Detection of Behavioral Patterns for Increasing Attentiveness Level

• Published in: Intelligent Systems Design and Applications Vol. 557; pp. 592 - 601
• Main Authors: Durães, Dalila, Gonçalves, Sérgio, Carneiro, Davide, Bajo, Javier, Novais, Paulo
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2017; Springer International Publishing
• Series: Advances in Intelligent Systems and Computing
• Subjects: Ambient intelligence; Artificial intelligence; Attentiveness; Innovative scenarios; Learning activities
• ISBN: 9783319534794; 3319534793
• ISSN: 2194-5357; 2194-5365
• DOI: 10.1007/978-3-319-53480-0_58

In the current world, performance is one of the most important issues concerning work and competition. Performance is strongly connected with learning and when it comes to acquiring new knowledge, attention is one the most important mechanisms as the level of the learner’s attention affects learning results. When students are doing learning activities using new technologies, it is extremely important that the teacher has some feedback from the students’ work in order to detect potential learning problems at an early stage. The goal of this research is to propose a system that measures the level of attentiveness in real scenarios, and detects patterns of behavior associated to different attention levels among different students. This system measures attention and uses this information for training a decision support system that shows the level of attention of a group of students in real time.