Skip to main navigation Skip to search Skip to main content

NSF FF: Planning: Ethical AI Game Creation Toolbox for ADHD Youth

Project: Research

Abstract & Details

Description

Award ID: 2627752

This FINDERS Foundry award supports the co-creation of an AI-enhanced toolbox for the development of digital games for teachers and their students with ADHD and other learning differences. Many students who think and learn in different ways have fewer chances to create games or use design tools. This project will strengthen participation in STEM by giving more students access to game design tools that are accessible, ethical, and supportive of student wellbeing. Families, educators, and students will codesign the prototype to make sure the experience encourages creativity, reflection, and confidence. The tools will help students express ideas, try new designs, and see themselves as creators. By making creative technology more inclusive, the project hopes to open new doors for youth and help them build STEM and AI skills that support longterm success. This FINDERS Foundry award aims to decrease barriers for students with learning differences to participate in STEM activities. The interdisciplinary team will design an AIenabled gamecreation toolbox that incorporates ethical AI frameworks and inclusive technology practices. The project will develop prototype workflows that embed reflective AI supports and operationalize models such that prioritizes flexible learning environments and children's well being. Technical efforts will focus on aligning gamecreation tools with responsible AI principles, identifying accessibility considerations, and integrating scaffolds that promote student agency and ethical engagement. Usability testing with teachers and families will generate qualitative and quantitative data on tool performance and instructional fit. Outputs will include prototype components, designevaluation insights, ethical reasoning, and learner autonomy. The work supports research AI literacy, creativity, and youth wellbeing. 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 date07/15/2611/30/26

Lead and Sub-Awardee Organization(s)

Active Fiscal Year

  • FY2027
  • FY2026

Start Fiscal Year

  • FY2026

TIP Programs

  • (FF) FINDERS FOUNDRY

Key Technology Areas

  • Artificial Intelligence
  • (confidence score: 98%)

Technology Foci

  • Machine Learning Training Data
  • (confidence score: 96%)
  • Artificial Intelligence (excluding ML)
  • (confidence score: 97%)

Congressional District at Award

  • District n. 18 of New York

Current Congressional District

  • District n. 18 of New York

United States

  • New York

Core Based Statistical Area (CBSA)

  • Kiryas Joel-Poughkeepsie-Newburgh, NY

County

  • County: Dutchess, NY

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