2026
AAAI
AAAI 2026
Model AI Assignments 2026
Abstract
Abstract The Model AI Assignments session seeks to gather and disseminate the best assignment designs of the Artificial Intelligence (AI) Education community. Recognizing that assignments form the core of student learning experience, we here present abstracts of eight AI assignments from the 2026 session that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs. Assignment specifications and supporting resources may be found at \url{http://modelai.gettysburg.edu}.
👥
Mega-Team
— 23 authors
🧭
Keyword Pioneer
— pedagogical tool
🐝
Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Robotics
Authors
Todd W. Neller
,
Steve Geinitz
,
Kevin Wang
,
Zach Dodds
,
Nicholas Dodds
,
Ryan O Connor
,
Aimen Taha
,
Ananta Manoranjan
,
Saurabh Ray
,
Deepak Ajwani
,
Fang Sun
,
Paul Zhang
,
Pranav Subbaraman
,
Yizhou Sun
,
Lisa Dunlap
,
Taehan Kim
,
Deena Sun
,
Ishir Garg
,
Mark Ogata
,
Aakarsh Vermani
,
Narges Norouzi
,
Joseph Gonzalez
,
Varada Kolhatkar