Data science can be used in higher education both to forecast the final grades of the students considering continuous evaluations and to help students to perform their tasks when the teacher is not with them. These two use cases can help both students and teachers to improve the learning experience. 

This webinar will help attendees learn about: 

 Final grades forecasting in higher education from continuous grades 

 Intelligent Tutoring Systems to help zooarchaeology students to classify animals from bone fragments in Middle Palaeolithic excavation sites

 Analyzing educational data from a sex and gender perspective

Local ODSC chapter in London, UK

Instructor's Bio

Laia Subirats

Data Science researcher at Eurecat

Laia is a part-time lecturer at the Open University of Catalonia too. She holds an MSc in Telecommunications Engineering from Pompeu Fabra University, an MSc in Telematics Engineering from the Technical University of Catalonia, and a Ph.D. in Computer Science from the Autonomous University of Barcelona. Since 2006, she has worked in the field of research and innovation, and since 2016, she has also been a lecturer at the university. She has worked in national and international centers (Eurecat, Telefónica R&D, and European Organization of Nuclear Research (CERN)), as an expert evaluator for the European Commission, and in initiatives such as the Google Summer of Code. She has participated in collaborative national and international research projects, and she has been a speaker at different courses, conferences, and congresses. She is interested in spreading science and in encouraging women to pursue technical careers.


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    ON-DEMAND WEBINAR: Intelligent Tutoring Systems in higher education

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