Learning Analytics: Harnessing Data to Power Educational Outcomes
The Wisconsin Idea is one of the deepest and longest-held principles surrounding the University of Wisconsin: that education should influence people’s lives beyond the boundaries of the classroom. The Masters in Learning Analytics program empowers graduates to impact teaching, learning, and policy by harnessing vast amounts of educational data. This program is intended to help students break down this ‘big data’ into dynamic analyses that will help guide decisions and improvements in education to bridge the equity gap. Coursework equips students with the foundational knowledge and skills necessary to successfully navigate the educational data mining landscape: A focus on both quantitative and qualitative courses provides balance and trains students to make calculated analyses and have meaningful conversations. Students will learn the theoretical perspectives on learning, cognition, and ethical decision-making, as well as practice applying and adapting analytic methodologies and tools. This 24-month program includes a capstone project that partners students with an educational organization, providing the opportunity to practice and present real-world data. The program is committed to bridging the equity gap in education; learning analytics is the first step to do so.
Is this program right for you?
The Masters in Learning Analytics is a convenient, fully online education program offered through the Department of Educational Psychology in the School of Education at the University of Wisconsin-Madison. In just two years, working professionals can complete this Master of Science in Educational Psychology degree in one of the leading educational psychology departments (as listed in the rankings of the U.S. News & World Report’s edition of best graduate schools).
Interested?
Join us for a live informational webinar on August 12, 2020 at 4:00 pm (CST). The Program Director will provide a program overview, discuss admissions requirements, and answer your questions.
Program Overview
Format
Online
Program Type
Masters degree
Commitment
24 contiguous months beginning in summer
Credits
30 graduate credits
Prerequisite Courses
None
Tuition
$1,000 per credit for residents & non-residents
Application Deadline
Rolling admissions close May 15
For complete application details, visit the UW-Madison Guide
International Eligible
Yes. Classification of Instructional Programs (CIP): 42.2806. More information: international students
Offered By
Degree Conferred
Master of Science in Educational Psychology, Learning Analytics option
A Message From Our Chair
"Between the exciting curriculum emphasizing effective use and interpretation of cutting-edge integrated methodologies, the opportunities to interact with and learn from the world-renowned faculty, and the accessibility and convenience that can only arise from an entirely online program, the Masters of Learning Analytics at UW-Madison provides a truly world-class education, and an educational experience unlike that of any other program available."
James Wollack, Department Chair
Leader in inclusion and equity
The School of Education is a diverse and inclusive campus leader of academic programs that focus on equitable solutions and innovative research through the Office of Equity, Diversity, and Inclusion.
VISIT THE OFFICE OF EQUITY, DIVERSITY, AND INCLUSION
The Power & Promise of Learning Analytics
"Learning Analytics provides researchers with exciting new tools to study teaching and learning. Moreover, as data infrastructures improve — from data capture and analysis, to visualization and recommendation — we can close the feedback loop to learners, offering more timely, precise, actionable feedback. In addition, educators, instructional designers and institutional leaders gain new insights once the learning process is persistent and visible."
Society for Learning Analytics Research (S0LAR)
"Whether educational data is taken from students’ use of interactive learning environments, computer-supported collaborative learning, or administrative data from schools and universities, it often has multiple levels of meaningful hierarchy, which often need to be determined by properties of the data itself, rather than in advance. Issues of time, sequence, and context also play important roles in the study of educational data."
The International Educational Data Mining Society (IEDMS)
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