Paper Info
Title
A domain-independent data ADHD student model for computer-based educational systems. Data analysis in higher education.
Abstract
In traditional learning, teachers can easily have an understanding of how their students work and learn. However, in e-Learning it is more difficult for teachers to monitor how their students behave and learn in the system. As well as to identify if they have any specific awkwardness in their educational process. In this paper, a student model to infer the presence of ADHD symptoms in a Computer-Based Educational System (also known as Learning Management Systems (LMS)) is presented. The student model takes into account two types of students' characteristics: generic and psychological. Each one is measured through a set of variables, which are correlated to obtain a final profile that can be useful to assist the teaching-learning process. In order to reach this purpose, three Web application tools that collect information about these characteristics have been developed, integrated into a LMS and validated in a case study composed of 30 students (5 suffering from ADHD, 5 that present similar characteristics to ADHD and 20 that supposed do not suffer from ADHD). This case study was carried out through a quantitative research approach and a descriptive scope. Results show that the implemented tools are useful to identify attention problems symptoms in students enrolled in e-learning courses.
Year
DOI
Venue
2017
10.3233/AIS-170455
JOURNAL OF AMBIENT INTELLIGENCE AND SMART ENVIRONMENTS
Keywords
Field
DocType
Inclusive education,attention deficit hyperactivity disorder,student model,e-learning
Computer science,Educational systems,Multimedia,Higher education
Journal
Volume
Issue
ISSN
9
5
1876-1364
Citations 
PageRank 
References 
0
0.34
7
Authors
5
Name
Order
Citations
PageRank
Laura Mancera110.68
Silvia Baldiris24311.58
Ramón Fabregat310725.34
Magle Sánchez400.34
Ferran Viñas500.34