Local learning trajectory with multimodal approach through mathematical transfer: Bibliometric analysis 2015 – 2025

The fundamental challenge in analyzing learning trajectory in geometry learning using mathematical transfer needs to be done. The problem of geometry learning focuses on the condition of students who often have difficulty constructing conceptual understanding and connecting it with various mathematical representations. This study aims to comprehensively analyze research trends on local learning trajectories with a multimodal approach through mathematical transfer in the time span of 2015 to 2025. Research questions are 1) What are the annual publication trends related to local learning trajectories using a multimodal approach through mathematical transfer from 2015 to 2025, based on data from Scopus, 2) Who are the most influential country and journals, and the research trend in this field? The method used is bibliometric analysis with the help of Biblioshiny to map publication trends, identify research gaps, and find keywords and topics that have not been widely explored. The data for this study will be analyzed using bibliometric methods, involving the identification of publication trends, collaboration networks, and thematic clusters of relevant from relevant articles sourced from Scopus databases between 2015 and 2025 using 221 documents. The results of the research novelty search are Publications on local learning trajectories with multimodal approaches and mathematical transfer increased rapidly from 2020 to 2022, according to Scopus data. The United States and the United Kingdom were major contributors, and journals such as the Journal of Mathematical Behavior became important platforms. Overall, this study highlights the growing interest in adaptive learning trajectory models and learning technologies, providing guidance for future educational research and practice