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@PHDTHESIS{Heinemann:1015570,
      author       = {Heinemann, Birte},
      othercontributors = {Schroeder, Ulrik and Spannagel, Christian},
      title        = {{E}xploring teaching and learning in virtual reality:
                      challenges and opportunities with multimodal learning
                      analytics},
      school       = {RWTH Aachen University},
      type         = {Dissertation},
      address      = {Aachen},
      publisher    = {RWTH Aachen University},
      reportid     = {RWTH-2025-06448},
      pages        = {1 Online-Ressource : Illustrationen},
      year         = {2025},
      note         = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
                      University; Dissertation, RWTH Aachen University, 2025},
      abstract     = {Virtual Reality (VR) in education offers promising
                      opportunities to design immersive and interactive learning
                      environments. As interest in VR grows, research focuses on
                      the conditions under which learning in VR becomes effective.
                      Beyond exploring what can be taught in VR, it is essential
                      to investigate how immersive features—such as
                      interactivity, presence, and spatial metaphors—shape
                      learning processes. At the same time, challenges persist in
                      systematically evaluating VR learning scenarios and in
                      developing scalable, reusable infrastructures for
                      educational research. Open key questions include: Which VR
                      features are most beneficial for learning? How can
                      onboarding and usability be optimized for diverse learners?
                      And how can multimodal learning analytics (MMLA) support
                      both learners and educators in making data-informed
                      decisions? This dissertation addresses these questions
                      through the design, implementation, and evaluation of three
                      VR learning projects, each supported by a modular analytics
                      infrastructure: (1) simulation-based teacher training in
                      classroom management using Teach-R, (2) immersive learning
                      of the rendering pipeline with RePiX VR, and (3)
                      interdisciplinary lab-based learning scenarios. Together,
                      these cases demonstrate how MMLA can be meaningfully
                      integrated into VR for both research and educational
                      practice. Methodologically, the work follows an iterative,
                      agile approach, combining design-based research (DBR),
                      human-centred design, and design-make-learn cycles.
                      Empirical studies using pre-test, intervention, and
                      post-test designs were conducted for Teach-R and RePiX VR,
                      while the third case contributed to infrastructure
                      development and conceptual generalization. Key contributions
                      include (1) a reusable, xAPI-based infrastructure for
                      learning analytics in VR; (2) empirical insights into
                      onboarding, presence, and usability; (3) two exemplary VR
                      applications for teacher education and computer graphics;
                      and (4) dashboards and visualizations that support
                      reflection and curriculum development. These contributions
                      are grounded in existing research across educational
                      technology, learning sciences, and human-computer
                      interaction and are validated against state-of-the-art
                      methods and the xAPI specification. By shifting away from
                      traditional media comparison studies, the work avoids
                      pitfalls such as novelty effects and confounding variables,
                      instead focusing on how and when learning in VR works. It
                      shows that VR — when paired with multimodal analytics —
                      can meaningfully enhance teaching and learning. This
                      dissertation provides pedagogical insights, and technical
                      solutions for scalable, data-informed educational
                      innovation.},
      cin          = {122420 / 120000},
      ddc          = {004},
      cid          = {$I:(DE-82)122420_20140620$ / $I:(DE-82)120000_20140620$},
      typ          = {PUB:(DE-HGF)11},
      doi          = {10.18154/RWTH-2025-06448},
      url          = {https://publications.rwth-aachen.de/record/1015570},
}