EDUMONDO: Prototyping a learning analytics system

Rasmus Tange Præstegaard, Daniel Myltoft Wiencken, Tom Collins, Mirko Presser

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review


With education being a core driver in the modern individual's self-realization, the quality of this education must be systematically managed. This paper explores the complexities of measuring and optimizing the quality of lectures. In this paper a concept for a Learning Analytic System (LAS) is presented, which has been developed through multiple iterations, consisting of two Internet of Things (IoT) prototypes and one high-level concept. The prototypes were used to explore the feasibility of collecting classroom data as well as implementing a teacher feedback loop. The conceptual LAS was used to explore the teachers' opinion as well as a potential value proposition for such a system. The results contain a description and a visual mockup for this proposed LAS, called EDUMONDO, that could systematically improve the quality of lecturing. In conclusion, this paper presents several opportunities, challenges, and recommendations for implementing teacher and classroom assisting technologies. This paper should serve as a platform for public discussion on how education should and should not change, in the face of technologies pushing towards a paradigm shift in education.

Original languageEnglish
Title of host publicationGlobal IoT Summit, GIoTS 2019 - Proceedings
Publication date1 Jun 2019
Article number8766372
ISBN (Electronic)9781728121710
Publication statusPublished - 1 Jun 2019
Event3rd Global IoT Summit, GIoTS 2019 - Aarhus, Denmark
Duration: 17 Jun 201921 Jun 2019


Conference3rd Global IoT Summit, GIoTS 2019
SponsorIEEE, IEEE Communications Society (ComSoc), IEEE Internet of Things


  • Educational Quality
  • Internet of Things
  • Learning Analytics
  • Quantified Self


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