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For several years EDIA has collaborated with various companies to promote and improve the use of adaptive learning across digital education. We do this through AI and machine learning techniques which allow traditional content, like books and articles to be converted into digitally tagged and classified content which can be used to achieve fully personalized and adaptive learning.

EC LOGOOur most recent success has been working with the EU Horizon 2020 iRead project, which is due for completion in 2020. The iRead project involves 14 companies across 8 European countries and develops personalized technology to help primary school children to advance their reading skills. The goal of the project is to fast-track innovation processes related to the development of literacy based technology, while targeting a key skill for primary aged children which can have long term effects on later learning. 

What is iRead?
iRead has 3 components – a reading game app, a child-centric eReader device and a content classification component which allow teachers and students to easily access reading material which matches a child’s reading ability. These were designed by 3 separate EdTech partners specialising in these fields. EDIAs APIs allow these three applications to operate seamlessly together. 

Reading Game App

Child Centric e-reader

iRead also involves an ‘English as a Foreign Language’ component as well as provisions for students with dyslexia and other learning difficulties.

How does EDIA help?

At EDIA we use machine learning algorithms to find and classify content according to different criteria. This makes finding appropriate content simple, even within massive digital libraries. For this reason EDIA focused heavily on the content classification component of the project, ensuring that teachers and children can easily find age-appropriate content.

To do this EDIA build a machine learning algorithm to identify the appropriate reading age of children’s texts. The iRead software can then match appropriate content with the student’s age and learning needs.

In order to develop a machine learning algorithm, EDIA determined quantitative, linguistic, syntactic and word difficulty metrics which when combined, constitute appropriate age levels. Once these standards were developed, a neural network was ‘trained’ to predict the appropriate age range of various texts, based on these standards.

For each age level, the neural network was trained on around 100 texts which matched the level. The resulting AI model can then automatically classify any new text it is given, according to age appropriateness. Each text was given a minimum and maximum age, creating a range of appropriate ages for each text. Once the model was trained, its results were extensively validated manually.

The AI model is on average within 0.5 years accuracy for both maximum and minimum ages, which is considered a good result.

EDIA also worked to develop APIs allowing this machine learning to be integrated into all the iRead applications. At EDIA we specialize in providing technology which can be integrated into all sorts of different software solutions. 

What does this look like?

While the technology of AI may seem confusing, for the user the results are very simple. Within the iRead product, each child has a dynamic profile which helps them (and their teachers) to select future content. Based on the child’s age, appropriate content is filtered from the entire iRead library.

For example, a child of 9 years old would have access to content in the range of 8-9 years. From this sub-selection, the piece of content with the best match of linguistic and syntactic features indicated by linguistics is selected. This selected text is then delivered to the iRead reader app. The child receives a piece of content selected according to their personal needs.

What’s coming next?

The iRead project is now entering its final stage and is being evaluated in schools and families. However, the project also welcomes the support from other organisations in the EdTech industry. If you want to learn more about opportunities to work with the iRead project team, contact Noel Duffy from Dolphin Computer Access Ltd

iRead will be exhibiting at the annual BETT conference in London, allowing interested parties an opportunity to observe the project in action. 

To learn more about the development of personalized learning for your customers, reach out to Walter Montenarie at EDIA. 

flag_yellow_highThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 731724.
This article reflects only the author's view and that the Agency is not responsible for any use that may be made of the information it contains.

About EDIA
EDIA education technology was founded in 2004 and is based in Amsterdam, the Netherlands. In 2006, EDIA launched its first AI product for education, which used machine learning and natural language processing to curate online text sources for vocabulary training. The product won several international awards and is still widely used today. In recent years EDIA transformed into a SaaS platform by applying Artificial Intelligence technology to analyse text.

To learn more, schedule an appointment with EDIA sales team today at https://www.edia.nl/contact.

Topics: AI in Education, metatagging, personolised learning, smartcontent

Mark Breuker

Written by Mark Breuker

Mark Breuker is EDIA's Managing Director and has been working on EdTech at the intersection between business and IT for over 10 years.