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Understanding Undergraduates’ Problem-Solving Processes

    Author: Ross H. Nehm1,*
    VIEW AFFILIATIONS HIDE AFFILIATIONS
    Affiliations: 1: School of Teaching and Learning, and Dept. of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43210
    AUTHOR AND ARTICLE INFORMATION AUTHOR AND ARTICLE INFORMATION
    • Published 20 December 2010
    • †This material is based in part upon research supported by the National Science Foundation under REESE grant number 0909999 (Nehm, P.I.). Any opinions, findings and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the NSF.
    • *Corresponding author. Mailing address: School of Teaching and Learning, and Dept. of Evolution, Ecology, and Organismal Biology, 1945 N. High Street, 333 Arps Hall, The Ohio State University, Columbus, OH 43210. Phone: (614) 688-5373. Fax: (614) 755-4241. E-mail: [email protected].
    • Copyright © 2010 American Society for Microbiology
    Source: J. Microbiol. Biol. Educ. December 2010 vol. 11 no. 2 119-122. doi:10.1128/jmbe.v11i2.203
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    Abstract:

    Fostering effective problem-solving skills is one of the most longstanding and widely agreed upon goals of biology education. Nevertheless, undergraduate biology educators have yet to leverage many major findings about problem-solving processes from the educational and cognitive science research literatures. This article highlights key facets of problem-solving processes and introduces methodologies that may be used to reveal how undergraduate students perceive and represent biological problems. Overall, successful problem-solving entails a keen sensitivity to problem contexts, disciplined internal representation or modeling of the problem, and the principled management and deployment of cognitive resources. Context recognition tasks, problem representation practice, and cognitive resource management receive remarkably little emphasis in the biology curriculum, despite their central roles in problem-solving success.

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Natural Selection
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References & Citations

1. Atran S, Medin D 2008 The native mind and the cultural construction of nature MIT Press Cambridge, MA
2. Baddeley AD 1986 Working memory Oxford University Press Oxford, UK
3. Chi MTH 2006 Methods to assess the representations of experts’ and novices’ knowledge 167 184 Ericsson KA, Charness N, Feltovich P, Hoffman R Cambridge handbook of expertise and expert performance Cambridge University Press Cambridge, UK 10.1017/CBO9780511816796.010 http://dx.doi.org/10.1017/CBO9780511816796.010
4. Chi MTH, Feltovich PJ, Glaser R 1981 Categorization and representation of physics problems by experts and novices Cognitive Science 5 121 152 10.1207/s15516709cog0502_2 http://dx.doi.org/10.1207/s15516709cog0502_2
5. D’Avanzo C 2008 Biology concept inventories: overview, status, and next steps BioScience 58 1079 1085 10.1641/B581111 http://dx.doi.org/10.1641/B581111
6. Duit R 2004 Bibliography: students’ and teachers’ conceptions and science education database University of Kiel Germany http://www.ipn.uni-kiel.de/aktuell/stcse/stcse.html
7. Dunker K 1945 On problem solving Psych Monographs 58 270
8. Gabel D, Bunce D 1994 Research on problem solving: Chemistry Gabel DL Handbook of Research on Science Teaching and Learning: a project of the National Science Teachers Association MacMillan Publishing Company New York, NY
9. Maloney D 1994 Research on problem solving: Physics Gabel DL Handbook of research on science teaching and learning: a project of the National Science Teachers Association MacMillan Publishing Company New York, NY
10. National Research Council Committee on a New Biology for the 21st Century: Ensuring the United States Leads the Coming Biology Revolution 2009 A new biology for the 21st century National Academy Press Washington, D.C.
11. National Research Council Committee on Undergraduate Biology Education to Prepare Research Scientists for the 21 st Century, Board on Life Sciences 2003 BIO2010: Transforming undergraduate education for future research biologists National Academy Press Washington, D.C.
12. National Research Council Committee on the Foundations of Assessment 2001 Knowing what students know: the science and design of educational assessment National Academy Press Washington, D.C.
13. Nehm RH, Ha M [in press]. Item feature effects in evolution assessment J Res Sci Teaching
14. Nehm RH, Schonfeld IS 2008 Measuring knowledge of natural selection: a comparison of the CINS, an open-response instrument, and an oral interview J Res Sci Teaching 45 1131 1160 10.1002/tea.20251 http://dx.doi.org/10.1002/tea.20251
15. Newell A, Simon HA 1972 Human problem solving Prentice-Hall Englewood Cliffs, NJ
16. Novick L, Bassok M 2005 Problem solving 321 350 Holyoak KJ, Morrison RG The Cambridge handbook of thinking and reasoning Cambridge University Press Cambridge, UK
17. Plass JL, Moreno R, Brunken R 2010 Cognitive load theory Cambridge University Press Cambridge, UK
18. Reif F 2008 Applying cognitive science to education: thinking and learning in scientific and other complex domains MIT Press Cambridge, MA
19. Reif F, Heller JI 1982 Knowledge structure and problem solving in physics Edu Psychologist 17 102 127 10.1080/00461528209529248 http://dx.doi.org/10.1080/00461528209529248
20. Science Education Resource Center Developing concept maps Accessed online June 3, 2009 at: http://serc.carleton.edu/introgeo/assessment/conceptmaps.html
21. Sinatra GM, Brem SK, Evans EM 2008 Changing minds? Implications of conceptual change for teaching and learning about biological evolution Evo Edu Outreach 1 189 195 10.1007/s12052-008-0037-8 http://dx.doi.org/10.1007/s12052-008-0037-8
22. Staver JR 1986 The effects of problem format, number of independent variables, and their interaction on student performance on a control of variables reasoning problem J Res Sci Teaching 23 533 542 10.1002/tea.3660230606 http://dx.doi.org/10.1002/tea.3660230606
23. Stewart J, Hafner R 1994 Research on problem solving: Genetics Gabel DL Handbook of research on science teaching and learning: a project of the National Science Teachers Association MacMillan Publishing Company New York, NY

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/content/journal/jmbe/10.1128/jmbe.v11i2.203
2010-12-20
2019-08-19

Abstract:

Fostering effective problem-solving skills is one of the most longstanding and widely agreed upon goals of biology education. Nevertheless, undergraduate biology educators have yet to leverage many major findings about problem-solving processes from the educational and cognitive science research literatures. This article highlights key facets of problem-solving processes and introduces methodologies that may be used to reveal how undergraduate students perceive and represent biological problems. Overall, successful problem-solving entails a keen sensitivity to problem contexts, disciplined internal representation or modeling of the problem, and the principled management and deployment of cognitive resources. Context recognition tasks, problem representation practice, and cognitive resource management receive remarkably little emphasis in the biology curriculum, despite their central roles in problem-solving success.

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Author and Article Information

  • Published 20 December 2010
  • †This material is based in part upon research supported by the National Science Foundation under REESE grant number 0909999 (Nehm, P.I.). Any opinions, findings and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the NSF.
  • *Corresponding author. Mailing address: School of Teaching and Learning, and Dept. of Evolution, Ecology, and Organismal Biology, 1945 N. High Street, 333 Arps Hall, The Ohio State University, Columbus, OH 43210. Phone: (614) 688-5373. Fax: (614) 755-4241. E-mail: [email protected].
  • Copyright © 2010 American Society for Microbiology

Figures

Understanding Undergraduates’ Problem-Solving Processes
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Citation: Nehm R. 2010. Understanding undergraduates’ problem-solving processes . J. Microbiol. Biol. Educ. 11(2):119-122 doi:10.1128/jmbe.v11i2.203
/content/jmbe/10.1128/jmbe.v11i2.203.f1-jmbe-11-2-119
FIGURE 1

A magnet metaphor for problem-solving. In novices, many cognitive resources are highly attracted to problems. Such knowledge is often poorly organized and sensitized, leading to working memory overload. In experts, much naive knowledge has been appropriately sensitized to context (demagnetized) so that it is not attracted to problems but may be used in other contexts.

jmbe/11/2/jmbe-11-2-119f1_thmb.gif
jmbe/11/2/jmbe-11-2-119f1.gif
Image of FIGURE 1

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FIGURE 1

A magnet metaphor for problem-solving. In novices, many cognitive resources are highly attracted to problems. Such knowledge is often poorly organized and sensitized, leading to working memory overload. In experts, much naive knowledge has been appropriately sensitized to context (demagnetized) so that it is not attracted to problems but may be used in other contexts.

Source: J. Microbiol. Biol. Educ. December 2010 vol. 11 no. 2 119-122. doi:10.1128/jmbe.v11i2.203
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