Мультимодальная учебная аналитика: библиометрический и онтологический анализ

Образование и наука. 2025. Т. 27. № 7. С. 33–71.

Patarakin Y., Kutuzov A., Dvoretskaya I.

Abstract. Introduction. Multimodal Learning Analytics (MMLA) is an emerging research domain in education that has been gaining global attention. The relevance of this approach lies in its potential to provide a more comprehensive and accurate understanding of learning processes by integrating various data types, including digital, physical, physiological, psychological, psychometric, and environmental data. MMLA serves as a foundation for developing recommender systems and adaptive environments that account for the multi-layered and multimodal nature of learning activities and provide meaningful and detailed feedback to participants in the educational process. Purpose. This article aims to move beyond descriptive analysis of current practices towards a structural understanding of the entities and relationships shaping the MMLA research landscape. It not only clarifies the boundaries of MMLA as a scientific field but also contributes to identifying latent areas of potential application including collaborative learning. Methodology and Methods. The bibliometric analysis allowed us to trace the major developmental milestones of MMLA from its emergence to the present day. Key research groups were identified, along with their thematic focuses and preferred data sources. Dominant research themes were extracted, and their evolution over time was analyzed. Shifts in research interests were found to reflect a transition from the analysis of individual learning trajectories to the study of group dynamics within collaborative learning contexts - an especially promising direction in light of the increasing emphasis on teamwork and cooperation in education. The study also explored the application of MMLA to various forms of collective learning activity, such as collaborative problem solving, group-based tasks, and project-based learning. Ontological modeling of the field enabled the identification of existing conceptual spaces and methodological approaches, as well as the projection of emerging directions. Practical Significance. The findings can inform the design of learning environments aimed at fostering communication, collaboration, and teamwork skills, including interdisciplinary educational contexts.

Keywords: библиометрический анализ, bibliometric analysis, ACM, VOSviewer, ACM, multimodal learning analytics, collaborative analytics, Zotero, fractal matrix tables, мультимодальная учебная аналитика, коллаборативная аналитика, Zotero, веерная матрица