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Who We Are John R. Frederiksen


Dr. Frederiksen's interests are broadly concerned with the application of the cognitive sciences to learning and instruction within both classroom settings and computer-based learning environments. His background in cognitive science encompasses work in experimental cognitive psychology, artificial intelligence, and educational measurement. His recent work focuses on how middle school science students can develop an understanding of scientific inquiry processes and apply this knowledge in creating models of scientific phenomena. In this context, he is carrying out a longitudinal study of how developing students' inquiry skills may enhance their learning across the middle school curriculum. His research on assessment focuses on both teachers and students. He has studied how teachers' use of video portfolios for assessing teaching may support their inquiry into effective teaching practices, and how students' peer and self assessments of their inquiry processes facilitates their learning. He has also investigated how assessments of scientific inquiry may be incorporated into large-scale science assessments. In prior work, he has explored students' understanding of physical theories (particularly of electricity) and, within this domain, he has developed intelligent computer-based learning environments for understanding basic circuit theory and troubleshooting. In all his research, he applies cognitive theories to educational practice, and uses evaluations of instructional processes and outcomes to illuminate further development of cognitive theory.

John R. Frederiksen
University of Washington's Web site
Learning Inquiry Through Reflective Assessment's Web site

Ph.D., 1966 (Psychology and Psychometrics), Princeton University.

B.A., 1963 (Psychology, magna cum laude), Harvard University.


Professor (2001 onward), University of Washington.

Adjunct Professor, (1990 onward) School of Education, University of California at Berkeley.

Principal Scientist (1990-2000), Educational Testing Service.

Division Scientist (1987-1990), Senior Scientist (1975-1987), BBN Laboratories.

Assistant Professor (1968-1975), Brandeis University.

Member of the AAAS, American Educational Research Association, Cognitive Science Society, National Association for Research in Science Teaching, and Sigma Xi. Chair, Lindquist Award Committee, American Educational Research Association, 1997-1998; Member: Technical Advisory Committee, California Assessment Program. 1990-1995; National Center for Research in Mathematical Sciences Education, 1990-1995. Editorial: Journal of the Learning Sciences.


Frederiksen, J. R., & White, B. Y. (2002). Conceptualizing and constructing linked models: Creating coherence in complex knowledge systems. In P. Brna, M. Baker, K. Stenning and A. Tiberghien (Eds.), The Role of Communication in Learning to Model. Mahwah, NJ: Erlbaum.

Frederiksen, J. R., White, B. Y., & Gutwill, J. (in press). Dynamic mental models in learning science: The importance of constructing derivational linkages among models. Journal of Research in Science Teaching, 28(9), 799-822.

Frederiksen, J. R., Sipusic, M., Sherin, M., and Wolfe, E. (1998). Video portfolio assessment: Creating a framework for viewing the functions of teaching. Educational Assessment, 5(4), 225-297

White, B., & Frederiksen, J. (1998). Inquiry, Modeling, and Metacognition: Making Science Accessible to All Students. Cognition and Instruction, 16(1), 3-118.

Frederiksen, J. R., & Collins, A. (1996). Designing an Assessment System for the Workplace of the Future. (pp. 193-221). In L. B. Resnick, J. Wirt, & D. Jenkins (Eds.). Linking School and Work: Roles for Standards and Assessment. Jossey-Bass.

Frederiksen, J. R., & White, B. (1995). Teaching and Learning Generic Modeling and Reasoning Skills. Journal of Interactive Learning Environments, 5(1), 33-52.

Frederiksen, J. R., & White, B. Y. (1993). The Avionics Job-Family Tutor: An approach to developing generic cognitive skills within a job-situated context. Proceedings of the International Conference on Artificial Intelligence and Education.

Frederiksen, J. R., & White, B. Y. (1992). Mental models and understanding: A problem for science education. In E. Scanlon & T. O'Shea (Eds.), New Directions in Educational Technology. New York, NY: Springer Verlag.

White, B. Y., & Frederiksen, J. R. (1990). Causal model progressions as a foundation for intelligent learning environments. Artificial Intelligence, 42, 99-157.

Frederiksen, J. R., & Collins, A. (1989). A systems approach to educational testing. Educational Researcher, 18 (9), 27-32.

Frederiksen, J. R., & White, B. Y. (1989). An Approach to Training Based Upon Principled Task Decomposition. ACTA Psychologica, 71 (1-3), 89-146.

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