Analyzing research connections in the development of systems thinking for science problem solving: A systematic literature network analysis (SLNA) approach

Abstract

This study investigates the emerging trends and research opportunities focused on promoting systems thinking within the context of scientific problem-solving. To facilitate this exploration, the research employs the Systematic Literature Network Analysis (SLNA) method. This study is based on the analysis of scientific articles related to systems thinking in science education, collected from the Scopus database of science direct from 2020-2024. Initially, a total of 7,512 relevant articles were retrieved, then 1,000 were successfully retrieved, but through the removal of duplicates and non-journal sources, a more accurate data set was created. Following a preliminary screening process based on article titles, the dataset was narrowed down to 250 articles. Further refinement involved keyword searches and specific inclusion criteria, which culminated in the selection of 9 articles for comprehensive analysis. The most frequently discussed topics include "system thinking," with strong connections to other concepts such as problem-solving strategies and inquiry-based learning. While research on system thinking in science education is well-established, there are still underexplored areas, such as the development of innovative teaching models that integrate system thinking facilitation. Future research could focus on developing innovative instructional models that incorporate strategies to facilitate system thinking, offering new ways to enhance students' ability to approach complex science problems.