Click here if you wish to read this and the AI guide in a language other than English.
The eCraft2Learn project is developing a set of extensions to the Snap! programming language to enable children (and non-expert programmers) to build AI programs. You can use all the AI blocks after importing this file into Snap! or Snap4Arduino. Or you can see examples of using these blocks inside this Snap! project.
A guide that describes the extensions, projects, and the larger context currently consists of five chapters:
|Adding speaking to your programs||Speech synthesis requires only speakers or earphones|
|Adding listening to your programs||Speech recognition requires a microphone (builtin or connected to a USB port)|
|Adding image recognition to your programs||Requires a camera (builtin or connected to a USB port) and registering to get API keys|
|Adding machine learning to your programs||Many examples rely upon a camera. It is very slow unless your device has a GPU.|
|Working with words and language New!||No special hardware requirements|
The paper AI Programming by Children by Ken Kahn and Niall Winters describes this work and was published in the Proceedings of the Constructionism 2018 Conference. AI Programming by Children using Snap! Block Programming in a Developing Country by Ken Kahn, Rani Megasari, Erna Piantari and Enjun Junaeti was published at the EC-TEL 2018 conference and describes workshops with high school students in Indonesia using these AI blocks. An early version of the AI extension to Snap! is described in the paper Child-friendly Programming Interfaces to AI Cloud Services also by Ken Kahn and Niall Winters.
The following demonstration programs use the AI Snap! blocks. They run best in the Chrome browser.
We have collected some projects by students who have used these AI blocks.
Send email to Ken Kahn (email@example.com) if you encounter problems or have questions.
Nearly all modern computers have a GPU. Without one or with a very primitive one programs using machine learning may run very slow. For example, the image machine learning commands run very slowly on Raspberry Pis. The audio training primitives, however, do run well on Raspberry Pis.
You can import this file into your existing or new projects. The AI blocks can then be found in the Snap! palette under , , or .