Analytics in Glocal Classrooms: Integrating Multimodal Learning Analytics in a Smart Learning Environment

In the dynamic landscape of digital education, the Glocal Classroom (GC) stands out as a multifaceted smart learning environment. The integration of Multimodal Learning Analytics (MMLA) comes as an intriguing proposition, promising insights into learning dynamics and enhancing educational outcomes. Encountering numerous interdependent considerations involved in the design and integration of MMLA systems, the MMLA design framework (MDF) addresses this challenge, providing a systematic approach. MDF consists of a phased and iterative method for designing MMLA systems. In this study, we delve into the details of the fifth phase, focusing on the development phase. Our primary objective is to assess and refine the applicability of MDF, by taking the integration of MMLA in GC as a use case. We analyze GC's technological infrastructure, evaluating existing hardware, network capabilities, and potential challenges. The central emphasis is on the technical architecture, specifically the hardware components supporting MMLA. By focusing on the technical complexities, the study provides insights into challenges and opportunities associated with MMLA implementation. The outcomes will deepen our understanding of technology in education and refine the MDF model, making it more effective for designing MMLA systems.

I. Introduction

In the ever-evolving landscape of education, the Glocal Classroom (GC) emerges as a captivating and versatile smart learning environment, transcending geographical boundaries to foster diverse interactions among students and educators [1]. Within this unique educational space, the integration of Multimodal Learning Analytics (MMLA) is a promising proposition, offering insights into collaborative learning dynamics and the potential to [2]. Navigating the complex process of designing and integrating MMLA systems poses considerable challenges due to numerous interdependent considerations [2]. To address this complexity, the MMLA design framework (MDF) presents a systematic approach, offering a structured and phased method for creating MMLA systems. With six distinct phases, MDF provides a workflow that takes into account the logic, relations, and dependencies of various key considerations in the design process. Notably, the initial four phases have already undergone refinement, setting the stage for an in-depth exploration of the fifth phase, focusing on the development and implementation.