Leveraging learning analytics to enhance immersive teacher simulations: Challenges and opportunities
Sumin Hong, Jewoong Moon, Taeyeon Eom, Juno Hwang, Jibeom Seo

TL;DR
This paper explores how learning analytics can improve immersive teacher simulations by analyzing multimodal data to reveal pedagogical reasoning, highlighting challenges and opportunities for advancing teacher education.
Contribution
It introduces a framework for integrating multimodal analytics into immersive simulations to enhance reflective teaching practices and professional learning.
Findings
Multimodal analytics reveal pedagogical discourse patterns.
Sequential interaction patterns emerge in immersive simulations.
Analytics make pedagogical reasoning processes visible.
Abstract
This chapter examines how data analytics can be leveraged to enhance immersive teacher simulations, situating this inquiry within the broader learning sciences discourse on embodied cognition, data-informed feedback, and teacher professional learning. It explores both conceptual foundations and empirical cases to illustrate how analytics serve as mediational tools that connect immersive experiences with reflective teaching practice. The chapter unfolds in multiple sections: (1) The Innovation Journey: An Overview of Immersive Teacher Simulations outlines the evolution from traditional simulations to XR-based environments, highlighting the need for professional decision-making under realistic constraints. (2) Innovation in Existing Research and Practice situates teacher analytics within the trajectory from descriptive observation to multimodal and predictive modeling. (3) Study Approach…
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Taxonomy
TopicsInnovative Teaching Methodologies in Social Sciences · Online Learning and Analytics · Educational Theory and Curriculum Studies
