Maria Rauschenberger is awarded wth the fem:talent Scholarship 2017 for her research on Dyslexia.
The University of Applied Science Emden/Leer has awarded for the second time promising students and Ph.D. fellows with the fem:talent Scholarship. The students have to already succeed in their field of expertise or are expected to succeed in the future. The fem:talent Scholarship provides a financial support for a year and a pool to exchange ideas and support.
Maria Rauschenberger has received the fem:talent Scholarship twice for her research on “playful and early approach to screen children with dyslexia while playing a game”. She will be continuing her work in the next year. “I am very happy to be supported from Emden for the next phase of my Ph.D. topic. This will be hopefully very helpful for children with dyslexia in the future.”
Do you wanna support the research on Dyslexia?
The research project is looking for children between 8 and 12 years old with dyslexia and without dyslexia. Only a computer or a tablet, headphones, and Internet are needed.
Participants can be native speakers of English, Spanish or German.
Maria’s advisors are Ricardo Baeza-Yates Professor at Universitat Pompeu Fabra & CTO of NTENT and Luz Rello Special Faculty en Cargenie Mellon University & Fundadora de Change Dyslexia. Also, special thanks to Prof. Dr. Jörg Thomaschewski from the University of Applied Science for his mentoring.
With your collaboration, you would help our research immensely. The goal of our research is to contribute to the development of support tools for dyslexia in English.
Participants would have to play for 5-10 minutes the game MusVis (see Screenshot). This game explores how musical and visual elements have an impact on children with and, without dyslexia. We are looking for children between 8 and 11 years old. Only a desktop or laptop computer OR tablet, headphones, and Internet are needed.
Please if you would like to participate – leave your contact details and we contact you with the study details. Duration only 5 – 10 Minutes.
The prototype was designed with the help of five children and five parents who tested the game and the results of the usability study have been presented this year at the research conference Web for all (W4A) in Australia in April.
Title: Prediction of Dyslexia from Maria Rauschenberger from Web Research Group (WRG)
In regards to the #ESCOLA (22 February 2017) the Universitat Pompeu Fabra (UPF) welcomes the polytechnic School at the Poblenou Campus of Pompeu Fabra University.
Maria Rauschenberger presented the new prototype of MusVis to around 100 students at the ESCOLAB 2017. MusVis is a research application and aims to analyze how people with and without Dyslexia perceive music and visual elements.
Please leave your contact if you would like to participate!
Abstract: Dyslexia is a specific reading disorder, which is probably caused by the ‘phonological skills deficiencies associated with phonological coding deficits’ (Vellutino, Fletcher, Snowling, & Scanlon, 2004). A person with dyslexia has visual and auditory difficulties that cause problems in reading and writing (Deutsches Institut für Medizinische Dokumentation und Information, 2008). Dyslexia is frequent: worldwide, about 10% of the population and from 5 to 12% of the German students have dyslexia.
The problem is that children with dyslexia can learn the spelling of words or decode words for reading but they need more time to practice. For example, two years instead of one for learning how to spell phonetically accurate words (Schulte-Körne, 2010).
Therefore we will first show the power of misspellings for intervention and how a game can help children to decrease their spelling mistakes. We will present the annotation of the errors, the creation of the exercises, and the Dyseggxia application in German.
In contrast to the intervention with misspellings – linguistic features have also the power to predict the risk of dyslexia for children. Therefore the linguistic features which are implemented in the game Dytective will be presented.
Finally, we show the concept of a possible and different approach of ‘How to predict dyslexia without linguistic features’.