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Start Your Career in Data Science
Study with a faculty of internationally recognized experts and work with real-world data collected from operating online and digital learning environments in the K-12 and post-secondary sectors.
Notice the Big Data trend in the corporate world?! We have!
Join a growing field and apply to the Learning Analytics program.
The Learning Analytics Capstone Expo 2024
The annual learning analytics program capstone expo took place on August 21st. The event allowed for current students to showcase their projects. This event was held in a virtual environment using a platform called Gather. Please read more to see the capstone project titles and descriptions.
Welcome to the Learning Analytics program
The Learning Analytics program prepares graduate students to make data-driven decisions about education using quantitative methods drawn from computer science, statistics, and cognitive science. We study the "big data" generated by online and digital learning environments and develop new insights that benefit students, teachers, and administrators. Our students learn analyses methods through coding, statistical model building, and visualization as well as relevant policy, legal, and ethical issues involved in conducting analysis on education data. Graduates of our masters program pursue jobs in educational technology companies and startups, think tanks, and governmental data groups.
STUDENT PROJECTS
Our students complete an integrative capstone project that draws on the perspectives and skills acquired during their studies.
Predicting State Test Scores at Imagine Learning
Katherine and Qingying built models of student state test performance to predict which students might benefit from extra help.
Using Learning Theories to Inform Game Design at Teachley.com
Anna and Xixuan investigated how learning design principles can be used to assign difficulty levels within an online educational math game at Teachley.
Pattern Mining of Eye Tracking Data at Okimo
Yun and Haogang investigated student eye tracking data to identify patterns that might provide useful markers of student reading level at Okimo.
Developing Personalized Learning Strategies at Learnabi
Lena and Mandy developed a personalized learning strategy including data and UX design at Learnabi.
Pattern Mining of Log File Data at Squiggle Park
Sihan and Linjin analyzed log files for patterns in student reading performance at Squiggle Park.
Automated Project Based Learning Recommendations for Teachers
Sherry and Victoria designed a system for automated recommendations of project based learning lessons for teachers at Camino Education.
Geospatial Mapping of Student Performance
Melissa and Eli identified geographical patterns in student performance data at MarGrady Research.
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Admissions Information
Application Requirements
- Master of Science