We use network science and data analysis to decipher collective phenomena at biological and social scales
We work at the frontier of political sciences, sociology, and cognitive sciences on the one hand, and mathematics and computer sciences on the other. We rely on massive web, social media, and survey data, aided by High Performance Computer Clusters. We bring these models and tools to the study of epistemically-demanding phenomena occurring in large algorithmically-mediated social and political systems. Several of the phenomena that we study, relate to disorders of digital public spaces: fragmentation, concentration, polarization, epistemic drift in internet communities.
The "Teachers as Researchers" programme: Citizen science to engage educators in the production of structured practice-based evidence at a large-scale
Every day, millions of educators try out new practices to improve education. To be effective, they need to build upon each other’s successes and failures. However, collaboratively producing evidence about their practices that can be trustworthy, compared across contexts, and aggregated at a large scale is challenging.
Since 2019, we are developing the “Teachers as Researchers” programme, a citizen science project to engage educators in the collaborative production of practice-based evidence as they daily experiment with new educational practices.
The "Teachers as Researchers" programme trains volunteer educators to create communities and to facilitate regular workshops in which community members follow a methodology designed to motivate collaboration and reflection about their practices while at the same time producing structured records of practice-based evidence. The work of communities is undertaken in a collaborative publication platform to promote wide collaboration across communities and to feed a shared and public database of practice-based evidence (https://plateforme.profschercheurs.org).