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Development and Instructional Application of a Public Data-Based Population Prediction Simulator and Its Effects on Elementary Students’ Understanding of Population Change and Computational Thinking

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2026, 31(6), pp.243~254
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : April 9, 2026
  • Accepted : June 1, 2026
  • Published : June 30, 2026

Han-Bin Lee 1 Kwi-hoon Kim ORD ID 1

1한국교원대학교

Accredited

ABSTRACT

This study aims to develop a public data-based population prediction simulator for upper elementary students and to design an instructional model using it. Population issues such as low birth rate, aging society, and regional depopulation require social understanding as well as data-based interpretation and prediction competence. To address this, this study proposes an approach integrating public population data, AI-based prediction, and simulation-centered inquiry. The simulator, developed using KOSIS data, provides regression-based prediction and visualization of future population changes, and a ten-session instructional model was designed based on the ASSURE framework. The study examines the effects of instruction on students’ understanding of population change, data literacy, computational thinking, and problem-solving competence, and presents a model linking AI education with social issues.

Citation status

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