Graduate opportunities

The Department of Learning Technologies at the University of North Texas creates an atmosphere for the intellectual exchange of ideas and research related to workforce learning and performance. Our program reflects the multidisciplinary nature of the field.

You can pursue a Master of Science degree in Workforce Learning and Performance if you're seeking:

  • A career in training and development
  • A career in technical and career education
  • Certification in trade and industrial education, health education or marketing education

All courses are offered online, allowing you to better balance your work, personal and academic obligations.

Careers in this field are rapidly expanding because of restructuring in the private and public sectors. This restructuring often requires the current workforce to develop new skills. Graduates play key roles in educational and business settings as:

  • Cooperate trainers
  • Program evaluators
  • Career technical educators (K-12)
  • Career technical education directors
  • Community college faculty members

Research centers and laboratories

Several laboratories and research centers provide you the resources and facilities needed for in-depth study of information and technology.

The Center for Knowledge Solutions empowers scholars and practitioners to make evidence-based decisions that optimize learning and performance systems to improve organizational knowledge. The center's unique focus is learning and performance across disciplines and professions. Its mission is to generate, integrate and disseminate knowledge solutions through learning and performance innovation for business and education.

The Advanced Research Lab serves doctoral students and faculty members in educational computing, instructional technology and technology-based learning systems.

The Institute for the Integration of Technology into Teaching and Learning conducts research and implements best practices in teaching and learning with technology. Its instruments and online data collection systems have gathered data from thousands of educators in recent years.

The Texas Center for Educational Technology facilitates and conducts research; develops and evaluates collaborations among industry, education and educational communities; and serves as a focal point where instructional technology can be created and adapted for integration into educational programs.

Attending UNT

Admission requirements

You must meet the requirements for the Toulouse Graduate School® and the following specific program requirements:

  • One-page statement of career goals and how the master's degree will assist in achieving them
  • Documentation of professional work experience in education or training
  • Professional résumé
  • GRE scores

Admission to the program is based on a holistic review of your qualifications. Because of our program's competitive nature, achieving a particular score on generalized tests doesn't guarantee admission. You may enroll for one semester without GRE scores.

International students whose native language isn't English may substitute completion of our Graduate Preparation Course for their GRE verbal score.

Degree requirements

  • 30 credit hours of required applied technology, training and development courses
  • 3 credit hours of an educational statistics course
  • 3 credit hours of an applied technology, training and development elective (taken in consultation with your advisor)

Financial assistance

We offer several financial awards to help you pursue your graduate degree. These include competitive scholarships, grants, and teaching and research assistantships. Visit the grad school website for more information on these opportunities. Information about other financial assistance programs is available at the financial aid website.


Jeff M. Allen, Professor and Director of the Center for Knowledge Solutions; Ph.D., Pennsylvania State University. Technology planning; organizational development; systems theory; integration of career-academic education; team assessment; evaluation.

Demetria Ennis-Cole, Associate Professor; Ph.D., Kansas State University. Computer education instruction and administration; systems development; user training.

Jonathan Gratch, Lecturer; Ph.D., University of North Texas. Emerging technologies; games and simulations; technology integration; multimedia production for education.

Gerald A. Knezek, Regents Professor and Director of Institute for the Integration of Technology into Teaching and Learning; Ph.D., University of Hawaii. Technology integration; telecommunications; educational research and measurement.

Lin Lin, Associate Professor; Ed.D., Columbia University. Instructional technology; human computer interaction; online/ hybrid teaching and learning; mind, brain and education.

Cathleen Norris, Regents Professor; Ph.D., University of North Texas. Mobile technologies; computer-based education; human factors; teacher professional development.

Laura Pasquini, Lecturer; Ph.D., University of North Texas. Corporate training; evaluation; research.

Peggy Rouh, Lecturer; Ph.D., University of North Texas. Corporate training; course design; computer-based instruction.

J. Michael Spector, Professor; Ph.D., University of Texas at Austin. Complex learning; program evaluation; simulationbased learning.

Tandra Tyler-Wood, Professor; Ph.D., University of North Carolina. Assessing and determining appropriate curriculum for special needs populations.

Scott Warren, Associate Professor; Ph.D., Indiana University.Digital learning environments; games and simulations to support literacy and learning; technology-supported research methods.

Jerry L. Wircenski, Regents Professor; Ph.D., Ohio State University. Special populations; interactive instruction; delivery strategies; courseware development; evaluation.

Michelle Wircenski, Professor; Ed.D., University at Buffalo. Special populations; teaching/learning styles; diversity.

Robert Wright, Lecturer; Ph.D., University of North Texas. Multimedia production for technology applications; technology-based learning environments; student-instructor rapport in distributed learning systems; foundational learning and design theory.