Abstract: Visual programming languages make programming more accessible for novices, which open more opportunities to innovate and develop problem-solving skills. Besides, deep learning is one of the trending computer science fields that has a profound impact on our daily life, and it is important that young people are aware of how our world works. In this study, we partially attribute the difficulties novices face in building deep learning models to the used programming language. This paper presents DeepScratch, a new programming language extension to Scratch that provides powerful language elements to facilitate building and learning about deep learning models. We present the implementation process of DeepScratch, and explain the syntactical definition and the lexical definition of the extended vocabulary. DeepScratch provides two options to implement deep learning models: training a neural network based on built-in datasets and using pre-trained deep learning models. The two options are provided to serve different age groups and educational levels. The preliminary evaluation shows the usability and the effectiveness of this extension as a tool for kids to learn about deep learning.

Nora Alturayeif, Nouf Alturaief and Zainab Alhathloul, “DeepScratch: Scratch Programming Language Extension for Deep Learning Education” International Journal of Advanced Computer Science and Applications(IJACSA), 11(7), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110777

@article{Alturayeif2020,
title = {DeepScratch: Scratch Programming Language Extension for Deep Learning Education},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110777},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110777},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {7},
author = {Nora Alturayeif and Nouf Alturaief and Zainab Alhathloul}
}