Paper Info
Title
Supervising and Improving Attentiveness in Human Computer Interaction.
Abstract
The collection, storage, management, and anticipation of contextual information about the user to support decision-making constitute some of the key operations in most Ambient Intelligent (AmI) systems. When the instructor has a computer-based class it is often difficult to confirm if the students are working in the proposed activities. In order to mitigate problems that might occur in an environment with learning technologies we suggest an AmI system aimed at capturing, measuring, and supervising the students' level of attentiveness in real scenarios and dynamically provide recommendations to the instructor. With this system it is possible to assess both individual and group attention, in real-time, providing a measure of the level of engagement of each student in the proposed activities and allowing the instructor to better steer teaching methodologies.
Year
DOI
Venue
2016
10.3233/978-1-61499-690-3-255
INTELLIGENT ENVIRONMENTS 2016
Keywords
Field
DocType
Ambient Intelligence,Learning Styles,Innovative Scenarios,Attentiveness
Learning styles,Simulation,Computer science,Ambient intelligence,Human–computer interaction,Functional testing (manufacturing)
Conference
Volume
ISSN
Citations 
21
1875-4163
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Dalila Durães156.84
Davide Carneiro27014.90
Javier Bajo31451118.96
Paulo Novais4883171.45