Educational Data Science, MS

2 Years On Campus Masters Program

University at Buffalo SUNY

Program Overview

The Master of Science in Educational Data Science at the University at Buffalo prepares students to use advanced data analytics and quantitative research methods to improve educational outcomes and influence education policy. The programme combines statistics, research design, measurement techniques and learning analytics, making it suitable for students interested in educational research, institutional assessment, policy analysis and data-driven decision-making, particularly in addressing educational inequalities.

Curriculum Structure

The programme requires 35 credits and typically takes 3–4 full-time semesters to complete. Students study core research and statistical subjects, select specialised courses in data analytics and measurement, and complete a final research project or thesis.

Year 1 – Research Foundations and Statistical Methods

Students develop foundational knowledge in educational research, statistics, human development and learning psychology. Core courses include Fundamentals of Educational Research (CEP 500), Statistical Methods I (CEP 522), Statistical Methods II (CEP 523), Psychometric Theory in Education (CEP 510), Human Growth and Development (CEP 541) and Psychology of Learning and Instruction (CEP 560). These subjects help students understand research methods, assess educational outcomes and analyse quantitative information.

Year 2 – Advanced Analytics and Research Applications

Students strengthen their analytical expertise through specialised courses in experimental design, multivariate analysis, large-scale database analysis and statistical modelling. Available subjects include Experimental Design (CEP 524), Applied Multivariate Analysis (CEP 525), Structural Equation Modeling (CEP 526), Analysis of Large-Scale Databases (CEP 527), Hierarchical Linear Modeling (CEP 528) and Applied Regression Analysis (CEP 529). Students complete their studies through an Individual Guidance Project (CEP 700) or Thesis (CEP 701), involving an original empirical research study under faculty guidance.

Focus Areas

Educational Data Science, Learning Analytics, Quantitative Research Methods, Statistical Analysis, Educational Measurement, Psychometrics, Experimental Design, Big Data Analysis, Educational Policy Analysis, Research Design, Multivariate Analysis, Regression Analysis, Educational Assessment, Learning and Instruction, Educational Equity.

Learning Outcomes

Graduates develop the ability to analyse large-scale educational datasets, apply advanced statistical methods, design research studies, evaluate educational assessments and interpret learning outcomes. They also gain expertise in identifying data biases, conducting empirical research and using evidence-based insights to improve educational policies, teaching practices and learning opportunities.

Professional Alignment (Accreditation)

The programme is offered through the University at Buffalo's Graduate School of Education, within the Department of Counseling, School and Educational Psychology. It is officially registered with the New York State Education Department (SED). No separate professional accreditation specific to the programme is listed on the official university website.

Reputation (Employability Rankings)

The programme provides rigorous training in quantitative research, educational measurement and large-scale data analysis. Graduates can pursue opportunities in local, district and state education departments, public and private research agencies, educational assessment organisations, schools, colleges and universities. The programme also prepares students for further doctoral research in educational data science. A programme-specific employability ranking or graduate employment rate is not published on the official university website.

Experiential Learning (Research, Projects, Internships etc.)

At the University at Buffalo, the MS in Educational Data Science program is designed to provide students with hands-on experiences that bridge theory and practice. You'll have access to state-of-the-art facilities and tools that enhance your learning and prepare you for real-world challenges in the field of educational data science. The program emphasizes experiential learning through collaborative projects, internships, and the use of advanced software and digital tools.

Here are some key aspects of the experiential learning opportunities available in the MS Educational Data Science program:

- Collaborative Projects: Engage in group projects that simulate real-world data analysis scenarios, allowing you to work alongside peers and faculty to solve complex educational problems.

- Internships: Gain valuable industry experience through internships with local schools, educational organizations, and tech companies, providing you with insights into the application of data science in education.

- Software Proficiency: Learn to use essential software tools such as R, Python, and Tableau, which are critical for data analysis and visualization in educational contexts.

- Research Laboratories: Access dedicated research labs equipped with the latest technology for data analysis, where you can conduct your own research or collaborate with faculty on ongoing projects.

- Field Trips: Participate in field trips to educational institutions and organizations that utilize data science, giving you a firsthand look at how data informs decision-making in education.

- Libraries and Resources: Utilize the extensive resources available at the UB libraries, including access to academic journals, databases, and research materials specific to educational data science.

- Institute for Educational Research: Collaborate with the Institute for Educational Research, which focuses on innovative research in education, providing opportunities for networking and professional development.

These experiential learning opportunities are designed to equip you with the practical skills and knowledge necessary to excel in the field of educational data science. By immersing yourself in these experiences, you'll be well-prepared to make a meaningful impact in education.

Progression & Future Opportunities

The MS in Educational Data Science at the University at Buffalo SUNY prepares graduates for a dynamic career in the rapidly evolving field of education technology and data analysis. With a strong foundation in data science principles and their application in educational settings, graduates can pursue roles such as Data Analyst, Educational Consultant, Learning Experience Designer, or Research Scientist.

Here’s what you can expect in terms of progression and future opportunities:

- University Services: The Career Services office offers personalized career counseling, resume workshops, and interview preparation to help you secure internships and job placements. Additionally, the university hosts job fairs and networking events specifically tailored for data science and education technology fields.

- Employment Stats and Salary Figures: Graduates from the program have a high employment rate, with over 90% securing jobs within six months of graduation. The average starting salary for graduates in educational data science roles is around $70,000, with potential for growth as you gain experience.

- University–Industry Partnerships: The University at Buffalo has established partnerships with leading organizations in the education sector, such as Pearson and Blackboard, providing students with opportunities for internships and collaborative projects that enhance real-world learning.

- Long-term Accreditation Value: The program is accredited by the Middle States Commission on Higher Education, ensuring that your degree holds value and recognition in the job market for years to come.

- Graduation Outcomes: Alumni of the program have gone on to work in prestigious institutions and companies, contributing to innovative projects that shape the future of education.

Further Academic Progression: After completing the MS in Educational Data Science, you may choose to further your studies by pursuing a PhD in Educational Technology or Data Science. This advanced degree can open doors to academic positions, research opportunities, and leadership roles in educational policy and administration. Additionally, you could explore certifications in specialized areas such as machine learning or data visualization to enhance your expertise and marketability in the field.

The University at Buffalo SUNY is committed to your success, and the MS in Educational Data Science is a fantastic step toward a fulfilling career in education and technology.