Student perceptions of pedagogy and associated persistence in calculus
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There is a clear need to increase student persistence in Science, Technology, Engineering, or Mathematics (STEM). Prior analyses have shown that students who change their Calculus II intention (a proxy for STEM intention) report being less engaged during class than students who persist onto Calculus II. This led us to ask: Are these students in different classes, or are they in the same classes but experiencing them differently? We present descriptive and univariate analyses of the relationship of calculus persistence to student demographics, background characteristics, and reported instruction for 1,684 STEM intending students and 330 non-STEM intending students enrolled in introductory calculus in Fall 2010 in the United States. We then develop regression models that control for the group effect of course enrollment to understand how perceiving low levels of various pedagogical activities within a class is associated with calculus persistence. These analyses show that different student perceptions of the frequency of a number of pedagogical activities, and thus different ways of experiencing the same class, are related to students’ decision to continue studying calculus. Specifically, among initially STEM intending students, there was a relationship between persistence and the perceived frequency of the instructor showing students how to work specific problems, preparing extra material to help students understand calculus concepts or procedures, holding a whole-class discussion, and requiring students to explain their thinking on exams. Among initially non-STEM intending students, there was a relationship between persistence and the perceived frequency of being required to explain thinking during class.
KeywordsPost-secondary education Instructional activities and practices Data analysis and statistics Calculus instruction Student persistence
- Bagley, S. (2013). A comparison of four pedagogical strategies in calculus. Poster presented at the 35th Annual Conference of the North American Chapter of the International Group for the Psychology of Mathematics Education, Chicago, IL.Google Scholar
- Carnevale, A. P., Smith, N., & Melton, M. (2011). STEM: Science, technology, engineering, mathematics. Georgetown University, Center on Education and the Workforce. http://www.georgetown.edu/grad/gppi/hpi/cew/pdfs/stem-complete.pdf.
- Ferguson, R. (2012). Can student surveys measure teaching quality? Phi Delta Kappan, 94(3), 24–28.Google Scholar
- Hurtado, S., Eagan, M.K., & Chang, M. (2010). Degrees of success: Bachelor’s degree completion rates among initial STEM majors. http://www.heri.ucla.edu/nih/downloads/2010Hurtado,Eagan,Chang-DegreesofSuccess.pdf.
- Kogan, M., & Laursen, S.L. (2013). Assessing long-term effects of inquiry-based learning: a case study from college mathematics. Innovative Higher Education, 1–17.Google Scholar
- Lodico, M. G., Spaulding, D. T., & Voegtle, K. H. (2010). Methods in educational research: From theory to practice (2nd ed.). San Francisco: Jossey-Bass.Google Scholar
- Lutzer, D. J., Rodi, S. B., Kirkman, E. E., & Maxwell, J. W. (2007). Statistical abstract of undergraduate programs in the mathematical sciences in the United States. CBMS: American Mathematical Society, Providence, RI.Google Scholar
- Mihaly, K., McCaffrey, D.F., Staiger, D.O., & Lockwood, J.R. (2013). A Composite Estimator of Effective Teaching. http://www.nbexcellence.org/cms_files/resources/Jan2013ACompositeEstimatorofEffectiveTeachingResearchPaper.pdf.
- President’s Council of Advisors on Science and Technology (PCAST). (2012). Engage to excel: Producing one million additional college graduates with Degrees in Science, Technology, Engineering, and Mathematics. Washington, DC: The White House.Google Scholar
- Rasmussen, C., & Ellis, J. (2013). Who is switching out of calculus and why? In A. M. Lindmeier & A. Heinze (Eds.), Proceedings of the 37th Conference of the International Group for the Psychology of Mathematics Education (Vol. 4, pp. 73–80). Kiel, Germany: PME.Google Scholar
- Rasmussen, C., & Marrongelle, K. (2006). Pedagogical content tools: Integrating student reasoning and mathematics into instruction. Journal for Research in Mathematics Education, 37, 388–420.Google Scholar
- Seymour, E. (2006). Testimony offered by Elaine Seymour, Ph.D., University of Colorado at Boulder, to the Research Subcommittee of the Committee on Science of the US House of Representatives Hearing on Undergraduate Science, Math and Engineering Education: What’s Working? Wednesday, March 15, 2006.Google Scholar
- Seymour, E., & Hewitt, N. M. (1997). Talking about leaving: Why undergraduate leave the sciences. Boulder, CO: Westview Press.Google Scholar
- Steen, L. A. (Ed.). (1988). Calculus for a New Century: a Pump, not a Filter, Mathematical Association of America, MAA Notes Number 8. DC: Washington.Google Scholar
- Szafran, R. (2012). Answering questions with statistics. Los Angeles, CA: Sage Publications.Google Scholar
- Tinto, V. (2004). Linking learning and leaving. In J. M. Braxton (Ed.), Reworking the student departure puzzle. Nashville, TN: Vanderbilt University Press.Google Scholar
- Wake, G. (2011). Introduction to the Special Issue: deepening engagement in mathematics in pre-university education. Research in Mathematics Education 13(2), 109–118.Google Scholar