Talk: Science-based adaptive learning improving educational outcomes at all levels of education
In this talk, Hedderik van Rijn will discuss the SlimStampen/MemoryLab adaptive learning system which is in use with 2 million students
In this talk, Hedderik van Rijn will discuss the SlimStampen/MemoryLab adaptive learning system which is in use with 2 million students. The SlimStampen/MemoryLab system is based on computational memory theories, tracing the knowledge states of individual elements studied by the learner.
By presenting the items just before they are forgotten, optimal spacing is obtained, increasing scores on post-test – both in the lab and in classroom settings – by 10 to 20%. We have extended this system to allow for the assessment of Mastery of the knowledge materials, allowing this tool to be used as an alternative to formative testing of declarative knowledge. Based on collaborations with large international publishing houses (e.g., Noordhoff’s Infinitas Learning, Klett und Balmer), a large dataset of study materials is collected that are used to refine the adaptive learning system, and propose alternatives to existing computational memory models, bringing the research to full circle.
This activity may count towards your Continuing Professional Development (CPD) if relevant to your situation.
About the trainer
Prof. Hedderik van Rijn is chair of Cognitive Science and Neuroscience at the University of Groningen, The Netherlands.
Also read
-
Workshop: Building trust and safety in the classroom
This interactive workshop explores the link between psychological safety and high-performance standards, drawing on Amy Edmondson’s research and your own real-life experiences.
12 May -
Workshop: Fostering teacher well-being through nature connectedness
In this workshop, we'll explore different scientifically established pathways to conscious nature connectedness that will help you get the best out of being in nature and aid your well-being.
13 May -
Workshop: Playing with ChatGPT
Hello it’s me… ChatGPT: What exactly are Large Language Models and what challenges and opportunities do they bring for teaching at university?
20 May