Artificial Intelligence and Learning: NSF ITEST Projects At-A-Glance

Artificial Intelligence and Learning: NSF ITEST Projects At-A-Glance

DESCRIPTION

Artificial intelligence (AI) is permeating the world around us, changing the ways we live, work, and learn. The National Science Foundation (NSF) lists AI as one of its organization-wide priorities, and is encouraging programs like ITEST to pursue what it means to prepare youth for careers in AI. In response to this, the STELAR convened an AI working group comprised of more than 20 projects funded through a variety of NSF programs. This paper is designed to highlight the areas being explored by these projects, to provide an overview of what has been funded within the ITEST portfolio to date, and to inspire others to join these research efforts. STELAR thanks the AI Working Group, listed below, for their contributions and expertise:

Innovative Technology Experiences for Students and Teachers (ITEST)

  • Tiffany Barnes, North Carolina State University
  • Kristy Boyer, University of Florida
  • Jie Chao, Concord Consortium
  • Sylvia Celedón-Pattichis, University of New Mexico
  • Christina Gardner-McCune, University of Florida
  • Shuchi Grover, Looking Glass Ventures
  • Suren Jayasuriya, Arizona State University
  • Irene Lee, Massachusetts Institute of Technology
  • Carlos López Leiva, University of New Mexico
  • Marios Pattichis, University of New Mexico
  • Ramana Pidaparti, University of Georgia
  • Elisabeth Soep, YR Media
  • David Touretzky, Carnegie-Mellon University
  • Mark Weckel, American Museum of Natural History
  • Helen Zhang, Boston College

Advancing Informal STEM Learning (AISL)

  • Mark Warschauer, UC Irvine
  • Secure and Trustworthy Cyberspace
  • Lin Lin, University of North Texas

STEM + Computing K–12 Education (STEM+C)

  • Gautam Biswas, Vanderbilt University
  • Kayla DesPortes, New York University
  • Krista Glazewwski, Indiana University
  • James Lester, North Carolina State University
  • Ben Shapiro, University of Colorado, Boulder
  • Ning Wang, University of Southern California
  • Tom Yeh, University of Colorado at Boulder

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Artificial Intelligence

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2022