The aim of the MANIP project-team is to improve machine perception of interactions between humans on the one hand, and the models and theories developed in the social sciences for education on the other hand. The expected outcomes are perceptive computational models, combining machine learning and statistical modelling, to describe teacher–students interactions within a CAC. These models will allow to validate, consolidate, or elaborate new models and theories on instructional science. They will offer empirically grounded knowledge about the concrete social conditions that shape students’ learning and thus will allow improving teachers’ pedagogical practices in the long run.
The MANIP project-team integrates within the Interaction, Perception and Usage (IPU) research axis. Research addresses multimodal artificial perception and modeling of social interactions between humans within a perceptive environment (the classroom).