• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.395-396
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• 2022

본 논문에서는 블록 프로그래밍 언어를 선행조직자로 하여 텍스트 프로그래밍 언어를 학습하는 도구 활용 전략을 연구하였다. 텍스트 프로그래밍 언어는 파이썬이며, 블록 프로그래밍 언어는 엔트리, 활용하는 도구는 주피터 노트북으로 선정하였다. 주피터 노트북을 활용한 블록 프로그래밍 언어 선행조직자 학습 전략은 code cell에 IPython.display.IFrame 클래스를 활용하여 결과 창에 엔트리 작업환경을 불러와 선행조직자로 제시하여 엔트리를 학습 후 code cell에서 파이썬으로 학습한다. 주피터 노트북을 통해 블록 프로그래밍 언어를 선행조직자로 제시 후 텍스트 프로그래밍 언어를 제시함으로써 텍스트 프로그래밍 언어를 학습할 때 인지적 부담을 줄어들고 긍정적 전이가 일어나 효과적인 학습이 될 것으로 기대된다.

• Journal of The Korean Association of Information Education
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• v.25 no.4
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• pp.603-610
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• 2021

As part of recent SW education methods, entry sites have been used in all practical textbooks in elementary schools. However, they are all learning block-type programming languages, making it difficult to produce programs that can be used in everyday life. This study is a study on the effects of learning programming using entry python on logical thinking ability and programming interest in elementary school students. Logical thinking ability and programming interest tests were conducted before and after the 8th class. Before and after classes, logical thinking ability score rose from an average of 6.6 to 9.4 and programming interests score also rose from an average of 46.7 to 59.1. This results in programming learning using Entry Python is significant for enhancing the logical thinking ability and programming interest of elementary school students.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.1015-1024
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• 2021

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.