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Development of CNN-Based Data Crawler to Support Learning Block Programming

Author

Listed:
  • HuiJae Park

    (Department of Computer Science and Engineering, Graduate School, Korea University, Seoul 136701, Korea)

  • JaMee Kim

    (Major of Computer Science Education, Graduate School of Education, Korea University, Seoul 136701, Korea)

  • WonGyu Lee

    (Department of Computer Science and Engineering, College of Informatics, Korea University, Seoul 136701, Korea)

Abstract

Along with the importance of digital literacy, the need for SW(Software) education is steadily emerging. Programming education in public education targets a variety of learners from elementary school to high school. This study was conducted for the purpose of judging the proficiency of low school-age learners in programming education. To achieve the goal, a tool to collect data on the entire programming learning process was developed, and a machine learning model was implemented to judge the proficiency of learners based on the collected data. As a result of determining the proficiency of 20 learners, the model developed through this study showed an average accuracy of approximately 75%. Through the development of programming-related data collection tools and programming proficiency judging models for low school-age learners, this study is meaningful in that it presents basic data for providing learner-tailored feedback.

Suggested Citation

  • HuiJae Park & JaMee Kim & WonGyu Lee, 2022. "Development of CNN-Based Data Crawler to Support Learning Block Programming," Mathematics, MDPI, vol. 10(13), pages 1-12, June.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:13:p:2223-:d:847585
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    References listed on IDEAS

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    2. Vinod Sharma Bhaugeerutty, 2021. "Difficulties in Learning and Teaching Programming at Lower Secondary Level in Mauritius," Journal of Contemporary Research in Social Sciences, Learning Gate, vol. 3(3), pages 48-61.
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