Using data to organise education smarter and more personalised
Using data in vocational and education training schools, universities of applied sciences and research universities offers opportunities to organise education smarter and personalise education for learners. The three sectors have similar needs in that area: how can the use of learning data, learning analytics and AI contribute to personalising education? How do we improve automated feedback delivery, improve study advice, curriculum construction and educational research using learning data? And how can the use of data and AI provide insights for effective interventions?
For each type of education, institutions are looking to work together. There are also more and more issues where an individual institution is not getting anywhere. As a result, there is a growing need for agreements around legal and ethical frameworks, an autonomous and flexible digital infrastructure, control over data and shared, proven approaches. By sharing knowledge and experiences, there is no need for everyone to reinvent the wheel. In this way, institutions are better able to monitor learners’ wellbeing, progress and risk of dropping out (student success) and respond with targeted interventions. Learners gain insight into their own learning process and tools to guide it. Lecturers are better able to increase the effectiveness of their teaching. Researchers use data as a source for evidence-informed educational innovation. Lifelong learning and the transformation hub Agile and efficiently organised education are supported by the use of data.
Who are we doing this for?
Learners
Lecturers
Researchers
Student counsellors
Policy advisors
Knowledge bank
Practical case: Research is key to successful educational innovation
This practical case shows how Utrecht University approached research into the willingness of teachers to change. To make educational innovation successful, it is important to involve the teachers. Which research methods can you use for this, how do you set this up and how do you monitor the results? Mabelle Hernández and Sebastiaan Steenman (UU) explain this in this document.Collaboration SURF and Kennisnet
An ecosystem for digital educational resources that meets the public values important to the sector. This is what SURF, Kennisnet and Npuls will be working on over the next few years.What would we like to achieve?
The pilot hub Data and AI aims to have a strong, active national network around the topics of data and AI in two years’ time. Within this network, different communities can share knowledge, collect best practices and translate questions from the sector into concrete products and services. The team of the pilot hub will actively connect and support existing communities, and develop products and services together with them -and other (market) parties.
Stay up to date
In the sprint presentation of the pilot hub, we bring you up to date on the latest developments in Data and AI. Would you like to attend the next sprint presentation? Join us via the link below. There you can also replay previous sprint presentations.
