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NSF FF: Planning: Reimagining Creative Computing with Pedagogical AI Code Assistance

Project: Research

Abstract & Details

Description

Award ID: 2627624

This FINDERS Foundry award helps students become more confident and thoughtful computer programmers. Many students use AI tools to write code, but they often accept the results without understanding how the code works or how to improve it. This project will design a creative coding tool where AI acts as a partner, not a replacement. The tool will encourage students to read, test, and change AIgenerated code so they build real skills. High school teachers, students, and families will help design the tool to make sure it supports creativity, responsibility, and clear learning goals. The platform will help students try new ideas, understand mistakes, and grow stronger coding habits. By giving students a safe and supportive place to explore coding with AI, the project hopes to prepare them for future classes, jobs, and opportunities in computer science. This FINDERS Foundry award collaboratively designs approaches for integrating Pedagogical Code Assistance (PCA) features into a creative coding environment to support highschoollevel programming. Technical design elements incorporate modelgrounded feedback, scaffolds for code interpretation, and structures that position AI as a collaborative partner rather than an automated answer provider guided by focus groups with teachers, students, and parents; development of early prototypes; and preliminary testing across two high school settings. The project documents how learners interact with AIgenerated suggestions and how PCA features can enhance conceptual understanding without diminishing problemsolving agency. The project results in responsibleuse guidelines for PCA implementation, wireframes for a full development proposal, and evidencebased insights into learnerAI interaction patterns. The resulting co-created framework demonstrates a responsible, instructionally aligned AIsupported coding environments that strengthens computational reasoning and enhances K12 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 date07/15/2611/30/26

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: 100%)

Technology Foci

  • Machine Learning Training Data
  • (confidence score: 96%)
  • Artificial Intelligence (excluding ML)
  • (confidence score: 100%)

Congressional District at Award

  • District n. 13 of New York

Current Congressional District

  • District n. 13 of New York

United States

  • New York

Core Based Statistical Area (CBSA)

  • New York-Newark-Jersey City, NY-NJ

County

  • County: New York, NY

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