Instructional Materials Based on Generative Learning Models in Context of Science and Physics Learning: A Bibliometric Analysis

Abstract

Developing instructional materials based on the generative learning model has become critical in science and physics education. However, a systematic analysis of research trends in this domain must be more conspicuously present. This study aims to conduct an in-depth analysis of research investigating the impact of generative learning model-based instructional materials in science and physics education, encompassing their classification and trends and identifying potential research variables for future scholarly investigations. The methodological approach employed a literature review utilizing bibliometric analysis, initiating with the definition of keywords “generative learning model” and “journal” within the Publish or Perish application and using Google Scholar as the primary database. A systematic filtering process was applied to the search results, identifying 10 pertinent articles within the “Science and Physics” domain from an initial pool of 200 publications. Researchers utilized Mendeley and Vosviewer to compile metadata and visualize research trends. Findings indicated that research on generative learning models in science and physics clusters into two primary categories: generative learning models, conventional learning approaches, learning outcomes, population characteristics, and pedagogical influences. However, this study’s limitations, stemming from the restricted article sample, underscore the need for future research to explore a broader range of topics.