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.
Careers:
Data analysis represents one of the fastest growing career paths, and employers in the education sector are increasingly looking to hire individuals with the skills to make data-driven decisions. The Master of Science in Learning Analytics prepares researchers and professionals for a range of careers in:
-Education technology companies and startups
-Educational evaluation
-Educational think tanks
-Data groups in city, state, and federal departments of education
TOEFL: Minimum score requirement: 100 internet-based test (IBT)
IELTS: Minimum score requirement: 7.0
GRE: required
序号 | 课程介绍 | Curriculum |
1 | 教育数据挖掘核心方法 | Core Methods in Educational Data Mining |
2 | 学习分析:过程和理论 | Learning Analytics: Process and Theory |
3 | 数据、学习与社会 或 网络和在线学习 | Data, Learning, and Society or Networked and Online Learning |
4 | 管理教育数据 | Managing Educational Data |
5 | 特性工程工作室 | Feature Engineering Studio |
6 | 人类认知与学习 | Human Cognition and Learning |
7 | 教育心理学 | Educational Psychology |
8 | 视觉解释 | Visual Explanations |
9 | 媒体心理学 | Psychology of Media |
10 | 指导研究与实践 | Supervised Research and Practice |