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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:

  1. Affectiva (Scratch 2)
  2. Arduino Robot: Scratch 2 | Scratch 3 | Firmware download | Chrome extension
  3. micro:bit robot: Scratch 3 | Firmware download
  4. PoseBlocks (Scratch 3)
  5. Speech-to-Text and Text-to-Speech: Scratch 2 | Scratch 3
  6. Teachable Machine (Scratch 3) English | Español
  7. 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).