Ph.D. in Education - Human-Technology Collaboration Concentration

Innovate Responsibly

In a world where we rely on personalized news alerts, where online education adapts to us, and where ChatGPT makes learning easier, it's clear that AI and Large Language Models (LLMs) are changing the game. These technologies, powered by data science, machine learning, and artificial intelligence wizardry, have incredible potential. While popular culture and real-world incidents have highlighted the potential risks of irresponsible use, scientists have also unveiled an array of boundless possibilities where these technologies can bring immense benefits.

Acknowledging that the prevalence of these technologies and computational thinking will only escalate in our classrooms, workplaces, and everyday lives, GSEHD offers an innovative PhD concentration in Human-Technology Collaboration. Our objective is to gain insights into how this collaboration between people and machines will shape our future and the wide-ranging implications it holds, both positive and negative.

Preparing the global workforce to create, train, interact, and collaborate with intelligent technologies is an immediate challenge. We must all develop new skills and effective strategies to truly harness the power of technology to enhance performance. We must learn to post the right questions, skillfully interpret data analytics, navigate the uncertainties of machine intelligence, make ethical and policy judgments that seamlessly integrate data and social values, and explore novel collaborative approaches that truly engage technologies as our valued partners in learning and work.





Thinking Outside of the Box
Drawing upon faculty and experts from education, data science, engineering, psychology, business, public health, and medical informatics, the PhD takes an interdisciplinary approach to education and research into how the collaborations of people and machines shape the future.


Hands-On Experiential Learning
Take part in our larger inclusive cross-disciplinary team as well as a more focused research project. You’ll bring your experience in education to the design, development, data collection, and analyses of a research project.


Principles of Research
Gain a deeper understanding of the responsible conduct of research with human subjects, research ethics, and how to consider the social impact of the work.




The GW Advantage

As a Carnegie R1 institution (very high research activity), the George Washington University is home to world-class faculty that are leading cutting-edge research, along with diverse labs, cross-collaborative initiatives between schools and local organizations, and unparalleled educational and employment opportunities.

GW is home to the Human-Technology Collaboration Research Lab where you can join the vanguard exploring the frontiers of this new science. Current research projects include AI Literacy & Ethics, Intelligent Tech in Education, Collaborating with Cognitive Assistants, and more.





 Program at a Glance


Doctor of Philosophy (PhD) in Education, Human-Technology Collaboration Concentration

Course Delivery:

Main Campus

Program Entry:



Our Mission

The mission of the PhD concentration in Human-Technology Collaboration is to explore and harness the transformative power of intelligent technologies in a world where they have become an integral part of our daily lives. Through rigorous research and interdisciplinary collaboration, we aim to gain profound insights into the intricate relationship between humans and machines, understanding how it shapes our future and the multifaceted implications it carries. Our program is committed to equipping the global workforce with the skills and strategies necessary to navigate this evolving landscape. We strive to foster the ability to ask critical questions, interpret complex data analytics, leverage data for enhanced performance, navigate the uncertainties of machine intelligence, make ethical and policy judgments that integrate data and social values, and forge new collaborative approaches that fully engage intelligent technologies as valued partners in learning and work. By embracing the challenges and opportunities presented by human-technology collaboration, we aim to create a future where innovation and progress harmoniously coexist. Through our research and education, we seek to shape a society that harnesses the remarkable potential of intelligent technologies, contributing to a world where individuals and communities thrive in an era of transformative possibilities.

The following requirements must be fulfilled: 60 credits, including 36 credits in core courses, and 24 credits in the concentration, successful completion of a second-year research project, successful completion of the comprehensive examination; oral defense of both the dissertation proposal and the dissertation.
Core Courses:  
SEHD 8200 Foundations of Education I  
SEHD 8201 Foundations of Education II  
SEHD 8100 Special Topics (taken twice for a total of 6 credits)  
Research Methods:  
12 credits of doctoral-level research methods coursework, selected in consultation with advisor. At least one course must be in quantitative research methods and one in qualitative research methods.  
SEHD 8999 Dissertation Research (taken for at least 12 credits)  
Additional Requirements:  
Successful completion of second-year research project.  
Successful completion of the comprehensive examination.  
Oral defense of both the dissertation proposal and the dissertation.  
Human-Technology Collaboration Concentration Requirements:  
24 credits in graduate-level courses determined in consultation with the advisor. Course selections are determined by the focus of the concentration and the specific interests of the student.  
Open Science
The CRT is dedicated to the principles and practice of open science for accelerating scientific progress. The concentration supports the development of research and analysis that is widely available for peer feedback and potential replication or reproduction. The sharing of collaborative and student research is encouraged at all phases from conceptualization and design to publication and dissemination. Replication studies, preregistration of research proposals, open sharing of data and code, and the preprinting of publications are among the tools used within the concentration to open our science.
Example Research Questions
Preparing for data intensive environments powered by intelligent technologies requires research-based approaches to answering these and other questions:
  • How can educational institutions and private sector organizations collaborate in preparing a workforce for increasing collaborations with intelligent technologies?
  • How do varying levels of algorithm transparency influence the application of those algorithmic outputs in the decisions being made in the workplace?
  • What factors lead to faster and deeper learning in virtual reality training environments? Which grounded instructional strategies are most effective for teaching critical and computational thinking skills to students of all ages? How can data visualization improve the efficiency of professionals (e.g., lawyers, teachers, nurses, engineers, school administrators) in interpreting predictive data outputs?
  • What variables do people consider when trusting machines that make mistakes, or when machines are not certain about their uncertainty?
  • What are the policy and ethical implications of algorithm design, transparency, and accountability within a learning analytics context?
  • Is there a balance of human intuition and machine learning automation that best facilitates creative design while also fully leveraging analytical capability?
  • How do team dynamics and collective intelligence change when intelligent machines are team members?



 Apply Now

GSEHD’s Office of Admissions invites you to apply for a spot in our program. Please review the following admission and financial information.

Ready to take the next step in your career? Review our step-by-step guide to applying to GSEHD >

To learn more about the program, admission process, and upcoming events, please connect with the GSEHD Admissions Team at or 202-994-9283.

Apply Now   Schedule Consultation with Admissions Counselor  

To be considered for admission, applicants must submit the online application form as well as the following required supporting documents. There is no application fee.

  • Prerequisite: Master's Degree in in a field relevant to cross-disciplinary study and research in the area of Human-Technology Collaboration

  • Curriculum Vitae
  • Statement of Purpose: An essay of less than 1200 words, in which the candidate states his/her purpose in undertaking cross-disciplinary graduate study including: (a) rationale for seeking a Ph.D. in the specified concentration; (b) articulation of personal research interests; and (c) how his/her background and related qualifications have prepared him/her for this work and will align with long term goals. Please list your specified concentration at the top of your statement of purpose.
  • 3 Letters of Recommendation, with one preferred from a professor in the applicant’s Master’s degree program. Letters will document potential for analytical thinking, research skills/experiences, scholarly writing capabilities, and capacity to explore cross-disciplinary/complex issues.
  • Transcripts from all previously attended colleges or universities; The concentration goal is an average GPA of at least 3.7 in previous undergraduate and graduate programs.

  • Interview with Faculty to include a scholarly discussion of how the candidate’s work will fit with the proposed topic of the concentration.
  • Writing Sample (Optional): Candidates are encouraged to submit a current writing sample. The sample should reflect the candidate’s abilities to articulate complex ideas and to utilize evidence in support of his/her arguments. The writing sample should also provide an example of the candidate’s research skills, as well as her/his engagement with scholarship in pursuing his/her research interests.

Please note: The GRE is not required.

*Additional application requirements may exist for international applicants.

The deadline for Fall 2024 has passed, but applications may be accepted on a case-by-case basis. For more information or to inquire about the next admissions cycle, contact the GSEHD Admissions Team at or 202-994-9283. We encourage you to apply as early as possible.

Application Timeline Fall 2024
Priority Deadline Nov 1, 2023
Round 1 Deadline Dec 15, 2023
Round 2 Deadline Jan 16, 2024



 Tuition & Financial Aid

We know embarking upon graduate school is a big decision - due in part to the costs of attending. At GW, we understand the time and thought behind making graduate school work for you. Please take a moment to learn more about the options and opportunities available to help fund your graduate education.

Learn more about scholarships, grants & financial aid 

Graduate tuition is charged per credit hour, unless otherwise noted. Rates vary by program and location.

The tuition rate for the PhD in Education - Human-Technology Collaboration Concentration program is $1,870 per credit hour. This program requires 60 credits.

Please note: Additional fees may apply for international students, late fees, etc. Current tuition rates may be updated during the year.

*Summer 2023, Fall 2023 and Spring 2024

View the current fee chart  

Scholarships are available to eligible admitted students. Review eligibility requirements and learn more about funding your education >




 Career Outlook

Students graduating from the Human-Technology Collaboration program can expect a promising career outlook in various sectors. With their comprehensive understanding of the symbiotic relationship between humans and intelligent technologies, graduates will be well-equipped to pursue opportunities in academia, research institutions, think tanks, technology companies, government agencies, and consulting firms, where their expertise in navigating the ethical, policy, and collaborative aspects of human-technology interaction will be highly valued. Additionally, their proficiency in data analytics, machine learning, and interdisciplinary problem-solving will open doors to leadership roles and innovative positions at the forefront of technological advancements.

Human-Technology Collaboration Career Opportunities
professional female takes notes in notebook while looking at computer screen
  • Academic Researcher/Professor: PhD graduates in education routinely pursue careers in academia. They can become professors, researchers, or postdoctoral fellows at universities and institutions. They conduct research, publish scholarly articles, and teach courses related to human-technology collaboration.
  • EdTech Entrepreneur: Entrepreneurial PhD graduates may choose to start their own educational technology companies or join early-stage startups. They can develop innovative tech solutions aimed at improving human-technology collaboration in settings where learning in central.
  • Educational Technology Specialist: Graduates can work as educational technology specialists or consultants for educational institutions, school districts, or edtech companies. They can help in the integration of technology into curriculum design, teacher training, and educational program development.



Human-Technology Collaboration (PhD) Faculty

Dr. Michael Corry

Professor, Educational Technology

(202) 994-9295
Dr. Natalie B. Milman

Associate Dean, Office of Student Life; Professor, Educational Technology Leadership

(202) 994-1884
Dr. Yoshie Tomozumi Nakamura

Assistant Professor, Human and Organizational Learning

Dr. Ellen Scully-Russ

Associate Professor, Human and Organizational Learning

(571) 553-3786
Dr. Ryan Watkins

Interim Associate Dean of Research and External Relations; Professor, Educational Technology

(202) 994-2263



Affiliated Faculty

Columbian College of Arts and Sciences

Sarah Shomstein
Professor, Cognitive Neuroscience | 202.994.5957

Milken Institute School of Public Health

Helmchen, Lorens
Associate Professor, Health Policy and Management | 202.994.3816

School of Business

Hill, Sharon
Associate Professor of Management | 202.994.1314

School of Engineering and Applied Sciences

Barba, Lorena
Associate Professor, Mechanical and Aerospace Engineering | 202.994.3715

JP Helveston
Assistant Professor, Engineering Management and Systems Engineering | 202.994.7173

School of Medicine and Health Sciences

Morizono, Hiroki
Associate Research Professor, Genomics and Precision Medicine



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