The Research Trends on the Multiple Representation Learning Model, A Systematic Review (2016-2025)

Research Trends on the Multiple Representation Learning Model

Abstract

This study aims to identify and analyze research trends on multi-representational learning models in science education during the period 2016-2025 through a systematic review approach. Data were collected from the Dimensions.ai and Google Scholar databases, then analyzed using PoP and VOSviewer software to reveal publication patterns, types of publications, and collaboration networks between researchers. The results show a significant increase in the number of publications, dominated by journal articles, followed by conference proceedings and research reports. Bibliometric analysis reveals increasingly close collaboration networks, especially in Asia and Europe, which strengthen the development of multi-representational learning theories and practices. The main research topics include the effectiveness of models in improving understanding of science concepts, technology integration, and the development of multi-representational-based learning media. These findings emphasize the important role of multi-representational learning models in improving the quality of science learning through various forms of visual, verbal, and symbolic representations. This study provides a strong foundation for the development of innovative and adaptive learning practices and recommends further research in various contexts and levels of education.