Journal of Information Processing
Online ISSN : 1882-6652
ISSN-L : 1882-6652
 
Connect DB: An Online Learning System for Data Analysis
Tomonari KishimotoYuki HondaKosuke UrushiharaMaiko ShimabukuSusumu Kanemune
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ジャーナル フリー

2024 年 32 巻 p. 150-158

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In Japan, data analysis has become an important part of the ‘Informatics’ subject in high schools. Data analysis is also becoming increasingly important at universities due to the promotion of ‘Mathematical, Data Science, and AI Education Programs’ and other programs. Students learn how to manipulate statistical processing and graph drawing using the computer. We therefore developed a system called ‘Connect DB’ that has an easy-to-learn operation system and supports learning data analysis. This system supports learners in learning data analysis, such as collecting, organizing, and formatting data, by enabling them to analyze data with just a few mouse operations and by suggesting appropriate analysis methods based on the type of data. In addition, the system also provides sample data that can be used in classes to support teachers. This paper describes the design and implementation of the Connect DB data analysis learning system. By comparing the number of operations with spreadsheet software and analyzing the post-training questionnaire for university students and their operation logs, we confirmed that this system is easy to learn and that it can be used for practical training in data analysis.

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© 2024 by the Information Processing Society of Japan
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