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

Huijae Park, Ja Mee Kim, Wongyu Lee

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number2223
JournalMathematics
Volume10
Issue number13
DOIs
Publication statusPublished - 2022 Jul 1

Keywords

  • computer education
  • leaner classification
  • log collection
  • programming education
  • Scratch

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Mathematics(all)
  • Engineering (miscellaneous)

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