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In designing the Data Puzzles, we have drawn on a generation of efforts by educators to increase students' use of authentic materials in K-12 education.
We share with many data-in-education projects a deep conviction that learning from data is an inherently rewarding activity, and a habit of mind that sets scientists apart from most non-scientists; and as such, it deserves a central place in science education. Projects and tools that have pioneered the use of data in education include Worldwatcher (Edelson et al, 1999), Discover our Earth, the Earth Exploration Toolbook (Ledley et al, 2003), GLOBE (Means, 1998), the Center for Innovation in Engineering & Science Education K-12 data-using activities, NASA Image Composite Editor, Columbia University's Earth's Environmental Systems curriculum (Hays et al, 2000), and many others (see appendix in Manduca & Mogk, 2002).
Reaching all the way back to the National Association of Geoscience Teacher's 1970's-vintage Crustal Evolution Education Project, we draw inspiration from the encouraging, respectful, step-by-step, interleaved teachers' guidance (Stoever, 1979) that project provided to help teachers teach material (plate tectonics) that they themselves had not studied in school (Mayer and Stoever, 1978).
From the Data-based Questions that have become common in Social Studies education (e.g. Tidd and Tidd, 2002), we draw confidence that there is high pedagogical value in having students examine small but carefully selected snippets of primary source material, and especially in having students draw inferences by combining observations from different types of documents (Rouet et al, 1996).
In Data Tips of the Month, sponsored by the National Association of Marine Educators and disseminated through the BRIDGE website, we find another example of data activities built around selected small marine data sets. Larkin and Clark (2002) report that the data tips are well received at teacher workshops and the data tips area is among the most visited part of the BRIDGE website.
From the popularity of the Math Forum Problem of the Week, we conclude that there is a subset of the population that finds solving "non-routine problems" to be rewarding and even fun, that solving such problems increases students' quantitative thinking skills (Renninger et al 2000), and that the problem solving approach has been of value even in school districts where the "technology and math skills of the teaching staff were largely underdeveloped" (Shumar & Renninger, 2003).
Our own previous experiences in trying to foster the use of data in education, have shown us that when it works, use of authentic Earth data is empowering and exhilarating for both students and teachers—but that there are many barriers to overcome in scaling up data-use to reach more than a relative handful of talented teachers and learners. When we have involved teachers in collecting Hudson River data, only a minority of them made use of the data when they returned to the classroom—although all were eager to return the next year and hear the scientist-participants talk about what they had done with the data. When we worked with teachers to develop modules in which students explored on-line databases (environmental data from Black Rock Forest and bathymetric and age data from mid-ocean ridges), we found that the resulting modules worked well for the teacher-developers, but were so complicated that they intimidated other teachers who considered adopting them. Off the record conversations with colleagues working on use of data in education suggest that they are encountering some of these same problems. From these experiences and conversations, we conclude that (a) many teachers think that it takes too much class time to extract insights from data, when those same insights could be stated in just few minutes, (b) most teachers don't have time to explore an uninterpreted data set on their own, and they are uncomfortable launching their students on an exploration of a data set they themselves have not explored, and (c) many teachers don't know how to guide students' productive exploration through the labyrinth of a large geoscience data set, and aren't sure how to assess whether students have done a good job analyzing and interpreting complex data.
As recounted in the last paragraph, it was our own experiential learning that led to our conviction that many teachers and their students would benefit from data-using activities that are low-barrier-to-entry and high insight-to-effort. But our reading of the literature finds support for this conclusion as well. For example, the GLOBE project (Means, 1998, her tables I and II) found that a high percentage of the teachers they trained did not implement GLOBE with their students, citing lack of time. Krajick et al (1998) report that in an inquiry-based science unit, middle school teachers did not demonstrate how students might go about the process of data analysis and interpretation; the authors hypothesized that this was because, "although middle school teachers may have considerable content knowledge, they are less likely to have had experience dealing with real data…" Bowen and Roth (2005) find that "despite considerable preparation, and for many, bachelor of science degrees, preservice teachers do not enact the ('authentic') practices that scientists routinely do when asked to interpret data or graphs.
And our final inspiration:
The fog comes
on little cat feet.
It sits looking
over harbor and city
on silent haunches
and then moves on.
---- Carl Sandburg
When we want children to learn to analyze and interpret the complex, multi-layered, non-linear, metaphorical, pattern-rich representation system called "poetry," we find simple but authentic and rewarding examples for them to start with. We seek the science equivalent of Sandburg's low barrier-to-entry, high insight-to-effort poem.
Bowen, G.M., and Roth, W.-M., 2005, Data and graph interpretation practices among preservice science teachers: Journal of Research in Science Teaching.
Donovan, M.S., and Bransford, J.D., 2005, How Students Learn: Science in the Classroom.: Washington, DC, National Research Council, Division of Behavioral and Social Sciences and Education.
Duschl, R.A., 2000, Making the nature of science explicit, in Millar, R., Osbourne, J., and Leach, J., eds., Improving Science Education: Contributions from research, Open University Press.
Edelson, D.C., Gordin, D.N., and Pea, R.D., 1999, Addressing the challenges of inquiry-based learning through technology and curriculum design: Journal of the Learning Sciences, v. 8, p. 391-450.
Hammer, D., 2004, The variability of student reasoning, Proceedings of the Enrico Fermi Summer School in Physics Course CLVI, The Italian Physical Society.
Hassard, J., 2005, The Art of Teaching Science: Oxford, Oxford University Press, 476 p.
Hays, J.D., Pfirman, S., Blumenthal, M., Kastens, K., and Menke, W., 2000, Earth Science Instruction with Digital Data: Computers and the Geosciences, v. 26, p. 657-668.
Krajcik, J., Blumenfeld, P.C., Marx, R.W., Bass, K.M., and Fredricks, J., 1998, Inquiry in Project-based Science Classrooms: Initial Attempts by Middle School Students: The Journal of the Learning Sciences, v. 7, p. 313-350.
Larkin, F.L., and Clark, V., 2002, Bridge: Ocean Science Education Teacher Resource Center. Unpublished report online at: http://www.coreocean.org/nopp/project-reports/reports/02larkin.pdf
Ledley, T., Dahlman, L., McAuliffe, C., Haddad, N., Manduca, C., Fox, S., Blaha, D., Freuder, R., and Downs, R., 2003, The Earth Exploration Toolbook: Facilitating the Use of Data to Teach, Geological Society of America Annual Meeting: Seattle (November 2-5, 2003), Geological Society of America, p. paper number 56-3.
Mayer, V.J., and E.C. Stoever, J., 1978, NAGT Crustal Evolution Education Project: a unique model for science curriculum materials, development and evaluation: Science Education, v. 62, p. 173-199.
Means, B., 1998, Melding authentic science, technology, and inquiry-based teaching: Experiences of the GLOBE program: Journal of Science Education and Technology, v. 7, p. 97-105.
National Research Council, 1996, National Science Education Standards: Washington, DC, National Academy Press, 262 p.
New Jersey Department of Education, 1998, New Jersey Curriculum Framework.
New York State Education Department, 1996, Learning Standards for Mathematics, Science and Technology: Albany, NY, The State Education Department, 103 p.
Renninger, K.A., Farra, L., and Feldman-Riordan, C., 2000, The impact of the Math Forum's Problem(s) of the Week on Student's Mathematical Thinking, in Fishman, B., and O'Connor-Divelbiss, S., eds., Fourth International Conference of the Learning Sciences: Mahwah, NJ, Erlbaum, p. 52-53.
Rouet, J.F., Britt, M.A., Mason, R.A., and Perfetti, C.A., 1996, Using multiple sources of evidence to reason about history: Journal of Educational Psychology, v. 88, p. 478-493.
Shulman, L.S., 1986, Those Who Understand: A Conception of Teacher Knowledge,
American Educator, p. 9-15+.
—, 1987, Knowledge and Teaching: Foundations of the New Reform: Harvard Educational Review, v. 57, p. 1-22.
Shumar, W., and Renninger, K.A., 2003, The centrality of culture and community to participant learning at and with The Math Forum, in Barab, S., Kling, R., and Gray, J., eds., Designing for Virtual Communities in the Service of Learning: Cambridge, Cambridge University Press.
Stoever, E.C., Jr., 1979, Crustal Evolution Education Project Modules, Teacher's Guides, National Association of Geology Teachers, p. 33 modules.
Swenson, Sandra, 2005. Exploring Seafloor Topography, in The Earth Exploration Toolbook. Online at: http://serc.carleton.edu/eet/seafloor/index.html
Tidd, L.V., and Tidd, C.C., 2002, Doing History: A Strategic Guide to Document-Based Questions, Great Source Education Group, 108 p.
Thomas, Jeff, 2005. Investigating the Dynamics and Geomorphology of Mid Ocean Ridges, in The Earth Exploration Toolbook. Online at: http://serc.carleton.edu/dev/eet/rodes_6/index.html
Last updated February 25, 2011