MDOI Convergence Chronicles 110.1190/CON.2026.01161
110.1190/CON.2026.01161
Article

Research trends in multimodal learning analytics: A systematic mapping study

Hamza Ouhaichi, Daniel Spikol, Bahtijar Vogel 2023 Convergence Chronicles

Abstract

Understanding and improving education are critical goals of learning analytics. However, learning is not always mediated or aided by a digital system that can capture digital traces. Learning in such environments can be studied by recording, processing, and analyzing different signals, including video and audio, so that traces of actors’ actions and interactions are captured. Multimodal Learning Analytics refers to analyzing these signals through the use and integration of these multiple modes. However, a need exists to evaluate how research is conducted in the emerging field of multimodal learning analytics to aid and evaluate how these systems work. With the growth of multimodal learning analytics, research trends and technologies are needed to support its development. We conducted a systematic mapping study based on established systematic literature practices to identify multimodal learning analytics research types, methodologies, and trending research themes. Most mapped papers presented different solutions and used evaluation-based research methods to demonstrate an increasing interest in multimodal learning analytics technologies. In addition, we identified 14 topics under four themes––learning context, learning process, systems and modality, and technologies––that can contribute to the growth of multimodal learning analytics.

Identifier Metadata

Identifier 110.1190/CON.2026.01161
Canonical mdoi:110.1190/CON.2026.01161
Resolver URL https://mdoi.org/110.1190/CON.2026.01161
Resource URL Open resource
Document URL Open document
Content Type Article
Authors Hamza Ouhaichi, Daniel Spikol, Bahtijar Vogel
Year 2023
Depositor Convergence Chronicles Organisation
Prefix 110.1190
Registered Aug. 21, 2026
Updated Aug. 21, 2026
Status Active
Visibility Public

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