Abstract
The main goal of multimodal learning analytics (MLA) research is to extend the application of learning analytics tools and services in learning contexts to collect, analyze, and combine digital traces and learning data of completely different sources that are available in lab-based learning contexts. Moreover, the characteristics and properties of these learning contexts cannot be described by a single source of data traces, but a combination of several modes and sources are vital in understanding these particular learning processes (Ochoa, Multimodal learning analytics. In: Handbook of learning analytics. Society for Learning Analytics Research (SoLAR), pp 129–141. https://doi.org/10.18608/hla17.011, 2017). One specific learning setting in which there are hardly any scientific findings and research in learning analytics is using MLA in hybrid laboratory environments in connection with experiential learning. In our chapter, we would like to demonstrate the potentials and prospects of providing MLA tools and services in laboratory-based learning scenarios. For this reason, an exploratory approach was chosen, in order to investigate the possibilities of MLA for the selected laboratories.
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Notes
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Radio-frequency identification
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University of Applied Sciences Stuttgart
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Ultra-high-frequency Tags
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Augmented reality
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Received signal strength indicator
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Radio-frequency-friendly
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Electronic Product Code
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Virtual reality
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Acknowledgment
The presented work was done in the scope of the research project Open Digital Lab for You (DigiLab4U), funded by the German Federal Ministry of Education and Research between 2018 and 2022.
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Pfeiffer, A., Lukarov, V., Romagnoli, G., Uckelmann, D., Schroeder, U. (2020). Experiential Learning in Labs and Multimodal Learning Analytics. In: Ifenthaler, D., Gibson, D. (eds) Adoption of Data Analytics in Higher Education Learning and Teaching. Advances in Analytics for Learning and Teaching. Springer, Cham. https://doi.org/10.1007/978-3-030-47392-1_18
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