A Block-Based Interactive Programming Environment for Large-Scale Machine Learning Education

The existing block-based machine learning educational environments have a drawback in that they do not support model training based on large-scale data. This makes it difficult for young students to learn the importance of large amounts of data when creating machine learning models. In this paper, w...

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Vydané v:Applied sciences Ročník 12; číslo 24; s. 13008
Hlavní autori: Park, Youngki, Shin, Youhyun
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 01.12.2022
Predmet:
Education
K-12 education
large-scale training
Machine learning
natural language processing
Programming languages
Scratch
Secondary school students
Secondary schools
Tooee
ISSN:2076-3417, 2076-3417
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Shrnutí:The existing block-based machine learning educational environments have a drawback in that they do not support model training based on large-scale data. This makes it difficult for young students to learn the importance of large amounts of data when creating machine learning models. In this paper, we present a novel programming environment in which students can easily train machine learning models based on large-scale data using a block-based programming language. We redefine the interfaces of existing machine learning blocks and also develop an effective model training algorithm suitable for block-based programming languages to enable “instant training” and “large-scale training”. As example educational applications based on this environment, we presented what is termed a “Question-Answering Chatbot” program trained on 11,822 text data instances with 7784 classes as well as a “Celebrity Look-Alike” program trained on 4431 image data instances with 7 classes. The experimental results show that teachers and pre-service teachers give high scores on all four evaluation measures for this environment.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:2076-3417
2076-3417
DOI:10.3390/app122413008