Block-based Programming Learning Tool for ML and AI Education (Work in Progress)

This work presents a prototype of a learning tool that was developed to remedy current challenges and issues in the field of block-based programming for ML and AI education. Based on recent research strengths and weaknesses of current solutions were identified. Most of tools don't follow defined guidelines, don't meet certain requirements, or they neglect important points such as simple design or manageable black-box consideration. Based on these and other criteria we developed a block-based programming learning tool prototype that consists of three different learning games about supervised and reinforcement learning. Unsupervised learning might be included in further steps. The tool provides an introduction to algorithms such as decision trees, image classification, and agent based systems. These were identified as common algorithms to be taught in the area of ML and AI. Finally, we talk about current and expected results of this work. First study shows that the prototype we developed made a noticeable impact for programming newbies. Furthermore, younger people seem to enjoy using the block-based tool more than the older ones. The main goal of this work is to create a block-based programming environment that represents complex ML and AI concepts in a simplified way and makes them tangible for the students.