Learning Analytics
Learning analytics is acknowledged to be a key aspect of the future of technology-enhanced learning environments. The data generated by these platforms and other systems (e.g., EEG or eye-tracking) can inform the design of these environments (e.g., multimedia resources), instructors seeking to make informed data-driven decisions (e.g., early warning systems), and students seeking a personalized learning experience (e.g., recommendation systems). Using complex quantitative methods from disciplines like computer science, statistics, and cognitive sciences, graduates of this certificate program will be prepared to transform learning experiences in the 21st century by managing, analyzing, visualizing, and interpreting complex learning data. Completers of this certificate program will be competitive candidates for educational technology software and online learning companies in need of data scientists or designers who can use data to make informed decisions.
Students may only start this certificate in the Fall semester and classes must be taken in the order listed to the right under Required Courses.
Required Courses
- EDF 6400: Quantitative Foundations in Educational Research: Overview (Offered every Fall by Research & Evaluation program)
- EDF 6402: Quantitative Foundations in Educational Research: Inferential Statistics (Offered every Spring by Research & Evaluation program)
- EME 6651 Learning Analytics Concepts and Techniques (Spring 8W2; See Ed Tech Course Calendar)
- EME 6637: Managing and Analyzing Multimodal Educational Data (Summer 8W1; See Ed Tech Course Calendar)