Master of Science (M.S.) in Learning Analytics
Your graduate studies in our program will train you to understand key learning analytics and educational data-mining (LA/EDM) methodologies and apply them to real-world problems across a variety of learning environments. In addition to learning about relevant policy, legal, and ethical issues involved in conducting analytics on educational data, you will be challenged to use learning analytics methods to change education for the better.
Sample Syllabi:
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
Admission Information
Displaying requirements for the Spring 2025, Summer 2025, and Fall 2025 terms.
Master of Science
- Points/Credits: 32
- Entry Terms: Fall
- Enrollment Formats: Full-Time Campus-Based, Part-Time Campus-Based
Application Deadlines
| Entry Term Available | Priority Deadlines | Final Deadlines | Extended Deadlines |
|---|---|---|---|
| Spring | N/A | N/A | N/A |
| Summer | N/A | N/A | N/A |
| Fall | January 15, 2025 | April 1, 2025 | N/A |
Select programs remain open beyond our standard application deadlines, such as those with an extended deadline or those that are rolling (open until June or July). If your program is rolling or has an extended deadline indicated above, applications are reviewed as they are received and on a space-available basis. We recommend you complete your application as soon as possible as these programs can close earlier if full capacity has been met.
Application Requirements
| Requirement | |
|---|---|
| Online Degree Application, including Statement of Purpose and Resume | |
| Transcripts and/or Course-by-Course Evaluations for all Undergraduate/Graduate Coursework Completed | |
| Results from an accepted English Proficiency Exam (if applicable) | |
| $75 Application Fee | |
| Two (2) Letters of Recommendation |
For admission-related inquiries, please contact HUDadmission@tc.columbia.edu.
Requirements from the TC Catalog (AY 2024-2025)
Displaying catalog information for the Fall 2024, Spring 2025 and Summer 2025 terms.
Required Program Core Courses: (minimum of 5 courses for 15 points/credits)
-
HUDK 4050: Core Methods in Educational Data Mining
-
HUDK 4051: Learning Analytics: Process and Theory
-
HUDK 4052: Data, Learning, and Society OR HUDK 4011 Networked and Online Learning
-
HUDK 4054: Managing Educational Data OR HUDK 4031 Data, Testing, and Meritocracy
-
HUDK 5053: Feature Engineering Studio OR HUDK 5324 Research Work Practicum
Additional Courses in Learning (HUDK): (minimum of 3 courses for 9 points/credits)
Three courses with the HUDK prefix selected in consultation with your advisor:
Courses in Statistics (minimum of 2 courses for 6 points/credits) Also satisfies the College Breadth Requirement
-
HUDM 4122 Probability and statistical inference OR HUDM 4125 Statistical inference
-
HUDM 5122 Applied regression analysis
Students with prior coursework in statistics may place out of one or more statistics courses and consider these additional options:
-
HUDM 5026 Introduction to data analysis in R
-
HUDM 5123 Linear models and experimental design
-
HUDM 5124 Multidimensional scaling and clustering
-
HUDM 5133 Causal inference for program evaluation
-
HUDM 5199 Programming for data science
(Note that the two courses in statistics (HUDM) also satisfy the college breadth requirement.)
Capstone Project:
Students will complete an integrative capstone project, involving analysis with educational data to address a real-world problem or question.
For the M.S. degree, no transfer credit is granted for work completed at other universities.
Satisfactory Progress
Students are expected to make satisfactory progress toward the completion of degree requirements. If satisfactory progress is not maintained, a student may be dismissed from the program. Program faculty annually review each student’s progress. Where there are concerns about satisfactory progress, students will be informed by the program faculty. If a student is performing below expectations, remedial work within an appropriate timeline may be required. If satisfactory progress is not maintained, a student may be dismissed from the program. Further policy details can be found in the Teachers College Student Handbook: https://www.tc.columbia.edu/student-handbook/
Full-time Program
Students can apply for and be admitted to the full-time program in the fall semester only. This program takes up to 3 semesters of study.
For International Students on Visas: Each semester international students must maintain 9 points for full time status. In the last semester, they will need a “Reduced Course load” form signed by the Program Director.
For all students: In their last semester, students will need to submit an “Intent to Graduate” form early in the semester.