technology in education phd program

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Learning sciences and technologies, doctor of philosophy (ph.d.), you are here, a doctoral program emphasizing research and innovation in education through technology, data, and curriculum design..

The Ph.D. program in Learning Sciences and Technologies is designed to build and study the learning technologies of tomorrow, to analyze large-scale educational data, to develop expertise in learning analytics, and to develop cutting-edge curricula and learning materials.

What Sets Us Apart

About the program.

The program is designed to draw together course work, research apprenticeship, and other professional academic activities to build a comprehensive learning experience that is tailored to students’ interests and needs.

Fall: 3; Spring: 3

Culminating experience Dissertation

Coursework and research experiences in the Learning Sciences and Technologies program address a range of practice-based and theoretical problems in schools, in online learning, and in community settings. Coursework and research experiences consider learning in its full richness and context, using sociocultural, cognitive, and psychological perspectives. Taking an interdisciplinary stance, faculty and students explore how to enhance learning, motivation, and engagement, for the world's diversity of learners, in a range of formal, informal, and online educational settings. Our graduate students study learning in traditional contexts using new technological approaches, and they study new and emerging pedagogies for learning such as constructionist environments, simulations, massive online open courses, serious games, and intelligent tutoring systems. Because of the significance we attach to the building of knowledge from experiences as educators and educational designers, we expect most students to have, on admission to the program, either teaching/instructional experiences (in or outside of school settings), educational design/development experience, or experience as a learning analytics practitioner. Students will build a program of study that includes courses in teaching and learning, social foundations, and research methods. Students in the program participate in field-based research and collaborative projects with practitioners in schools or other educational settings, and/or work with large-scale educational data sets. Students learn not only from a rigorous program of study, but also from active participation in a community of learners including practicing and prospective teachers, and educational designers and researchers.

The Ph.D. in Learning Sciences and Technologies focuses on the preparation of researchers and researcher/developers in education. The program includes formal courses, mentored research, and informal seminars. Ph.D. students are required to hold a master’s degree prior to beginning the Ph.D. program, and are expected to have experience in educational practice. You will build a program of study that includes courses in teaching and learning, social foundations, and research methods. The program is designed to draw together coursework, research apprenticeship, and other professional academic activities to build a complete professional program that is tailored to your interests and needs. For more information about courses and requirements, visit the Learning Sciences and Technologies Ph.D. program in the University Catalog .

• Learning Sciences: Past, Present, and Future • Foundations of Teaching and Learning • Education, Culture, and Society

Methods courses (3 required)

• Core Methods in Educational Data Mining • Mixed Methods • Social Network Analysis • Qualitative Modes of Inquiry • Quantitative Modes of Inquiry

Design (2 required)

• Design of Learning Environments • Maker Studio • Integrated Design Studio • Design Thinking and Product Development

Applications (2 required)

• Games for Learning • Entrepreneurship in Education • Technologies for Language Learning and Teaching • Digital Literacies • Big Data, Education, and Society

Professional Practice

• Research Apprenticeship Course

Our Faculty

Our award-winning faculty design and research formal and informal learning environments. Innovations developed by our faculty range from online learning communities and teacher professional development workshops to more effective curricular and pedagogical approaches. They work in school clubs, museums, classrooms, and virtual worlds across multiple educational settings. With grant-funded projects, as well as ties to Philadelphia schools and institutions, the faculty offer students direct access to nationally significant research on education. Their work connects closely to Penn GSE’s broader focus on equitable access to education across social strata.

Affiliated Faculty

Betty Chandy Director for Online Learning, Catalyst @ Penn GSE Ed.D., University of Pennsylvania

Matthew Duvall Lecturer Ph.D., Drexel University

L. Michael Golden Vice Dean of Innovative Programs and Partnerships, Catalyst @ Penn GSE Ed.D., University of Pennsylvania

Sarah Schneider Kavanagh Associate Professor Ph.D., University of Washington

Sharon M. Ravitch Professor of Practice Ph.D., University of Pennsylvania

Abby Reisman Associate Professor Ph.D., Stanford University

Janine Remillard Professor Ph.D., Michigan State University

Our Graduates

The Ph.D. program in Learning Sciences and Technologies prepares graduates to work in learning sciences research and development in universities, industry, and non-profits. Graduates of this new program are anticipated to work in teaching and research positions in institutions of higher education, or in research and development positions in industry and non-profits. Graduates will learn to build and study the learning technologies of tomorrow, to analyze large-scale educational data, and to develop cutting-edge curricula and learning materials.

Admissions & Financial Aid

Please visit our Admissions and Financial Aid pages for specific information on the application requirements , as well as information on tuition, fees, financial aid, scholarships, and fellowships.

Contact us if you have any questions about the program.

Graduate School of Education University of Pennsylvania 3700 Walnut Street Philadelphia, PA 19104 (215) 898-6415 [email protected] [email protected]

Noemí Fernández Program Manager [email protected]

Please view information from our Admissions and Financial Aid Office for specific information on the cost of this program.

All Ph.D. students are guaranteed a full scholarship for their first four years of study, as well as a stipend and student health insurance. Penn GSE is committed to making your graduate education affordable, and we offer generous scholarships, fellowships, and assistantships.

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The Collaboratory for Teacher Education at Penn GSE is a laboratory for the design, implementation, and study of experimental approaches to teacher education.

You May Be Interested In

Related programs.

• Teaching, Learning, and Teacher Education Ed.D.
• Reading/Writing/Literacy Ph.D.
• Reading/Writing/Literacy Ed.D.
• Learning Sciences and Technologies M.S.Ed.
• Teaching, Learning, and Leadership M.S.Ed.
• Education, Culture, and Society Ph.D.

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Doctoral programs.

The goal of the GSE PhD in Education is to prepare the next generation of leading education researchers. The cornerstone of the doctoral experience at the Stanford Graduate School of Education is the research apprenticeship that all students undertake, typically under the guidance of their academic advisor, but often with other Stanford faculty as well.

In this apprenticeship model, doctoral students are provided with a multi-year funding package that consists of opportunities each quarter to serve as teaching and research assistants for faculty members' courses and research projects. By this means, and in combination with the courses they take as part of their program, students are prepared over an approximately five-year period to excel as university teachers and education researchers.

The doctoral degree in Education at the GSE includes doctoral program requirements as well as a specialization, as listed below, overseen by a faculty committee from one of the GSE's three academic areas.

Doctoral programs by academic area

Curriculum studies and teacher education (cte).

• ‌ Elementary Education
• ‌ History/Social Science Education
• ‌ Learning Sciences and Technology Design
• ‌ Literacy, Language, and English Education
• ‌ Mathematics Education
• ‌ Science, Engineering and Technology Education
• ‌ Race, Inequality, and Language in Education
• ‌ Teacher Education

Developmental and Psychological Sciences (DAPS)

• ‌ Developmental and Psychological Sciences

Social Sciences, Humanities, and Interdisciplinary Policy Studies in Education (SHIPS)

• ‌ Anthropology of Education
• ‌ Economics of Education
• ‌ Education Data Science
• ‌ ‌Educational Linguistics
• ‌ Educational Policy
• ‌ Higher Education
• ‌ History of Education
• ‌ International Comparative Education
• ‌ Organizational Studies
• ‌ Philosophy of Education
• ‌ Sociology of Education

Cross-area specializations

Learning sciences and technology design (lstd).

LSTD allows doctoral students to study learning sciences and technology design within the context of their primary program of study (DAPS, CTE, or SHIPS).

Race, Inequality, and Language in Education (RILE)

RILE trains students to become national leaders in conducting research on how race, inequality, and language intersect to make both ineffective and effective educational opportunities. RILE allows students to specialize within their program of study (DAPS, CTE, or SHIPS).

Other academic opportunities

• ‌ Concentration in Education and Jewish Studies
• ‌ PhD Minor in Education
• ‌ Stanford Doctoral Training Program in Leadership for System-wide Inclusive Education (LSIE)
• ‌ Certificate Program in Partnership Research in Education
• ‌ Public Scholarship Collaborative

“I came to Stanford to work with faculty who value learning in informal settings and who are working to understand and design for it.”

Doctoral graduates were employed within four months of graduation

of those employed worked in organizations or roles related to education

For more information about GSE admissions and to see upcoming events and appointments:

To learn more about the Academic Services team:

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Search NYU Steinhardt

Doctor of Philosophy Educational Communication and Technology

This rigorous research-oriented doctorate prepares you for academic and leadership positions in research, technology, and learning in all contexts. You will work with technology-based multimedia learning environments and research the factors that influence learning when individuals and groups engage with these environments and each other. Our highly selective program is fully funded for full-time students.

Degree Details

Official degree title.

PhD in Educational Communication and Technology

Your Academic Experience

What you'll learn, contact information.

Your research and course work will draw from cognitive sciences, learning sciences, game studies, and design-based methodologies as you conduct original research on how technology and media can support learning.

You will have opportunities to work with some of the preeminent scholars in the field , along with internationally recognized research centers. In addition, you will participate in our design-oriented studio-based learning courses, and are encouraged to combine theoretical research with design and practice in appropriate learning contexts.

The doctoral program is interested in the design of rich, technology-based multimedia learning environments and in conducting research on factors that influence learning, as individuals engage with these environments, and as groups interact with them and each other. Educational Communication and Technology (ECT) doctoral courses and research focus on those representational features and structural characteristics of technology-based learning environments and media that may, in a particular set of circumstances, have cognitive, affective, motivational and socio-cultural significance for learners who interact with them.

ECT faculty and  doctoral students represent a multitude of areas of inquiry in the field of educational technology, from the design of features in games that support problem solving to the effects of narrative structure in linear video dramas on the exercise of critical thinking; from the role of prior knowledge on learning from different forms of representation in simulations of science principles to the design of technology-based environments that support the social construction of knowledge to strengthen collaborative and negotiation skills; from the design of electronic portfolio environments that scaffolds metacognition to the comparative effects of fictional reality and testimonial reality on attitude change.

For more information about the PhD program, please contact

[email protected] or  Xavier Ochoa  ECT Doctoral Coordinator  [email protected]

Funding for Full-Time PhD Students

If you are accepted as a full-time NYU Steinhardt PhD student without an alternate funding source, you are eligible for our generous funding package, which includes a scholarship and tuition remission.  Learn more about our funding opportunities .

Take the Next Step

Advance your personal and professional journey – apply to join our community of students.

Ph.D. in Education: Information Technology in Education

This emphasis area provides advanced training for educators or prospective educators a strong theoretical and practical foundation in dynamic instructional design, and concurrent knowledge and skills to integrate contemporary digital technology in a variety of educational and training settings.

World-Improving Research and Creativity

The Ph.D. in Education with an emphasis in Information Technology in Education provides advanced training for educators or prospective educators a strong theoretical and practical foundation in dynamic instructional design, and concurrent knowledge and skills to integrate contemporary digital technology in a variety of educational and training settings.

About Our Program

Students in the Information Technology in Education doctoral program are well prepared to be an active researcher with solid research skills and an academic publication agenda. Career options for students with this Ph.D. can be (but not limited to):

• Instructional design assistant professors working in teaching and research institutions
• Universities and colleges
• K-12 schools
• Educational software/gaming companies, industry, and organizations
• Leading technology officers for industry companies working in their education and training divisions
• Senior positions on technology related evaluation and assessment for government, schools, or grant sponsors

For more information, please contact: Dr. Leping Liu Professor and Information Technology in Education Doctoral Program Coordinator [email protected] 775-682-5511

The Information Technology in Education area of emphasis is guided by the general framework found in the Doctoral Program in Education Handbook . The manual provides general information about doctoral concentrations offered in the College of Education. This page will provide you with specific information that is unique to the Information Technology in Education strand.

Request More Information

Admission deadlines.

Applications and all associated documents must be received by the following dates to be considered. Fall Semester: July 1 | Spring Semester: Oct. 1.

Program Information

If you miss the Graduate School deadline, you may still apply to be a Graduate Special to begin taking coursework for your intended first semester. Materials and criteria for the Information Technology in Education area of emphasis are as follows:

• Undergraduate and graduate GPA of 3.00 or higher
• At least two years of relevant experience
• Resume or curriculum vitae
• Statement of Intent that includes a philosophy of using technology in education
• Three letters of recommendation
• One sample of scholarly writing

To get started on the application process, please contact Dr. Leping Liu, program coordinator, at [email protected] .

All materials are submitted through the University's application portal . Once you create your account, go back to MyNevada to log in and start your application. Please contact Dr. Leping Liu if you have any questions.

Program Structure

The doctoral degree includes a minimum of 72 semester credits beyond the baccalaureate degree. The chair and advisory committee will work with students to formulate the program of study that meets the following requirements:

Research Core Courses (24 credits)

As described in the doctoral manual, the core curriculum for research includes courses in quantitative design, advance statistics, qualitative design, and mixed methods.

Area Courses (24-36 credits; dependent upon number of dissertation credits carried)

Area core courses consist of instructional design theories and methods, assessment and new technology skills, design courses in online teaching and learning, digital visual app, Web app for instruction, technology integration field work, and special topics such as gamification, robotics, or any new topics needed. Courses from other colleges on campus, approved by the advisory committee, can also be included and counted for the degree.  

Transfer from Master's Program (24 credits maximum)

Approved by the chair and advisory committee

Dissertation: (minimum of 12 credits credits)

The primary focus of the Doctor of Philosophy program is on research skills. The dissertation must represent an original and independent investigation that reflects a contribution to knowledge. The dissertation must also reflect mastery of research skills and an ability to select a significant problem for investigation. To meet the requirements of the degree, students must pass:

• Proposal defense
• Dissertation defense  

Ongoing activities/to-do list:

• Mid-program review (at the second year of your doc studies)
• Comprehensive exam (at the completion of course credits)
• Conference activities (start as early as possible, work with your professor)
• Research and journal publications (start as early as possible, work with your professor)
• Instructional design field activities

Tuition, Cost, and Graduate Assistantships

Please see the University tuition and fee rates for information regarding costs and financial aid.

Graduate assistantships are available through various departments in the College of Education & Human Development. Prospective students who indicate their interest in a graduate assistantship will be interviewed for one of multiple positions within the department following their application.

Looking for a Graduate Assistantship?

The College of Education & Human Development has a limited number of Graduate Assistantships for full-time students admitted to masters or doctoral programs. 

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• Educational Technology

Doctor of Philosophy

• Programs at the University of Northern Colorado
• Educational Technology PhD

Innovate. Create. Design. Research.

Immerse yourself in research-intensive experiences that explore how pedagogies and technology blend with critical and educational theories to inform innovative practices in educational contexts. In the Educational Technology program, you'll develop rich understanding about educational theory and practice; design and develop digital materials such as games, visual media and multimodal compositions; and engage in authentic research projects. You'll work closely with faculty who are top educators and researchers, while having opportunities to engage in unique, hands-on learner experiences.

Degree Details

Credits required:, location/delivery:.

Cost Estimator

Ph.D. in Educational Technology

This program is research intensive and builds a deep theoretical base in critical and innovative pedagogy as well as developed technology application skills. It provides different areas of focus, or cognates, including innovation and integration and instructional technology. You'll also explore your own research interests, publish your findings and present your work in scholarly venues. Earn your degree on campus with opportunities for in-person and blended learning a part of this unique doctoral program.The PhD program culminates in a dissertation of original research in the field.

Degree Requirements

Your Future in Educational Technology

• Aspire to be an education professional or classroom teacher
• Seek opportunities for research that explores technology as a transformational tool to teaching and learning
• Or desire to develop a deep understanding in blending education theory and practice

...then this program is for you!

You’ll learn:

• Foundational theoretical knowledge of technology-infused pedagogy and its place in transformative teaching and learning.
• Theory and application of critical and innovative pedagogy as well as developed technology application skills.

Sample courses:

• Global and Cultural Perspectives in Educational Technology
• Performance Technology for Instructional Environments
• Innovations in Technology and Education
• Gaming and Application Design
• Multimodal Composing
• Visual Methods for Educational Research in Digital Contexts

Where can your degree take you?

When you earn your degree in Educational Technology from UNC, you’ll be ready to work in a variety of learning contexts, including K-12, higher education, online environments, military training, business/organizational, international settings and more.

Higher Education Faculty

Innovation Officer

Curriculum developer

Ready for what's next? Here's what you need to know.

If there's anything else we can do, be sure to connect with us . We're only a shout away.

Still not completely sold? We understand. Here's more information on costs and funding  and how to apply .

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College of Education and Human Development

Department of Curriculum and Instruction

Learning technologies MA / PhD

The MA/PhD track in learning technologies prepares students to conduct research and engage in technology-related practices in higher education, K-12, and business settings. Core focus areas include learning analytics, K-12 technology integration, online distance learning, and multimedia design and development.

Quote from Rukmini Avadhanam

I’m really fortunate to work with faculty who are extremely knowledgeable, very approachable, and who have had a lot of impact on the way I started looking at my research and career. Rukmini Avadhanam PhD candidate, 2023

Coursework in learning technologies includes hands-on learning and use of current technologies, development of technological solutions, consideration of theory and research, and conducting educational research. 

The MA in learning technologies is designed for students interested in a stronger research orientation compared to those who pursue the MEd degree in learning technologies. Students complete a thesis (plan A) or a final paper (plan B). View the required courses in the graduate catalog under subplan "learning technologies." 

The PhD experience is based upon your research interests with your faculty adviser. To view the curriculum requirements in detail visit the course catalog go to Requirements, go to program sub-plan, and scroll down to Learning Technologies. 

Research opportunities

Students can engage in research that ties into their area of interest. Faculty work closely with each cohort to achieve research and educational goals. Learn more about the student research experience in the Department of Curriculum and Instruction. 

Areas of research include: 

• Learning analytics 
• Technology integration in K-12 classrooms 
• Computer science education 
• Educational technology 
• Instructional Design 
• Remote and distance online learning 

Sample plan of study

• Core courses: CI 8131 + CI 8132 (6 cr) 
• Research courses: CI 8134 + CI 8135, OLPD 5056, OLPD 5528, ESPY 8251, ESPY 8252 (18 cr) 
• Major courses: CI 5331, CI 5330, CI 5365, CI 8391, CI 8395 (15 cr) 
• Supporting courses: CI 5472, ESPY 5151, CI 5651, CI 5641 (12 cr) 
• Elective course: CI 8461 (3 cr) 
• Thesis credits: 8888 (24 cr) 

Career outlook

MA graduates engage in advanced media and software design and development, lead K-12 technology integration initiatives, and work as researchers. MA students often apply to PhD programs.

PhD graduates earn academic positions in higher education institutions and become leaders within community organizations, K12 schools, and businesses.

Current students and recent graduates have found employment in the following positions:

Academic Developer in the Teaching and Learning Innovation Center at Goldsmiths College, University of London

Academic Technologist, University of Minnesota 

Assistant Professor of Digital Marketing Technologies, University of Wisconsin-Stout 

Associate Professor + Canada Research Chair in Innovative Learning and Technology, Royal Roads University 

Instructor of Instructional Technology, University of South Florida 

John Bartucz John Bartucz

• Teaching Specialist
• [email protected]

I believe that everything that is meaningful in life is built through connections and relationships. Nothing is learned or accomplished in a vacuum.

Angelica Pazurek Angelica Pazurek

• Teaching Associate Professor
• she, her, hers
• 612-625-0320
• [email protected]

I have a very personal appreciation for the empowering potential of education and am interested in leveraging learning technologies, especially online learning affordances and mobile technologies, to improve access to education and learning…

Cassie Scharber Cassie Scharber

• Associate Professor of Learning Technologies, Director of the L+T Collaborative, Bonnie Westby Huebner Chair in Education and Technology
• 612-625-6607
• [email protected]

I am troubled by the narrow conceptions and practices of literacy and learning that proliferate in schools and current educational inequalities that are rooted in the gendered, racist, and classist histories of U.S. schooling.

George Veletsianos George Veletsianos

• Professor of Learning Technologies, Bonnie Westby Huebner Chair in Education and Technology
• [email protected]

I pursue a socially responsible and critical research agenda focused on responding to complex education problems in online and blended contexts, such as inequitable access, participation divides, and online harassment.

How to apply

Application deadline and instructions.

Priority deadline : December 1 for admission to the fall of the following year Admissions decisions : January

Applications submitted after this date are considered on a case-by-case basis and may not be reviewed until the following year. Faculty review applications in mid-late December, and the Graduate School will notify applicants about admission decisions shortly thereafter. Final admission decisions are based on complete applications. All application materials must be included for the application to be released for review.

Before applying online , go through the application checklist to ensure you have all the required materials. We are here to help! If you have questions, please contact the Graduate Studies Coordinator . If you are a returning Graduate School student, follow the Readmission guidelines . If you are a current Graduate School student and need to change your program, follow the Change of Status guidelines.

Tuition and funding

We have several funding options to support students full-time through program completion. Support is available in the form of:

• Teaching Assistantships. The majority work as student teaching supervisors for MEd initial licensure students. Daytime availability, a teaching license, and teaching experience are required
• Research Assistantships
• Fellowships. Based on a departmental nomination process. You will be notified by the Director of Graduate Studies if you are being considered for a fellowship. Decisions are made by April 15.
• Graduate students are also eligible to apply for fellowships and graduate assistantships through other University departments. Visit the University's employment page or fellowships through the Graduate School's Graduate Fellowship Office .
• Find more detailed federal financial aid and graduate tuition information.
• Financial support through Teaching Assistantships in MELP , the Writing Center , or the undergraduate TESL program.
• Fellowships such as FLAS

Application requirements

What we look for.

Admission to our master's of arts and doctoral programs are competitive and we look for candidates whose goals and interests align with the program’s research and scholarship. Program faculty make admissions decisions based on the candidate’s experience and research competencies, along with compatibility of research goals.

Please look at our current faculty members’ research interests.

Our masters and doctoral candidates display

• Evidence of strong interest in research and in the development of research competencies
• Evidence of substantial experience in the discipline
• Strong writing skills
• Bachelor's degree from an accredited U.S. institution or foreign equivalent

Required application documents

• Unofficial transcripts .Upload your transcripts into the application system. Please include all transcripts from any institution you have attended, even if you did not earn a degree or certificate. Please do not mail your transcripts. Official transcripts are required only after you are admitted. Tips for uploading your transcript(s) .
• CI Application Form . Upload in the graduate program additional materials section.
• Three letters of recommendation . Ask professors, employers, or supervisors to speak to your potential for successfully completing your degree; they will upload their letters directly into the online application.

The GRE is being waived for those applicants applying for Fall 2025.

Required written statements

• Why you want to study in our department
• What strengths, expertise, and research experience would contribute to your success in our program
• Your professional goals for pursuing a research-focused degree
• Diversity statement .Upload to the Applicant Statements section of the online application. Identify the distinctive qualities, characteristics, and life experiences you would contribute to our community. You may wish to include examples that address your contribution to the diversity of the student body and illustrate your motivation to succeed by setting high standards for accomplishing intellectual and other goals, overcoming obstacles to achievement, and/or helping others to gain access to the resources necessary for success. (please do not exceed one page in length)
• Short writing sample .(Optional except for Literacy Education applicants). For example, an excerpt from a term paper or research paper for publication. No longer than five pages in English.
• Common Ground Consortium Fellowship. (Optional) The primary purpose of the CGC is to assist graduate programs in the College of Education and Human Development to recruit exceptional students with the distinct experience provided by HBCUs or similarly distinguishing contexts, provide these students with financial assistance support during their graduate studies, and assistance with career development and job placement afterwards. It offers a pipeline to excellence and an opportunity to diversify perspectives in the academy. If you wish to apply, submit a statement that describes how your participation as a CGC scholar would a) enhance your graduate student experience, b) prepare you for your chosen career, and c) benefit the public. Upload to graduate program additional materials section.

Additional admissions information

Application checklist.

Before applying online , go through the application checklist to ensure you have all the required materials. We are here to help! If you have questions, please contact the Graduate Program Coordinator .

If you are a returning Graduate School student, follow the Readmission guidelines. If you are a current Graduate School student and need to change your program, follow the Change of Status guidelines .

Transfer credits

MA students must complete at least 60 percent of their coursework (not including thesis credits) within our program. PhD students may transfer no more than 15 credits from an outside institution.

A maximum of 12 graduate course credits taken as non-degree seeking or non-admitted status at the University of Minnesota can be transferred; this is counted separately from the maximum 60 percent or 15 non-UMN credits. For example, a PhD student could transfer a maximum of 27 credits (15 non-UMN and 12 non-degree from UMN).

If you earned a MA at the UMN, please contact the Graduate Studies Coordinator to discuss transfer procedures. Thesis credits cannot be transferred.

After you are admitted, you will work with your adviser to determine which credits may transfer.

International applicants

International applicants may also need:

• An English translation of your transcripts, if the transcript is not in English. Please note: the Graduate School Admissions Office will not accept an evaluation of your international coursework by an outside agency such as ECE or WES; they only accept the original transcripts.
• TOEFL/IELTS or MELAB. You may qualify for an exception if you have completed 16 semester or 24 quarter credits within the past 24 months in residence as a full-time student at an accredited institution of higher learning in the United States or other country where English is the official language (i.e. U.K, Canada). Score requirements and submission guidelines

Request information

We’re here to help. Simply complete one of these forms and a member of our department will be in touch

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PhD in Educational Studies, Learning Technologies

The PhD program in Learning Technologies is an intensive and interdisciplinary research and leadership program focused on the intersections between learning and technology in formal and informal educational environments. You will be immersed in both the theoretical and practical studies of learning with technology. Your experience can include pedagogical, social, cultural, economic, psychological, historical and political inquiry and critique. 

Research Interests 

Faculty and students in the PhD program integrate theoretical and practical studies of technologies and media through pedagogical, psychological, social, cultural, economic, historical and political research. Areas of focus studied by faculty and students include:

Computer-supported collaborative learning

Design-based research

Digital learning design and development

Policy and Learning

Entrepreneurship in Educational Technology

Games and simulations

Learning analytics and modeling

Learning technologies, digital divides and diverse populations

Motivation and engagement in online learning

Online, blended, and mobile learning and teaching

Social and cultural interactions in online learning

Technology and educator preparation

Technology professional development for K-12

Wearables and virtual reality

Youth, technology, and non-school environments

Career Paths

Funding Options 

Key to teaching, research and learning in the college, associateships provide students with professional experience and financial support. 

These financial awards are made by Ohio State to students based on academic merit through a university-wide competition. 

The college annually awards scholarships to its students to support their academic goals.  

Degree Requirements 

Prerequisites

Master's degree, academic writing sample

Minimum Program hours

51, post-master's degree

Deadline to apply

December 1 

Program start

Autumn Semester 

View Learning Technologies (EDUCST-PH, LTN) Curriculum Sheet

Additional Application Requirements

Academic Writing Sample

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PhD Pathways in Education Technology

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Educational technology, commonly known as EdTech, refers to tools that facilitate active learning through collaboration, allowing educators to create interactive digital textbooks, gamify lessons, and more. Digital devices have increased education’s reach, enabling learning in remote areas and continuity through disruptions like pandemics.

Learn more about Ed Tech industry

• Check out EdSurge , the Ed Tech industry news source
• Overview of Education Technology
• Stanford Report: How technology is reinventing education?
• TED talks by Luis von Ahn (Duolingo’s CEO)

Key Career Opportunities

• Career Development in Education Technology, ISTE
• Job Board -EdSurge

Get Involved and Gain Experience

• Teaching Online at Yale-Poorvu Center for Teaching and Learning
• Participate in Tsai CITY programs to learn skills in innovation and entrepreneurship
• Digital Humanities Lab
• Go on information interviews with Yale alumni

Office of Career Strategy

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Doctor of Philosophy in Education

The Johns Hopkins School of Education’s full-time PhD program offers an individually tailored learning experience based on a student’s interest in finding solutions to pressing education problems. Select applicants receive full tuition and a stipend.

The School of Education will pause admission to the Doctor of Philosophy in Education (PhD) program for the 2025-26 academic year while we add several programmatic improvements. The next intake for admission to the PhD program will be for students who want to matriculate in the Fall 2026 semester. The online application will open in August 2025 to begin accepting submissions, and the application completion deadline will be December 16, 2025. Please complete our Request for Information Form to receive updates and announcements for the next admission period.

The program provides rigorous interdisciplinary training that develops students’ abilities to conduct evidence-based research on real-world educational challenges. Instruction and mentorship emphasizes the development and evaluation of policies and practices that address real-world educational problems.

Students benefit from a one-to-one apprenticeship model that pairs exceptional interdisciplinary candidates with nationally acclaimed faculty mentors, along with engaging coursework, sophisticated methodological training, and cohort-based learning.

Questions? Please reach out and we’ll be in touch soon.

Learn about our PhD students.

Upcoming Admissions Events

Have questions about our degree programs, the application, or financial aid and costs? Join us for an inside look at a graduate experience defined by innovation and driven by evidence-based research. Learn more about your area of interest or career path, meet some of our faculty, and connect to the Johns Hopkins School of Education community. Check out our admissions events and register for a virtual information session today.

International Teaching & Global Leadership Cohort Info Session

Education Policy Info Session

Doctor of Education Info Session

Core Faculty

Jennifer adams, phd.

Associate Professor Director, International Teaching and Global Leadership

Affiliation

Innovative Teaching & Leadership

International Teaching & Global Leadership

Robert Balfanz, PhD

Professor Co-Director, Center for Social Organization of Schools

Center for Social Organization of Schools, SOE Leadership

Education Policy & Politics, Research, Evaluation & Assessment, Social Context of Education

Ashley Rogers Berner, PhD

Associate Professor Director, Johns Hopkins Institute for Education Policy

Institute for Education Policy, SOE Leadership

Curriculum Studies, Education Policy & Politics, Research, Evaluation & Assessment

Rebecca Cruz, PhD

Assistant Professor

Center for Safe and Healthy Schools, Innovative Teaching & Leadership

Education Policy & Politics, Social Context of Education, Special Education

Marcia Davis, PhD

Associate Professor (Research) Co-Director, Center for Social Organization of Schools Director of Research, Baltimore Education Research Consortium

Learning & Instruction, Research, Evaluation & Assessment

Norma L. Day-Vines, PhD

Professor Associate Dean for Diversity and Faculty Development

SOE Leadership

Counseling & Human Development

Hunter Gehlbach, PhD

Professor Faculty Lead, PhD Program

Advanced Studies in Education

Learning & Instruction, Measurement & Research Methodologies

Odis Johnson, Jr., PhD

Bloomberg Distinguished Professor Executive Director, Johns Hopkins Center for Safe and Healthy Schools Director, Institute in Critical Quantitative, Computational, and Mixed Methodologies

Center for Safe and Healthy Schools, SOE Leadership

Education Policy & Politics, Measurement & Research Methodologies, Social Context of Education

Richard Lofton, PhD

Center for Safe and Healthy Schools

Education Policy & Politics, Social Context of Education

Douglas J. Mac Iver, PhD

Center for Social Organization of Schools

Curriculum Studies, Research, Evaluation & Assessment

Martha Abele Mac Iver, PhD

Associate Professor Associate Dean of Research

Research, Evaluation & Assessment

Olivia Marcucci, PhD

Advanced Studies in Education, Center for Safe and Healthy Schools

Social Context of Education

Ebony McGee, PhD

Counseling & Human Development, Postsecondary Education, Social Context of Education, Urban Education

Stephen Morgan, PhD

Bloomberg Distinguished Professor

Measurement & Research Methodologies, Social Context of Education

Jonathan Plucker, PhD

Research Professor Faculty Lead, Master of Science in Education Policy

Counseling & Educational Studies

Education Policy & Politics, Gifted Education, Learning & Instruction

Eric Rice, PhD

Social Context of Education, Urban Education

Joshua C. Schuschke, PhD

Educational Technology

Alexandra Shelton, PhD

Learning & Instruction, Special Education

Angela R. Watson, PhD

Assistant Research Professor

Institute for Education Policy

Education Policy & Politics

Program Overview

With its goal of pursuing big ideas and sharing knowledge to address real-world challenges, Johns Hopkins University takes pride in its founding mission as the U.S.’s first research university. The full-time Doctor of Philosophy (PhD) in Education at the Johns Hopkins School of Education embraces that tradition. We offer a world-class, research-focused program that prepares exceptional scholars to investigate and develop policies and practices that improve educational outcomes from pre-K through secondary school and beyond.

Students draw insights from different disciplines (e.g., educational psychology, learning sciences, sociology of education), synthesizing their knowledge to craft multidisciplinary, evidence-based approaches to address educational policies and practices — particularly those that can improve outcomes for historically underserved populations. Immersion in modern research methods — advanced statistical techniques, open science approaches, and data science — facilitates students’ capacities to argue for research-based educational reforms.

Students benefit from the mentorship of nationally acclaimed researchers in an apprenticeship model as well as collaborative learning opportunities from courses, research groups, and their cohort. Our graduates go on to careers in higher education as professors, policymakers, and influential scholars at research-intensive universities, institutes, and centers.

All PhD students at the School of Education are eligible for a fellowship for up to four years. The fellowship includes a yearly stipend and will cover tuition and fees. The fellowship also covers individual health, dental, and vision insurance. All PhD students must be registered full time and be in good academic standing every semester to continue to be eligible for their fellowship.

Through our PhD program, students acquire cutting-edge research skills that position them for tenure-track faculty positions in higher education, policymaking roles with state agencies or school systems, and leadership positions in educational research organizations.

• Research and Post Secondary Teaching
• University Professor
• University Researcher
• Policy Analyst

“ What set my experience apart was the chance to work with remarkable mentors who are not only impactful researchers in the field, but also genuinely care about me as a person.

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STEM Education, Ph.D.

Download the Curriculum for STEM Education, Ph.D.

Find out what courses you'll be taking

The PhD in STEM Education

The PhD in STEM Education is designed for those who seek to increase their competence in a selected area of STEM education (e.g., science education, mathematics education, educational technology), including competence in a particular STEM field (science, technology, engineering, mathematics). Recipients gain appropriate knowledge and skills for teaching, supervisory, research, and administrative positions in higher education, including college and university STEM Education programs, and programs in STEM fields in community and state colleges, liberal arts colleges, and universities.

There are three primary specializations within the PhD in STEM Education program: Science Education, Mathematics Education, and Educational Technology.

Who May Apply for This Program

Admission to this PhD program requires completion of a Master's degree. Program requirements include completion of:

• a major technical area (MTA), with 21 graduate credits in a STEM field beyond the Bachelor's degree; and
• a minimum of 42 credits of PhD coursework and research.

In addition, Master's graduates who have a strong background in their content field because of their Bachelor's degree and graduate coursework have been admitted into this PhD program. For example, doctoral students with a background and interest in Environmental Education have pursued their PhD studies in Science Education.

Although it is advisable that Master's students seeking to pursue a PhD complete a research experience, students with non-thesis research experience have been allowed to pursue PhD study in STEM Education.

There are three phases of study in this PhD program:

• Phase 1 consists of coursework, both for the MTA requirement and in educational theories and trends, research, and statistics. The coursework in Phase 1 is designed to broaden and deepen students' knowledge in their STEM field and in education, as well as prepare them for dissertation research. Upon completion of the coursework, PhD students take their doctoral comprehensive exams.
• Phase 2 involves the development and defense of a research proposal, with guidance from your major advisor and committee. The preparation and defense of a proposal ensures that each student is able to translate their knowledge into a coherent and feasible research plan.
• Phase 3 involves carrying out all aspects of the proposed study, collecting and preparing data, running analyses, and completing and defending a dissertation. Students enhance their understanding of what goes into the conduct and reporting of educational research in an area of STEM education.

Typically, Phases 1 - 3 require at least four years of full-time effort, but can require more time.

The knowledge and experience gained in this program are useful to graduates as teachers, consumers of research, researchers, and research advisors.

Do Cutting-Edge, Real-World Research

The PhD program in STEM Education is designed to emphasize coursework and research; unlike Bachelor's and Master's degrees, it does not include an internship opportunity. However, courses in educational theories, research, and statistics engage students in projects, and these can be as real-world as students wish. MTA coursework often includes lab and fieldwork.

In addition, although dissertation studies usually emphasize theory and research, many PhD students also design their study to address needs within a particular area of educational practice.

Internationally Recognized Faculty

Among the faculty who teach in this program, Dr. Thomas Marcinkowski has received the Walter E. Jeske Award (2010) and the award for Outstanding Contributions to Research in Environmental Education (1994), both from the North American Association for Environmental Education. His emphasis is on assessment, evaluation, and research studies in the areas of environmental literacy, responsible environmental behavior, and environmental quality. He has been involved in the development of assessment tools in these areas and, more generally, in program evaluation studies.

Samantha Fowler has received the Outstanding Position Paper Award (2013) from Southeastern Association for Science Teacher Education. She focuses on socio-scientific reasoning - how the general public uses scientific information in their day-to-day lives and how policy-makers use scientific evidence in their decisions. She is currently researching how social media effects socio-scientific reasoning, particularly regarding controversial issues. She also explores the effectiveness of new pedagogy styles in lecture and laboratory classes.

Career Benefits

This PhD degree is not designed to help doctoral students satisfy credentialing requirements - that is undertaken at the Bachelor's and Master's levels. However, from both an occupational and a professional perspective, one of the benefits of completing a PhD is to become more competitive career-wise, which is vital in today's challenging job environment. The research background and experience students gain in this PhD program adds depth to their teaching, and provides them with insights that aid them in their future research and research advisory work.

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• 100% Online

Educational Technology, PhD

• Program description
• At a glance
• Degree requirements
• Admission requirements
• Tuition information
• Career opportunities
• Contact information

Teacher, approved for STEM-OPT extension, classroom, computers, design, edupltpe, teachers college

ASU is not currently accepting applications for this program. Prospective students might consider the Learning Design and Technologies, MEd .

The focus of the PhD program in educational technology is on the design, development and evaluation of instructional systems and on educational technology applications that support learning. The doctoral program emphasizes research using educational technology in applied settings.

This program may be eligible for an Optional Practical Training extension for up to 24 months. This OPT work authorization period may help international students gain skills and experience in the U.S. Those interested in an OPT extension should review ASU degrees that qualify for the STEM-OPT extension at ASU's International Students and Scholars Center website.

The OPT extension only applies to students on an F-1 visa and does not apply to students completing a degree through ASU Online.

• College/school: Mary Lou Fulton Teachers College
• Location: Tempe
• STEM-OPT extension eligible: Yes

84 credit hours, a written comprehensive exam, a prospectus and a dissertation

Required Courses (24 credit hours) EDP 540 Learning Theories and Instructional Strategies (3) EDP 552 Multiple Regression and Correlation Methods (3) EDP 554 Analysis-of-Variance Methods (3) LDT 501 Foundations of Learning Design and Technologies (3) LDT 502 Design and Development of Instruction (3) LDT 503 Design of Effective Communications (3) LDT 504 Modalities of Learning (3) LDT 506 Evaluation of Learning Systems (3) EDT 701 Research in Educational Technology (3)

Elective Courses (30 credit hours) Students select a minimum of 30 credit hours of elective coursework in consultation with a faculty advisor or doctoral committee chair.

Practicum Hours (6 credit hours and research) Students must earn at least 18 credit hours for practicum courses. Students complete three different practica while in the program: instructional design (typically EDT 780 Practicum for three credit hours), teaching (typically EDT 680 Practicum for three credit hours), and a research practicum.

Research (12 credit hours)

Culminating Experience (12 credit hours) EDT 799 Dissertation (12)

Applicants must fulfill the requirements of both the Graduate College and the Mary Lou Fulton Teachers College.

Applicants are eligible to apply to the program if they have earned a bachelor's or master's degree in any field from a regionally accredited institution.

Applicants must have a minimum cumulative GPA of 3.20 (scale is 4.00 = "A") in their first bachelor's degree program, or a minimum cumulative GPA of 3.20 (scale is 4.00 = "A") in an applicable master's degree program.

All applicants must submit:

• graduate admission application and application fee
• official transcripts
• three email addresses for professional recommendations
• personal statement
• proof of English proficiency

Additional Application Information An applicant whose native language is not English must provide proof of English proficiency regardless of their current residency. The Mary Lou Fulton Teachers College requires a minimum score of 100 on the TOEFL iBT.

Scores of 500 or above on the verbal reasoning and quantitative reasoning sections of the GRE are required, as well as a score of four or greater on the analytical writing section of the GRE. ASU does not accept the GRE® General Test at home edition.

The program prepares students for a variety of professional positions. Graduates are employed as faculty, educational technologists or instructional designers in universities, community colleges and schools, or as training managers in corporate settings.

Educational Leadership & Innovation, Division | ED 118 [email protected] 480-965-5555

Doctor of Education in Educational Technology

100% online program.

The doctoral program in educational technology, leading to an EdD degree, has as its goal the development of innovative leaders in the field. You can explore the use of current and emerging technologies for effective and efficient teaching in a dynamic, global society. Areas of particular focus include online teaching and learning, technology integration, academic technology leadership, innovative teaching in K-12 and higher education, educational software development for the web and mobile platforms, and educational Games and simulations.

The EdD in Educational Technology program at Boise State University can be completed entirely online; there are no on-campus or in-person requirements. All courses and exams/defenses can be completed at a distance, though in some cases synchronous (same time) attendance is required.

About this Program

• Format : The EdD in Educational Technology program is 100% online.
• Official Degree Name:  Doctor of Education in Educational Technology
• Degree Type:  Doctor of Education

Note: Content on this page is provided as a quick reference for planning. All official course descriptions/degree requirements/admission standards/program learning outcomes/etc. are published on the Graduate College’s website  Graduate Catalog .

What can I do with this degree?

Graduates from our EdD program have opportunities in different areas. For example, some of our graduates work in higher education either as faculty or instructional designers helping faculty and students with the course design and technical support. Other graduates work as instructional designers in different environments such as schools, school districts, or other educational environments.

Our students do research in diverse areas in educational technology, such as professional development, online learning, learning analytics, data mining, games and simulations, and mobile technologies.

Degree Requirements and Advising Resources

Admission requirements.

Applicants are required to have earned at least a baccalaureate degree and a master’s degree from a regionally accredited U.S. college or university or a degree from a non-U.S. institution of higher education that is judged equivalent to a U.S. baccalaureate degree and master’s degree by the International Admissions office and have an undergraduate grade point average (GPA) of 3.00 (based on a 4-point scale) computed for all undergraduate credits from the applicant’s most recent baccalaureate degree and a graduate (GPA) of 3.50 (based on a 4-point scale) computed for all graduate credits.

A prospective student may apply at any time and should follow the general graduate application procedure for degree-seeking students (see Graduate Admission Regulations ). Admission to the program is based on:

• Official transcripts from all colleges attended.
• A letter of application that adheres to the guidelines linked from the EdD Program Application page.
• A current résumé or curriculum vitae.
• A writing sample.
• Three letters of recommendation.
• GRE Scores: The GRE is not required for an application, but can be submitted if the applicant desires to do so.

Learn more about our Admissions process by reading our  EdD Application Guidebook

Note: Ed.D. students can also earn a graduate certificate in one of the specializations: GAMES AND SIMULATIONS, ONLINE TEACHING, SCHOOL TECHNOLOGY COORDINATION, INSTRUCTIONAL TECHNOLOGY COACHING, TECHNOLOGY INTEGRATION, COMPUTER ASSISTIVE LANGUAGE LEARNING, ASSISTIVE TECHNOLOGY (STARTING FALL 2021), DIGITAL LITERACIES INSTRUCTION (STARTING FALL 2021), or DESIGNING ACCESSIBLE ONLINE EDUCATION (STARTING FALL 2021). In order to do so, please indicate the appropriate certificate on the Graduate Admissions application form. It is important for students to apply for a certificate before starting the course work.

Program Requirements

For course descriptions, please visit our  Course Information .

Students in the online Doctor of Education in Educational Technology program are not required to be physically present on campus for classes, presentations, etc. In most cases, students are required to be enrolled in seven graduate credit hours per semester for the first two years of the program (exceptions are made based on a plan of study that accounts for transfer credits). Students must be enrolled in at least one credit hour every semester thereafter until successfully defending the dissertation (even if all courses and thesis hours have been completed).

Application Deadlines

Submit application and admission materials well in advance of the deadline to ensure the application is complete by the deadline. Please note that all new cohorts start in the FALL semester.

• Early Review Deadline: No later than the first Monday of November*
• Regular Deadline: No later than before the first Monday of February

* At the early review deadline, selected applications will go through our review process. If an applicant is offered a place in the upcoming cohort (which starts the following fall semester), they can take class(es) in the upcoming spring and/or summer semesters related to the elective or cognate requirements, if so desired – there is no obligation to do so. If a completed application is ready by early November, but is not reviewed in the “early review” cycle, it will be reviewed again during the regular Spring review starting in February.

EdD Program Handbook

Advanced Graduate Programs Handbook

Estimated Costs

The cost per credit is $599 for courses numbered in at the 600 level, and $478 per credit for courses numbered at the 500-level. Doctoral students take a total of 60 credits with a mix of 500-level and 600-level courses.

To see an estimate of the other costs, please refer to our Tuition page .

The College of Education also offers a range of scholarship opportunities. 

Have questions or need more information? Contact us or explore related resources.

Request More Information

Edd application guidelines.

Education (PhD) – Instructional Design and Technology

Program at a glance.

• In State Tuition
• Out of State Tuition

Learn more about the cost to attend UCF.

The Instructional Design and Technology track in the Education PhD program prepares students for teaching and research in the field of instructional design and technology, instructional systems, educational technology, and e-learning in professions such as university professor, corporate directors of training and human resources, and corporate researchers.

The focus is on the design of conventional in-class, online and hybrid training and educational programs, and the application of appropriate instructional technologies to facilitate adult learner. For more information about the Instructional Design and Technology track, visit education.ucf.edu/insttech .

The Instructional Design and Technology track in the Education PhD program requires a minimum of 60 credit hours beyond the master's degree. Students must complete 24 credit hours of core courses, 9 credit hours of specialization courses, 9 credit hours of electives, 3 credit hours of internship, and 15 credit hours of dissertation. All students must also complete the candidacy examination.

Total Credit Hours Required: 60 Credit Hours Minimum beyond the Master's Degree

Application Deadlines

• International

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Enter your information below to receive more information about the Education (PhD) – Instructional Design and Technology program offered at UCF.

Track Prerequisites

A master's degree in a closely related field.

Degree Requirements

Required courses.

• IDS7500 - Seminar in Educational Research (1 - 99)
• IDS7501 - Issues and Research in Education (3)
• EDF7475 - Qualitative Research in Education (3)
• EDF7403 - Quantitative Foundations of Educational Research (3)
• EDF7463 - Analysis of Survey, Record, and Other Qualitative Data (3)
• IDS7502 - Case Studies in Research Design (3)
• EDF7406 - Multivariate Statistics in Education (3)
• IDS 7502 - Case Studies in Research Design may be substituted with one of the approved research electives in Group A listed under Program Details EDF 7406 - Multivariate Statistics in Education may be substituted with one of the approved research electives in Group B listed under Program Details

Specialization

• IDS6504 - Adult Learning (3)
• IDS6503 - International Trends in Instructional Systems (3)
• EME7634 - Advanced Instructional Systems Design (3)

Elective Courses

• Earn at least 9 credits from the following types of courses: Cognate or elective; approved by adviser

Dissertation

• Earn at least 15 credits from the following types of courses: EME 7980 - Dissertation Research Doctoral students must present a prospectus for the dissertation to the doctoral adviser, prepare a proposal and present it to the dissertation committee, and defend the final research submission with the dissertation committee.

Required Internship

• EME7942 - Doctoral Internship in Educational Technology (3)
• To enter candidacy for the PhD, students must have an overall 3.0 GPA on all graduate work included in the planned program and pass all required examinations. Examinations will be scheduled by the student and major adviser. Students must be enrolled in the university during the semester an examination is taken. The following are required to be admitted to candidacy and enroll in dissertation hours: - Submission and completion of approved program of study, except for dissertation hours. - Successful completion of the candidacy examination. - The dissertation advisory committee is formed, consisting of approved graduate faculty and graduate faculty scholars. - Satisfactory progress toward the independent learning requirements as evidenced by the annual accomplishments and activities report.

Candidacy Examinations

• All PhD candidates will be required to complete two examinations. Please note that there may be variations in length of exam time and content based on the respective requirements of each track. - Research in the Specialization—8-hour written examination. - Specialization—3-hour oral examination.

Grand Total Credits: 60

Application requirements, financial information.

Graduate students may receive financial assistance through fellowships, assistantships, tuition support, or loans. For more information, see the College of Graduate Studies Funding website, which describes the types of financial assistance available at UCF and provides general guidance in planning your graduate finances. The Financial Information section of the Graduate Catalog is another key resource.

Fellowship Information

Fellowships are awarded based on academic merit to highly qualified students. They are paid to students through the Office of Student Financial Assistance, based on instructions provided by the College of Graduate Studies. Fellowships are given to support a student's graduate study and do not have a work obligation. For more information, see UCF Graduate Fellowships, which includes descriptions of university fellowships and what you should do to be considered for a fellowship.

• EDF 7406 - Multivariate Statistics in Education 3 Credit Hours
• EDF 7405 - Quantitative Methods II 3 Credit Hours
• EDF 7410 - Application of Nonparametric and Categorical Data Analysis in Education 3 Credit Hours
• EDF 7415 - Latent Variable Modeling In Education 3 Credit Hours
• EDF 7473 - Ethnography in Educational Settings 3 Credit Hours
• EDF 7474 - Multilevel Data Analysis In Education 3 Credit Hours
• EDF 7488 - Monte Carlo Simulation Research in Education 3 Credit Hours
• SPA 7495 - Doctoral Seminar II: Spoken and Written Language Disorders 3 Credit Hours (Communication Sciences Track students only)
• IDS 7938 - Research Cluster Seminar 3 Credit Hours

Independent Learning

During their program of study, PhD students are required to meet the following requirements for independent learning to enter candidacy, including:

• Submitting a manuscript that is deemed appropriate by at least one program faculty member for publication in a peer-reviewed journal.
• Presenting research in at least one international, national or state conference.
• Presenting at university and/or college research symposiums annually.
• Providing service to professional organization, community partner, and/or program.
• Documenting and presenting independent learning accomplishments and activities along with development of an individual research agenda deemed satisfactory by at least two or more program faculty on an annual basis.

Department of Counseling, Educational Psychology & Special Education

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Ph.D. in Educational Psychology and Educational Technology

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A Unique & Rich Combination in an Ed Psych and Ed Tech Doctoral Program

The  nationally ranked  Educational Psychology and Educational Technology (EPET) doctoral program produces scholars and leaders in the study of human learning and development and/or in the design and study of diverse technologies supporting learning and teaching. It emphasizes rigorous scholarship and diverse analytical perspectives on learning, development and technology embedded in culture and society.

The program prepares graduates to pursue careers in university research and teaching, research on and development of educational technologies and leadership roles in school systems and the private sector.

YOU’RE WELCOME AT MSU

The EPET doctoral program welcomes applicants from a wide variety of disciplinary backgrounds, educational and technological experiences, and social, economic, and cultural backgrounds. We enact our commitment to sustaining a community that is inclusive, and diverse through ongoing engagement in equity-focused learning and program reform, and systems for student representation and community accountability.

The flexibility of the EPET program allowed me to explore extant research in a variety of areas, which allowed me to bring multiple forms of expertise to project work and proposal development. —Katie Rich (2021) Senior Researcher, American Institutes for Research

I always thought that the faculty were invested in my growth and development, were themselves intellectually curious, held us to high standards, and helped us to meet those standards. —Amy Chapman (2019) Director, Teachers College, Columbia University

Students develop expertise in Ed Psych, Ed Tech, or the intersection of these emphasis areas

Educational psychology.

Investigate human learning, motivation, and development in schools, workplaces, communities and homes. Understand and improve educational practice. Students can base their inquiry in specific domains (e.g., mathematics, literacy, science) or age groups (e.g., adolescents, adults). In 2024, MSU was named #4 in the nation for educational psychology.

EDUCATIONAL TECHNOLOGY

Investigate and improve the use of technologies to support learning and teaching. Engage in research and development on the pedagogy, policy and design of media and technologies in support of learning in formal environments (e.g. face-to-face, online classes) and in informal settings (e.g. homes, after-school programs).

In EPET, especially with the mentorship of my co-advisors, I learned how to think and how to write. During my time in EPET, I was supported in exploring a wide range of research interests, methodologies, and tools for data analysis. I use these skills in research design and alignment every day as an assistant professor. — Bret Staudt Willet (2021) Faculty, Florida State University. Recently awarded a Sloan Foundation Grant , “Programming Language: How Descriptions of Graduate Programs Affect Student Outcomes at MSIs”

One program, two different modes

On-campus mode.

Designed for students willing and able to pursue their degree on a full-time basis. On-campus students typically complete three courses each semester, work 20 hours per week on paid teaching or research assistantships, and require four or more years to earn their degree.

Learn More ›

HYBRID MODE

Designed for students who are working full-time and want to pursue their degree on a part-time basis. Hybrid students typically enroll in two courses per semester and require five or more years to earn their degree. Hybrid students do not receive paid assistantships from the program.

My time in EPET gave me the research skills, broader career skills, and networks that made it possible for me to get this job and thrive in it. In addition to the excellent mentorship I got from my advisor, committee, and lab group, EPET’s brownbags, social events, and communications were so welcoming and helped me feel and become a part of the ed psych research community. I feel very lucky that I got my PhD training in such a collaborative, supportive program that gave me such confidence and joy in being part of this great group of scholars. — Kristy A. Robinson (2019) Faculty, McGill University

Land Acknowledgment:

We collectively acknowledge that Michigan State University occupies the ancestral, traditional, and contemporary Lands of the Anishinaabeg – Three Fires Confederacy of Ojibwe, Odawa, and Potawatomi peoples. In particular, the University resides on Land ceded in the 1819 Treaty of Saginaw. We recognize, support, and advocate for the sovereignty of Michigan’s twelve federally-recognized Indian nations, for historic Indigenous communities in Michigan, for Indigenous individuals and communities who live here now, and for those who were forcibly removed from their Homelands. By offering this Land Acknowledgement, we affirm Indigenous sovereignty and will work to hold Michigan State University more accountable to the needs of American Indian and Indigenous peoples. More information

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Education, PhD

School of education.

The School of Education will pause admission to the Doctor of Philosophy in Education (PhD) program for the 2025-26 academic year while we add several programmatic improvements. The next intake for admission to the PhD program will be for students who want to matriculate in the Fall 2026 semester. The online application will open in August 2025 to begin accepting submissions, and the application completion deadline will be December 16, 2025.

The overarching goal of the School of Education’s PhD in Education program is to develop scholars who will have advanced research skills for improving education practice, with specific emphases on policy analysis and education improvement. The program strives to prepare candidates that are equipped to:

• meet the myriad challenges associated with systemic education change;
• apply exceptional content area expertise contextualized within a comprehensive multidisciplinary frame of reference;
• successfully bridge the theory and research to evidence-based practice gap;
• be actively involved in public policy development and evaluation;
• conduct research on complex databases linking educational practices to student outcomes, or lead laboratory- or school-based research programs that inform efforts to improve educational practices and student outcomes; and
• develop national models of educational practice that guide curriculum development and educator preparation.

For Program updates and more information, please visit the website .

Admission Requirements

At minimum, applicants to the PhD program should hold a master’s degree from an accredited college or university. Previous degrees must document outstanding academic achievement in an area of study closely associated with the objectives of the program. Applicants must submit the online admission application form, application fee, and official transcripts from all post-secondary institutions attended. If the earned degree or credit is from an educational institution abroad, the candidate’s academic record must be evaluated by a credential evaluation agency before consideration for admission. Applicants are required to earn superior scores on the Graduate Record Examination (GRE) (taken within the past five years), present acceptable TOEFL or IELTS scores (if an international student), and demonstrate potential to become top scholars. Additionally, applicants are required to submit a curriculum vitae, a personal statement (outlining professional plans, goals, and expectations related to the PhD program), dispositions survey, and three letters of reference affirming the applicant’s qualifications for advanced graduate study and potential for professional development in the field. Selected applicants who meet the entrance requirements will be invited to interview with the doctoral admissions committee.

Program Requirements

Program structure and requirements.

Program requirements include earning a minimum of 72 graduate credits taken at the doctoral level at Johns Hopkins University. While the program will be tailored to the specific learning needs of each student, it includes the following coursework components:

• ED.855.725 Research Landscape*
• ED.883.812 Data Workflow*
• ED.883.601  Basic and Inferential Statistics*
• *indicates a required course
• ED.855.815 Science of Learning*
• ED.855.764 Schools in Society*
• ED.855.835 Socio-Cultural Perspectives*
• ED.855.723 Education Policy Practicum*
• ED.855.855  Research Proseminar^
• ED.855.854 Practice Proseminar
• ED.855.852 Research Practicum^
• ED.883.723 Hierarchical Linear Models^
• ED.883.711  Qualitative Research Methodology^
• ED.855.853 Savvy Surveys^
• ED.855.704 Economics of Education
• ED.855.701 Introduction to Causal Inference^
• ED.855.702 Casual Inference When Regression Fails^
• ED.855.840 Doctoral Research
• ^indicates a research elective
• Dissertation Research (18 credit hours)

In addition to successfully completing all the coursework requirements, candidates must also satisfy the following program benchmarks:

• Research progress
• Written and oral comprehensive examinations
• Dissertation proposal oral examination
• Graduate Board oral examination
• Final dissertation exam

Each student will receive an annual written evaluation from the School of Education’s Doctoral Studies Committee detailing their progress in meeting the required benchmarks at the end of each spring semester.

All School of Education PhD students will devote at least four years to full-time study and research as a resident student. This period of time will provide opportunity for full engagement and participation in the academic community and allow students to develop and demonstrate the scholarly capabilities required of the degree. The typical program of study is eight semesters, with six semesters devoted to coursework and research/teaching intensive experiences and two semesters devoted primarily to independent dissertation research. Students will typically enroll in 12 hours per semester for the first three years of their program and 9 hours per semester during the fourth year of their program, for a total of 90 credit hours. All students are expected to maintain enrollment as full-time graduate students over the course of the program. With the approval of their major adviser and director of the PhD program, students may transfer up to 12 credit hours of previously completed graduate-level coursework to substitute for selected required courses in the program.

Typically, each year four-to-eight PhD students will be admitted each year to begin classes in the fall semester. The majority of required courses will be delivered on the Baltimore Homewood campus in a face-to-face format, although students may (with approval) enroll in selected elective courses in divisions throughout the university.

Students must complete qualifying exams after completing two years of study. The successful completion of the written documents and oral defense of those documents allows the student to proceed to the dissertation proposal.

Dissertation

The program is designed as an apprenticeship model leading to a traditional research dissertation. The expectation is that students will be developing the skills and background knowledge throughout the program required to pursue a traditional research dissertation. Although the dissertation is not part of the formal coursework, the program is designed to put a student on track to develop an area of expertise as the foundation for an independent research project directed by the adviser. Students are expected to complete and defend a dissertation proposal by the end of the third year of study and use the final year of the program to complete and defend the dissertation. The dissertation is expected to demonstrate mastery of the relevant literature and scholarship in the collection and interpretation of data. The work should be appropriate for publication in high impact journals in the student’s area of expertise. The dissertation will be presented at a final oral defense before the student’s Dissertation Advisory Committee.

Note: Full tuition assistance and annual stipends are available to support selected outstanding candidates . For more information about the PhD program, please visit the website .    

Please see Academic Standards .

Learning Outcomes

Program goals.

Graduates will be prepared to fill faculty and research scientist positions at research-intensive universities or secure positions at research institutes and centers that conduct and manage large-scale education-based evaluations. Upon successful program completion we expect that graduates will:

• Be prepared for employment in research/faculty positions at top-tier research institutions.
• Contribute to the interdisciplinary public discourse on education improvement.
• Engage in and promote evidence-based practices through the application of rigorous methodology.
• Link education research to policy and practice.
• Provide leadership in the field by developing an independent line of ethical and culturally responsive research.
• Contribute to development of the next generation of scholars.
• Be able to influence school policy and reform.

Doctoral Degrees

A doctoral degree requires the satisfactory completion of an approved program of advanced study and original research of high quality..

Please note that the Doctor of Philosophy (PhD) and Doctor of Science (ScD) degrees are awarded interchangeably by all departments in the School of Engineering and the School of Science, except in the fields of biology, cognitive science, neuroscience, medical engineering, and medical physics. This means that, excepting the departments outlined above, the coursework and expectations to earn a Doctor of Philosophy and for a Doctor of Science degree from these schools are generally the same. Doctoral students may choose which degree they wish to complete.

Applicants interested in graduate education should apply to the department or graduate program conducting research in the area of interest. Some departments require a doctoral candidate to take a “minor” program outside of the student’s principal field of study; if you wish to apply to one of these departments, please consider additional fields you may like to pursue.

Below is a list of programs and departments that offer doctoral-level degrees.

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Higher Education - Ph.D.

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Degree Information

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Degree details.

The online Ph.D. in Higher Education is designed for professionals in the field who are interested in using data science to best prepare students and confront challenges facing higher education. The program will provide preparation to be adapted to any post-secondary role with a focus to improve college access, student success, and persistence to completion. Driven by data science, program candidates will apply actionable approaches to face challenges confronting higher education. Graduates will use their data science knowledge and skills to guide colleges and universities, state higher education agencies, foundations, and related associations.

Admissions Requirements

Students seeking admission to the Higher Education Ph.D. program are required to have:

• Degree:  a Master’s degree from an accredited institution
• GPA:  at least 3.0 on a 4.0 scale
• Professional Curriculum Vitae (CV) / Resume
• Letters of Recommendation:  Two letters of recommendation that speak to the individual’s scholarly aptitude and capability, particularly with respect to graduate-level work
• Statement of Intent: that speak to the individual’s scholarly aptitude and capability, particularly with respect to graduate-level work
• Academic Writing Sample: a sample that demonstrates excellent scholarly writing ability (applicant must be sole author)
• Interview:  must interview at the discretion of the Higher Education Ph.D. application review committee.

International students are required to demonstrate competency in spoken and written English by taking appropriate standardized tests. See accepted standardized tests and minimum required scores »

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The future of educational technology

Dan Schwartz is a cognitive psychologist and dean of the Stanford Graduate School of Education.

He says that artificial intelligence is a different beast, but he is optimistic about its future in education. “It’s going to change stuff. It’s really an exciting time,” he says. Schwartz imagines a world not where AI is the teacher, but where human students learn by teaching AI chatbots key concepts. It’s called the Protégé Effect, Schwartz says, providing host Russ Altman a glimpse of the future of education on this episode of Stanford Engineering’s The Future of Everything podcast.

Listen on your favorite podcast platform:

Related : Dan Schwartz , professor of educational technology

[00:00:00] Dan Schwartz: You know, the tough question for me is, should you let the kid use ChatGPT during the test? Right? And we had this argument over calculators, right? And finally they came up with ways to ask questions where it was okay if the kids had calculators. Because the calculator was doing the routine stuff and that's not really what you cared about. What you cared about was, could the kid be innovative? Could they take another, a second approach to solve a problem? Things like that.

[00:00:33] Russ Altman: This is Stanford Engineering's The Future of Everything, and I'm your host, Russ Altman. If you're enjoying The Future of Everything podcast, please hit the follow button in the app that you're listening to now. This will guarantee that you never miss an episode. 

[00:00:46] Today, Dan Schwartz will tell us how AI is impacting education. He studies educational technology and he finds that there's a lot of promise and a lot of worries about how we're going to use AI in the classroom. It's the future of educational technology. Before we get started, please remember to follow the show in the app that you listen to. You'll be alerted to all of our episodes and it'll make sure that you never miss the future of anything.

[00:01:16] You know, the rise of AI has been on people's minds ever since the release of ChatGPT. Especially the powerful one that started to do things that were scary good. We've seen people using it in business, in sports, in entertainment, and definitely in education. When it comes to education, there are some fundamental questions, however, are we teaching students how to use AI? Or are we teaching students? How do we assess them? Can teachers grade papers with AI? Can students write papers with AI? Why is anybody doing anything? Why don't we just have the AI talk to itself all day? These are real questions that come up in AI. 

[00:01:55] Fortunately, we're going to be talking to Dan Schwartz, who's a professor of education and a dean of the School of Education at Stanford University about how AI is impacting education.

[00:02:06] Dan, the release of ChatGPT has had an impact all over the world, people are using it in all kinds of ways. And clearly one of the areas that AI, especially generative AI has made impact is in education. Students are clearly using it, teachers are thinking about using it or using it. You're the Dean of Education at Stanford. What's your take on the situation right now for AI in education? 

[00:02:33] Dan Schwartz: Okay, so lots of answers to that, but, but, you know, the thing I've enjoyed the most is, uh, showing it to people and watching their reaction. So I'm a cognitive psychologist. I study creativity, learning, what it means to understand. And you show this to people and you just see them go, oh my lord.

[00:02:53] And then the next thing you see is they begin to say, uh, what's left for humans? Like what's left? And then they sort of say, wait a minute, will there be any jobs? And then finally they sort of say. Oh my goodness, education needs to change. And as a dean who raises money for a school, this is the best thing to ever happen. No, whether it's good or bad, it doesn't matter. Everybody realizes it's going to change stuff. And so it's really an exciting time. 

[00:03:22] Russ Altman: So that is really good news. I have to say going into this and I have to reveal a bias. I have often wondered if technology has any place in a classroom. And I think it's because I was, uh, I was injured as a youth.

[00:03:37] This is in the 1970s when some teachers tried to put a computer program in front of me and I was a pretty motivated student and I worked with this computer for about six minutes, and I should say, I'm not an anti-computer person. I literally spent all my time writing algorithms and doing computation work. But I just felt as a youth that I wanted to have a teacher in front of me, a human telling me things. Uh, and so that is clearly not the direction, I hear you laughing. So talk to me about the appropriate way to think about computers. Because I really have a big negative reaction to the idea of anything standing between me and a teacher.

[00:04:18] Dan Schwartz: You must have had very good teachers. 

[00:04:19] Russ Altman: I might have. 

[00:04:19] Dan Schwartz: So Russ, you sound like someone who doesn't play video games. 

[00:04:23] Russ Altman: I do not play video games. 

[00:04:24] Dan Schwartz: So there's this world out there where people can experience things they could never experience, uh, directly. And no teacher can deliver this immersive experience of you in the Amazon searching for anthropological artifacts. There's also something called social media that people use. 

[00:04:43] Russ Altman: I've heard about this. 

[00:04:43] Dan Schwartz: Yeah. Yeah. 

[00:04:44] Russ Altman: I think we disseminate the show using it. 

[00:04:46] Dan Schwartz: So back in the day. 

[00:04:47] Russ Altman: Okay. So I'm a dinosaur. 

[00:04:49] Dan Schwartz: Uh, back in the day, you got the Apple 2 maybe, and it's about 64 K, maybe. It's got a big floppy drive and it takes all its CPU power to draw a picture of a two plus two on the screen. So I think things have changed a little bit Russ. But I appreciate your desire to be connected to teachers. I don't think we're replacing them. 

[00:05:14] Russ Altman: I'm not going to give you a lecture about teaching. But I will say this one sentence that was reverberating through my brain when I was getting ready for our interview, which was when I'm in a classroom, and this has been since I've been in third grade. I am watching the teacher trying to understand, how they think about the information and how they struggle with it to like understand it and then try to relay it to me.

[00:05:34] And so it is, that's where I'm learning. I'm, it's not even what they're saying. It's they're painting a picture for their cognitive model of what they're talking about. And that's what I'm trying to pull out to this day. And so that's why I have such a negative reaction to anything standing between me and this other human who has a model that is more advanced than mine about the material that we're struggling with and I just, I'm trying to download that model. 

[00:06:01] Dan Schwartz: Wow. You're, you are a cognitive psychologist, Russ? 

[00:06:03] Russ Altman: I don't know. 

[00:06:05] Dan Schwartz: Like I had a buddy who sort of became a Nobel laureate. And he talked about how he loved take apart cars, and I'd say I love to watch you take apart cars, just to figure out what you're doing. No, so I think, let's separate this. There's the part where you think the interaction with the teacher is important. I don't know that you need it eight hours a day. You know, that's an awful lot of interaction. I'm not sure I want to be with my mom and dad for eight hours a day trying to figure out their thinking. So you don't need it all the time.

[00:06:34] On the other side, you know, we can do creative things with the computers. So for example, I wrote a program where students learn by teaching a computer agent. And so they're trying to figure out how to get the agent to think the way it should in the domain. Turns out it's highly motivating. The kids learn a lot. The problem was the technology quickly became obsolete. Because after kids used it for a couple of days, they no longer needed it, 'cause they'd figured out sort of how to do the kind of reasoning that we wanted them to teach the agent to do for reasoning. 

[00:07:06] Russ Altman: That's exactly what I was talking about before, about my relationship with my teacher. And you just flipped it, but it's the same idea, which is that there's a cognitive model that you're trying to transfer. And by doing that transfer, you get in, you introspect on it and you understand what it is that you're thinking about. 

[00:07:22] Dan Schwartz: I think that's right. You know, so the concern is the computer does all the work, right? And so I'm just sitting there pressing a button that isn't relevant to the domain I'm trying to learn. But you know, uh, one of the things computers are really good at, like as good as casinos, is motivation. So some computer programs, they gamify it. I'm not sure that's a great use of it. Because you, you know, you try and you learn to just beat the game for the reward. 

[00:07:49] Russ Altman: Right.

[00:07:49] Dan Schwartz: As opposed to learn the content. But things like having, teaching an intelligent agent how to think. There's something called the protege effect, which is you'll try harder to learn the content to teach your agent than you will to prepare for a test. Right? So we can make the computer pretty social. 

[00:08:08] Russ Altman: Okay. So you are clearly a technology optimist in education. And in addition to the amazing fundraising and like, there's so many questions to be answered. What I think a lot of people are worried about is, are we at risk of losing a gen. We've already lost a few generations of students, some people argue, because of the pandemic and the terrible impact it had, especially on, uh, on people who weren't privileged in society and in their education.

[00:08:34] Are we about to enter yet another shock to the system where, because of the ease of having essays written and having, and grading papers, that we really don't serve a generation of students well? Or do you think that's a overhyped, unlikely to happen thing? 

[00:08:51] Dan Schwartz: No, it's a good question. You know, that part of this is people's view about cheating, you know? And so it's too easy for students to do certain things. But there's another response that I want to hang on to. I want to ask you, Russ, are you using, you teach. 

[00:09:07] Russ Altman: Yeah. 

[00:09:07] Dan Schwartz: Are you like putting in all sorts of rules to prevent students from cheating, or are you saying, use it, do whatever you can. I'm going to outsmart your technique anyway.

[00:09:17] Russ Altman: It's a little bit more on the latter. So we, uh, I teach an ethics class, which is a writing class. And we allow ChatGPT because the, my fellow instructor and I decided, and this was the quote, we want to be part of the future, not part of the past. So we said to the students, 

[00:09:33] Dan Schwartz: Sorry, The Future of Everything, Russ.

[00:09:34] Russ Altman: Thank you. Thank you. Thank you. And thanks for the plug. So, uh, we allow it. We asked them to tell us what prompt they used and to show us the initial output that they got from that prompt. And then we, of course, have them hand in the final thing. And we instruct the TAs and ourselves, when we grade that we're grading the final product with or without a declaration of whether ChatGPT is used.

[00:09:56] We do have engineers as TAs, which means that they did a careful analysis. Students who used ChatGPT, and I don't think this is a surprise, got slightly lower grades, but spend substantially less time on the assignment. So if you're a busy student, you might say, I will make that trade off because the grades weren't a ton worse. It was like two points out of a hundred, like from a ninety to an eighty-eight, and they completed it in like half the time. 

[00:10:25] Dan Schwartz: Uh, do you think they learned less? 

[00:10:28] Russ Altman: So we don't know. We don't know. And, uh, the evaluation of learning is something that I'm looking to you, Dan. Uh, how do I tell? So, um, so we do try to use it. But we are stressed out. We have seen cases where people say they used ChatGPT, but tried to mislead us in how they use it. They said, I only used it for copy editing, but it was clear that they did more than copy editing with it. And so there's at the edges, there are some challenges. But in the end, we said motivated students who want to learn will use it as a tool and we'll learn. And the students who we have failed to motivate, and it is our failure, you could argue. They're just going to do whatever they do, and we're not going to be able to really impact that trajectory very much. 

[00:11:12] Dan Schwartz: Yeah, you know, you sort of see the same thing with video, video-based lectures. So I'm online. I've got this lecture. Do I really want to sit and listen to the whole thing? Not really. I'm going to skim forward to find the information. I skim back. I'm probably going to end up doing the minimum amount if it's not a great lecture. 

[00:11:29] Russ Altman: Yeah.

[00:11:29] Dan Schwartz: So I'm not sure this is a ChatGPT phenomenon. It's just, it's sort of an enabler. I think the challenge is thinking of the right assignment. So like, you can grade things on novel and appropriateness. So, are they novel? You know, if they use ChatGPT like everybody else, they won't be novel. They'll all produce the same thing. 

[00:11:48] Russ Altman: It's incredibly, yes. It, so it is, um, there's the most common type of, uh, moral theory is called common morality. And it turns out that ChatGPT does pretty well at that one because there's so many examples that it has seen. And it's terrible at Kant. Deontology, it really can't do. Okay, so let me. 

[00:12:07] Dan Schwartz: So let me get back to your question. 

[00:12:09] Russ Altman: Yeah. 

[00:12:09] Dan Schwartz: So here's what I see going on right now. There, there are like, uh, big industry conferences. Because they're going to, they're producing the technology that schools can adopt. Right? And there's a lot of money there. And twenty years ago, there were zero unicorns, and about, uh, I think last year, fifty-four billion dollar valuation companies in ed tech. So this is a big change. So what are they doing? They're basically creating things to do stuff to students, right? 

[00:12:42] So maybe they're marketing to the teachers, but it's, you know, it's, I'll make a tutor that, uh, is more efficient at delivering information to the students. Or, I will make a program that can correct their math very quickly. And so what's happening is the industry is sort of using the AI in the way that nobody else uses it.

[00:13:04] Because everybody who's got this tool wants to create stuff, right? Like, uh, my brother. It's my birthday, what does he do? He has ChatGPT to write me a poem about Dan Schwartz at Stanford. What he doesn't know is that there's a lot of Dan Schwartz's and so evidently I wear colorful ties, but this is what everybody wants to do. They want to create with it. Meanwhile, the field is trying to push towards efficiency. Can we get the kids done faster? Can we get them through the curriculum faster? Can we correct them faster? In which case the kids are going to optimize for being really efficient, right? As opposed to just trying to be creative, innovative, use it for deeper kinds of things. So this is my big fear. 

[00:13:42] Russ Altman: And so you're watching these companies and I'm guessing that they don't always ask your opinion about what's, what would you tell, so let's say a, one of these unicorn billion dollar or more companies comes to you and says, we want to do this right. We want to use the best educational research to create AI that can bring education to people who might otherwise not have quality education. What would you tell them? 

[00:14:04] Dan Schwartz: So this is a challenge, right? This is something we're actively trying to solve. So we've created a Stanford accelerator for learning to kind of figure out how to do this. 'Cause I've been in this ed tech position for quite a while. And the companies come in and they say, we really want your opinion. And then they present what they're doing. And I go, uh, have you ever thought of, and they go, wait, let me finish. And this goes on for fifty-five minutes. Where they're telling me what they want to do. And I'm trying to say, you know, if you just did this. And the way it ends is I say to them, look, you, if you do these three things, I'll consider being an advisor.

[00:14:42] Russ Altman: Right.

[00:14:42] Dan Schwartz: They never come back. 

[00:14:45] Russ Altman: So the message you're sending them is just not in their worldview. 

[00:14:50] Dan Schwartz: It's because they have a vision. Everybody wants to start their own school. 

[00:14:53] Russ Altman: Yeah. 

[00:14:53] Dan Schwartz: They have their vision of what it should be and they're urgent to get it done. And you know, it's a startup mentality. So trying to figure out how can we educate them? You know, I think we know a lot about how people learn that, uh, that we didn't know twenty years ago when they went to school. And the AI, you know, one of the things it can do is implement some of these theories of learning in ways that don't exist in textbooks and things like that.

[00:15:17] So that's the big hope. And the question is, how can you take advantage of industry? You know, education is a public good, but they still buy all their products. And so going through those companies is one way to sort of bring a positive revolution. But again, I'm a little worried that the companies are, and they're sort of optimizing for local minima.

[00:15:41] Russ Altman: Yeah. 

[00:15:41] Dan Schwartz: You know, to accommodate the current schools and things like that. 

[00:15:44] Russ Altman: Should we take, so what, should we take solace in the teachers? So many of us are fans of teachers, grammar school teachers, middle school teachers, high school teachers, but many of these folks are incredibly dedicated. Will they be a final, um, uh, a final filter that looks at these, uh, educational technologies and says, absolutely not. Or yeah, we'll use that, but we're going to use that in a way that makes sense for my way of teaching. Or are they not in a position to make those kinds of, what you could call courageous decisions, about kind of modifying the use of these tools to make them as good as possible in, uh, on the ground? 

[00:16:21] Dan Schwartz: So it's pretty interesting. The surveys I've seen, uh, sort of over the last year, the different groups do different surveys. It, it sort of, if I take the average, about sixty percent of K 12 teachers are using GenAI, right? And about thirty percent of the kids. If I go to the college level, about thirty percent of the faculty are using GenAI in teaching and about eighty percent of the kids are using it. So I do think in the pre K to 12 space, the teachers are making decisions. They do a lot of curriculum. There are, so a great application is, um, project-based learning. So project-based learning is a lot of fun. Kids learn a lot. They sort of develop a passion, a certain depth. As opposed to just mastering sort of the requirements, but it's really hard to manage. You know, when I was a high school teacher, I had a hundred and thirty kids, right?

[00:17:11] If all of them have a separate project, I have to help plan them and make them goal, you know, learning goal appropriate. So the GenAI can help me do that. It can help me, uh, have the kids sort of help use it to help them design a successful project. Uh, it can help me with a dashboard that helps manage them, hitting their milestones, things like that.

[00:17:31] And there, you know, it's, it, the, teacher is like, I can do something I just couldn't do before. 

[00:17:35] Russ Altman: Yeah. Yeah. 

[00:17:36] Dan Schwartz: It's different than the model where you put the kids in the back of the room who finished early and say, go use the computer. I think, you know, most schools, kids are carrying computers in classes. So it's a little different. It's more integrated than it used to be. 

[00:17:52] Russ Altman: This is the Future of Everything with Russ Altman. More with Dan Schwartz, next.

[00:18:06] Welcome back to The Future of Everything. I'm Russ Altman and I'm speaking with Dan Schwartz, professor of education at Stanford University. 

[00:18:12] In the last segment, Dan told us about AI, education, some of the promises and some of the pitfalls that he's looking at on the ground, thinking about how to educate the next generation.

[00:18:23] In this segment, I'm going to ask him about assessment, grading. How do we do that with AI and how do we make sure it goes well? Also going to ask him about physical activity, which turns out physical ness is an important part of learning. 

[00:18:39] I want to get a little bit more detailed, Dan, in this next segment, and I want to start off with assessment, grading. I know you've thought about this a lot. People are worried that um, AI is going to start to doing, be doing all the grading. Everybody knows that a high school teacher with a big, couple of big classes can spend their entire weekend grading essays. It is so tempting just to feed that into ChatGPT and say, hey, how good is this essay? How should we think about, maybe worry about, but maybe just think about, assessment in education in the future? 

[00:19:11] Dan Schwartz: Yeah, this was, uh, you remember the MOOCs? 

[00:19:14] Russ Altman: Yes. 

[00:19:14] Dan Schwartz: Massively online, open courses. And, uh, you're hoping you have ten thousand students, and then you gotta grade the papers for ten thousand students. So what do you do? You give a multiple-choice tests, which can be machine coded, right? So, so I think that's always there. I'm going to take it a slightly different direction, which is, uh, I'm interacting with a computer system and while I'm interacting with it, it's, it can be constantly assessing in real time, right?

[00:19:41] And so there's a field that's sometimes called educational data mining or learning analytics. And there's thousands of people who are working on, how do I get informative signal out of students interactions. Like, are they trying to game the system? Are they reflecting? And so forth. So this is something the computer can do pretty well, right?

[00:20:02] It can sort of track what students are doing, assess, and then ideally deliver the right piece of instruction at the moment. So yours, you could use the assessments to give people a grade, but really the more important thing is, can you use the assessments to make instructional decisions? So I think this is a big area of advancement, but here's my concern.

[00:20:25] We've gotten very good at assessing things that are objectively right and wrong. Like did you remember the right word? Did you get two plus two correctly? For most of the things we care about now, they're like strategic and heuristic, which means it's not a guaranteed right answer. And so what you really want to do is assess students choices for what to do. So for example, uh, creativity, it's just for the most part, it's a large set of strategies. Right? There's a bunch of strategies that help you be creative. The question is, do the students choose to do that or do they take the safe route? 'Cause creativity is a risk, right? 'Cause you're not sure.

[00:21:02] So I think this is where the field needs to go. Is being willing to say that certain kinds of choices about learning are better than others. Uh, and it's a, it becomes more of an ethical question now. Instead of saying two plus two equals four, there's no ethics to it. 

[00:21:16] Russ Altman: Are you going to be able to convince non educators who hold purse strings, let's call them the government, that these kinds of assessments are important and need to be included? Because my sense is that when it filters up to boards of education or elected leaders, a lot of that stuff goes out of the window. And they just want to know how good are they at reading comprehensive and can they do enough math to be competitive with, you know, country X? 

[00:21:43] Dan Schwartz: Yeah. Yeah. So different assessments serve different purposes. Like the big year end tests that kids take, those aren't to inform the instruction of that child. They're not even for that teacher. They're for school districts to decide are our policies working. And so it's really a different kind of assessment than me as a teacher trying to decide what should I give the kid next. So I think it's going to vary. You know, the tough question for me is should you let the kid use ChatGPT during the test? Right?

[00:22:14] And we had this argument over calculators, right? And finally they came up with ways to ask questions where it was okay if the kids had calculators. Because the calculator was doing the routine stuff. And that's not really what you cared about. What you cared about was, could the kid be innovative? Could they take a, another, a second approach to solve a problem? 

[00:22:34] Russ Altman: Yeah. 

[00:22:34] Dan Schwartz: Things like that. 

[00:22:34] Russ Altman: We, so I teach another class where it's a programming class, the students write programs, and we have switched, um, and we've actually downgraded the value. So as you know, very well, just as background, there is now an amazing, ChatGPT can also write computer code essentially. And so a lot of coding now is kind of done for you and you don't need to do it. We are trying to make sure that they understand the algorithms that we ask them to code. And so what we're doing is we're downgrading the amount of points you get for working code.

[00:23:04] You still get some, but we're upgrading the quiz about how the algorithm works. Do you understand exactly why this happened the way it did? Why is this data structure a good choice or a bad choice? And so it's forcing us, and you could have argued that we should have done this twenty years ago in the same class, but this is making it a more urgent issue, because if we don't, people can just get an automatic piece of code. They can run it. It'll work. They have no understanding of what happened. And so it's really a positive. It's putting more of a burden on us to figure out why the heck did we have them write this code in the first place? 

[00:23:39] Dan Schwartz: No, this was my point. It makes you sort of rethink what is valuable to learn. And you stop doing what was easy to grade. So I have an interesting one. This is a little nerdy. 

[00:23:51] Russ Altman: Okay. I love it. I love it. 

[00:23:52] Dan Schwartz: I teach the intro PhD statistics course in education. And lots of students say, I took statistics, right? And I'm sort of like, well, that's great. Let me ask you one question. And I say, I'm going to email you a question and you'll have five minutes to respond. You let me know when you're ready for it. And I ask them, uh, this is just for you, Russ. But why is the tail of the T distribution fat in small sample sizes? And I, what I get back usually is because they're small sample sizes.

[00:24:24] Russ Altman: Right. Or because it's the T distribution. 

[00:24:27] Dan Schwartz: Or it's, yes, even better. And then I come back and I sort of say, well, have you ever heard of the standard error? And I begin to get at the conceptual stuff, right? And, uh, I suspect if I gave it, uh, so there are ways to get conceptual questions that are really important. But you know, being able to prompt or write R code, you know, that's a good thing. You want them to learn the skills as well. 

[00:24:50] Russ Altman: Exactly. 

[00:24:51] Dan Schwartz: So I don't know, you know, when the calculator showed up, there's a big debate, right? What should students learn? Can they use the calculator? The apocryphal solution was you had to learn the regular math and the calculator now. You just had to learn twice as much. And so maybe that's what it's going to be. 

[00:25:08] Russ Altman: And that's a very likely transitional strategy and then we'll see where we end up. Okay. In the final few minutes, I, this seems like it's unrelated to AI, but I bet it's not. You've done a lot of work on physical activity and learning. You've even been on a paper recently where you talk about having a walk during a teaching session and whether you get better outcomes than if you were just standing or sitting. So tell me about that interest and tell me if it has anything to do with today's topic. 

[00:25:37] Dan Schwartz: I can make the bridge. I can do it, Russ. Right. So we did some studies. Um, I've done a lot of it. It's called embodiment where, yeah, there was, I got clued into this where, uh, I was asking people about why, about gears. And I say, you know, you have three gears in a line, and you turn the gear on the left clockwise. What does the gear on the right do? Far right. And I'd watch them, and they'd go like this with their hands. They'd model with their hands. And then I was sort of like, well, what's the basis of this? And I'd say well why? And they say because this one's turning that way that one, I go but why. And in the end, they just bottom out. They just show me their hands. They didn't say things like one molecule displaces another. 

[00:26:20] Russ Altman: Right. 

[00:26:21] Dan Schwartz: So that sort of clued me in. 

[00:26:22] Russ Altman: This pinky is going up and this other pinky is going down. 

[00:26:26] Dan Schwartz: Yes. 

[00:26:26] Russ Altman: What don't you understand about that? 

[00:26:28] Dan Schwartz: Pretty much. Well, it was nonverbal. 

[00:26:31] Russ Altman: Yeah. 

[00:26:31] Dan Schwartz: So we went on, you know, we discovered that the basis for negative numbers, right? Is actually perceptual symmetry. And we did some neuro stuff. And so the question is sort of how does this perceptual apparatus, which some people, we're just loaded with perception, right? The brain's just one giant perceiving. So how do you get that going? So part of the embodiment is my ability to take action, right? And so this is where we started, right? Right now, the AI feels very verbal, very abstract. Even the video generation, it's amazing, but it's pretty passive for me. So enter virtual worlds, they're still working on the form factor where I can move my hand in space. 

[00:27:16] Russ Altman: Yeah. 

[00:27:17] Dan Schwartz: And something will happen in the environment in response to that. You know, I think medicine is, you know, really been working on haptics so surgeons can practice. Uh, there was a great guy who made a virtual world for different heart congenital defects, and you could go in and practice surgery and see what would happen to the blood flow. So I think, uh, that embodiment where you get to bring all your senses to bear, it's not just words, but it's everything, can really do a lot for learning, for engagement, uh, not just physical skills. 

[00:27:49] Russ Altman: So that's a challenge to, I'm hearing a challenge to AI, which is as an educator, you know that this physicality can be an critical part of learning. And by the way, would this be a surprise? I mean, we're, we've been on earth evolving for several hundred million years. And, uh, you would be surprised if our ability to manipulate and look at three dimensional situations wasn't critical to learning, and yet that's not what AI is doing right now. So this is a clear challenge to AI among other things. 

[00:28:17] Dan Schwartz: Right. So, uh, I have a colleague, Renate Fruchter. And, uh, she teaches architecture, and she has students make a blueprint for the building, right? And then she feeds the blueprint to a CAD system that creates the building. She then takes the building and puts it into a physics engine, it can basically render the building and make walls so you can't move through them, and it has gravity and things like that.

[00:28:42] She then puts the, uh, original student who designed the building in a wheelchair and has them try to navigate through that environment. At which point they sort of understand, oh this is why you need so much space so they can turn around, so they can navigate near the door. I am sure that is an incredibly compelling experience that allows them to be generative about all their future designs.

[00:29:03] So yeah, this is a challenge and part of the co-mingling of the AI and the virtual worlds, I think this is a big challenge. It's computationally very heavy, but it will open the door for lots of ways of teaching that you just couldn't do before. 

[00:29:17] Russ Altman: Thanks to Dan Schwartz. That was the future of educational technology.

[00:29:21] You've been listening to The Future of Everything and I'm Russ Altman. You know what? We have an archive with more than 250 back episodes of The Future of Everything. So you have instant access to a wide array of discussions that can keep you entertained and informed. Also, remember to rate, review, and follow. I care deeply about that request. 

[00:29:41] And also, if you want to follow me, you can follow me on X @ @RBAltman, and you can follow Stanford Engineering @ StanfordENG.

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M.S. in IT Management vs. MBA: Which Program Should You Choose?

Pursuing a graduate degree in information technology (IT) is a significant investment of time, money and effort. However, it can also help shape your career trajectory and open the door to new and exciting opportunities for advancement.

Two popular advanced degree options that you may choose to pursue are a master's in information technology management (M.S. in IT Management ) and a Master of Business Administration (MBA) .

While both degrees can lead to rewarding careers, they each cater to different interests, goals and career paths. Below, we'll help you determine which program aligns better with your long-term objectives and personal preferences.

Explained: Master's in IT Management vs. MBA

An M.S. in IT Management is a theory-to-practice master's program that combines foundational business and leadership knowledge with IT project management, information security and data management skills.

In contrast, an MBA is a graduate-level degree program designed to prepare you for the managerial responsibilities of businesses across many different areas, such as operations, marketing and human resources.

While an MBA provides a comprehensive understanding of business management, leadership skills and best practices that can help you succeed in high-level roles, an M.S. in IT Management equips you with the technical expertise and managerial skills necessary to lead and oversee the proper use of information technology solutions.

However, it’s worth noting that there is a third program option available if you’re looking to bridge the gap between these two offerings. 

Dr. Alyncia Bowen, dean of Franklin University’s Ross College of Business and executive director of the university’s Leadership Center, encourages prospective students to investigate MBA programs specializing in IT .

"The MBA specializing in IT Management promotes the development of skills in strategic and project management and business analytics as a means of leading organizations,” Bowen says. “This option combines the comprehensive business education of an MBA with a concentrated focus on information technology typically found in an IT master's program.”

What matters most when choosing a master’s program? Compare features, benefits and cost to find the right school for you.

The ideal candidate for a master's in information management vs. master’s in business administration .

A master's in IT management program is ideal for IT professionals looking to advance their careers and assume leadership roles in technology.

The MBA program , on the other hand, is a lucrative option if you're a business professional seeking to assume managerial or executive roles. It's also an excellent choice if you have a business background, are interested in entrepreneurship and leadership or want to broaden your knowledge and skills.

The M.S. in IT Management can provide a pathway for non-technical professionals to enter the technology sector, while the MBA can open doors for those seeking to move into business-related roles.

However, if you want to bridge the difference between these two programs, Dr. Bowen notes that an MBA specializing in IT may be your best bet.

"Those interested in and passionate about business and technology will find the MBA specialization more attractive than the general MBA,” she said. “This is because of the ability to advance in technical careers with strong business knowledge. It also gives individuals the opportunity to advance in either discipline."

Technical Skills: Master's in IT Management vs. MBA Programs  

In M.S. in IT Management programs , you'll gain hands-on experience with various computer systems, tools and methodologies related to information technology. You'll learn to analyze and solve complex computer problems, manage IT projects and implement effective IT solutions within organizations.

These technical skills can be applied in industries such as healthcare, finance, manufacturing and government, where the integration of technology and business processes is essential.

For example, you could utilize your skillset as an M.S. in IT Management graduate to develop and implement a cybersecurity strategy for a hospital, ensuring the protection of sensitive medical data.

While a generalized MBA program may delve less deeply into technical skills (unless you choose to specialize in IT), it does provide opportunities for you to develop proficiency in data analytics, business intelligence and digital marketing. These business skills are valuable across various industries and can be applied in market research, enterprise resource planning, network security, operations management and strategic planning.

For instance, you could leverage your data analysis skills as an information systems manager to identify market trends and consumer behaviors. This would help your organization make informed business decisions and stay competitive in the market.

Which Degree is Better for Cultivating Project Management Skills?

High-level project managerial skills are very valuable in both the business and technology sectors. While both MBA and M.S. in IT Management programs offer management training as part of their curriculums, their approach differs slightly.

In an MBA, you'll learn specifically about project planning, resource allocation, risk management and stakeholder communication.

Dr. Bowen says that these skills can be practically applied across various business functions, such as product development, marketing campaigns and organizational change initiatives.

"The culminating experience gained from this program allows MBA graduates to apply what they've learned across various sectors. This allows you to display project knowledge and management capabilities to current and future employers."

Conversely, a master's in information technology management strongly emphasizes managerial skills within the information technology framework.

Pursuing this educational path will ensure you learn methodologies and best practices specific to IT project management , such as Agile and Scrum, as well as tools and techniques for managing software development projects. This includes IT managerial skills such as system implementations and infrastructure upgrades.

Which is Harder, an M.S. in IT or an MBA?

This is a very subjective experience. What you find difficult, someone else may find easy (and vice-versa). In this way, the perceived difficulty of a graduate program can vary depending on your educational background, experience, interests and strengths.

Admission requirements for MBA programs typically include a bachelor's degree, competitive GMAT or GRE scores, relevant work experience and/or strong academic credentials. Some secondary institutions may also require prerequisite statistics, economics and accounting courses.

Within the MBA program itself, you may find courses in quantitative analysis, finance and economics particularly challenging, especially if you have a non-business background. The program's emphasis on case studies and group projects can also be demanding, requiring strong communication, teamwork and critical thinking skills.

For M.S. in IT Management programs , admission requirements often include a bachelor's degree in a related field (such as computer science, information technology or engineering), relevant work experience and strong academic performance.

The curriculum can be challenging if you have a limited technical background. The most common struggles are with programming, computer engineering, database management and system architecture, and the combination of business and technology concepts can be a steep hill to climb if you still need to become familiar with them.

Are These Graduate Programs Worth It?

Pursuing a graduate degree is a significant investment, both in terms of time and financial resources. As such, it's natural to question whether the benefits outweigh the costs.

In terms of job prospects across all industries over the next 10 years, the Bureau of Labor Statistics projects a moderate increase of 2.8% . 

However, data from Lightcast™ suggests the job market outlook for business administration and information technology professionals is far more promising.

Jobs in business administration and management are expected to increase by 15.8% through 2032, reflecting the ongoing demand for skilled business leaders and managers across various industries.

Similarly, IT-related jobs are expected to grow by 18.5% during that same time frame, driven by the increasing reliance on technology and the need for professionals who can effectively manage and implement technical solutions.

In terms of earning potential, the average salary for MBA graduates can vary significantly depending on factors such as industry, location and years of experience.

However, according to Lightcast™ data, the advertised median annual salary for individuals with an MBA in the United States is around $74,500. For those with an M.S. in IT Management, the average yearly salary is approximately $98,800.

Do What You Love With a Degree from Franklin

Franklin University understands the importance of pursuing your passions and aligning your education with your career aspirations. That's why the university offers flexible and accessible options to help you achieve your goals.

The M.S. in IT Management program at Franklin is designed to equip you with the knowledge and skills necessary to lead and manage technology initiatives within organizations. 

For those seeking a comprehensive business education, Franklin's MBA program provides a well-rounded curriculum that covers essential areas such as finance, marketing, operations and strategic management. With the option to specialize in areas like IT, you can also tailor your degree to align with your specific interests and career goals.

Learn more about our M.S. in IT Management and MBA programs , or apply today to get started!  

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Master of Science in Technology Management

Advance your career and learn to manage evolving systems with your technology management master’s degree.

Shape the future of technology today. East Carolina University’s Master of Science in Technology Management program is designed to help you thrive in this growing field, teaching you management principles and building your creative problem-solving skills for technology-driven industries and businesses. Our master of technology management program provides instruction in advanced technology, management, and leadership concepts to meet the needs of our rapidly changing technological global economy.

With ECU’s technology management master’s degree you can transform your past experience and education into a highly sought-after degree to meet your professional goals. Graduate prepared to secure upper-level positions in the fields of quality, manufacturing, distribution and logistics, automation, and production planning.

Complete your degree entirely online

Earn your master of technology management degree online without sacrificing your personal life or career. For more than 30 years, we’ve offered our technology management degree in a remote format—proving a long track record of providing students quality and convenient curriculum. In East Carolina University’s Master of Science in Technology Management online program, you’ll network with peers and become an expert in the evolving field of technology management.

No GMAT or GRE required

30+ years of remote/online delivery

Complete degree in 18–24 months - Designed for working professionals

Why earn a master of technology management degree at East Carolina University?

Our master of technology management degree is a longstanding online program that has been continually upgraded over the past several decades to meet the needs of busy working professionals, helping them gain a competitive edge in the job market. In affordable, online courses, you’ll examine complex business situations and conduct applied research in professional settings through statistical analytical concepts.

Real-world experience

Immerse yourself in applied industry projects with a heavy focus on service-based learning.

World-class instruction

Learn from tenured faculty with extensive industry experience and active research agendas.

Tailored to meet your needs

Choose among three different tracks—thesis, practicum, or comprehensive—to complete your Master of Science in Technology Management degree.

Courses you will take in the master of technology management online program

In ECU’s innovative online educational community, you’ll learn to solve problems and make technical decisions related to smart manufacturing, production planning, and inventory control in technology companies and entities.

Develop leadership, data analysis, and collaboration skills through courses that include:

• Smart Manufacturing
• Lean Six-Sigma
• Project Management
• Transportation Logistics Management
• Supply Chain Logistics Management
• Quality Planning and Analysis
• Engineering Economics

The length of the Master of Science in Technology Management program depends on which track you choose to pursue:

• Thesis Track: 30 credit hours
• Practicum Track: 30 credit hours
• Comprehensive Track: 33 credit hours

You’ll be assigned a dedicated graduate faculty advisor who will work with you throughout your program of study. Learn more about courses  for the master of technology management online program.

Hear from our technology management master’s degree students

The ECU MSTM graduate program and faculty have provided me with direction and education that has made me more successful in my career, putting me on a path of continuous improvement on a personal and professional level.

—Patrick Godbey, MS in Technology Management student

What can you do with your master of technology management online degree?

Most of the students in the master of technology management program are working professionals who are pursuing the degree for career advancement.

Reach your professional goals

Move up in your career in technology and open doors to challenging and rewarding upper-level leadership positions.

Where are technology management master’s degree graduates working?

Graduates with the technology management degree are successful in many fields and careers, including:

• Application engineer/manager
• Distribution center/branch manager
• Fleet manager
• Industrial engineer/manager
• Industrial sales manager
• Project engineer/manager
• Quality assurance manager
• Scheduling and planning manager
• Technology manager
• Transportation broker
• Warehouse manager

Your master of technology management online degree is a wise investment, according to the U.S. Bureau of Labor Statistics:

Median annual salaries (2020)

• Software developers, quality assurance analysts, and testers—$110,140
• Industrial engineers—$95,300

Get started on your master of technology management online degree

Take the next step toward earning your East Carolina University degree. We have the resources to answer all your questions and help you get started.

Degree programs and certificates related to our master of technology management

Considering the ECU technology management master’s degree but would like to explore similar options? You may be interested in the following graduate degree programs and certificates:

• Master of Business Administration
• Master of Science in Network Technology
• Graduate Certificate in Lean Six Sigma Black Belt

Accreditation for East Carolina University

East Carolina University is accredited by the Southern Association of Colleges and Schools Commission on Colleges (SACSCOC) to award baccalaureate, master’s, and doctoral degrees.

About the Program

Are you interested in transforming your undergraduate education into a highly sought after technology management degree for a management position? Would you like to keep moving up in your professional career in technology and open up challenging and rewarding upper-level leadership positions for you? If so, the Master of Science in Technology Management (MSTM) degree is for you.

The Master of Science in Technology Management degree focuses on learning creative problem solving and management principles for technology-driven industries and businesses. The program provides instruction in advanced technology, management and leadership concepts geared toward the needs of our rapidly changing technological global economy. Students learn advanced problem solving skills and develop technological decision making capabilities through analytical thinking, applied research, technology development, and productivity improvement.

For more information on the program, please print our one page flyer (PDF) for the program.

Mission/Outcomes

Mission statement:.

The mission of the MSTM program is to prepare students for leadership positions in technological enterprises and conduct research in technology management. This is achieved through instruction in statistical tools, project management, engineering economics, research methods, and technological ethics, diversity and leadership. Elective courses in quality systems, manufacturing systems or industrial distribution and logistics are pursued based on students’ professional goals. Students interested in research may undertake a practicum or a thesis.

Program Objectives

• Graduates solve problems and make technical decisions related to smart manufacturing, production planning and inventory control in technology companies and entities.
• Graduates lead and manage enterprises involved in transportation, supply chain, and global logistics.
• Graduates lead associates and teams in technology driven enterprises and promote ethical business behavior, through the understanding of diversity and professional issues.
• Graduates analyze complex business situations and conduct applied research in professional settings through statistical analytical concepts.
• Graduates promote operational excellence and continuous improvement in technology enterprises.

Program Outcomes

Upon graduating, students will:

• Be able to conduct creative problem-solving and technological decision-making through mastery in cost management and project management. (ITEC6406, ITEC6200)
• Possess the necessary skills to conduct applied research in professional settings through statistical analytical concepts.  (ITEC6000 and ITEC6060)
• Be prepared for leadership and team member roles in technology driven enterprises through the understanding of ethics, diversity and leadership concepts. (ITEC6011).

They will also be knowledgeable and skilled in one or more of the following according to their professional goals:

• An ability to achieve operational excellence through the use of lean enterprise, six-sigma principles and design of experiments.  (ITEC6005, ITEC6110, ITEC6112)
• The ability to facilitate production planning and inventory control functions, and smart manufacturing.  (ITEC6003, ITEC6407)
• The ability to lead and manage enterprises involved in transportation, supply chain, and global logistics.  (IDIS6515, IDIS6525, IDIS6535, and IDIS6545)

The Master of Science in Technology Management (MSTM) degree is designed to serve the needs of students who possess a baccalaureate degree in industrial technology, technology management, applied engineering, engineering technology, and other similar technology oriented disciplines.

Admission into the Master of Science in Technology Management (MSTM) is accepted for the fall semester, spring semester, and the 11-week summer session.

Application Materials needed for the application includes:

• Completed application with fee
• Official transcripts ( guidelines and information )
• Current resume
• Three letters of recommendation from persons who can attest to the applicant’s potential to complete the degree
• Written statement of purpose
• Official GRE, MAT, or GMAT standardized test scores*. See below for MSTM GRE waiver options.

Admission information for  International students :

Interested applicants should forward a resume and unofficial transcripts, if available, to  [email protected] for consideration prior to submitting an application.

*GRE Waiver  – Students applying for either the MS in Technology Management may request consideration to have the GRE requirement waived based on one of the following considerations:

• The prospective graduate student has an overall GPA of 3.3 or higher from a regionally accredited institution with a related Baccalaureate degree program;
• The prospective graduate student is a current member of the ECU Honors College in good standing with a related Baccalaureate degree program and a minimum GPA of 3.3 or higher;
• The prospective graduate student has completed at least one of the graduate certificates offered within the department with an overall GPA of 3.2 or higher;
• The prospective graduate student has an overall GPA of 2.7 or higher from a regionally accredited institution with a related Baccalaureate degree program and has accumulated a minimum of 7 years of related professional experience over the past 10 years.

Program/Courses

What Will You Study The program of study includes course work composed of core courses, and electives based on the personal interest of a student. Students need to create a plan of study and get it approved by faculty. A current plan of study should be on file at all times. Three options for degree completion are available:

• MSTM degree with a comprehensive exam requirement. This option requires a total of 33 s.h. The degree can be structured to a student’s personal interest in manufacturing systems, quality systems, or industrial distribution and logistics. The student will complete 15 s. h. from the common core and 18 s. h. from the electives. Students are required to take a comprehensive exam to demonstrate mastery of course work. The comprehensive exam can only be taken after completion of 24 s.h. or more of total course work.
• MSTM degree with thesis option requires 6 s.h. of thesis work, which are taken by the student as ITEC 7000 – Thesis. This option requires a total of 30 s.h. The student will conduct thesis research and make a presentation to faculty based on the thesis. The thesis proposal and the thesis document must be approved by the student’s advisor and a committee composed of three faculty members from the Technology Systems Department. Students desiring to pursue the thesis option should consult their faculty advisor and identify a thesis advisor and topic in the first semester.
• MSTM degree with practicum option requires 3 s.h. of practical work in industry, which are taken by the student as ITEC 6100 – Practicum in Industrial Technology. This option requires a total of 30 s.h. Students may choose to pursue their own independent industry-based practicum. Work carried out in industry under the practicum option needs to be approved by the faculty from the Technology Systems Department before commencing. The student will write a report based on their practicum experience and present a seminar. Students desiring to pursue practicum work should declare their intent to do so in the first semester.

The common core of 15. s. h. is mandatory for all MSTM options. The common core consists of the following courses:

• ITEC 6000 – Statistical Applications in Technology Management
• ITEC 6011 – Technological Ethics, Diversity, and Leadership
• ITEC 6060 – Research Methods in Technology
• ITEC 6200 – Technology Project Management
• ITEC 6406 – Capital Project and Cost Analysis for Technology

The approved list of electives is shown below. Students will choose electives according to the option selected to make up the required number of semester hours:

• IDIS 6515 – Logistical Security and Safety Management
• IDIS 6525 – Transportation Logistics Management
• IDIS 6535 – Supply Chain Logistics Management
• IDIS 6545 – Global Logistics Management
• ITEC 6003 – Production Planning and Inventory Management
• ITEC 6005 – Lean Enterprise
• ITEC 6110 – Quality Planning and Analysis
• ITEC 6112 – Design of Experiments for Products and Processes
• ITEC 6407 – Smart Manufacturing
• ITEC 6903 – Special Topics in Technology
• SAFT 6250 – Occupational Ergonomics
• SAFT 6402 – Applied Safety Management

Find out more about the program and courses offered with the MSTM one page flyer (PDF) .

The Master of Science in Technology Management is accredited by:   ATMAE: The Association of Technology, Management, and Applied Engineering

To learn more about accreditation, please view this video:

Inclusive Excellence

College of engineering, women in engineering (wie).

Empowerment, leadership, and innovation converge here at Georgia Tech's Women in Engineering (WIE) program. We're dedicated to not only attracting the brightest minds to the field of engineering but also nurturing their development into groundbreaking engineers and influential leaders.

Since our inception in 1994, WIE has been a driving force in fostering a supportive environment where every student, regardless of gender, can excel. Our initiatives have led Georgia Tech to distinguish itself as the premier institution for women engineers in the United States, producing more female engineering graduates than any other U.S. institution since 2009.

At Georgia Tech, we champion the belief that excellence in engineering is achieved by drawing from a diverse talent pool. Our approach is holistic, supporting women from their formative school years through to advanced degrees and beyond into the professional world.

WIE's commitment to increasing the presence of women in engineering is unwavering. We provide the resources, support, and community necessary for women to blaze new trails in engineering and leadership. Our mission is clear: to ensure every woman with the drive and interest in engineering can pursue her dreams with a robust foundation and the full support of a world-class institution.

Join us as we shape a more inclusive and innovative future in engineering.

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