This Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides USD 427,056 to The Regents of the University of Colorado, doing business as the University of Colorado Office of Contracts and Grants Division, to conduct research on enhancing the future of teacher practice through AI-enabled formative feedback for job-embedded learning. The primary goals are to: 1) Work with teachers to design and refine automated feedback systems, 2) Enhance the...
This $349,999 Project Grant award from the National Science Foundation (NSF) STEM Education program (CFDA 47.076) will support a research project at the University of North Carolina at Chapel Hill (UNC-CH) to investigate how to design and integrate artificial intelligence (AI) to support equitable K-12 science education. The project plans to explore the use of multimodal AI to provide automated feedback for formative science assessments, with the goal of generating design principles to develop...
The National Science Foundation (NSF) awarded a $900,000 Project Grant under its STEM Education (CFDA 47.076) program to Northeastern University. The grant, awarded on November 1, 2024, supports the development of an "AI-Empowered Reflective Learning" tool that aims to deepen and accelerate learning through the use of AI-supported prompts and feedback across different interaction contexts, including digital learning environments, virtual reality simulations, and augmented reality...
The National Science Foundation (NSF) awarded The Leland Stanford Junior University (doing business as Stanford University) a $200,000 Project Grant under the STEM Education (CFDA 47.076) program. The goal of this "RAPID" project is to understand how instructional coaches can implement AI-based teacher feedback tools to help teachers, especially those in resource-poor schools, integrate AI technologies into their classrooms. The project will involve interviewing coaches, developing...
This $1.7 million project grant from the National Science Foundation's STEM Education program (CFDA 47.076) will fund the development of a novel AI-powered student support system to improve metacognitive calibration skills at the University of Illinois from August 2022 to July 2025. The project aims to research methods for enhancing students' ability to accurately estimate their own level of knowledge using short, personalized training exercises delivered through a decentralized AI framework....
This Project Grant award of $298,375.00 from the National Science Foundation's (NSF) Division of Undergraduate Education STEM Education (CFDA 47.076) program aims to design and implement an artificial intelligence (AI)-augmented formative assessment and feedback system. The system will support the development of STEM text summarization and problem-solving skills among students in large, introductory undergraduate physics courses at an urban university serving diverse and underrepresented student...
This $299,997 Project Grant award, funded by the National Science Foundation's (NSF) STEM Education program (CFDA 47.076), is supporting the development of an AI-powered, app-based platform to deliver targeted instructional feedback and professional development to early childhood educators. The research team at the University of Notre Dame, the grant recipient, is collaborating with early education teachers to co-design the platform, which aims to provide timely feedback on teachers' shared book...
The National Science Foundation (NSF) awarded a $1,999,680 Project Grant under its STEM Education (CFDA 47.076) program to the University of Southern California (USC) to develop an "Intelligent, Adaptive Program with Just-in-Time Feedback for Preservice Teachers." This program aims to improve preservice teachers' evidence-based teaching practices, mathematical content knowledge, pedagogical content knowledge, and teaching skills related to ratios and proportional relationships...
This $199,503 Project Grant awarded by the National Science Foundation (NSF) under the STEM Education (CFDA 47.076) program will fund a large-scale, mixed-methods study to understand perceptions and use of artificial intelligence (AI) technologies in K-12 education. The one-year project will survey a nationally representative sample of parents, teachers, and youth to identify opportunities, risks, and supports needed for integrating AI-driven learning tools. The study will employ both...
This National Science Foundation (NSF) STEM Education (CFDA 47.076) Project Grant award provides $749,996 to the University of Florida to develop an innovative artificial intelligence model that can provide feedback on student proofs in proof-oriented mathematics courses. The project aims to improve the proof-writing abilities of undergraduate students by training the AI model to give immediate, iterative, research-based feedback on student proofs. The project involves sub-awards to St. Olaf...
The National Science Foundation (NSF) awarded a $250,000 Project Grant under the STEM Education program (CFDA 47.076) to the University of Pittsburgh to conduct collaborative research on enhancing teacher professional learning through AI-enabled formative feedback systems. The project, titled "Collaborative Research [FW-HTF-RL]: Enhancing the Future of Teacher Practice via AI-Enabled Formative Feedback for Job-Embedded Learning", will work with teachers to co-design and test automated feedback mechanisms that aim to drive professional development and improve student outcomes in middle and high school English/language arts classrooms. The research will focus on comparing the effectiveness of evaluative versus non-evaluative feedback models. The project will leverage the expertise of industry partner Teachfx, Inc., which will receive a sub-award, to develop robust, fair, and interpretable feedback algorithms based on classroom observation data. The findings from this multidisciplinary research effort are expected to generate a blueprint for leveraging technology to provide efficient and effective professional feedback, ultimately enhancing STEM teaching and learning.