Smart Information Flow Technologies
  • Sameer Singh, University of California Irvine
  • Sarah Zelikovitz, College of Staten Island
  • Scott Alfeld, Amherst College
  • Simon Parsons, University of Lincoln
  • Stavroula Prantsoudi, Greek Public Schools
  • Stephanie August, Loyola Marymount University
  • Steven Bogaerts, DePauw University
  • Susan Imberman, City University of New York
  • Sven Koenig, University of Southern California
  • Terry Zimmerman, University of Washington-Bothell
  • Tom Williams, Colorado School of Mines
  • Ute Schmid, University of Bamberg
  • Uzay Macar, Columbia University
  • Vibhu Mittal, Mettle Works/Edmodo
  • Vincent Cicirello, Stockton University
  • William Kerney, Clovis College
  • Xiaoyan Li, Princeton University
  • Yuanlin Zhang, Texas Tech University
  • Zachary Dodds, Harvey Mudd College
  • Zitao Liu, TAL Education Group

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