Stanford University

Overview

The M.S. in Education Data Science at Stanford University uniquely integrates data science techniques with educational research. This program is designed to empower students to analyze learning processes, evaluate educational interventions, and foster evidence-based decision-making. Offered as a full-time, on-campus study option, the curriculum emphasizes both research and practical experiences to equip graduates with the skills necessary for success in the field of education data science.

What you'll study

Format: The program spans two years of full-time, on-campus study, featuring a blend of core coursework and applied research initiatives.

Indicative course areas include:

• Natural Language Processing
• Network Science
• Experiments and Causal Methods
• Measurement
• Learning Analytics

Applied components: Students engage in original research projects and may have opportunities for internships or other practical experiences, contingent on program requirements and availability.

Capstone/research requirement: Completing original research is a fundamental component of the degree, ensuring students develop a deep understanding of education data science.

Entry requirements

While specific GRE/GMAT scores and minimum GPA requirements are not detailed, applicants should prepare to submit a comprehensive application package that includes:

• Application Form
• Application fee (non-refundable)
• Statement of Purpose
• Resume/CV
• Three Letters of Recommendation
• Transcripts from previous academic institutions

Career prospects

Graduates of the M.S. in Education Data Science are well-prepared for a variety of roles in the educational sector, including data analyst positions, educational consultants, and research roles within academic institutions and educational technology companies. The skills acquired through this program also equip alumni to contribute to policy-making and the evaluation of educational programs, ensuring they can make a significant impact in the field of education.