In 2016 the Norwegian Ministry of Education and Research awarded funding for the establishment of the interdisciplinary Centre for the Science of Learning & Technology (SLATE), a national competence and research centre which contributes to international research and national competence development on the use of data and data approaches in understanding education and lifetime learning. As such SLATE carries out research that will clarify and explore concepts such as learning analytics, big and small data in education, assessment for learning, and learning & technology in all facets of human learning. SLATE draws together researchers from various disciplines, and thereby conducts integrated research that will advance the frontiers of the sciences of learning, as well as inform education practice and policy.

MANDATE from the Ministry of Education and Research:


  • SLATE shall carry out research of high quality on learning analysis*.

  • SLATE shall be an R&D unit that contributes to national competence and knowledge development withing learning analytics.

  • SLATE shall map and be a central resource for the possibilities and challenges related to the use and research on learning analytics in Norway.

  • SLATE shall be internationally oriented and seek relevant international collaboration within learning analytics.

  • SLATE shall through its R&D activity develop and disseminate knowledge to the relevant actors in the Educational sector.

  • SLATE shall through seeking collaboration influence competence development within the learning analytics discipline in other milieu in the Higher Education sector.


The long term ambition is that SLATE will develop into a broad milieu for the learning sciences by drawing together an even larger spectrum of relevant disciplines such as cognitive psychology, pedagogy, information/computer science, statistics, sociology, design, development psychology, and neuroscience.


*learning analysis covers the use of data and data approaches in understanding learning, including Learning Analytics and Knowledge (LAK), Education Data Mining, and Big Data in Education, as well as perspectives from the sciences of learning