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Analytics in Glocal Classrooms: Integrating Multimodal Learning Analytics in a Smart Learning Environment
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0002-9278-8063
Copenhagen University, Department of Science Education, Copenhagen, Denmark.ORCID iD: 0000-0001-9454-0793
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0001-6708-5983
Copenhagen University, Departement of Computer Science, Copenhagen, Denmark.
2024 (English)In: 2024 IEEE International Conference on Advanced Learning Technologies (ICALT), Nicosia, North Cyprus, Cyprus, 2024, IEEE, 2024Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
IEEE, 2024.
Series
IEEE International Conference on Advanced Learning Technologies, E-ISSN 2161-3761
Keywords [en]
Multimodal Learning Analytics, Glocal Classroom, Smart Learning Environment, Learning Dynamics, MMLA Design
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mau:diva-70106DOI: 10.1109/ICALT61570.2024.00033ISI: 001308583600027Scopus ID: 2-s2.0-85203798128ISBN: 979-8-3503-6205-3 (electronic)OAI: oai:DiVA.org:mau-70106DiVA, id: diva2:1887709
Conference
ICALT 2024 – 24th IEEE International Conference on Advanced Learning Technologies, July 1 – 4 2024, North Nicosia, North Cyprus.
Available from: 2024-08-09 Created: 2024-08-09 Last updated: 2025-02-04Bibliographically approved
In thesis
1. A framework for designing and analyzing multimodal learning analytics systems
Open this publication in new window or tab >>A framework for designing and analyzing multimodal learning analytics systems
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The integration of technology in education offers transformative potential, especially with the advent of data-driven approaches that can personalize learning, support educators, and provide valuable insights into the learning process. Multimodal learning analytics (MMLA) holds remarkable promise within this context. By capturing and analyzing data from multiple sources—including video, audio, and digital interactions—MMLA systems offer a holistic view of learning experiences and the ability to tailor interventions in real time. This application has profound implications for understanding and enhancing learning experiences. However, the design of such sophisticated systems poses a significant challenge. Without conventional and field-tested frameworks, MMLA system development often remains self-driven and tailored to specific contexts, limiting both these systems’ broader adoption and full utilization. This thesis proposes a structured framework for designing MMLA systems across diverse educational contexts to address this fundamental challenge. The development of the framework followed a multifaceted methodology. In addition, action design research involving empirical studies, literature reviews, and expert interviews was employed to establish a set of foundational design considerations. The framework was then applied and refined within real-world educational settings. These included applications in the context of a globally distributed classroom and language acquisition environments. This practical application led to refinements that enhanced the framework’s adaptability and user-centric design. This thesis makes three key contributions: (1) a set of design considerations for MMLA systems, (2) a framework offering a structured guide for the design of MMLA systems, and (3) a conceptual system demonstrating the framework’s principles. The implications of this work are significant for researchers and stakeholders in MMLA, providing a foundation for future MMLA system development and ensuring more systematic and conventional design practices. This structured approach paves the way for broader adoption and integration of MMLA, ultimately enhancing educational outcomes and fostering personalized learning environments.

Place, publisher, year, edition, pages
Malmö: Malmö University Press, 2024. p. 83
Series
Studies in Computer Science ; 26
Keywords
Multimodal Learning Analytics, Educational Technology, Smart learning Environments, Internet of Things
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mau:diva-70111 (URN)10.24834/isbn.9789178775217 (DOI)978-91-7877-520-0 (ISBN)978-91-7877-521-7 (ISBN)
Public defence
2024-09-24, Auditorium C, Niagara, auditorium C, Nordenskiöldsgatan 1, Malmö, 09:00 (English)
Opponent
Supervisors
Available from: 2024-08-26 Created: 2024-08-09 Last updated: 2024-09-18Bibliographically approved

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Ouhaichi, HamzaSpikol, DanielVogel, Bahtijar

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