Trends of Computer Models Used in Science Learning: Systematic Literature Network Analysis

Abstract

This study aims to describe research trends related to computer models. The method used is Systematic Literature Network Analysis (SLNA). The research data consists of articles on computer models without time limit, which are taken from the Scopus database, including IEEE, Springer, and the Publish or Perish (PoP) application. There were 1161 articles found up to 2024. After filtering by title, the number of articles was reduced to 265 articles, then filtering by keywords and other criteria obtained 32 articles for further analysis. The analysis results show fluctuations in the number of articles and the number of citations each year. Topics that often appear in discussing computer models or other visual media are simulations, videos, games, and most recently deep learning models. Future research can focus on the use of computer models as a tool in science learning models that can explain phenomena that occur in everyday life.