Dr. David Feldon (he/him)


Dr. David Feldon (he/him)

Contact Information

Office Hours: By Appointment
Phone: (435) 797-0556
Email: david.feldon@usu.edu
Additional Information:

Educational Background

Ph.D., Educational Psychology (2004), University of Southern California, Rossier School of Education, Inaccuracies in Expert Self-Report: Errors in the Description of Strategies for Designing Psychology Experiments. Richard E. Clark (Chair), Lee Shulman, John L. Horn, and David D. Marsh

M.S. Ed., Instructional Technology (1999), University of Southern California, Rossier School of Education, Evaluation of a Bottom-Up Technology Integration Approach Emphasizing Software for Classroom Settings. Allen Munro (Chair)

B.A., Cognitive Science; Minor in Philosophy (1997), Johns Hopkins University


David Feldon is interested in the development of expertise, specifically in STEM disciplines. As part of his research, he develops and validates training and assessment systems that use simulations. His work focuses on understanding the cognitive components of expertise and the development of research skills as a function of instruction.

David teaches a unique course on Mixed Methods Research. Most people do either qualitative or quantitative work. This course shows students how to use both kinds of data to reach meaningful conclusions.

David also teaches an Instructional Design Studio. This course was designed to be an alternative to classic ADDIE model, a widely used but flawed method for instructional design. David teaches the 4C-ID model, which is intentionally designed to handle the kinds of systems students must design for, ones with high levels of complexity and interactivity. 4C-ID is the same instructional design model used to train air traffic controllers in Europe.

David works to help diversify the future of STEM, particularly when it comes to faculty. He is the director of assessment and evaluation for a Howard Hughes Inclusive Excellence grant that was awarded to Utah State University in 2017. David is also the external evaluator for the Virginia-North Carolina Alliance for Minority Participation. He just completed a comparative evaluation of doctoral outcomes for participants in the Southern Regional Education Board’s Institute for Teaching and Mentoring, which supports the training of over 1,000 STEM scholars of color pursuing their doctorates in their respective disciplines.

David is looking for PhD and Master’s students who are interested in understanding the deeper methods of learning related to instructional design. He’s also looking for students who want to understand the training mechanisms and motivations of adult learners in high performance contexts.

Featured Work

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Significant Contribution to Educational Measurement and Research Methodology Award

Dr. David Feldon and Dr. Colby Tofel-Grehl (TEAL Department) received this award in 2019 for their article titled, “Phenomenography as a Foundation for Mixed Models Research.” This was the first time this recognition was awarded to an article about mixed methods research. Read the ITLS article.

trajectories of early learning

The Early Career Research Project

The goal of this project is to examine student development outcomes and equity among doctoral students in the biological sciences. The project will follow 268 biology students through the final stages of graduate school and into their careers, considering how features of graduate education affect career trajectories. Contributors: Feldon, D. F. (P.I.), Roksa, J., & Griffin, K. (2018-2022).

Learn more about this project at The Early Career Research Project

Panelist for the National Academies of Science

David’s paper, “Null Effects of Boot Camps and Short-Format Training for Ph.D. Students in Life Sciences,” was published in the Proceedings of the National Academy of Sciences. David also had the honor of presenting his work at an NAS committee meeting in Washington, D.C. Based on the work of David and others, the committee produced a report about how we can enhance and revitalize graduate STEM education.

LEAP NIRS Brain Imaging Lab

The goal of this project is to examine how manipulating cognitive load can directly impact people’s motivation, especially their confidence in what they are learning. The authors found that self efficacy and motivational beliefs are an important outcome that results from instruction.  Learn more at the Emma Eccles Jones Early Childhood Education and Research Center site.

Implications of measurement issues for advancing the socialization framework (book)

Socialization theory is the rising theory of research in graduate education theory. David’s research has found that either this theory is incorrect, or the instruments being used are incorrect. In this chapter, David analyzes the instruments to address measurement issues in socialization theory.

Feldon, D. F. (in press).  In L. DeAngelo & J. C. Weidman (Eds.), Socialization in higher education and the early career: Theory, research and application. New York: Springer International Publishing AG.

Research Focus

Dr. Feldon’s research examines two lines of inquiry that are distinct but mutually supportive.

The first characterizes the cognitive components of expertise as they contribute to effective and innovative problem solving, as well as how they affect the quality of instruction that experts can provide.

The second examines the development of research skills within STEM disciplines as a function of instruction and other educational support mechanisms. He also conducts some research into technology-facilitated instructional approaches and research methods for examining them.

David’s work currently focuses on:

  • Cognitive load and motivation with brain imaging and eye tracking
  • Longitudinal study of PhD students in the biological sciences
  • Simulation based assessments of open ended problem solving.

Selected Publications

See C.V or Google Scholar for a comprehensive list of publications.

Feldon, D. F., Callan, G., *Juth, S., & *Jeong, S. (2019). Cognitive load as motivational cost. Educational Psychology Review, 31(2).

Feldon, D. F., *Franco, J., *Chao, J., Peugh, J., & Maahs-Fladung, C.  (2018).  Self-efficacy change associated with a cognitive load-based intervention in an undergraduate biology course.  Learning & Instruction, 56, 64-72.

*Chao, J., Feldon, D. F., & Cohoon, J.  (2018).  Invisible scaffolding in dynamic mental model construction: A Knowledge-in-Pieces based explanation for computing students’ erratic performance on recursion.  Journal of the Learning Sciences, 27, 431-473.

Feldon, D. F., *Jeong, S., Peugh, J., Roksa, J., Maahs-Fladung, C., *Shenoy, A., & *Oliva, M.  (2017).  Null effects of boot camps and short-format training for Ph.D. students in life sciences.  Proceedings of the National Academy of Sciences, 114(37), 9854-9858.

Feldon, D. F., Maher, M., Roksa, J., & Peugh, J.  (2016).  Cumulative advantage in the skill development of STEM graduate students: A mixed methods study.  American Educational Research Journal, 53, 132-161.

Feldon, D. F., Peugh, J., Timmerman, B. E., Maher, M. A., *Hurst, M., Strickland, D., Gilmore, J. A., & *Stiegelmeyer, C.  (2011).  Graduate students’ teaching experiences improve their methodological research skills.  Science, 333(6045), 1037-1039.

Books, Book Chapters, and Reports

Feldon, D. F., *Franco, J., & *Jeong, S. (2017). Education and STEM. In P. Ward, J. M. Schraagen, Gore, J., & E. Roth (Eds.), The Oxford Handbook of Expertise: Research & Application. Oxford, UK: Oxford University Press.

Clark, R. E., & Feldon, D. F.  (2014).  Ten common but questionable principles of multimedia learning.  In R. E. Mayer (Ed.), The Cambridge Handbook of Multimedia Learning (2nd ed.) (pp. 151-173).  New York: Cambridge University Press.

Clark, R. E., Feldon, D., van Merriënboer, J. J. G., *Yates, K., and *Early, S.  (2008).  Cognitive task analysis.  In J. M. Spector, M. D. Merrill, J. J. G. van Merriënboer, & M. P. Driscoll (Eds.).  Handbook of research on educational communications and technology (3rd ed.) (pp. 577-593). New York:  Macmillan/Gale.

Clark, R. E., Feldon, D., van Merriënboer, J. J. G., *Yates, K., and *Early, S.  (2008).  Cognitive task analysis.  In J. M. Spector, M. D. Merrill, J. J. G. van Merriënboer, & M. P. Driscoll (Eds.).  Handbook of research on educational communications and technology (3rd ed.) (pp. 577-593). New York:  Macmillan/Gale.