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

Journal of Information Systems Engineering & Management, Volume 1, Issue 1, pp. 41-54.

https://doi.org/10.20897/lectito.201608

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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

Citation

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 & Management, 1(1), pp. 41-54. https://doi.org/10.20897/lectito.201608

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