Analytics of biometric data from wearable devices to support teaching and learning activities

Francisco de Arriba Pérez; Juan Manuel Santos Gago; Manuel Caeiro Rodríguez

doi:10.20897/lectito.201608

Analytics of biometric data from wearable devices to support teaching and learning activities

Francisco de Arriba Pérez ¹ ^* , Juan Manuel Santos Gago ¹, Manuel Caeiro Rodríguez ¹

More Detail

¹ Universidad de Vigo, SPAIN
^* Corresponding Author

Full Text (PDF)

Research Article

Journal of Information Systems Engineering and Management, 2016 - Volume 1 Issue 1, pp. 41-54
https://doi.org/10.20897/lectito.201608

Published Online: 10 Mar 2016

Views: 4401 | Downloads: 2249

Open Access

How to cite this article

APA 6th edition

In-text citation: (de Arriba Pérez et al., 2016)
Reference: de Arriba Pérez, F., Santos Gago, J. M., & Caeiro Rodríguez, M. (2016). Analytics of biometric data from wearable devices to support teaching and learning activities. Journal of Information Systems Engineering and Management, 1(1), 41-54. https://doi.org/10.20897/lectito.201608

Vancouver

In-text citation: (1), (2), (3), etc.
Reference: de Arriba Pérez F, Santos Gago JM, Caeiro Rodríguez M. Analytics of biometric data from wearable devices to support teaching and learning activities. J INFORM SYSTEMS ENG. 2016;1(1):41-54. https://doi.org/10.20897/lectito.201608

AMA 10th edition

In-text citation: (1), (2), (3), etc.
Reference: de Arriba Pérez F, Santos Gago JM, Caeiro Rodríguez M. Analytics of biometric data from wearable devices to support teaching and learning activities. J INFORM SYSTEMS ENG. 2016;1(1), 41-54. https://doi.org/10.20897/lectito.201608

Chicago

In-text citation: (de Arriba Pérez et al., 2016)
Reference: de Arriba Pérez, Francisco, Juan Manuel Santos Gago, and Manuel Caeiro Rodríguez. "Analytics of biometric data from wearable devices to support teaching and learning activities". Journal of Information Systems Engineering and Management 2016 1 no. 1 (2016): 41-54. https://doi.org/10.20897/lectito.201608

Harvard

In-text citation: (de Arriba Pérez et al., 2016)
Reference: de Arriba Pérez, F., Santos Gago, J. M., and Caeiro Rodríguez, M. (2016). Analytics of biometric data from wearable devices to support teaching and learning activities. Journal of Information Systems Engineering and Management, 1(1), pp. 41-54. https://doi.org/10.20897/lectito.201608

MLA

In-text citation: (de Arriba Pérez et al., 2016)
Reference: de Arriba Pérez, Francisco et al. "Analytics of biometric data from wearable devices to support teaching and learning activities". Journal of Information Systems Engineering and Management, vol. 1, no. 1, 2016, pp. 41-54. https://doi.org/10.20897/lectito.201608

ABSTRACT

This paper introduces the preliminary results of a piece of research whose main purpose is to take advantage of data collected from wearable devices to support learning processes. This goal is approached through the application of learning analytic techniques. The innovation point is the use of data collected from wearables, that will be used in conjunction with data collected from other sources (e.g. Learning Management Systems, Student Information Systems). The paper reviews the results achieved during the last year about the relationships among biometric data collected from wearables and relevant features described in the educational literature. In this way sleep and stress have been identified as interesting areas that could be informed from data collected in wearables and processed by applying machine learning techniques. Our preliminary results show some initial promising results that need further validation, also these results show an interesting opportunity to support awareness and intervention functionalities.

KEYWORDS

learning analytics wearable sensors wearable computing smartphones sensors smartphones computing sleep detection stress detection

REFERENCES

---

LICENSE

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.