Revita tries to emulate a good teacher. A good teacher knows: 1. the subject domain, 2. the students, 3. how to teach — given what we know about each learner, what are the best exercises to offer to them next, to optimize the learning outcomes.
In Educational Data Science, this is done by:
We aim to address both written and oral skills. For oral skills, the research lab is developing new components to analyze the students' ability to process spoken language. This will allow us to test hypotheses about the mechanisms for processing of audio input by learners, and to create components to train this ability by following a personalized path for each student.
For additional information, please consult the Project's publications.
Also, please feel free to contact the Revita team directly!
Revita builds on resources and tools developed by our many international colleagues and collaborators.
With our collaborators we develop components to support learning various languages.
Some important resources that Revita builds upon, and content providers, who have granted us permission to use their resources:
The Revita Project is supported in part by: