TY - GEN
T1 - A framework for automatic identification and visualization of mobile device functionalities and usage
AU - Lima, Renan H.P.
AU - El-Bishouty, Moushir M.
AU - Graf, Sabine
PY - 2013
Y1 - 2013
N2 - While mobile learning gets more and more popular, little is known about how learners use their devices for learning successfully and how to consider context information, such as what device functionalities/features are available and frequently used by learners, to provide them with adaptive interfaces and personalized support. This paper presents a framework that automatically identifies the functionalities/features of a device (e.g., Wi-Fi connection, camera, GPS, etc.), monitors their usage and provides users with visualizations about the availability and usage of such functionalities/features. While the framework is designed for any type of device such as mobile phones, tablets and desktop-computers, this paper presents an application for Android phones. The proposed framework (and the application) can contribute towards enhancing learning outcomes in many ways. It builds the basis for providing personalized learning experiences considering the learners' context. Furthermore, the gathered data can help in analyzing strategies for successful learning with mobile devices.
AB - While mobile learning gets more and more popular, little is known about how learners use their devices for learning successfully and how to consider context information, such as what device functionalities/features are available and frequently used by learners, to provide them with adaptive interfaces and personalized support. This paper presents a framework that automatically identifies the functionalities/features of a device (e.g., Wi-Fi connection, camera, GPS, etc.), monitors their usage and provides users with visualizations about the availability and usage of such functionalities/features. While the framework is designed for any type of device such as mobile phones, tablets and desktop-computers, this paper presents an application for Android phones. The proposed framework (and the application) can contribute towards enhancing learning outcomes in many ways. It builds the basis for providing personalized learning experiences considering the learners' context. Furthermore, the gathered data can help in analyzing strategies for successful learning with mobile devices.
KW - Context modeling
KW - device functionalities and their usage
KW - mobile learning
KW - personalization
KW - ubiquitous learning analytics
KW - visualization
UR - http://www.scopus.com/inward/record.url?scp=84879876405&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-39146-0_14
DO - 10.1007/978-3-642-39146-0_14
M3 - Published Conference contribution
AN - SCOPUS:84879876405
SN - 9783642391453
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 148
EP - 159
BT - Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data - Third International Workshop, HCI-KDD 2013, Held at SouthCHI 2013, Proceedings
T2 - 3rd International Workshop on Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data, HCI-KDD 2013, Held at SouthCHI 2013
Y2 - 1 July 2013 through 3 July 2013
ER -