The Master of Science degree in Learning Technologies at the University of North Texas gives you the foundation in learning and educational technologies required to create, deliver and enhance learning experiences in a variety of contexts.
The Master of Science degree in Learning Technologies at the University of North Texas gives you the foundation in learning and educational technologies required to create, deliver and enhance learning experiences in a variety of contexts.
Our rigorous and accredited curriculum explores human learning and cognition, instructional design and educational tools, and technologies in education. Upon graduation, you’ll be prepared for dynamic roles in instructional design and technology in academic and corporate settings.
Course work can be completed in a traditional classroom environment or as part of an accelerated online program (AOP). The AOP option allows you to earn a degree in as few as 14 months. More information about this option is available at Learning Technologies Master of Science.
You can pursue degree tracks in instructional systems, instructional systems technology, instructional systems design, and teaching and learning with technology. Some tracks have additional specializations.
Our program is enhanced by nationally and internationally recognized faculty members who have expertise in learning technologies and other related fields.
This track provides theoretical and research foundations, tools and experience focused on instructional systems. You will be prepared to work in educational and instructional technology areas as developers of instructional design and media projects, processes and outcomes in corporate, higher education, K-20 and other instructional and training environments. The track is provided in both normal and accelerated delivery.
This area expands on the Instructional Systems track by focusing on systems and technology used in the delivery of learning. You’ll be prepared to work in the same areas as the Instructional Systems track as well as become directors, managers or developers of learning systems technology.
This track involves the practice of maximizing the effectiveness, efficiency and appeal of instruction and other learning experiences. With this track, you’ll be prepared to work as an instructional systems designer in academic or corporate settings.
This area is designed for education professionals serving in administrative, teaching or research positions in a variety of educational settings, especially positions in K-20 and higher education. The track focuses on theoretical foundations, technology skills, technology integration strategies for teaching and learning, active research, innovations in technology and paradigms for effective online delivery assessment. The degree emphasizes application-oriented technology skills that are valuable for independent study and research, classroom teaching and personal and professional projects.
To help you pursue your master's degree, you'll have access to the:
You'll need to meet the admission requirements for the graduate school and the following set of program requirements:
You must file a degree plan within the first 12 credit hours after being admitted to the program. A copy of your approved degree plan will be sent to you for documentation and reference purposes. Any deviations from your approved degree plan will require an official degree plan change. The degree requirements are:
All courses for the Instructional Systems, Instructional Systems Technology, Instructional System Design and Teaching and Learning With Technology tracks are available online. For specific information about course requirements, visit Master of Science in Learning Technologies.
Information about financial assistance programs is available at the financial aid website.
Yunjo An, Associate Professor and Department Chair; Ph.D., Indiana University. Game-based learning; complex problem solving.
Rose Baker, Assistant Professor; Ph.D., Pennsylvania State University. Workplace learning; performance improvement.
Deborah Cockerham, Lecturer; Ph.D., University of North Texas.
Demetria Ennis-Cole, Professor; Ph.D., Kansas State University. Computer education instruction and administration; systems development; user training.
Aleshia Hayes, Assistant Professor; Ph.D., University of Central Florida. VR, AR, and simulation-based learning.
Tai-Yi Huang, Lecturer; Ph.D., University of North Texas. Learning Analytics; Educational Data Mining; Quantitative Data Analysis; Information Visualization.
Karen Johnson, Assistant Professor; Ph.D., University of Minnesota. Workplace learning and training solutions.
Regina Kaplan-Rakowski, Lecturer; Ph.D., Southern Illinois University, Carbondale. Immersive learning environments; computer-assisted language learning; mobile learning; 3D visualizations of learning content.
Gerald A. Knezek, Regents Professor; Ph.D., University of Hawaii. Technology integration; telecommunications; educational research and measurement.
Youngjin Lee, Associate Professor; Ph.D., University of Illinois. Learning analytics.
Lin Lin, Professor; Ed.D., Columbia University. Instructional technology; human-machine interaction; online teaching and learning; teacher professional development.
T. Fred McMahan, Assistant Professor; Ph.D., University of North Texas. Adaptive Virtual Environments; Computer Programming; VR; Augmented Reality.
Cathleen Norris, Regents Professor; Ph.D., University of North Texas. Mobile technologies; computer-based education; human factors; teacher professional development.
Thomas Parsons, Professor and Director of the NetDragon Digital Research Center, Ph.D., Fuller Graduate School of Psychology. Neuroscience and learning.
J. Michael Spector, Professor; Ph.D., University of Texas at Austin. Complex learning; program evaluation; simulation-based learning.
Tandra Tyler-Wood, Professor, Ph.D., University of North Carolina. Assessing learning and curricula for special needs students.
John Turner, Assistant Professor; Ph.D., University of North Texas. Team cognition and team learning; multi-level analysis methods.
Scott J. Warren, Professor; Ph.D., Indiana University. Digital learning environments; games and simulations to support literacy and learning; technology-supported research methods.