Hot Spots and Insights in the International Research Field of Multimodal Learning Analytics: Data Visualization and Analysis Based on CiteSpace

Multimodal Learning Analytics (MLA) is able to comprehensively utilize the multimodal data generated by learners during the learning process to provide in-depth understanding and evaluation of learning behaviors, cognitive processes and affective states. This study focuses on 403 articles in the core dataset of the Web of Science (WoS) database on the topic of “Multimodal Learning Analytics” as the sample for analysis. CiteSpace 6.2.R6 software was used to perform multidimensional cluster analysis, including keyword citation frequency analysis, emergence analysis, centrality analysis, keyword co-occurrence mapping analysis, and timeline view analysis. According to the results of the visual analysis of bibliometrics, the English classic literature was screened for review, and at the same time, closely combining with the current research status of multimodal learning analysis in China, we refined the three revelations of future research hotspots within the territory, which enriches the theoretical framework of multimodal learning analysis to a certain extent, and provides valuable reference basis and direction guidance for the localized research in China.