Model AI Assignments 2023

Authors

  • Todd W. Neller Gettysburg College
  • Raechel Walker Massachusetts Institute of Technology
  • Olivia Dias Massachusetts Institute of Technology
  • Zeynep Yalçın Wellesley College
  • Cynthia Breazeal Massachusetts Institute of Technology
  • Matt Taylor Massachusetts Institute of Technology
  • Michele Donini Amazon Web Services
  • Erin J. Talvitie Harvey Mudd College
  • Charlie Pilgrim The University of Warwick
  • Paolo Turrini The University of Warwick
  • James Maher United States Air Force Academy
  • Matthew Boutell United States Air Force Academy
  • Justin Wilson United States Air Force Academy
  • Narges Norouzi University of California, Santa Cruz
  • Jonathan Scott University of California, Santa Cruz

DOI:

https://doi.org/10.1609/aaai.v37i13.26913

Keywords:

MAIA

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 six AI assignments from the 2023 session that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs. Assignment specifications and supporting resources may be found at http://modelai.gettysburg.edu .
AAAI-23 Proceedings Cover

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Published

2024-07-15

How to Cite

Neller, T. W., Walker, R., Dias, O., Yalçın, Z., Breazeal, C., Taylor, M., Donini, M., Talvitie, E. J., Pilgrim, C., Turrini, P., Maher, J., Boutell, M., Wilson, J., Norouzi, N., & Scott, J. (2024). Model AI Assignments 2023. Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 16104-16105. https://doi.org/10.1609/aaai.v37i13.26913

Issue

Vol. 37 No. 13: AAAI-23 Special Programs, IAAI-23, EAAI-23, Student Papers and Demonstrations

Section

EAAI Symposium: Model AI Assignment Abstracts