Open Science: Citizen Science and Open Educational Resources

15 April 2025 10:00 - 14:00
Max Planck Institute & online
Auditorium 163
Workshop
MEDAL logo
On April 15th at 10:00 hrs. we will have the final Open Science workshop! On popular demand, the themes of this workshop will be Citizen Science and Open Educational Resources, two very important topics when it comes to making science accessible to the whole population. We will have talks and a discussion with experts Yvonne Kuiper (Donders CityLab), Marc van Oostendorp (Radboud University) and Monique Schoutsen (Radboud University Library). Stay tuned for the precise schedule.

About the instructors

Yvonne Kuiper is the brain behind the Donders CityLab, a Citizen Science initiative of the Donders Institute in Nijmegen, committed to bringing research out of the lab and towards the public.

The latest initiative of the Donders CityLab is the Brain MuseumYou can read more about the Donders CityLab and the Brain Museum here.

Marc van Oostendorp is Professor of Dutch and Academic Communication at the Centre for Language Studies, Radboud University.

He teaches both classes on theoretical and applied linguistics, as well as courses on writing articles aimed at general audiences. Learn more about his work here or check out his YouTube channel here.

Monique Schoutsen is an information specialist and the coordinator of information skills and Open Education at the Radboud University Library.

You can read more about Open Educational Resources from Radboud University here.

 

Please click here to register!

 

About MEDAL

This is a workshop organised by Methodological Excellence in Data-Driven Approaches to Linguistics (MEDAL) is an international consortium initiated by the University of Tartu in Estonia, in collaboration with the Max Planck Institute for Psycholinguistics and Radboud University in the Netherlands and the University of Birmingham in the United Kingdom. Financed by the EU Horizon Europe programme (101079429) and UK Research and Innovation organisation (101079429). MEDAL’s mission is to build expertise in data-driven linguistics methodology among early-career researchers. Read more about MEDAL here.

 

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