Professor White's professional interest is in making science and scientific inquiry interesting and accessible to a wide range of students and teachers. She has been principal investigator on numerous projects concerned with the design of computer-based learning environments and their relationship to theories of human learning, understanding, and problem solving. Furthermore, she has been developing and evaluating new instructional approaches, centered around these environments, that enable students to work together to develop an understanding of both the subject matter and the processes of scientific modeling and inquiry.
Ph.D. Computer Science, Massachusetts Institute of Technology, USA, 1981.
Completed Ph.D. qualifying program in Psychology, University of New South Wales, Australia, 1975.
B.Sc. Mathematics, University of Victoria, Canada, 1971.
PROFESSIONAL AFFILIATIONS AND SERVICE
Professor (1995 onward), Associate Professor (1989-1995), University of California at Berkeley.
Senior Scientist (1985-1989), Scientist (1982-1985), BBN Laboratories, Cambridge, USA.
Member of the Cognitive Science Society, the American Association for Artificial Intelligence, the International AI and Education Society (on executive committee), the American Educational Research Association, and the National Association for Research in Science Teaching.
Serve on the editorial board for the International Journal of Artificial Intelligence in Education and the Journal of Interactive Media in Education.
SELECTED ORAL PRESENTATIONS
Enabling Young Learners to Develop QP Theories of Minds. Invited address given at the Fifteenth International Workshop on Qualitative Reasoning, San Antonio, May, 2001.
Conceptual Tools for Learning through Inquiry and Reflection. Invited talk given at the Annual Meeting of the American Educational Research Association, San Diego, April, 1998.
Technological Tools and Instructional Approaches for Improving Science Education. Invited talk presented at the Harvard Graduate School of Education, March, 1997.
The ThinkerTools Project: A Computer-Based Curriculum for Scientific Inquiry and Modeling. Invited address presented at the Annual Meeting of the National Association for Research in Science Teaching, San Francisco, April, 1995.
Intermediate Abstractions and Causal Models: A Microworld-Based Approach to Science Education. Invited address presented at the World Conference on Artificial Intelligence in Education. Edinburgh, Scotland, August, 1993.
SELECTED RECENT PUBLICATIONS
White, B., Shimoda, T., & Frederiksen, J. Enabling Students to Construct Theories of Collaborative Inquiry and Reflective Learning: Computer Support for Metacognitive Development. International Journal of Artificial Intelligence in Education, 10(2), 1999.
Frederiksen, J, White, B, & Gutwill, J. Dynamic Mental Models in Learning Science: The Importance of Constructing Derivational Linkages Among Models. Journal of Research in Science Teaching, 36(7), 806-836, 1999.
White, B., & Frederiksen, J. Inquiry, Modeling, and Metacognition: Making Science Accessible to All Students. Cognition and Instruction, 16(1), 3-118, 1998.
White, B., & Schwarz, C. Alternative Approaches to Using Modeling and Simulation Tools for Teaching Science. In N. Roberts, W. Feurzeig, & B. Hunter (Eds.), Computer Modeling and Simulation in Science Education. (pp. 226-256). New York, NY: Springer-Verlag, 1998.
Frederiksen, J., & White, B. Teaching and Learning Generic Modeling and Reasoning Skills. Journal of Interactive Learning Environments, 5, 33-51, 1998.
White, B. Computer Microworlds and Scientific Inquiry: An Alternative Approach to Science Education. In B. Fraser and K. Tobin (Eds.), the International Handbook of Science Education. Netherlands: Kluwer Publishers, 1998.
White, B. The ThinkerTools Project: Computer Microworlds as Conceptual Tools for Facilitating Scientific Inquiry. In S. Glynn & R. Duit (Eds.), Learning Science in the Schools: Research Reforming Practice, (pp. 201-227). Hillsdale, NJ: Lawrence Erlbaum Associates, 1995.
White, B. ThinkerTools: Causal Models, Conceptual Change, and Science Education. Cognition and Instruction, 10(1), 1-100, 1993.
White, B., Frederiksen, J., & Spoehr, K. Conceptual Models for Understanding the Behavior of Electrical Circuits. In M. Caillot (Ed.), Learning Electricity and Electronics with Advanced Educational Technology, (pp. 77-95) New York, NY: Springer Verlag, 1993.
White, B. Causal Models and Intermediate Abstractions: A Missing Link for Successful Science Education? In R. Glaser (Ed.), Advances in Instructional Psychology, Volume 4, (pp., 177-252). Hillsdale, NJ: Lawrence Erlbaum Associates, 1993.
White, B. A Microworld-based Approach to Science Education. In E. Scanlon & O'Shea (Eds.), New Directions in Educational Technology, (pp. 227-242). New York: Springer Verlag, 1992.
White, B., & Frederiksen, J. Causal Model Progressions as a Foundation for Intelligent Learning Environments. Artificial Intelligence, 24, 99-157, 1990.
Frederiksen, J., & White, B. An Approach to Training Based Upon Principled Task Decomposition. ACTA Psychologica, 71, 1-58, 1989.
White, B., & Frederiksen, J. Causal Models as Intelligent Learning Environments for Science and Engineering Education. Applied Artificial Intelligence, 3, 167-190, 1989.
CURRENT RESEARCH GRANTS
White, B. Modeling, Developing, and Assessing Scientific Inquiry Skills Using a Computer-Based, Inquiry Support Environment. Funded by the National Science Foundation.
White, B. & Frederiksen, J. Improving Students' Learning and Achievement Through Developing Generalizable Skills for Inquiry and Self-Reflection. Funded by the Department of Education's Office of Educational Research and Improvement.