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http://dx.doi.org/10.14352/jkaie.2021.25.6.1015

The Development of Interactive Artificial Intelligence Blocks for Image Classification  

Park, Youngki (Department of Computer Education, Chuncheon National University of Education)
Shin, Youhyun (Department of Computer Science and Engineering, Incheon National University)
Publication Information
Journal of The Korean Association of Information Education / v.25, no.6, 2021 , pp. 1015-1024 More about this Journal
Abstract
There are various educational programming environments in which students can train artificial intelligence (AI) using block-based programming languages, such as Entry, Machine Learning for Kids, and Teachable Machine. However, these programming environments are designed so that students can train AI through a separate menu, and then use the trained model in the code editor. These approaches have the advantage that students can check the training process more intuitively, but there is also the disadvantage that both the training menu and the code editor must be used. In this paper, we present a novel artificial intelligence block that can perform both AI training and programming in the code editor. While this AI block is presented as a Scratch block, the training process is performed through a Python server. We describe the blocks in detail through the process of training a model to classify a blue pen and a red pen, and a model to classify a dental mask and a KF94 mask. Also, we experimentally show that our approach is not significantly different from Teachable Machine in terms of performance.
Keywords
Artificial Intelligence; Scratch; Python; Interactive Blocks; Image Classification;
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