Skip to main content

Advertisement

SpringerLink
Log in

The Role of Content Knowledge in Ill-Structured Problem Solving for High School Physics Students

  • Published:
Research in Science Education Aims and scope Submit manuscript

Abstract

While Physics Education Research has a rich tradition of problem-solving scholarship, most of the work has focused on more traditional, well-defined problems. Less work has been done with ill-structured problems, problems that are better aligned with the engineering and design-based scenarios promoted by the Next Generation Science Standards. This study explored the relationship between physics content knowledge and ill-structured problem solving for two groups of high school students with different levels of content knowledge. Both groups of students completed an ill-structured problem set, using a talk-aloud procedure to narrate their thought process as they worked. Analysis of the data focused on identifying students’ solution pathways, as well as the obstacles that prevented them from reaching “reasonable” solutions. Students with more content knowledge were more successful reaching reasonable solutions for each of the problems, experiencing fewer obstacles. These students also employed a greater variety of solution pathways than those with less content knowledge. Results suggest that a student’s solution pathway choice may depend on how she perceives the problem.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. Some problem-solving researchers might refer to this question as an exercise instead of a problem, given the question’s “plug and chug” nature.

References

  • Bond, C. E., Philo, C., & Shipton, Z. K. (2011). When there isn’t a right answer: interpretation and reasoning, key skills for twenty-first century geoscience. International Journal of Science Education, 33(5), 629–652.

    Article  Google Scholar 

  • Bransford, J. D., & Stein, B. S. (1984). The ideal problem solver: a guide for improving thinking, learning, and creativity. New York: Freeman.

    Google Scholar 

  • Caballero, M. D., Greco, E. F., Murray, E. R., Bujak, K. R., Marr, M. J., Catrambone, R., & Schatz, M. F. (2012). Comparing large lecture mechanics curricula using the force concept inventory: a five thousand student study. American Journal of Physics, 80, 638.

    Article  Google Scholar 

  • Chi, M. T., & Glaser, R. (1985). Problem solving ability. In R. J. Sternberg (Ed.), Human abilities: an information processing approach (pp. 227–250). New York: W.H. Freeman and Company.

    Google Scholar 

  • Chi, M., Feltovich, P., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5(2), 121–152.

    Article  Google Scholar 

  • College Board (2006). Advanced Placement Report to the Nation. New York, NY.

  • Ericsson, K. A., & Simon, H. A. (1980). Verbal reports as data. Psychological Review, 87(3), 215–251.

    Article  Google Scholar 

  • Fortus, D. (2009). The importance of learning to make assumptions. Science Education, 93(1), 86–108.

    Article  Google Scholar 

  • Given, L. (2008). Open Coding. In The sage encyclopedia of qualitative research methods (pp. 582–583). Thousand Oaks, CA: Sage.

    Chapter  Google Scholar 

  • Hestenes, D., Wells, M., & Swackhamer, G. (1992). Force concept inventory. Physics Teacher, 30, 141–158.

    Article  Google Scholar 

  • Jonassen, D. H. (1997). Instructional design models for well-structured and ill-structured problem-solving learning outcomes. Educational Technology Research and Development, 45(1), 65–94.

    Article  Google Scholar 

  • Kitchner, K. S. (1983). Cognition, metacognition, and epistemic cognition. Human Development, 26(4), 222–232.

    Article  Google Scholar 

  • Kuhn, D. (2000). Metacognitive development. Current Directions in Psychological Science, 9(5), 178–181.

    Article  Google Scholar 

  • Larkin, J., McDermott, J., Simon, D., & Simon, H. (1980). Expert and novice performance in solving physics problems. Science, 208(4450), 1335–1342.

    Article  Google Scholar 

  • Lynch, S., & Bryan, L. (2014). Supporting the implementation of the Next Generation Science Standards (NGSS) through research: introduction to NARST position papers. Retrieved from https://narst.org/ngsspapers/

  • Milbourne, J., & Wiebe, E. N. (2013). How do high school students approach ill-defined physics problems? Presented at the NARST Annual Meeting, Rio Del Mar, PR.

  • National Research Council (2012). A framework for K-12 science education: practices, crosscutting concepts, and core ideas. Washington, DC: National Academies Press.

    Google Scholar 

  • NGSS Lead States (2013). Next Generation Science Standards: for states, by states. Washington, DC: The National Academies Press.

    Google Scholar 

  • Overton, T., Potter, N., & Leng, C. (2013). A study of approaches to solving open-ended problems in chemistry. Chemistry Education Research and Practice, 14(4), 468–475.

    Article  Google Scholar 

  • Palmer, D. (1997). The effect of context on students’ reasoning about forces. International Journal of Science Education, 19(6), 681–696.

    Article  Google Scholar 

  • Reitman, W. (1965). Cognition and thought. New York: Wiley.

    Google Scholar 

  • Sarsfield, E. (2014). Differences between novices’ and experts’ solving ill-structured problems. Public Health Nursing, 31(5), 444–453.

    Article  Google Scholar 

  • Schraw, G., Dunkle, M. E., & Bendixen, L. D. (1995). Cognitive processes in well-defined and ill-defined problem-solving. Applied Cognitive Psychology, 9(6), 523–538.

    Article  Google Scholar 

  • Schraw, G., & Moshman, D. (1995). Metacognitive theories. Educational Psychology Review, 7(4), 351–371.

    Article  Google Scholar 

  • Shin, N., Jonassen, D. H., & McGee, S. (2003). Predictors of well-structured and ill-structured problem solving in an astronomy simulation. Journal of Research in Science Teaching, 40(1), 6–33.

    Article  Google Scholar 

  • Simon, H. A. (1973). The structure of ill-structured problems. Artificial Intelligence, 4, 181–201.

    Article  Google Scholar 

  • Singh, C. (2002). When physical intuition fails. American Journal of Physics, 70(11), 1103–1109.

    Article  Google Scholar 

  • Sinnott, J. D. (1989). A model for solution of ill-structured problems: implications for everyday and abstract problem solving. In J. D. Sinnott (Ed.), Everyday problem solving: theory and applications (pp. 72–99). New York: Praeger.

    Google Scholar 

  • Strauss, A., & Corbin, J. (1998). Basics of qualitative research: techniques and procedures for developing grounded theory. Thousand Oaks, CA: Sage.

    Google Scholar 

  • Voss, J. F., & Post, T. A. (1988). On the solving of ill-structured problems. In M. T. H. Chi, R. Glaser, & M. J. Farr (Eds.), The nature of expertise. Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Education, North Carolina State University, Box 7801 – 326 Poe Hall, Raleigh, NC, 27695-7801, USA

    Jeff Milbourne & Eric Wiebe

Authors
  1. Jeff Milbourne
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eric Wiebe
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jeff Milbourne.

Ethics declarations

In submitting the paper “The Role of Content Knowledge in Ill-Structured Problem Solving for High School Physics Students,” there are no conflicts of interests involved, no financial support was involved, the listed authors are the sole authors of this paper, and there are no other ethical issues. Subjects of this research were consented and research methodologies utilized approved by the host institution’s Institutional Review Board.

Conflict of Interest

The authors declare that they have no conflict of interest.

Human Animal Rights

Research with human participants was conducted in this reported research and approved by our overseeing Institutional Review Board.

Informed Consent

All human participants in this study provided informed consent.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Milbourne, J., Wiebe, E. The Role of Content Knowledge in Ill-Structured Problem Solving for High School Physics Students. Res Sci Educ 48, 165–179 (2018). https://doi.org/10.1007/s11165-016-9564-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11165-016-9564-4

Keywords

Search

Navigation