Role of Multimodal Learning Systems in Technology-Enhanced Learning (TEL)

Abstract

Technology-enhanced learning systems, specifically multimodal learning technologies, use sensors to collect data from multiple modalities to provide personalized learning support beyond traditional learning settings. However, many studies surrounding such multimodal learning systems mostly focus on technical aspects concerning data collection and exploitation and therefore overlook theoretical and instructional design aspects such as feedback design in multimodal settings. This paper explores multimodal learning systems as a critical part of technology-enhanced learning used for capturing and analyzing the learning process to exploit the collected multimodal data to generate feedback in multimodal settings. By investigating various studies, we aim to reveal the roles of multimodality in technology-enhanced learning across various learning domains. Our scoping review outlines the conceptual landscape of multimodal learning systems, identifies potential gaps, and provides new perspectives on adaptive multimodal system design: intertwining learning data for meaningful insights into learning, designing effective feedback, and implementing them in diverse learning domains.