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A Multi-Stakeholder Perspective of Analytics for Learning Design in Location-Based Learning

A Multi-Stakeholder Perspective of Analytics for Learning Design in Location-Based Learning

Gerti Pishtari, María Jesús Rodríguez-Triana, Terje Väljataga
Copyright: © 2021 |Volume: 13 |Issue: 1 |Pages: 17
ISSN: 1941-8647|EISSN: 1941-8655|EISBN13: 9781799860440|DOI: 10.4018/IJMBL.2021010101
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MLA

Pishtari, Gerti, et al. "A Multi-Stakeholder Perspective of Analytics for Learning Design in Location-Based Learning." IJMBL vol.13, no.1 2021: pp.1-17. http://doi.org/10.4018/IJMBL.2021010101

APA

Pishtari, G., Rodríguez-Triana, M. J., & Väljataga, T. (2021). A Multi-Stakeholder Perspective of Analytics for Learning Design in Location-Based Learning. International Journal of Mobile and Blended Learning (IJMBL), 13(1), 1-17. http://doi.org/10.4018/IJMBL.2021010101

Chicago

Pishtari, Gerti, María Jesús Rodríguez-Triana, and Terje Väljataga. "A Multi-Stakeholder Perspective of Analytics for Learning Design in Location-Based Learning," International Journal of Mobile and Blended Learning (IJMBL) 13, no.1: 1-17. http://doi.org/10.4018/IJMBL.2021010101

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Abstract

Promoted by the growing access to mobile devices and the emphasis on situated learning, location-based tools are being used increasingly in education. Multiple stakeholders could benefit from understanding the learning and teaching processes triggered by these tools, supported by data analytics. For instance, practitioners could use analytics to monitor and regulate the implementation of their learning designs (LD), as well as to assess their impact and effectiveness. Also, the community around specific tools—such as researchers, managers of educational institutions, and developers—could use analytics to further improve the tools and better understand their adoption. This paper reports the co-design process of a location-based authoring tool that incorporates multi-stakeholder analytics for LD features. It contributes to the research community through a case study that investigates how analytics can support specific LD needs of different stakeholders of location-based tools. Results emphasise opportunities and implications of aligning analytics and LD in location-based learning.