Name
Abstract | ||
|---|---|---|
Attention is one of the most widely misused and overgeneralized constructs found in the educational, learning, instructional, and psychological sciences. It would be convenient for teachers if they could grasp the attentiveness states of learners in their classes precisely so that they could try to improve the way to deliver the course material in a manner that could attract more learners. When students are doing learning activities using the news technologies is very hard for the teacher detected if each student her/his level of attentiveness. Furthermore, different student learn in different ways, each one preferring a different learning style. This paper presents an experience using different learning styles with a system that monitoring attention, with the aim of providing a non-intrusive and non-invasive way, reliable and easy tool that can be used freely in schools, without changing or interfering with the established working routines. Specifically, we look at desk students in learning activities, in which the student spends long time interacting with the computer. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-60819-8_11 | METHODOLOGIES AND INTELLIGENT SYSTEMS FOR TECHNOLOGY ENHANCED LEARNING |
Keywords | Field | DocType |
Learning style,Attention,Behavior biometrics,Technologies in learning,Ambient intelligent system | Learning styles,GRASP,Psychology,Mathematics education,Desk | Conference |
Volume | ISSN | Citations |
617 | 2194-5357 | 0 |
PageRank | References | Authors |
0.34 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dalila Durães | 1 | 5 | 6.84 |
| Javier Bajo | 2 | 1451 | 118.96 |
| Paulo Novais | 3 | 883 | 171.45 |