Research Article
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Reasoning about multiple variables: Control of variables is not the only challenge
Deanna Kuhn,
Corresponding Author
Deanna Kuhn
Teachers College Columbia University, New York, NY 10027, USA
Teachers College Columbia University, New York, NY 10027, USASearch for more papers by this authorDeanna Kuhn,
Corresponding Author
Deanna Kuhn
Teachers College Columbia University, New York, NY 10027, USA
Teachers College Columbia University, New York, NY 10027, USASearch for more papers by this authorAbstract
Thirty fourth-grade students participated in an extended intervention previously successful in fostering skills of scientific investigation and inference, notably control of variables (COV). The intervention was similarly successful for a majority of students in the present study, enabling them to isolate the three causal and two noncausal variables operating in a multivariable system. However, when asked to predict outcomes of various constellations of variable levels, they tended not to take into account the effects of all of the causal variables they had identified. Moreover, they did not adhere to a consistency principle, i.e., that a factor that produces an effect can be expected to produce the same effect in the future, given similar conditions. These findings suggest that COV is not the only challenge students experience in reasoning about multiple variables. Elementary-school students' mental models of multivariable causality appear to deviate from a normative, scientific model, even after they have mastered that aspect of scientific method having to do with the design of controlled experiments to isolate effects of individual variables. The challenges, beyond COV, that appear to be involved in making prediction judgments involving multiple variables warrant attention in the design of curricula to foster development of scientific thinking skills. © 2007 Wiley Periodicals, Inc. Sci Ed 91:710–726, 2007
REFERENCES
- Abd-El-Khalick, F., BouJaoude, S., Duschl, R., Lederman, N., Mamiok-Naaman, R., Hofstein, A., Niaz, M., Treagust, D., & Tuan, H. (2004). Inquiry in science education: International perspectives. Science Education, 88, 397–419.
- Anderson, N. (1991). Contributions to information integration theory: Vol. III. Development. Hillsdale, NJ: Erlbaum.
- Cheng, P. (1997). From covariation to causation: A causal power theory. Psychological Review, 104, 367–405.
- Dean, D., Jr., & Kuhn, D. (2007). Direct instruction vs. discovery: The long view. Science Education, 91, 384–397.
- Detterman, D., & Sternberg, R. (1993). Transfer on trial: Intelligence, cognition, and instruction. Norwood, NJ: Ablex.
- Dixon, J., & Tuccillo, F. (2001). Generating initial models for reasoning. Journal of Experimental Child Psychology, 78, 178–212.
- Downing, C., Sternberg, R., & Ross, B. (1985). Multicausal inference: Evaluation of evidence in causally complex situations. Journal of Experimental Psychology: General, 114, 239–263.
- Duschl, R., & Grandy, R. (2005). Reconsidering the character and role of inquiry in school science: Framing the debates. Unpublished manuscript, Rice University.
- Glymour, C. (2001). The mind's arrows. Cambridge, MA: MIT Press.
- Gopnik, A., Sobel, D. M., Schulz, L. E., & Glymour, C. (2001). Causal learning mechanisms in very young children: Two-, three-, and four-year-olds infer causal relations from patterns of variation and covariation. Developmental Psychology, 37, 620–629.
- Hilton, D., & Slugoski, B. (1986). Knowledge-based causal attribution: The abnormal conditions focus model. Psychological Review, 93, 75–88.
- Keil, F. (1998). Cognitive science and the origins of thought and knowledge. In W. Damon (Series Ed.) & R. Lerner (Vol. Ed.), Handbook of child psychology ( 5th ed., Vol. I). New York: Wiley.
- Keselman, A. (2003). Promoting scientific reasoning in a computer-assisted environment. Journal for Research in Science Teaching, 40, 898–921.
- Klaczynski, P. (2004). A dual-process model of adolescent development: Implications for decision making, reasoning, and identity. In R. Kail (Ed.), Advances in child development and behavior (Vol. 31). San Diego, CA: Academic Press.
-
Klahr, D. (2000).
Exploring science: The cognition and development of discovery processes.
Cambridge, MA: MIT Press.
10.7551/mitpress/2939.001.0001 Google Scholar
- Klahr, D., Fay, A., & Dunbar, K. (1993). Heuristics for scientific experimentation: A developmental study. Cognitive Psychology, 25, 111–146.
- Klahr, D., & Nigam, M. (2004). The equivalence of learning paths in early science instruction: Effects of direct instruction and discovery learning. Psychological Science, 15, 661–667.
- Koslowski, B. (1996). Theory and evidence: The development of scientific reasoning. Cambridge, MA: MIT Press.
- Kuhn, D. (1989). Children and adults as intuitive scientists. Psychological Review, 96, 674–689.
- Kuhn, D. (1993). Science as argument: Implications for teaching and learning scientific thinking. Science Education, 77(3), 319–337.
-
Kuhn, D. (2002).
What is scientific thinking and how does it develop?
In
U. Goswami (Ed.),
Handbook of childhood cognitive development.
Oxford, England: Blackwell.
10.1002/9780470996652.ch17 Google Scholar
- Kuhn, D. (2005). Education for thinking. Cambridge, MA: Harvard University Press.
-
Kuhn, D. (2007, February/March).
Jumping to conclusions: Can people be counted on to make sound judgments?
Scientific American–Mind,
18(1), 44–51.
10.1038/scientificamericanmind0207-44 Google Scholar
- Kuhn, D., Amsel, E., & O'Loughlin, M. (1988). The development of scientific thinking skills. Orlando, FL: Academic Press.
- Kuhn, D., Black, J., Keselman, A., & Kaplan, D. (2000). The development of cognitive skills to support inquiry learning. Cognition and Instruction, 18, 495–523.
- Kuhn, D., & Brannock, J. (1977). Development of the isolation of variables scheme in experimental and “natural experiment” contexts. Developmental Psychology, 13, 9–14.
- Kuhn, D., & Dean, D. (2004). Connecting scientific reasoning and causal inference. Journal of Cognition and Development, 5, 261–288.
- Kuhn, D., & Dean, D. (2005). Is developing scientific thinking all about learning to control variables? Psychological Science, 16, 866–870.
- Kuhn, D., & Franklin, S. (2006). The second decade: What develops (and how)? In W. Damon & R. Lerner (Series Eds.) & D. Kuhn & R. Siegler (Vol. Eds.), Handbook of child psychology: Vol. II. Cognition, perception, and language ( 6th ed.). Hoboken, NJ: Wiley.
- Kuhn, D., Garcia-Mila, M., Zohar, A., & Andersen, C. (1995). Strategies of knowledge acquisition. Monographs of the Society for Research in Child Development, 60(No. 245).
- Kuhn, D., Katz, J., & Dean, D. (2004). Developing reason. Thinking and Reasoning, 10, 197–219.
- Kuhn, D., Schauble, L., & García-Mila, M. (1992). Cross-domain development of scientific reasoning. Cognition and Instruction, 9(4), 285–327.
- Lehrer, R., & Schauble, L. (2006). Scientific thinking and scientific literacy: Supporting development in learning contexts. In W. Damon & R. (Series Eds.) & K. A. Renninger & I. Sigel (Vol. Eds.), Handbook of child psychology ( 6th ed., Vol. IV). Hoboken, NJ: Wiley.
- Markovits, H., & Barrouillet, P. (2002). The development of conditional reasoning: A mental model account. Developmental Review, 22, 5–36.
- National Research Council (1996). The National Science Education Standards. Washington, DC: National Academy Press.
- Ruffman, T., Perner, J., Olson, D., & Doherty, M. (1993). Reflecting on scientific thinking: Children's understanding of the hypothesis-evidence relation. Child Development, 64, 1617–1636.
- Schauble, L. (1990). Belief revision in children: The role of prior knowledge and strategies for generating evidence. Journal of Experimental Child Psychology, 49, 31–57.
- Schauble, L. (1996). The development of scientific reasoning in knowledge-rich contexts. Developmental Psychology, 32, 102–119.
- Schulz, L., & Gopnik, A. (2004). Causal learning across domains. Developmental Psychology, 40(2), 162–176.
- Schustack, M., & Sternberg, R. (1981). Evaluation of evidence in causal inference. Journal of Experimental Psychology: General, 110, 101–120.
- Sedlak, A., & Kurtz, S. (1981). A review of children's use of causal inference principles. Child Development, 52, 759–784.
- Siegler, R. (2006). Microgenetic studies of learning. In W. Damon & R. Lerner (Series Eds.) & D. Kuhn & R. Siegler (Vol. Eds.), Handbook of child psychology: Vol. II. Cognition, perception, and language ( 6th ed.). Hoboken, NJ: Wiley.
- Sloman, S., & Lagnado, D. (2005). Do we “do?” Cognitive Science, 29, 5–39.
- Sodian, B., Zaitchik, D., & Carey, S. (1991). Young children's differentiation of hypothetical beliefs from evidence. Child Development, 62, 753–766.
- Spellman, B. (1996). Acting as intuitive scientists: Contingency judgments are made while controlling for alternative potential causes. Psychological Science, 7, 337–342.
- Steyvers, M., Tenenbaum, J., Wagenmakers, E., & Blum, B. (2003). Inferring causal networks from observations and interventions. Cognitive Science, 27, 453–489.
- Waldmann, M., & Hagmayer, Y. (2005). Seeing versus doing: Two modes of accessing causal knowledge. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31, 216–227.
- Waldmann, M. R., & Martignon, L. (1998). A Bayesian network model of causal learning. In M. A. Gernsbacher & S. J. Derry (Eds.), Proceedings of the Twentieth Annual Conference of the Cognitive Science Society (pp. 1102—1107). Mahwah, NJ: Erlbaum.
- Wilkening, F. (1982). Integrating velocity, time, and distance information: A developmental study. Cognitive Psychology, 13, 231–247.
- Zimmerman, C. (2000). The development of scientific reasoning skills. Developmental Review, 20, 99–149.
- Zimmerman, C. (in press). The development of scientific thinking in elementary and middle school. Developmental Review.
