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NSFDirectorate for Computer and Information Science and Engineering

RET Site: Biologically Inspired Computing Models, Systems, and Applications

Active
Institution
University of Notre Dame, IN
Principal investigator
Michael T Niemier
Funding
$599K
Duration
2023–2027
Open portfolio

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Abstract

This award renews a Research Experience for Teachers site at the University of Notre Dame. The site will form partnerships between Notre Dame computer science students and faculty, Notre Dame students in pre-service education programs, and teachers from elementary and middle schools in the greater South Bend area. During the summer, teacher participants will work on research projects focusing on the advances, capabilities, and challenges associated with machine learning (ML) / artificial intelligence (AI) algorithms that are currently driving efforts across the technology, manufacturing, and government sectors. To translate their research experience into the classroom, teacher participants will develop new curricular materials that focus on the mathematical techniques at the heart of many applications students already use on a daily basis (e.g., ML algorithms that draw boxes around individual faces when using an smartphone camera) and the ethical implications of such technologies. These materials will address newly released computer science standards from the Indiana Department of Education and be shared at the local, state, and national levels. Through this RET site experience, teachers will gain tools to introduce and prepare future generations of students to understand and develop ML/AI software and systems. The Computing RET site will recruit teacher cohorts from elementary and middle schools in the greater South Bend area, as well as several local colleges that partner with area school districts to form in-service/pre-service student teacher partnerships. A specific aim is to pair pre-service teachers with the in-service teacher with whom they will complete their student teaching assignment. Selected participants will work with ND faculty and students for seven weeks during the summer on an appropriately tailored, ML/AI-centric research project. Teachers will also be supported by professional development activities that include but are not limited to (1) strategies for translating research into the classroom, (2) presentations that introduce participants to the technical state-of-the-art with respect to ML/AI hardware and software, (3) the ethical challenges posed by ML/AI systems, etc. Developed materials will be shared through multiple channels including a Computer Science Teachers Association (CSTA) regional chapter, and online repositories such as the CSTA or TeachEngineering.org. RET personnel will also engage with educational foundations in local school districts that aim to broadcast developed materials district-wide. Summer activities will be complemented by extensive, post-program follow-up activities that share an overarching theme of helping RET participants provide their students with context about the scientific background and motivation for a module objective. Notre Dame personnel and in-service teachers will also work with pre-service teachers to discuss strategies and best-practices for integrating STEM into “day-to-day” lessons, how to engage diverse groups of students with said content, etc. Post-program engagements will ensure the translation of lab experiences into classroom practice, and to foster and strengthen long-term partnership between engineering faculty and the local school districts. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Research team

  • Michael T NiemierPI
  • Kevin W BowyerCo-PI
  • Gina N SvarovskyCo-PI

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Directorate for Computer and Information Science and EngineeringRES EXP FOR TEACHERS(RET)-SITERET SITE-Res Exp for Tchr Siteteachersteacherdistrictsretpre-serviceschool districtsret sitein-service

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