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  • Carolina Mejia
  • Beatriz Florian-Gaviria
  • Ravi Vatrapu
  • Susan Bull
  • Sergio Manuel Madero Gómez
  • Ramon Fabregat
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 regarding 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 of 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.

Publication information

Original languageEnglish
JournalIEEE Transactions on Learning Technologies
Volume10
Issue number1
Pages (from-to) 53-67
ISSN1939-1382
DOIs
StatePublished - 2017

Bibliographical note

CBS Library does not have access to the material
Published online: 8. November 2016

    Keywords

  • Learning analytics solutions, Dyslexia, University students, Reading difficulties, Open learner modeling

ID: 45710783