David A. Joyner, PhD

david@davidjoyner.net ♦ (404)-429-2380

Georgia Tech ♦ TSRB 225 ♦ Atlanta, GA 30332

Education ♦ Design ♦ Development ♦ Delivery

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About Me

Hi! I'm David Joyner. I'm an educator, and my personal passion is for leveraging new technologies to improve student learning. Presently, I focus on online learning not through MOOCs, but through large, closed online classrooms. I am most interested in the unique opportunities these classes have for individualizing and personalizing student learning, as well as granting students greater ownership and autonomy over their education. I've seen incredible things happen with online learning at the graduate level, and I'm excited to extend those opportunities to younger students.
I completed my Ph.D. in Human-Centered Computing at Georgia Tech with my thesis, Metacognitive Tutoring for Inquiry-Driven Modeling. I now work for Udacity as a Course Developer and General Course Manager on the Georgia Tech Online Master of Science in Computer Science, where I teach CS7637: Knowledge-Based AI (Summer) and CS6460: Educational Technology (Spring & Fall).

From the DavidJoyner.net Blog


OMS CS7637: Knowledge-Based AI: Cognitive Systems

MILA: Modeling & Inquiry Learning Application

Science is more than a body of knowledge. It is a way of thinking; a way of skeptically interrogating the universe with a fine understanding of human fallibility. –Carl Sagan

Read more about OMS CS7637: Knowledge-Based AI: Cognitive Systems

Beginning in February of 2014, I began co-developing a course for Udacity and the Georgia Tech Online Master's of Science in Computer Science with my thesis adviser, Ashok Goel. The course, Knowledge-Based AI: Cognitive Systems, is organized around three primary learning goals. First, this class teaches the concepts, methods, and prominent issues in knowledge-based artificial intelligence. Second, it teaches the specific skills and abilities needed to apply those concepts to the design of knowledge-based AI agents. Third, it teaches the relationship between knowledge-based artificial intelligence and the study of human cognition. After completing development of the course, I transitioned into co-instructing the course in Fall 2014.

From the beginning, my involvement in developing this course was intended as an exploration of and experiment in online learning. How do we leverage what we know from the learning sciences in an online course? What are the biggest obstacles to creating an engaging and effective learning experience online? And, perhaps most interestingly to me, what are the opportunities in online education to not only replicate traditional educational experiences, but improve them? What can we do online that we have difficulty doing in person?

Toward this end, we use this online course to explore several issues in online education. First, I have developed a collection of nanotutors -- AI agents that tutor small, specific skills -- that are deployed directly in the context of interactive exercises and activities within the lessons of the class to provide individualized, embedded feedback to students. Second, we have leveraged peer-to-peer feedback in order to explore scaling a rapid feedback cycle up to a large number of students. Third, we have explored project-based learning in the context of an online classroom as a way of providing engaging, personalizable, and measurable assessments. Fourth, we have investigated key issues in online learning, such as ways to overcome the feeling of isolation in an online class, the specific opportunities provided by online discussions, and the unique demographics, interests, and priorities of online students.

For more information on my experience with the Georgia Tech OMS generally and the Knowledge-Based AI class more specifically, take a look at my blog.

Read more about MILA: the Modeling & Inquiry Learning Application

For my dissertation research, I designed, implemented, deployed, and evaluated a collection of tools teaching an authentic process of scientific modeling and inquiry to middle school students. The suite of tools consists of three parts: an exploratory learning environment (MILA, Modeling & Inquiry Learning Application), a metacognitive tutoring system (MILA–Tutoring), and a simulation compilation agent (MILA–Simulation).

MILA is an exploratory learning environment implemented in Java. In MILA, students describe an ecological phenomenon, propose hypotheses for what might cause that phenomenon to occur, construct explanatory conceptual models for how that hypothesis might explain that phenomenon, and provide evidence in support of their explanation. Toward this end, MILA also allows students to participate in a variety of inquiry activities, like gathering data, experimenting with simulations, and exploring related systems.

Within MILA, my main research has been on a metacognitive tutoring system, MILA–T. MILA–T is comprised of five intelligent agents that monitor student behavior within MILA and provide mentorship, guidance, critiques, and support within the modeling and inquiry activity. MILA–T was tested in a controlled study with over 200 students, and analysis showed that engagement with MILA–T improved students' attitudes towards science, and also improved the explanations of ecological phenomena that students produced.

MILA, MILA–T, and MILA–S have spawned multiple ongoing collaborations striving to support the entire life cycle of a scientist, from secondary school to college to amateur to professional. Upcoming proposed work with the Georgia State University College of Education aims to scale MILA and MILA–T into a more comprehensive curriculum for inquiry-driven modeling in middle school science. Upcoming work with the Georgia Tech School of Biology explores how the same principles and tools can support college-level students. Proposed work with the Smithsonian Institute aims to connect MILA with amateur and professional scientists.

For more information on MILA, MILA–T, and MILA–S, take a look at the recent publications area of my blog, the project's dedicated homepage, or my CV.


On September 24th, 2015, I delivered a talk to the GVU Brown Bag officially titled, "Impact of Students in the OMSCS", and unofficially titled, "The OMSCS program attracts amazing students and empowers them to do amazing things." In the talk, I discuss the how the flexibility and accessibility of the OMSCS program have allowed it to attract incredible students; how the structure of the program gives those students great control over the classes; and how those two factors together have led to amazing results.

In Fall 2015, I launched my own OMSCS course, CS6460: Educational Technology. The class is made possible by the incredible work we've seen OMSCS students produce in the past, and the desire to give them the opportunity to pursue their ideas and contribute their work to the field. Rather than lectures, it is comprised of a library of course materials for students to navigate in their own way, culminating in an ambitious project proposal and, ultimately, a deliverable contribution to the EdTech community.

For CS6460: Educational Technology, I've filmed a series of interviews with professionals in EdTech. At present these professionals primarily come from Udacity, but more will be added in the coming months. The individuals interviewed for the course include Sebastian Thrun on Online Education (also on the left), Stuart Frye on the business of educational technology, Kathleen Mullaney on Gender, Technology, and Education, and Cameron Pittman on game- and simulation-based learning.

On December 4th, 2014, Prof. Ashok Goel and I delivered a talk to the GVU Brown Bag. The talk, titled "Putting Online Learning and Learning Sciences Together", covered our experience with bringing a learning science perspective to the online course development. We focus on a number of design principles surrounding online learning, and especially on the unique opportunities of the medium. To view the talk in its entirety, please visit talk's page on the GVU Brown Bag Archive, or watch the talk on YouTube on the right.

On August 19th, 2014, Ashok Goel and I launched CS7637: Knowledge-Based AI: Cognitive Systems as part of the Georgia Tech Online Master's in Computer Science. To the left is the first video in the course, where we introduce ourselves and our course to the students in the class. To date, the course has been offered four times: co-instructed by us both in Fall 2014 and Spring 2015, by myself alone in Summer 2015, and by Ashok alone in Fall 2015. The course is publicly available free at Udacity.

More About Me


  • Ph.D. in Human-Centered Computing ♦ Georgia Tech ♦ Specialized in Learning Sciences & Technology ♦ Thesis titled "Metacognitive Tutoring for Inquiry-Driven Modeling" ♦ 2009-2015
  • M.S. in Human-Computer Interaction ♦ Georgia Tech ♦ Specialized in Learning Sciences & Computing Education ♦ 2008 - 2009
  • B.S. in Computer Science with High Honor ♦ Georgia Tech ♦ Certificate in Social & Personality Psychology ♦ Specializing in People & Media ♦ 2005 - 2008


  • Udacity ♦ Mountain View, California ♦ Course Developer & General Course Manager ♦ February 2014 - Present
  • Georgia Tech ♦ Atlanta, Georgia ♦ Graduate Research Assistant ♦ August 2009 - January 2014
  • QOil ♦ Atlanta, Georgia ♦ User Interface Designer ♦ June 2008 - December 2008
  • Media Technology Solutions ♦ Norcross, Georgia ♦ User Interface Designer ♦ May 2006 - May 2008
  • Self-Employed ♦ Atlanta, Georgia ♦ Private Tutor ♦ August 2003 - Present


  • Georgia Tech ♦ August 2009 – December 2014 ♦ "Fostering Complex Systems Learning in Early Science Education" ♦ Supervised by Principal Investigator Dr. Ashok Goel.
  • Georgia Tech ♦ August 2008 – May 2009 ♦ "A Language-Neutral Assessment for Introductory CS Knowledge" ♦ Supervised by Investigators Allison Tew and Dr. Mark Guzdial.
  • Georgia Tech ♦ January 2008 – April 2008 ♦ "Investigating the Effects of Variously Moded Educational Materials on Learning" ♦ Supervised by Principal Investigator Dr. Jim Foley.


If parents want to give their children a gift, the best thing they can do is to teach their children to love challenges, be intrigued by mistakes, enjoy effort, and keep on learning. –Carol Dweck, Mindset: The New Psychology of Success