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Enhancing Educational Business Intelligence with Predictive Analytics and LLM-Driven Insights
This project aims to enhance the data analytics capabilities of an educational software company by upgrading its existing Business Intelligence (BI) system. Currently, the system mainly shows past trends, requiring educators to manually interpret data to spot issues like students at risk of failing. The research will integrate predictive machine learning models to forecast these risks earlier and use Large Language Models (LLMs) to automatically generate clear, plain-language insights from the data. The expected benefit to the partner organization is a more powerful and proactive analytics product that helps schools make faster, data-driven decisions, strengthening the company’s competitive edge in the educational technology market.
Faculty Supervisor:
Ajmery Sultana
Student:
Partner:
Plurilogic
Discipline:
Computer science
Sector:
Information and cultural industries; Manufacturing
University:
Algoma University
Program:
Business Strategy Internship
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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.