Project description
The ABCs of personalised reading education
Millions of children face significant hurdles in acquiring and developing essential reading abilities. Children with different abilities and linguistic backgrounds often encounter barriers that hinder their reading progress. Whether it be dyslexia, language barriers or diverse learning styles, the need for tailored approaches becomes evident. Traditional educational systems struggle to provide individualised support to address these unique needs. In this context, the EU-funded iRead project aims to develop a groundbreaking software to support the teaching and learning of essential reading skills. This scalable, cloud-based software infrastructure will harness the power of personalised, adaptive technologies and a diverse array of applications. By incorporating adaptive support, the project seeks to deliver a truly personalised experience, fostering optimum learning outcomes for each student.
Objective
The overarching aim of the iRead project is to develop a software infrastructure of personalised, adaptive technologies and a diverse set of applications for supporting learning and teaching of reading skills. The specific goals of the project proposed are to:
1. Develop a scalable, cloud-based software infrastructure of open, interoperable components, including real-time user
modelling and domain knowledge components, to support learning of reading skills by children with different abilities and
linguistic backgrounds
2. Develop domain models for English, Greek, German and Spanish learners, and to contextualise those models with
respect to skills and difficulties of (i) typically developing readers, (ii) English and Greek readers with dyslexia and (ii)
learners of English as a Foreign language. The domain models will utilise and generalise the domain model
implemented in a previous FP7 project – iLearnRW
3. Develop applications for supporting learning (literacy games, interactive e-books, Reader app) that utilise the
infrastructure to yield different types of personalised learning services and experiences
4. Develop and evaluate personalised content classification metrics that “enable reading” for use by electronic publishers
and libraries
5. Enable orchestrated use of the learning applications (games, e-books, Reader app) based on learning analytics, and a
personalised experience through adaptive support
6. Implement a number of large-scale evaluation pilots across European countries and providers in order to evaluate the
pedagogical effectiveness of the iRead ecosystem.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- humanitieslanguages and literaturegeneral language studies
- social scienceseducational sciencesdidactics
- natural sciencescomputer and information sciencescomputer securitydata protection
- social scienceseconomics and businessbusiness and managementemployment
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Programme(s)
Funding Scheme
IA - Innovation actionCoordinator
WC1E 6BT London
United Kingdom