First, let me say you’ve done a nice job of taking our ideas and linking them directly to geoscience education. Certainly the geosciences have been on the forefront of thinking about how graphics can be used for teaching and learning. Both Bertin (1983) and MacEachren (1995) have been important influences on my work, as have more focused work on visualization in geoscience education (e.g., Piburn, et al., 2002). More recent work in modeling in science education (e.g., Schwarz, 2009) has also been helping my thinking about concept-driven visualizations
My current work has been working in elementary science education and working with teachers on ways they can more effectively support student-produced graphics as a vehicle for science learning. We are looking closely at the kinds of graphics that are being produced at each stage of classroom activities that are done in conjunction with popular kit-based science curricula (Wiebe, et al., 2009). Concept-driven visualizations are very common during the pre-activity (lab) phase when the science concept that is the focus of the activity is introduced. This can be a text-book image or from another source. In most cases, as is your example, it represented a simplified or ‘idealized’ representation of a phenomena or idea. Students will then conduct an experiment/activity where they may be collecting data and creating a visualization. This empirically-driven visualization, as part of their post-lab activities, needs to be part of a reflective process where they link the ‘messy’ real-world results of their study back to the idealized concept-driven visualization. This can be a huge challenge for both the teacher and the student. I’m very interested in how students make these connections between concept-driven and data-driven visualizations, both of which are becoming an increasingly common part of science lab activities at all levels. Clearly, making these connections are central to inquiry learning in the geosciences.
Bertin, J. (1983). Semiology of graphics: Diagrams networks maps (W. J. Berg, Trans.). Madison, WI: University of Wisconsin Press.
MacEachren, A. M. (1995). How maps work: Representation, visualization, and design. New York: Guilford Press.
Piburn, M. D., Reynolds, S. J., Leedy, D. E., McAuliffe, C. M., Birke, J. P., & Johnson, J. K. (2002). The Hidden Earth; Visualization of Geologic Features and their Subsurface Geometry. Annual Meeting of the National Association for Research in Science Teaching. New Orleans, LA.
Schwarz, C. V., Reiser, B. J., Davis, E. A., Kenyon, L., Acher, A., Fortus, D., Shwartz, Y., Hug, B., & Krajcik, J. (2009). Developing a Learning Progression for Scientific Modeling: Making Scientific Modeling Accessible and Meaningful for Learners. Journal of Research in Science Teaching, 46(6), 632-654.
Wiebe, E. N., Madden, L., Bedward, J., Minogue, J., & Carter, M. (2009). Examining Science Inquiry Practices in the Elementary Classroom through Science Notebooks. Annual Meeting of the National Association for Research in Science Teaching, Garden Grove, CA.
My current work has been working in elementary science education and working with teachers on ways they can more effectively support student-produced graphics as a vehicle for science learning. We are looking closely at the kinds of graphics that are being produced at each stage of classroom activities that are done in conjunction with popular kit-based science curricula (Wiebe, et al., 2009). Concept-driven visualizations are very common during the pre-activity (lab) phase when the science concept that is the focus of the activity is introduced. This can be a text-book image or from another source. In most cases, as is your example, it represented a simplified or ‘idealized’ representation of a phenomena or idea. Students will then conduct an experiment/activity where they may be collecting data and creating a visualization. This empirically-driven visualization, as part of their post-lab activities, needs to be part of a reflective process where they link the ‘messy’ real-world results of their study back to the idealized concept-driven visualization. This can be a huge challenge for both the teacher and the student. I’m very interested in how students make these connections between concept-driven and data-driven visualizations, both of which are becoming an increasingly common part of science lab activities at all levels. Clearly, making these connections are central to inquiry learning in the geosciences.
Bertin, J. (1983). Semiology of graphics: Diagrams networks maps (W. J. Berg, Trans.). Madison, WI: University of Wisconsin Press.
MacEachren, A. M. (1995). How maps work: Representation, visualization, and design. New York: Guilford Press.
Piburn, M. D., Reynolds, S. J., Leedy, D. E., McAuliffe, C. M., Birke, J. P., & Johnson, J. K. (2002). The Hidden Earth; Visualization of Geologic Features and their Subsurface Geometry. Annual Meeting of the National Association for Research in Science Teaching. New Orleans, LA.
Schwarz, C. V., Reiser, B. J., Davis, E. A., Kenyon, L., Acher, A., Fortus, D., Shwartz, Y., Hug, B., & Krajcik, J. (2009). Developing a Learning Progression for Scientific Modeling: Making Scientific Modeling Accessible and Meaningful for Learners. Journal of Research in Science Teaching, 46(6), 632-654.
Wiebe, E. N., Madden, L., Bedward, J., Minogue, J., & Carter, M. (2009). Examining Science Inquiry Practices in the Elementary Classroom through Science Notebooks. Annual Meeting of the National Association for Research in Science Teaching, Garden Grove, CA.
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