Details

Autor(en) / Beteiligte

• Ouhaichi, Hamza
• Spikol, Daniel
• Vogel, Bahtijar

Titel

Research trends in multimodal learning analytics: A systematic mapping study

Ist Teil von

• Computers and education. Artificial intelligence, 2023, Vol.4, p.100136, Article 100136

Ort / Verlag

Elsevier Ltd

Erscheinungsjahr

2023

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• 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.