Skip to main navigation Skip to search Skip to main content

NSF FF: Planning: M-CONNECT: AI-Enabled Dashboard for Teachers and Families towards Supporting Student Motivation in Middle School Science

Project: Research

Abstract & Details

Description

Award ID: 2627536

This FINDERS Foundry award supports the creation of an AI-enabled dashboard that helps middleschool students stay engaged during science lessons by improving communication between teachers and families. Students often lose motivation as science becomes harder, and adults do not always know when support is needed. This project will design an AIenabled dashboard that shows realtime insights into how students are feeling and participating. The tool will help teachers notice changes in motivation and help families understand how to encourage their children at home. Codesigned sessions with teachers, parents, and students will guide the dashboard so it is clear, respectful, and helpful. By giving adults timely information, the project aims to help students stay confident, persistent, and connected during an important stage of their science education. This FINDERS Foundry award aims to translate students in-the-moment motivational experiences into meaningful insights through an integrated AI dashboard system. The dual integration features teacher and parentfacing views supported by an AIinterpretation layer that transforms studentfeedback data into actionable instructional insights. The project will investigate responsible datacollection and sharing practices, focusing on how motivational indicators can be presented in developmentally appropriate and pedagogically meaningful ways. Codesigned sessions with educators, students, and families will inform the creation of metrics, user requirements, and prototype interfaces aligned with science standards. Technical outputs will include wireframes, a feasibility memo, and early design principles that guide future development of scalable systems aimed at strengthening student motivation and broadening participation in STEM. The planning phase will lay the groundwork for a coherent, ethically grounded analytics platform that connects classroom and home learning. 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.

NSF Program Director: Lindsay Portnoy
StatusActive
Effective start/end date07/15/2609/30/26

Active Fiscal Year

  • FY2026

Start Fiscal Year

  • FY2026

TIP Programs

  • (FF) FINDERS FOUNDRY

Key Technology Areas

  • Artificial Intelligence
  • (confidence score: 95%)

Technology Foci

  • Machine Learning Training Data
  • (confidence score: 96%)
  • Artificial Intelligence (excluding ML)
  • (confidence score: 93%)

Congressional District at Award

  • District n. 01 of Nevada

Current Congressional District

  • District n. 01 of Nevada

United States

  • Nevada

Core Based Statistical Area (CBSA)

  • Las Vegas-Henderson-North Las Vegas, NV

County

  • County: Clark, NV

EPSCoR Jurisdiction

  • Yes

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint. Learn more about Elsevier's Fingerprint Engine here: https://beta.elsevier.com/products/elsevier-fingerprint-engine