EAAI 2023 : Educational Advances in Artificial Intelligence
Call For Papers
The 13th Symposium on Educational Advances in Artificial Intelligence 2023 (EAAI-23)
Call for Model AI Assignments
(collocated with AAAI-23)
February 11-12, 2022
Washington, D.C., USA
Sponsored by the Association for the Advancement of Artificial Intelligence
Good project assignments for AI classes are hard to come by. If you believe an assignment you have developed may be useful to other AI educators, we encourage you to prepare it for broad dissemination and submit it to the Model AI Assignments session. If selected, the project will be made available to other AI educators as a Model AI Assignment (http://modelai.gettysburg.edu/) and will be presented at EAAI (http://eaai.cs.mtu.edu).
· September 11, 2022 at 11:59pm UTC-12 (anywhere on earth): Model AI Assignment 200-word abstracts (via EasyChair) and assignment submissions (via email) due
· November 18, 2022: Author notifications
· February 11-12, 2023: Symposium dates
What is the Model AI Assignments Session?
The Model AI Assignments Session seeks to gather and disseminate the best assignment designs of the Artificial Intelligence (AI) Education community.
“One must learn by doing the thing; for though you think you know it, you have no certainty, until you try.” -Sophocles
Recognizing that assignments form the core of student learning experience, we invite AI educators to submit draft assignment materials that exemplify an approach to teaching AI topics at all levels.
Consider these challenges in assignment design:
· Introductory AI audience: As any AI educator knows, AI topics are diverse, and one can only effectively cover a sampling of topics at the introductory level. Pick an AI topic/subtopic you consider essential to Introductory AI (for example, search, constraint satisfaction, knowledge representation and reasoning, planning, probabilistic reasoning, machine learning, robotics, machine vision, and so on). What is your optimal assignment to ground the core concepts in experience?
· K-12/CS1/CS2 audience: Which AI assignment experiences best communicate the techniques, potentials, and challenges of the discipline? If you could offer a single assignment to attract the next generation of AI practitioners, which would it be?
· Emerging topics: When a new algorithm has high impact in a research area, there is a need to introduce the algorithm not only to students, but to all AI researchers as well. The creation of initial high-quality exercises to teach such groundbreaking techniques can accelerate research advancements and keep AI material fresh at all levels. Which emerging topic(s) are most in need of excellent tutorial materials?
Whether sharing the best of your time-tested assignment designs or offering a timely new creation, please consider how your creative assignment ideas can attract and prepare the next generation of AI researchers or accelerate the advancement of the current generation.
See http://modelai.gettysburg.edu/ for more information and detailed submission instructions.