Automated feedback for student-made protein models using phones and AI
Official title: Harnessing Machine Learning & Object Detection for Automated Evaluation of Student-folded Protein Models
Funded at 3d Molecular Designs · NIH-11183303 · Data updated 2026-11-12
A smartphone app uses AI to give students and teachers immediate feedback on their student-made protein models created with flexible foam tools.
Quick facts
| Grant type | Sbir 2 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | 3d Molecular Designs NIH-funded |
| Lab location | 1 site (Milwaukee, United States) |
| Project start | August 1, 2024 |
| Project end | July 31, 2028 |
| Funding year | 2026 |
| Award (this year) | $1,004,963 |
| NIH project number | 2R44GM154526-02 |
| Project ID | NIH-11183303 on NIH RePORTER |
Who could benefit from this research
✓Could help
Not applicable to patients; research focuses on educational tools for science learners and educators.
✕Less likely to help
This grant does not involve patients or patient care.
What this research studies
This project will develop and publish smartphone apps that use machine learning and object detection to analyze free-form protein models made by students. The goal is to provide real-time feedback on shape accuracy, secondary structures, and other features, helping educators guide learning more efficiently. The work combines education, software development, and AI imaging to support biology classrooms and outreach programs.
Why it matters
Potential benefit: If successful, students will receive fast, actionable feedback that can improve understanding of protein structure and science concepts.
How similar studies have gone: AI-based assessment and feedback for educational models is an emerging area with promising early results.
Where this research is happening
-
3d Molecular Designs
Milwaukee, United States Active
Researchers
- Principal investigator: Ryan, Heather Noelle — 3d Molecular Designs
- Study coordinator: Ryan, Heather Noelle
Related research
Other NIH-funded projects on the same topics.
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Using machine learning to improve protein modeling education
This study is all about making learning about proteins more fun and effective for students by using cool digital tools that give instant feedback on their protein models, helping them see and fix mistakes right away.
-
Preparing teachers for future pandemics through hands-on science education
This study is all about helping high school science teachers learn more about infectious diseases and new technologies, so they can teach their students better using fun, hands-on tools like 3D-printed protein models.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.