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A Novel Web-Based Approach for Visualization and Inspection of Reading Difficulties on University Students

Authors :
Mejia, Carolina
Florian, Beatriz
Vatrapu, Ravi
Bull, Susan
Gomez, Sergio
Fabregat, Ramon
Source :
IEEE Transactions on Learning Technologies. Jan-Mar 2017 10(1):53-67.
Publication Year :
2017

Abstract

Existing tools aim to detect university students with early diagnosis of dyslexia or reading difficulties, but there are not developed tools that let those students better understand some aspects of their difficulties. In this paper, a dashboard for visualizing and inspecting early detected reading difficulties and their characteristics, called PADA (acronym for the Spanish name "Panel de Analíticas de Aprendizaje de Dislexia en Adultos"), is presented. PADA is a web-based tool designed to facilitate the creation of descriptive visualizations required for a better understanding by students about their learner model. Through information visualization techniques, PADA shows students the knowledge in their learner models in order to help them to increase their awareness and to support reflection and self-regulation about their difficulties in reading. PADA provides different learning analytics on reading performance of students, so that they can self-identify their strengths and weaknesses and self-regulate their learning. This paper describes examples that cover a variety of visualizations (bar-charts, line-charts, and pie-charts) to show user model fragments as personal details, reading profiles, learning styles, and cognitive traits of the students. We tested PADA with 26 students (aged 21-53 years) of different academic programs and levels, dyslexic and non-dyslexic. The results show that PADA can assist students in creating awareness, and help them to understand their difficulties associated with the reading tasks, as well as facilitate reflection and self-regulation in the learning process. Implications for the design of learning analytics are discussed and directions for future work are outlined.

Details

Language :
English
ISSN :
1939-1382
Volume :
10
Issue :
1
Database :
ERIC
Journal :
IEEE Transactions on Learning Technologies
Publication Type :
Academic Journal
Accession number :
EJ1141042
Document Type :
Journal Articles<br />Reports - Research
Full Text :
https://doi.org/10.1109/TLT.2016.2626292