PRG AI Blocks
Our AI blocks are a suite of drag-and-drop coding blocks that allow student to integrate machine learning models, robotics, and other AI engines into their projects. We develop these blocks on a forked version of the open source Scratch Blocks repository. We typically associate these blocks with specific AI curricula, but they can also be used in a standalone manner.
Access live versions of the extensions using the links below:
- Affectiva (Scratch 2)
- Arduino Robot: Scratch 2 | Scratch 3 | Firmware download | Chrome extension
- micro:bit robot: Scratch 3 | Firmware download
- PoseBlocks (Scratch 3)
- Speech-to-Text and Text-to-Speech: Scratch 2 | Scratch 3
- Teachable Machine (Scratch 3) English | Español
- Text Classifier (Scratch 3): English | Español
Resources
Scratch 2 Github Repo Scratch 3 Github Repo
Team
Randi Williams
Personal Robots Group, MIT Media Lab
Brian Jordan
Personal Robots Group, MIT Media Lab
Nisha Devasia
Personal Robots Group, MIT Media Lab
Tejal Reddy
UROP, MIT
Pablo Alejo
UROP, MIT
Publications
Jordan, B., Devasia, N., Hong, J., Williams, R., & Breazeal, C (2021). PoseBlocks: A Toolkit For Creating (And Dancing) With AI. Proceedings Of The 10th Symposium On Education Advances In Artificial Intelligence (EAAI ’21). Reddy, T., Williams, R., & Breazeal, C. (2021). Text Classification For AI Education. Proceedings Of The 52nd ACM Technical Symposium On Computer Science Education (SIGCSE’21).