Human Learning is an application whose objective is to facilitate learning of abstraction by matching images. There are two main aspects to the application: learning on a dataset and managing datasets. Traditionnaly one would use this learning methods with printed images, but this takes a lot of time to prepare and update. Here you can do all of this digitally.
The application's database is organized in datasets who contain categories. Pictures are assigned to categories and each category has a picture which is set as its representative.
To compile the code from source you need to put the cleartext copy of the build secrets at the root of the repository. Please contact the development team to get access to them.
If you want to run the unit tests you need to first run the Firebase emulators:
firebase init
, everything is already setup in the project. You only have to do firebase login
.firebase emulators:start --import ./firestore_state_windows
or firebase emulators:start --import ./firestore_state_linux
from within the root directory of the project before running any tests (including through gradle)A special thank you to Sandy Ghelfi for designing the logo of our app.