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Teaching and Learning, Policy and Leadership - Technology, Learning and Leadership Specialization, M.A

Master of Arts
At a Glance
Leads to Teaching License?

No

Avg. Duration

2 years

Start Term

Fall

Required Credits

30

Course Load

Full-time, Part-time

Location

On-Campus

Application Deadline

March 3, 2027

At a Glance
Leads to Teaching License?

No

Avg. Duration

2 years

Start Term

Fall

Required Credits

30

Course Load

Full-time, Part-time

Location

On-Campus

Application Deadline

March 3, 2027

Program Overview

Preparing educators, designers, and leaders to curate meaningful learning experiences and redesign learning systems in an AI-rich world 

The Teaching and Learning, Policy and Leadership - Technology, Learning, and Leadership Specialization, Master of Arts (M.A) program is designed to prepare educators, designers, and leaders to curate transformative learning experiences and systems in an AI-rich world. The curriculum integrates learning sciences, computational thinking, educational biotechnology, data sciences, digital literacy, human-computer interaction, and education policy to equip students with both technical and pedagogical fluency. Graduates will be prepared for roles in education technology, learning systems and curriculum design, policy, program evaluation, and educational research.

#11
Best Curriculum and Instruction program by U.S. News & World Report
How to Apply

Information on admissions and application to this program can be found on the University Graduate Admissions website and the program handbook.

Admission Requirements          Guide to Applying

“I wanted to be part of a program learning from people who are doing the actual work; The College of Education’s relationships globally are unparalleled to other institutions. It’s never been a better time to be an EdTerp.”

Timothy F. Bryson, student

Program Requirements

The program is carefully crafted to give you a strong foundation and provide flexibility for your interests and goals.

Degree Requirements

The courses below outlines one possible pathway through the program. Upon admission, you will be able to work with your advisor to customize your course schedule.

  • TLPL 704: Research Methodologies and Educational Practice (3 credits)
  • TLPL 603: Data-driven Decision Making in Schools and Classrooms (or a 600-level TLL specialization course as negotiated with advisor) (3 credits)
  • TLPL 702: Theories of Learning and Leadership with Technology (3 credits)
  • TLPL 708X: AI Competency and Education (3 credits)
  • TLPL 708F: Human-AI Collaborative Learning and Work (or a 700-level TLL specialization course as negotiated with advisor) (3 credits)

 

  • TLPL 703: Research on Technology in Education (or equivalent courses as negotiated with advisor) (3 credits)
  • TLPL 798: Special Problems in Education (Independent study with advisor, or alternative with advisor approval) (3 credits)

Students must select three electives from the following options: 

  • TLPL 600: Technology-Augmented Learning Innovation and Systems Design (3 credits)

  • TLPL 602: Policy and Governance of Technology in Education (3 credits) 

  • TLPL 605: Social, Cultural & Ethical Dimensions of Teaching and Learning with Technology (3 credits)

  • Relevant 600- and 700-level courses in the College of Education (e.g., Assessment, Ethics, Leadership, Policy, Research Methodologies) (3 credits)

  • Relevant 600- and 700-level courses from departments outside of the College of Education, such as the School of Information Studies, Computer Science, Psychology, or Sociology (3 credits)

Our Faculty

Our faculty are chosen for their expertise and dedication; they provide exceptional guidance and support to foster your academic and professional success.

  • Fengfeng Ke, Professor
    Ph.D., Pennsylvania State University

  • Jing Liu, Associate Professor
    Ph.D., Stanford University

  • Sarah McGrew, AssociateAssistant Professor
    Ph.D., Stanford University

  • Justice Walker, Assistant Professor
    Ph.D., University of Pennsylvania

  • David Weintrop, Associate Professor
    Ph.D., Northwestern University

Contact

Kay Moon
Kay Moon
TLPL Graduate Coordinator
David Weintrop
Dr. David Weintrop