Development of Natural Language Queries Embedded Within a School Data Hub to Support Data-Informed Decision-Making by School-Based Practitioners

The University of Toronto Schools (UTS), through the Eureka Research Institute, is committed to advancing data-driven decision-making in K-12 education. This aligns with the growing recognition of the importance of data literacy in education, where students and teachers need to “read the world with data” and “write the world with data” (Louie, 2022). Recent research highlights that educators require user-friendly data tools that minimize the technical expertise needed to interact with educational data (National Academies of Sciences, Engineering, and Medicine, 2023). By integrating Natural Language Query (NLQ) capabilities into the Data Hub, this project enhances the ability of teachers and administrators to engage with school-wide data more effectively, supporting student performance analysis, curriculum planning, and intervention strategies.
This research will have a broader societal impact by making data-driven insights more accessible, ensuring equitable and effective educational strategies for student success.

Faculty Supervisor:

Steve Engels

Student:

Partner:

University of Toronto Schools

Discipline:

Computer science

Sector:

Education

University:

University of Toronto

Program: