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 language | English |
|---|---|
| Title of host publication | The 17th IEEE International Conference on Advanced Learning Technologies (ICALT 2017) |
| Editors | Maiga Chang, Nian-Shing Chen, Ronghuai Huang, Kinshuk, Demetrios G Sampson, Radu Vasiu |
| Place of Publication | Piscataway NJ USA |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| Pages | 89-91 |
| Number of pages | 3 |
| ISBN (Electronic) | 9781538638705 |
| ISBN (Print) | 9781538638712 |
| DOIs | |
| Publication status | Published - 2017 |
| Externally published | Yes |
| Event | IEEE International Conference on Advanced Learning Technologies 2017 - Timisoara, Romania Duration: 3 Jul 2017 → 7 Jul 2017 Conference number: 17th https://icalt.elearning.upt.ro/ https://ieeexplore.ieee.org/xpl/conhome/8001597/proceeding (Proceedings) |
Conference
| Conference | IEEE International Conference on Advanced Learning Technologies 2017 |
|---|---|
| Abbreviated title | ICALT 2017 |
| Country/Territory | Romania |
| City | Timisoara |
| Period | 3/07/17 → 7/07/17 |
| Internet address |
Keywords
- classroom
- computer vision
- indoor positioning
- mobility tracking
- physical spaces
- teamwork