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A.I. and the Future of STEM Instruction: Designing New Models to Automate Feedback to Teachers
Thu, April 21, 8:00 to 9:30am PDT (8:00 to 9:30am PDT), Marriott Marquis San Diego Marina, Floor: South Building, Level 1, Pacific Ballroom 18Session Type: Structured Poster Session
Abstract
The rapid development of artificial intelligence offers a critical design juncture for the future of K-12 STEM education. This structured poster session explores models for designing AI systems for promoting equitable teaching and learning. The presentations report on a range of emerging applications of AI ranging from smart dashboards, to adaptive assessment tools, to simulated teaching environments for professional development. With discussant commentary and multiple opportunities for participants to ask questions, we aim to promote a robust dialogue about designing AI technologies for STEM education and how to ensure that key stakeholders—such as students, educators, support staff and community members—are integrated into the design and deployment of these new technologies.
Sub Unit
Chairs
Joshua Littenberg-Tobias, Massachusetts Institute of Technology
Jim Bywater, James Madison University
Papers
From Avoidant to Aware: Automating Feedback in Simulations on Equity in Computer Science Education - Aria Eppinger; G.R. Marvez, Massachusetts Institute of Technology; Joshua Littenberg-Tobias, Massachusetts Institute of Technology; Garron Hillaire, Massachusetts Institute of Technology; Sydney Dell; Justin F. Reich, Massachusetts Institute of Technology
Calibrating an Automated Rater for Use With a Validated Observational Measure of Teacher Questioning - Jim Bywater, James Madison University; Jennifer L. Chiu, University of Virginia; Sarah Lilly, University of Virginia; Debajyoti Datta, University of Virginia; Maria Phillips, U.S. Air Force; Ginger S. Watson, University of Virginia; Don Brown, University of Virginia
Automated Teacher Feedback From a Game-Based Formative Assessment Targeting Data Science Concepts - Daisy Wise Rutstein, SRI International; Satabdi Basu, SRI International; Nathan Holbert, Teachers College, Columbia University; Matthew Berland, University of Wisconsin - Madison; Vishesh Kumar, University of Wisconsin - Madison
Designing a Teacher Dashboard to Support Multilingual Learners' Understanding of Science - Kihyun "Kelly" Ryoo, University of North Carolina - Chapel Hill; Emily Marie Decker, University of North Carolina - Chapel Hill
A Natural Language Processing–Driven Teacher Dashboard to Support Responsive Instruction - Libby F. Gerard, University of California - Berkeley; Sarah Bichler, University of California - Berkeley; Kelly R Billings, University of California - Berkeley; Allison Bradford, University of California - Berkeley; Marcia Linn, University of California - Berkeley
Teacher Noticing and Response to Students' Computational and Engineering Design Strategies - Nicole Hutchins, Vanderbilt University; Gautam Biswas, Vanderbilt University
Automated Collaboration Assessment Using Behavioral Analytics - Nonye Alozie; Anirudh Som
Developing Automated Feedback to Improve Teachers' Formative Assessment of Student Work in Technology-Enhanced Science Curricula - Trudi Lord; Hee-Sun Lee, Concord Consortium; Christopher Lore, The Concord Consortium; Amy R. Pallant, Concord Consortium
Methods of Comparing Teacher and Student Programming Behavior During Live Coding - Nicholas Lytle; Veronica Catete, North Carolina State University; Yihuan Dong; Mehak Maniktala; Danielle Cadieux Boulden, Code.org; Eric N. Wiebe, North Carolina State University; Tiffany Barnes