O Projeto "Ciência de dados na Educação Pública" foi apresentado na Universidade de Stanford a convite do Lemann Center for Educational Entrepreneurship and Innovation in Brazil

Português, Brasil

O Projeto "Ciência de dados na Educação Pública" foi apresentado na Universidade de Stanford a convite do Lemann Center for Educational Entrepreneurship and Innovation in Brazil. O projeto foi apresentado no dia 29 de setembro de 2020 pela professora Dra. Karla Esquerre, coordenadora do projeto e docente do DEQ / PEI - EPUFBA.

O link para acesso do seminário completo é https://lemanncenter.stanford.edu/events/data-science-public-education.

Data Science on Public Education

Data Science on Public Education is an initiative that aims at helping students of public schools to empower themselves. These students, mostly low-income and African descendants, receive economic and educational support to develop data-driven and scientific thinking skills. Furthermore, their background and voices are integral parts of their learning experience. Students were brought closer to STEM related subjects while working with a curriculum without the barriers that traditionally separate statistics and other disciplines. Data Science, Artificial Intelligence and Social leadership were connected with school, community and city related issues. Results are already visible as the students display more confidence, positive self-esteem and a disposition to become agents of social change. However, in order to achieve a permanent change in their schools, faculty staff has also been tutored about real world Data Science and Artificial Intelligence applications as well as social justice efforts. At an even bigger scale, four e-books are being written and a website is being developed and will be available for students and teachers. We hope that the integrated leadership between schools, universities and communities promotes the creation of new educational territories and contributes to the contemporary processes of reversal of social, racial and gender disparities.