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ILearnRW

Financiado

Cerrado

Integrated Intelligent Learning Environment for Reading and Writing

The aim of the project is to contribute towards a move away of traditional assistive software which uses a computer simply as an alternative to pen and paper and develop next generation learning software which uses a computer to f... ver más

30/09/2015

DOL

2M€

Presupuesto del proyecto: 2M€

Líder del proyecto

DOLPHIN COMPUTER ACCESS LTD No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 9 Participantes

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2015-09-30 No tenemos la información de la convocatoria

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

9 Participantes

DOL

0.00€ | Lider

UNIVERSITY OF MALTA

N.D. | Participante

UNIVERSITY COLLEGE LONDON

Youthworks Consulting ltd

N.D. | Participante

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Líder del proyecto

DOLPHIN COMPUTER ACCESS LTD No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 2M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto The aim of the project is to contribute towards a move away of traditional assistive software which uses a computer simply as an alternative to pen and paper and develop next generation learning software which uses a computer to facilitate the learning process for children with dyslexia and/or dysorthographia. The ILearnRW learning environment will demonstrate the following features: 1. User modeling. A profile for each learner should be built. The profile should include, among others, the type of dyslexia and the errors the user is most likely to make. 2. Teaching strategies. The interaction of a learning system with a child should be based on a teaching strategy that supports the individual user in fulfilling her specific learning goals. 3. Classification of learning material. Content classification must be a major component in any content management system. To think about it, a tutor helping a child to learn reading/writing always selects appropriate learning material based on the child's needs and capabilities. 4. Personalized content presentation. If we know the errors the user is likely to make, we can enrich the text presentation with visual cues by combining highlighting, text-reformatting and word segmentation. In addition, the type of dyslexia should also influence the presentation. 5. Engaging learning activities. High degree of learner engagement is sought in any learning activity. To achieve this goal, we integrate learning activities into serious games. A creative game scenario, coupled with a positive reinforcement mechanism, will extend child's engagement. 6. Evaluation of learning. When a game is coupled with a game usage logging mechanism, data collected related to the user's actions may lead to a quantitative assessment of learning. 7. On-line resource bank. Coherent collections of data which support specific teaching strategies should be accessible to learners and educators. The ILearnRW environment will support the English and Greek languages

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