The CADE Concentration

Coming Fall 2026

Housed within the MS in Education, the CADE concentration builds on one of the first graduate-level programs in Educational Data Science, a graduate certificate that has been offered since 2023, as well as the University of Tennessee’s established strengths in instructional technology, research methods and evaluation methodology, and STEM education. It extends the existing Graduate Certificate in Educational Data Science into a full master’s degree by offering greater depth and specialization. The program is part of the Interdisciplinary Learning and Teaching Unit in the Department of Theory and Practice in Teacher Education.

The program requires 33 credit hours and is organized around a shared core, a specialized track chosen by the student, and a capstone experience. Students work closely with a faculty advisor to build a program of study tailored to their goals and background. 

Research

Faculty and students in this area engage in research that explores concepts, methods and tools of educational data science; AI in education; learning analytics and quantitative methods; AI-powered learning technology for K-12 education; ethical frameworks for working responsibly with data and technology in educational contexts; types of coding and analysis tools and software programs; multimodal approaches to knowledge construction and assessment in technology-enhanced learning; and more.

Program

This program is designed for educators, professionals, and career changers who want to develop expertise in how data, computing, and AI can improve education — or who want to teach others about these topics. You do not need a technical background to succeed in this program; foundational courses build skills from the ground up.

The CADE concentration may be a good fit if you are a classroom teacher interested in data literacy, learning analytics, or AI integration; a professional in education, government, or nonprofit settings who wants to make more effective use of data; someone considering a career in instructional design, educational technology, or learning analytics; a current or former Graduate Certificate in Educational Data Science student who wants to extend your studies into a full degree; or someone who wants to teach K-12 students about data science, computing, or AI.

Graduate

We offer a Master of Science (M. S.) degree that provides opportunities for focused study in Computing, AI, and Data Analytics in Education.

More on the M.S. degree in Computing, AI, and Data in Education (CADE). (Link coming soon!)

Program of Study

The CADE program offers flexibility. Some courses are available online, while others are offered in person. Students work with their advisor to develop a program of study that fits their schedule, interests, and professional goals. Program totals are minimums; some students may complete additional coursework to address background needs.

Core (12 credit hours)

All students complete the same foundational coursework:

  • ESM 577 — Statistics in Applied Fields I. Foundational applied statistics for educational research.
  • CADE 680 — Foundations of Educational Data Science I. An introduction to the field of educational data science, including key concepts, methods, and tools.
  • LDT 525 — Ethics in Design, Technology, and Data Science.Ethical frameworks for working responsibly with data and technology in educational contexts.
  • CADE 691 — Visualizing Data Using R. Hands-on experience with data visualization and analysis using R.

Tracks (15 credit hours – choose one)

Students select one of the three tracks in consultation with their advisor.

  • Track 1: Data Science and Quantitative Methods For students interested in analytics, statistical modeling, and advanced research methods. Required courses include ESM 677 (Statistics in Applied Fields II) and CADE 685 (Learning Analytics and Advanced Data Science Methods), plus 9 credit hours chosen from advanced offerings in statistics, methodology, and psychometrics.
  • Track 2: AI and Emerging Technologies For students focused on designing with AI and digital learning tools. Coursework includes CADE 550 (AI for Educators), ESM 555 (AI for Human Development), and courses in instructional systems design, online learning, and multimedia instruction.
  • Track 3: Pedagogy of Data, Computing, and AI For students who want to teach with and about data, computing, and AI in K-12 settings. Coursework includes CADE 550 (AI for Educators) alongside courses in classroom technology, computational thinking across the K-12 curriculum, mathematics assessment, and technology leadership.

Capstone (6 credit hours)

All students complete CADE 695 — Capstone in Educational Data Science, a two-course sequence in which they build an online portfolio demonstrating their work across the program. The portfolio is evaluated by a committee, and a grade of Satisfactory/Pass is required to earn the degree.

Related Programs

Already know you’re interested but not ready to commit to a full master’s degree? The Graduate Certificate in Educational Data Science is a 12-credit-hour program that can serve as a starting point — and credits earned in the certificate may apply toward the MS. Talk to an advisor to learn more.

What Students Are Saying

Coming Soon!

Frequently Asked Questions about our Computing, AI, and Data in Education (CADE) Program:

How is the CADE program different from the Graduate Certificate in Educational Data Science?

The certificate is a 12-credit-hour program focused on foundational data science skills. This MS concentration wraps those foundations into a full 33-credit-hour master’s degree, adding depth through specialized tracks, a capstone, and eligibility for financial aid, scholarships, and full-time student status.

Should I complete the certificate or the master’s degree?

The certificate is good for someone already enrolled in another degree program who wants to learn more about educational data science or someone who wants a completely online credential. The master’s is a good fit for anyone who wants a stand alone degree program in computing, AI, and data in education or for someone who is interested in attending UT as an in person student.

Can I transfer credits from the Graduate Certificate in Educational Data Science?

Students who have completed the certificate should consult with their advisor about how those credits may apply toward the MS. 

What are the three tracks, and how do I choose?

The program offers three tracks: Data Science and Quantitative Methods (for those interested in analytics and statistical modeling), AI and Emerging Technologies (for those focused on designing with AI and digital learning tools), and Pedagogy of Data, Computing, and AI (for those who want to teach with and about data and AI in K-12 settings). You’ll work with your advisor to choose the track that best fits your goals.

Can I complete the program online? 

The program can be completed in person or online depending on the courses you select. Please consult the program director for advice on course selection.

How long does it take to complete? 

The program requires 33 credit hours. Full-time students can typically complete it in about two years; part-time students should work with their advisor to develop a realistic timeline.

Is there a thesis?

The master’s includes a capstone, not a thesis.

What is the capstone?

Students complete CADE 695, a two-course capstone sequence in which they build an online portfolio demonstrating their work. The portfolio is evaluated by a committee, and a Satisfactory/Pass grade is required to earn the degree.

Why is this called a “concentration” rather than its own degree?

The Computing, AI, and Data in Education Concentration is housed within the MS in Education, which serves as the broader degree program. The concentration defines your specialized coursework and focus area, while the degree you earn is a Master of Science in Education. Think of it the way a major works within a bachelor’s degree — the MS in Education is the degree, and CADE is the specialization you pursue within it.

Do I need to already know how to code?

No. The program is designed for educators and professionals from a variety of backgrounds. Courses like CADE 680 and CADE 691 build foundational skills in data science and R from the ground up. Your advisor will help you choose a track and courses that match your starting point.

Where do graduates end up working?

Graduates are prepared for roles in education, corporate training, government, and nonprofit settings — anywhere that data-informed decision-making and AI-literate leadership are in demand. Depending on your track, that could mean working as a learning analytics specialist, an instructional designer, a data science educator, or in education policy and research.

Contact

For questions about the program, admissions, or to discuss whether CADE is a good fit for you, please contact:

Joshua Rosenberg, Ph.D. Program Coordinator, Computing, AI, and Data in Education, 513 Bailey Education Complex, 1122 Volunteer Blvd., Knoxville, TN 37996 jrosenb8@utk.edu

Shaping strong beginnings through inclusive, research-informed practice.

Computing, AI, and Data in Education (CADE) Faculty

CADE Program courses are taught by faculty in educational data science, evaluation, statistics, and methodology, learning, design, and technology, and other programs across the college and campus. More details on CADE faculty are coming soon!

Program Faculty & Examples of Research

The CADE concentration is taught by faculty with deep expertise in educational data science, AI in education, learning analytics, and quantitative methods — complemented by adjunct instructors who bring experience from industry and other applied contexts. Examples of research are coming soon!