Challenges Inherent in Teaching Geosciencespublished Mar 12, 2010
Several inherent attributes of ocean, atmosphere and solid earth sciences contribute to making these disciplines challenging to teach and learn at the K-14 level. These include the large spatial scale of important processes, the consequent reliance on models and representations rather than actual target phenomena in hands-on activities, the centrality of systems thinking and emergent phenomena, and the importance of non-experimental modes of inquiry. None of these difficulties is unique to geosciences, and none is insurmountable, but they do require purposeful attention from educators, curriculum and program designers, and evaluators.
Key phenomena in ocean, atmosphere and solid sciences occur at spatial scales that span hundreds or thousands of kilometers. Examples include the "global conveyor belt" of ocean circulation, weather systems, and the zonal atmospheric circulation system that determines which latitude bands have wet and dry climates. Research on both students' and teachers' grasp of structures, processes and phenomena of varying scales has shown that understanding is strongest for phenomena closest in size to the human body and weakens as the scale becomes large (or small) relative to the body (Tretter, et al., 2006; Jones, et al., 2007b). Moving through space is an important formative experience in anchoring experts' sense of scale (Jones & Taylor, 2009). The large size of many important ocean and atmospheric phenomena, especially those too large for students to have experienced directly, may make it harder to students to form an accurate mental model.
Reliance on models for hands-on activities:
As a consequence of the large scale of many important geoscience phenomena, hand-on instructional activities on these topics often are built around models of the phenomena of interest, rather than the phenomena themselves. In other sciences, students can manipulate the actual phenomenon under study, gathering evidence of its existence and behavior. The teacher can bring an acid or lever or electric circuit or plant seeds into the classroom, and students can observe and manipulate an authentic chemical reaction or force or electrical current or growing plant. It is not possible to create an authentic hurricane or ocean current in a classroom. Recognizing the instructive power of hands-on activities, curriculum developers have developed a wealth of activities for students to explore ocean and atmospheric phenomena. But with few exceptions, these activities involve students in manipulating analog models of the geoscience phenomenon (e.g. examining convection in a fish tank), rather than the phenomenon actually targeted by the curriculum (e.g. convection in the atmosphere). Use of analog models can be of enormously valuable in helping students understand a process. But connecting the processes observed in the tabletop model with the full scale Earth System requires a difficult leap from small to large, concrete to abstract, and from that experienced through perception to that experienced through representation, using analogical reasoning (Gentner & Toupin, 1986; Gentner & Colhoun, in press) and proportional reasoning (Jones, et al., 2007a). Many instructional materials focus on learning about the model, rather than learning about the Earth System, and offer little to no scaffolding for the leap from table top to Earth (e.g. Freeman, 2008).
Well-crafted field experiences can help to overcome the scale issues to some extent. For example, direct observations of clouds and storms can help students build an experience-based, embodied sense of the scale of weather systems and atmospheric phenomena. However, for many phenomena there is still a need for careful curricular scaffolding to help the student scale up from the field experience to the scale at which the interpretive concepts are presented. For example, the connection between field observations in a tide pool and the orbital geometry of the sun-Earth-moon system is far from obvious.
Reliance on data that students didn't collect themselves:
When education researchers, teachers, or teacher educators envision inquiry in science education, they are most commonly referring to activities in which students collect some kind of data or observations, interpret that data, and present their findings orally or in writing (National Research Council, 2000, note especially Chapter 3). Planning and executing the data acquisition steps are considered central to understanding both the process of science and the phenomena under study. However, when the topic of study is the earth, many important processes are not amenable to study with student-collected data, because they are too large (e.g. global atmospheric circulation), too far away (e.g. diminishing summer ice in the Arctic), too slow (e.g. rise in atmospheric carbon dioxide concentration), too dangerous (e.g. tornados), or require instrumentation that is too expensive (e.g. seafloor hydrothermal vents).
Each of these large, distant, slow, dangerous or expensive processes is amenable to student investigation using professionally-collected data sets of broad scope and high quality, made available to the public at no charge through the World Wide Web. However, teaching and learning with large data sets that students did not collect themselves and small data sets that students did collect, are not quite the same. Researchers are just beginning to explore the differences. Hug and McNeill (2008) found considerable overlap in the classroom discourse occasioned by the two data types, but less discussion of error sources, more reliance on personal experiences, and different forms of meaning-making when students had not personally collected the data used in their inquiry. Teachers who are trained to guide students through an inquiry based on student collection of data may not view an activity based on professionally-collected data as a "real" inquiry, or may not know how to guide student generation of questions and explanations when there is no experiment to plan and no apparatus to manipulate.
Centrality of non-experimental modes of inquiry:
Most students and most pre-service teachers have been taught some variation of "the scientific method," in which an experimenter sets up a laboratory apparatus, manipulates one variable at a time, and considers the outcome as a function of the manipulated variable (Edwards 1997; Uthe 2000; Windschitl, et al., 2008). However, in geosciences, most major insights are not accomplished through classic laboratory experimentation. Seafloor spreading, global climate change, causes of the ice ages, El Niño: none of these first-order insights was developed primarily through classical experimentation. Other modes of inquiry are at least as important, and arguably more so for geoscientists, including methodical observation of variations across space and changes through time, and construction of computational and physical models (Kastens and Rivet, 2008).
To the extent that students have learned and believe the narrow scientific method (Windschitl, et al., 2008), they can develop a disconnect between the process of science part of their education and the conceptual content of their education (Kastens and Rivet, 2008). They won't be able to envision how the process of science as they have learned it could have given rise to the concepts they are being taught about the ocean, atmosphere, or climate—because, in fact, these concepts did not arise from laboratory experimentation. To construct an accurate understanding of many important ocean, atmospheric and climate phenomena may require a pedagogical detour to broaden students' understanding of how science is done.
All of the geosciences rely heavily on spatial thinking: the process of acquiring, representing, manipulating or reasoning about the position, orientation, shape or trajectory of objects, processes or phenomena in space. Geoscientists engage in spatial thinking when they describe and classify objects by shape (e.g. clouds), ascribe meaning to shape or trajectory (e.g. storm tracks), recognize significant patterns amid visual complexity (e.g. weather map interpretation), make and use maps and other spatial representations (e.g. block diagrams), synthesize one- or two-dimensional observations (e.g. CTD casts) into a three-dimensional mental image, envision the processes by which materials or objects change position or shape (e.g. the El Niño/ La Niña oscillation), or use spatial-thinking strategies and techniques to think about nonspatial phenomena (e.g. physical oceanographers' T-S diagrams) (Kastens & Ishikawa, 2006).
Many students struggle with spatial tasks (National Research Council, 2006; Liben, 2006). Spatial ability varies widely between individuals. Although spatial performance in general or on specific tasks can be improved through training and practice (Sorby & Baartmans, 2000; Piburn et al., 2005), most teachers have little training on how do to do this. In general, the formal education system tends not to value, assess or develop spatial skills, so students, teacher and parents may not recognize either deficiencies or talent in this dimension, and early remediation for difficulties in spatial cognition is all but non-existent. At the college level, oceanographers or atmospheric scientists who are themselves high-spatial may not appreciate the degree to which some students are spatially challenged (Kastens, et al, 2009).
Importance of Systems thinking and emergent phenomena:
Systems thinking is fundamental to understanding the workings of the ocean, atmosphere and solid earth. Systems thinking includes being able to envision an aspect of reality as a series of reservoirs linked by flows, and controlled by positive and negative feedbacks. Systems thinking fosters the expectation that variation in any given observable parameter may be emerging from multiple interacting causality chains rather than from changes in a single causative factor. Stabilizing (negative) feedback loops keep the Earth system sufficiently stable that complex forms of life, including humans, can exist. Reinforcing (positive) feedbacks underlie many environmental problems, including global climate change, and eutrophication of coastal waters.
The skills and habits of mind that enable rigorous thinking about systems and emergent phenomena can be taught, but rarely emerge spontaneously (Hmelo-Silver & Azevedo, 2006) in the absence of specialized pedagogy crafted with this learning goal in mind. Even at the college level, students favor explanations that invoke only a single, linear process to explain observations in complex systems (Raia, 2005). Kastens, et al. (2009) have suggested that understanding of positive and negative feedback loops is a "threshold concept" (Meyer & Land, 2003, 2006) in geoscience education, and Slotta & Chi (2006) have made a strong case that understanding of emergent processes requires learners to pass through an "ontological shift" in which they recategorize or reorganize their world view. Hmelo-Silver, et al. (2007) have had some success in helping students reason about complex systems by breaking ideas down into structures, behaviors and functions, and Rivet and colleagues (2006) has had some success with a multi-year learning progression that spans the entire middle school curriculum. Research on learning of systems thinking is in its infancy and on a fast learning curve.
None of these difficulties is unique to geosciences. None is insurmountable. In some cases the learning task for ocean/atmosphere/earth sciences may not be inherently more difficult than for other sciences, but merely less familiar. For example, it may not be more difficult to plan and execute an inquiry using methodical observation across space and time rather than an experimental manipulation. But if the process is less familiar to students, parents, teachers, and supervisors, the net effect can be that resistance and stumbles are more likely.
I assembled this collection of ideas while introducing "Teaching & Learning Concepts in Earth Sciences," to a mixed audience of future faculty from Columbia's Department of Earth & Environmental Sciences and pre-service K-12 teachers from Teachers College's program in science education. I thank my co-instructor Ann Rivet and the students in the class over the last five years. Some of these ideas can be found in the report of the National Research Council's Committee to Review NOAA's Education Program, of which I was a member.
Edwards, C.H. 1997. Promoting student inquiry. The Science Teacher,64(7): 18-21.
Freeman, C. (2008). Convection in a Fish Tank. The Science Teacher, January issue, 62-66.
Gentner, D., & Colhoun, J. (in press). Analogical processes in human thinking and learning. In B. Glatzeder, V. Goel & A. v. Muller (Eds.), On Thinking: Volume 2. Towards a Theory of Thinking. Berlin: Springer-Verlag.
Gentner, D., & Toupin, C. (1986). Systemicity and surface similarity in the development of analogy. Cognitive Science, 10, 277-300.
Hmelo-Silver, C. E., and Azevedo, R., 2006, Understanding Complex Systems: Some Core Challenges: Journal of the Learning Sciences,v. 15, no. 1, p. 53-61.
Hmelo-Silver, C. E., Marathe, S., and Liu, L., 2007, Fish swim, rocks sit, and lungs breathe: Expert-novice understanding of complex systems: Journal of Learning Sciences, v. 16, p. 307-331.
Hug, B., & McNeill, K. (2008). Use of first-hand and second-hand data in science: Does data type influence classroom conversations? International Journal of Science Education, 30(13), 1725-1751.
Jones, M. G., Taylor, A., Minogue, J., Broadwell, B., Wiebe, E., & Carter, G. (2007a). Understanding Scale: Powers of Ten. Journal of Science Education and Technology, 16(2), 1059-1145.
Jones, M. G., Tretter, T., Taylor, A., & Oppewal, T. (2007b). Experienced and novice teachers' concepts of spatial scale. International Journal of Science Education, 30(3), 409-429.
Jones, M. G., & Taylor, A. R. (2009). Developing a sense of scale: Looking backward. Journal of Research in Science Teaching, 46(4), 460-475.
Kastens, K. A., Manduca, C. A., Cervato, C., Frodeman, R., Goodwin, C., Liben, L. S., Mogk, D. W., Spangler, T. C., Stillings, N. A., and Titus, S., 2009, How geoscientists think and learn: EOS, Transactions of the American Geophysical Union, v. 90, no. 31, p. 265-266.
Kastens, K. A., & Ishikawa, T. (2006). Spatial Thinking in the Geosciences and Cognitive Sciences. In C. Manduca & D. Mogk (Eds.), Earth and Mind: How Geoscientists Think and Learn about the Complex Earth (pp. 53-76): Geological Society of America Special Paper 413.
Kastens, K. A., & Rivet, A. (2008, January). Multiple modes of inquiry in Earth Science. The Science Teacher, 26-31.
Liben, L. (2006). Education for Spatial Thinking. In K. A. Renninger & I. E. Sigel (Eds.), Handbook of child psychology, sixth edition, volume four: Child psychology in practice (pp. 197-247). Hoboken, NJ: Wiley.
Meyer, J., and R. Land, Threshold concepts and troublesome knowledge: Linkages to ways of thinking and practicing with the discipline, in Occasional Report of the Enhancing Teaching-Learning Environments in Undergraduate Courses Project, University of Edinburgh, School of Education, Edinburgh, 2003.
Meyer, J. H. F., & Land, R. (Eds.). (2006). Overcoming Barriers to Student Learning: Threshold Concepts and Troublesome Knowledge. London: Routledge.
National Research Council. (2000). Inquiry and the national science education standards. Washington, D.C.: National Academy Press.
National Research Council. (2006). Learning to Think Spatially. Washington, D.C.: National Academies Press.
Piburn, M., S. J. Reynolds, C. McAuliffe, D.E. Leedy, J.P. Birk, and J.K. Johnson, The role of visualization in learning from computer-based images, International Journal of Science Education, 27, 513-527, 2005.
Raia, F., 2005, Students' Understanding of Complex Dynamic Systems: Journal of Geoscience Education, v. 53, p. 297-308.
Rivet, A., Systems Thinking, in Fortus, D., Hug, B., Krajcik, J., Kuhn, L., McNeill, K., Reiser, B., Rivet, A., Rogat, A., Schwartz, C. & Shwatz, Y., Sequencing and Supporting Complex Scientific Inquiry Practices in Instructional Materials for Middle School Students, Paper presented at the annual meeting of the National Association for Research in Science Teaching, San Francisco, April 2006.
Slotta, J. D., & Chi, M. T. H. (2006). Helping students understand challenging topics in science through ontology training. Cognition and Instruction, 24, 261-289.
Sorby, S.A., and B.J. Baartmans, The development and assessment of a course for enhancing the 3-D spatial visualization skills of first year engineering students, Journal of Engineering Education, 89, 301-308, 2000.
Tretter, T. R., Jones, M. G., Andre, T., Negishi, A., & Minogue, J. (2006). Conceptual boundaries and distances: Students' and experts' concepts of the scale of scientific phenomena. Journal of Research in ScienceTeaching, 43, 282-319.
Uthe, R.E. 2000. Projecting the scientific method. The Science Teacher67(9): 44-47.
Windschitl, M., Thomson, J., & Braaten, M. (2008). Beyond the scientific method: model-based inquiry as a new paradigm of preference for school science investigations. Science Education, 92(5), 941-967.
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