M.S.Ed. Learning Analytics and Artificial Intelligence (Online)
About the Program
This fully online program prepares graduates to work as data scientists in research and development in areas such as at-risk prediction, and AI-based adaptive learning systems such as intelligent tutoring systems and educational recommender systems. You will emerge understanding when and why to use different methods for a range of applications in order to make a real-world impact.
Overview
Learning Analytics and AI uses educational data and modern algorithms to develop learning technologies that enhance student outcomes, support teachers and school leaders, and help identify and address gaps. The program teaches you the latest AI techniques, learning analytics algorithms and tools, as well as how to engineer data streams to turn raw data into features that are interpretable to humans and large language models (LLMs). Your use of contemporary methods will be grounded in the rich history of educational thought, with an understanding of how this grounding can support efforts to address challenges such as algorithmic bias to improve educational outcomes at scale.
This program can be completed within 16 months by following the recommended schedule (Fall, Spring, Summer, Fall), or students can enroll part-time and complete the program within two years. The program consists of coursework and a capstone project where students will develop projects with real-world relevance and of a quality that can be submitted as a demo or short papers to international conferences. The program is fully online (no in-person component) and will have a mixture of synchronous and asynchronous activities, with multiple sections/time slots for synchronous activities to accommodate students around the world.
Application deadline
Fall 2025 - Priority deadline February 1; rolling admission thereafter as space permits.
Entry term(s)
Fall, Spring
Course requirements
10 courses (8 required and 2 electives courses).
Typical course load
Fall: 3 courses; Spring: 3 courses; Summer: 2 courses; Fall: 2 courses and capstone.
Duration of program
16 months (full-time); 2 years (part-time)
Culminating experience
Master’s capstone project
Schedule
- Full-Time
- Part-Time
- Online
Modality
- Online
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