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Classroom Analytics Using Indoor Positioning Sensors

Primary supervisor

Roberto Martinez-Maldonado

I am seeking students doing Honours or a minor thesis in a Masters interested in working on designing Learning Analytics innovations to study classroom proxemics by analysing and visualising indoor positioning data (along with other sources of data such as audio, physiological activity and characteristics of the students).

This project aims to develop methods for supporting teachers in reflecting on their positioning strategies in the classroom by making key activity traces visible. This project is fundamentally about bridging the gap between substantial work on classroom proxemics (the study about how people use the physical space), based on qualitative observations; and the dearth of methods to provide feedback to teachers on their teaching practice using evidence, at a scale. This project is strategic because it aims to transform ephemeral teaching classroom activity, that currently is largely opaque to computational analysis, into a transparent phenomenon from which selected features can be captured and rendered visible for the purposes of professional development for teachers. 

The project may involve both the analysis of a dataset already captured or the capture of new positioning data or qualitative data from educational stakeholders.

Indoor positioning analytics in the classroom


Example publication related to this opportunity: Martinez-Maldonado, R. (2019) “I Spent More Time with that Team”: Making Spatial Pedagogy Visible Using Positioning SensorsInternational Conference on Learning Analytics and Knowledge, LAK 2019.

Student cohort

Double Semester


Depending on the trajectory that you take, examples of the questions that such a project could investigate include:

  • How can evidence on classroom proxemics be used to support novice teachers in developing classroom positioning strategies?
  • What is the role of the learning design to make sense of classroom proxemics?
  • How can indoor positioning and other sources of classroom data be visualised for sense-making?
  • What are the potential risks of showing teachers' positioning data to them and other stakeholders?
  • How can indoor positioning data be used to assess or analyse the classroom interior design and furniture arrangements?
  • How can positioning data be enriched with physiological, audio and other sources of classroom evidence?

Required knowledge

  • Strong interest in designing and conducting quantitative, qualitative or mixed-method studies
  • Strong programming skills in at least one relevant language (e.g. C/C++, .NET, Java, Python, R, etc.)
  • Experience with data mining, data analytics or business intelligence tools (e.g. Weka, ProM, RapidMiner)
  • Visualisation tools are a bonus