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Developing Human-Centred Methods to Optimize Machine Learning Fine-Tuning for Personalized Instruction in Education
This project will explore how large language models (LLMs), such as advanced AI systems that generate text, can be adapted to support education. The intern will design and test new ways of guiding these models using structured instructions (prompts and schemas) so that they provide clearer and more helpful answers for teachers and students. By testing these methods with human evaluators, the project will help create a foundation for a web-based platform that supports learning in real time. This collaboration will benefit both Canadian and Brazilian institutions by advancing Canadian-led innovations in educational AI, while ensuring they are tested and adapted to culturally diverse contexts. The work will also help reduce digital divides by improving access to advanced learning technologies across different regions.
Faculty Supervisor:
Vanessa Figueiredo
Student:
Partner:
Instituto Federal da Bahia
Discipline:
Computer science
Sector:
Artificial Intelligence
University:
University of Regina
Program:
Globalink Research Award
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Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.