Reuse & Permissions

It is not necessary to obtain permission to reuse this article or its components as it is available under the terms of the Creative Commons Attribution 3.0 License. This license permits unrestricted use, distribution, and reproduction in any medium, provided attribution to the author(s) and the published article's title, journal citation, and DOI are maintained. Please note that some figures may have been included with permission from other third parties. It is your responsibility to obtain the proper permission from the rights holder directly for these figures.

Export citation

Export citation

Choose format for download:

Download Citation
  • Open Access

Interpreting force concept inventory scores: Normalized gain and SAT scores

Vincent P. Coletta and Jeffrey A. Phillips

Jeffrey J. Steinert

  • Loyola Marymount University, Los Angeles, California 90045, USA

  • Edward Little High School, Auburn, Maine 04210, USA

Phys. Rev. ST Phys. Educ. Res. 3, 010106 – Published 23 May, 2007

DOI: https://doi.org/10.1103/PhysRevSTPER.3.010106

Abstract

Preinstruction SAT scores and normalized gains (G) on the force concept inventory (FCI) were examined for individual students in interactive engagement (IE) courses in introductory mechanics at one high school (N=335) and one university (N=292), and strong, positive correlations were found for both populations (r=0.57 and r=0.46, respectively). These correlations are likely due to the importance of cognitive skills and abstract reasoning in learning physics. The larger correlation coefficient for the high school population may be a result of the much shorter time interval between taking the SAT and studying mechanics, because the SAT may provide a more current measure of abilities when high school students begin the study of mechanics than it does for college students, who begin mechanics years after the test is taken. In prior research a strong correlation between FCI G and scores on Lawson’s Classroom Test of Scientific Reasoning for students from the same two schools was observed. Our results suggest that, when interpreting class average normalized FCI gains and comparing different classes, it is important to take into account the variation of students’ cognitive skills, as measured either by the SAT or by Lawson’s test. While Lawson’s test is not commonly given to students in most introductory mechanics courses, SAT scores provide a readily available alternative means of taking account of students’ reasoning abilities. Knowing the students’ cognitive level before instruction also allows one to alter instruction or to use an intervention designed to improve students’ cognitive level.

View figure in article

Article Text

References (33)

  1. D. Hestenes, M. Wells, and G. Swackhamer, Force concept inventory, Phys. Teach. 30, 141 (1992).
  2. E. Mazur, Peer Instruction: A User’s Manual (Prentice Hall, Upper Saddle River, NJ, 1997). We used Mazur’s version of FCI.
  3. R. R. Hake, Interactive-Engagement vs Traditional Methods: A Six-Thousand-Student Survey of Mechanics Test Data for Introductory Physics Courses, Am. J. Phys. 66, 64 (1998).
  4. R. R. Hake (unpublished), http://www.physics.indiana.edu/~hake/PERC2002h-Hake.pdf.
  5. D. Hestenes (private communication).
  6. V. P. Coletta and J. A. Phillips, Interpreting FCI Scores: Normalized Gain, Pre-instruction Scores, and Scientific Reasoning Ability, Am. J. Phys. 73, 1172 (2005).
  7. E. Redish and R. N. Steinberg, Teaching physics: Figuring out what works, Phys. Today 52 (1), 24 (1999).
  8. V. P. Coletta, J. A. Phillips, and J. J. Steinert, Why you should measure your students reasoning ability, Phys. Teach. 45, 235 (2007).
  9. A. E. Lawson, The development and validation of a classroom test of formal reasoning, J. Res. Sci. Teach. 15, 11 (1978). An updated multiple choice version of the test is in the appendix of Ref. [6].
  10. M. A. Dubson and S. J. Pollock, Can the Lawson Test Predict Student Grades?, AAPT Announcer 36, 90 (2006).
  11. P. M. Pamela and J. M. Saul, Interpreting FCI Normalized Gain, Pre-instruction Scores, and Scientific Reasoning Ability, AAPT Announcer 36, 89 (2006).
  12. J. W. Renner and A. E. Lawson, Piagetian theory and instruction in physics, Phys. Teach. 11, 165 (1973).
  13. B. Inhelder and J. Piaget, The Growth Of Logical Thinking From Childhood To Adolescence; An Essay On The Construction Of Formal Operational Structures (Basic Books, New York, 1958).
  14. A. E. Lawson, The generality of hypothetico-deductive reasoning: Making scientific thinking explicit, Am. Biol. Teach. 62, 482 (2000).
  15. D. Elkind, Quality conceptions in college students, J. Social Psych. 57, 459 (1962).
  16. J. A. Towler and G. Wheatley, Conservation concepts in college students, J. Genet. Psychol. 118, 265 (1971).
  17. A. B. Arons and R. Karplus, Implications of accumulating data on levels of intellectual development, Am. J. Phys. 44, 396 (1976).
  18. H. D. Cohen, D. F. Hillman, and R. M. Agne, Cognitive level and college physics achievement, Am. J. Phys. 46, 1026 (1978).
  19. J. W. McKinnon and J. W. Renner, Are colleges concerned with intellectual development?, Am. J. Phys. 39, 1047 (1971).
  20. A. E. Lawson and J. W. Renner, A quantitative analysis of responses to Piagetian tasks and its implications for curriculum, Sci. Educ. 58, 545 (1974).
  21. J. W. Renner and A. E. Lawson, Promoting intellectual development through science teaching, Phys. Teach. 11, 273 (1973).
  22. The College Board, SAT Program Handbook, 2005 http://www.collegeboard.com/prod_downloads/prof/counselors/tests/sat/2005-06-SAT-program-handbook.pdf.
  23. M. C. Frey and D. K. Detterman, The Relationship Between the Scholastic Assessment Test and General Cognitive Ability, Psychol. Sci. 15, 373 (2004).
  24. B. Bridgeman, L. McCamley-Jenkins, and N. Ervin, Predictions of Freshman Grade-Point Average From the Revised and Recentered SAT I: Reasoning Test (College Entrance Examination Board, New York, 2000) http://www.collegeboard.com/research/pdf/rr0001_3917.pdf.
  25. S. Geiser with R. Studley, UC and the SAT: Predictive Validity and Differential Impact of the SAT I and SAT II at the University of California, 2001 http://www.ucop.edu/sas/research/researchandplanning/pdf/sat_study.pdf.
  26. J. S. Shoemaker (unpublished).
  27. M. Wells, D. Hestenes, and G. Swackhamer, A modeling method for high school physics instruction, Am. J. Phys. 63, 606 (1995).
  28. R. Karplus, Science teaching and the development of reasoning, J. Res. Sci. Teach. 14, 169 (1977).
  29. R. Feuerstein, Y. Rand, M. B. Hoffman, and R. Miller, Instrumental enrichment: An intervention program for cognitive modifiability (University Park Press, Baltimore, 1980).
  30. P. S. Adey and M. Shayer, Really Raising Standards: Cognitive intervention and academic achievement (Routledge, London, 1994).
  31. P. S. Adey, M. Shayer, and C. Yates, Thinking Science: The curriculum materials of the CASE project, 3rd ed. (Nelson Thornes, London, 2001).
  32. B. Kurtz, Ph.D. dissertation in science and mathematics education, University of California, 1976.
  33. B. Kurtz and R. Karplus, Intellectual development beyond elementary school vii: teaching for proportional reasoning, Sch. Sci. Math. 79, 387 (1979).

Outline

Information

Sign In to Your Journals Account

Filter

Filter

Article Lookup

Enter a citation