The Unizin Data Platform (UDP) provides an extensive resource for teaching and learning data at the University of Michigan. This poster introduces the synthetic dataset created within the UDP. This dataset simulates realistic student and course information, allowing researchers, developers, and learning analytics practitioners to experiment and innovate without compromising real student data.
Designed to represent a university with 10,000 students over multiple semesters, the synthetic dataset offers a secure environment for exploring the UDP data model and developing prototypes for learning analytics visualizations, applications, and reports. Because the synthetic data format mirrors real data, this approach facilitates the transition from prototype to real-world application by easily switching the connection from synthetic to actual data.
This poster will provide an overview of the synthetic dataset, illustrating how it supports safe and effective innovation in data science and research. By leveraging this resource, U-M IT professionals can explore new possibilities in learning analytics, contributing to improved educational outcomes and informed decision-making.