Towards proximity tracking and sensemaking for supporting teamwork and learning

Roberto Martinez-Maldonado, Kalina Yacef, Augusto Dias Pereira Dos Santos, Simon Buckingham Shum, Vanessa Echeverria, Olga C. Santos, Mykola Pechenizkiy

Research output: Chapter in Book/Report/Conference proceedingConference PaperOtherpeer-review

6 Citations (Scopus)

Abstract

A large number of learning tools offering some sort of personalisation features rely mainly on the analysis of logged interactions between students and particular user interfaces. Much less attention has been given to the analysis of physical aspects so often present in 'traditional' intellectual tasks, although these are both important in the full development of a life-long learner. This paper (1) discusses existing literature focused on supporting learning using proximity and location analytics and sensors, and, based on this, (2) illustrates the feasibility and potential of these analytics for teaching and learning through an study in the context of proximity and location analytics in a team-based health simulation classroom.

Original languageEnglish
Title of host publicationThe 17th IEEE International Conference on Advanced Learning Technologies (ICALT 2017)
EditorsMaiga Chang, Nian-Shing Chen, Ronghuai Huang, Kinshuk, Demetrios G Sampson, Radu Vasiu
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages89-91
Number of pages3
ISBN (Electronic)9781538638705
ISBN (Print)9781538638712
DOIs
Publication statusPublished - 2017
Externally publishedYes
EventIEEE International Conference on Advanced Learning Technologies 2017 - Timisoara, Romania
Duration: 3 Jul 20177 Jul 2017
Conference number: 17th
https://icalt.elearning.upt.ro/
https://ieeexplore.ieee.org/xpl/conhome/8001597/proceeding (Proceedings)

Conference

ConferenceIEEE International Conference on Advanced Learning Technologies 2017
Abbreviated titleICALT 2017
CountryRomania
CityTimisoara
Period3/07/177/07/17
Internet address

Keywords

  • classroom
  • computer vision
  • indoor positioning
  • mobility tracking
  • physical spaces
  • teamwork

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