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Multimodal learning analytics: a bibliometric and ontological analysis

https://doi.org/10.17853/1994-5639-2025-7-33-71

Abstract

Introduction. Multimodal Learning Analytics (MMLA) is an emerging research domain in education that has garnered global attention. Its significance lies in its potential to offer a more comprehensive and accurate understanding of learning processes by integrating diverse data types, including digital, physical, physiological, psychological, psychometric, and environmental data.

Aim. This research aims to move beyond a descriptive analysis of current practices to develop a structural understanding of the entities and relationships that constitute the research field. This involves refining the boundaries of MMLA as a scientific discipline to identify unexplored areas with potential applications. Particular attention is given to collaborative analytics, a promising area focused on studying data related to joint activities.

Methodology and research methods. Bibliometric analysis was employed as the primary method. Additionally, fractal matrix table analysis was used to gain an ontological understanding of the field.

Results and scientic novelty. The bibliometric analysis enabled the tracing of major developmental milestones in MMLA from its inception 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 analysed. Shifts in research interests revealed a transition from analysing individual learning trajectories to studying group dynamics within collaborative learning contexts. The study also examined the application of MMLA to various forms of collective learning activities, such as collaborative problem solving, group-based tasks, and project-based learning. Ontological modelling of the field facilitated the identification of existing conceptual frameworks and methodological approaches, as well as the projection of emerging directions.

Practical signicance. The research findings can be used to design learning environments that foster communication, collaboration, and teamwork skills, including those in interdisciplinary educational contexts.

About the Authors

E. D. Patarakin
Moscow City Pedagogical University; National Research University Higher School of Economics
Russian Federation

Evgeny D. Patarakin – Dr. Sci. (Education,) Associate Professor, Professor, Department of Informatics, Management and Technology, Moscow City Pedagogical University; Professor, Institute of Education, National Research University Higher School of Economics

Moscow



A. I. Kutuzov
National Research University Higher School of Economics; Togliatti State University
Russian Federation

Anton I. Kutuzov – PhD Student, Institute of Education, National Research University Higher School of Economics; Director of the Centre, Togliatti State University

Moscow

Togliatti



I. V. Dvoretskaya
National Research University Higher School of Economics
Russian Federation

Irina V. Dvoretskaya – PhD (Education), Research Fellow, Associate Professor, Institute of Education

Moscow



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Patarakin E.D., Kutuzov A.I., Dvoretskaya I.V. Multimodal learning analytics: a bibliometric and ontological analysis. The Education and science journal. 2025;27(7):33-71. (In Russ.) https://doi.org/10.17853/1994-5639-2025-7-33-71

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ISSN 1994-5639 (Print)
ISSN 2310-5828 (Online)