- Physical Review Journals
All JournalsPhysics Magazine

Physical Review Physics Education Research

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 4.0 International 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

Evaluating a department-wide initiative incorporating computational methods into the undergraduate physics curriculum

Greg Gallagher1, Gautam Vemuri1, Danka Maric2, and Andrew Gavrin1,*

  • *Contact author: agavrin@iu.edu
PDF

Phys. Rev. Phys. Educ. Res. 22, 010138 – Published 28 April, 2026

DOI: https://doi.org/10.1103/2zmq-2t62

Abstract

We report on a department-wide initiative, implemented beginning in 2018, aimed at making computational methods a routine and integrated part of the undergraduate physics curriculum. Using survey data collected from undergraduate physics students across multiple years, we examined how students’ attitudes toward computation and their self-efficacy with computational skills change as they progress through the program. The survey includes attitudinal items and self-efficacy ratings for a range of computational tools and methods, as well as retrospective assessments of students’ initial skill levels. An exploratory factor analysis was conducted for both parts of the survey, and each part produced reliable, two-factor structures. Our analyses of student attitudes and self-efficacy throughout the program show that, at the program level, students generally report more positive views of computation and higher computational self-efficacy at later stages. However, these changes are not evenly distributed across the curriculum, with larger shifts concentrated in particular semesters. Together, these results show that our department-wide effort to integrate computational methods into the undergraduate curriculum supports growth in student attitudes and self-efficacy, but that this growth may be driven by specific experiences in the program rather than by progression alone. We also find that conclusions about growth in computational self-efficacy depend on how growth is measured. For some skills, growth based on present self-efficacy closely matches growth estimates that incorporate retrospective initial ratings, while for others, the two approaches differ substantially. Importantly, these differences are not uniform across skills but align with the underlying factor structure of the survey. Skills associated with specific computational tools or languages show relatively little response-shift effect, whereas skills associated with applied computational methods exhibit larger differences in growth estimates when retrospective measures are included. These findings suggest that retrospective pretest survey designs may be particularly important for assessing growth in methods-based computational skills. On the whole, this study highlights the importance of considering both curricular structure and measurement approach when evaluating our curriculum-wide initiative to integrate computation into undergraduate physics programs.

View figure in article

Physics Subject Headings (PhySH)

Article Text

References (38)

  1. J. M. Wilson and E. F. Redish, Using computers in teaching physics, Phys. Today 42, No. 1, 34 (1989).
  2. E. F. Redish, Is the computer appropriate for teaching physics?, Comput. Phys. 7, 613 (1993).
  3. T. J. Atherton, Resource letter CP-3: Computational physics, Am. J. Phys. 91, 7 (2023).
  4. R. H. Landau, Resource letter CP-2: Computational physics, Am. J. Phys. 76, 296 (2008).
  5. E. Behringer et al., AAPT Recommendations for Computational Physics in the Undergraduate Physics Curriculum (American Association of Physics Teachers, College Park, MD, 2016), https://www.aapt.org/Resources/upload/AAPT_UCTF_CompPhysReport_final_B.pdf [accessed July 1, 2025].
  6. P. Heron and L. McNeil, PHYS21: Preparing Physics Students for 21st Century Careers (American Physical Society, College Park, MD, 2016).
  7. American Physical Society and American Association of Physics Teachers, Computational Skills. EP3 Guide: Effective Practices for Physics Programs (2021), https://ep3guide.org/guide/computational-skills/.
  8. Partnership for the integration of computation into undergraduate physics, Available at https://www.compadre.org/picup/ [accessed July 9, 2025]
  9. D. H. McIntyre, J. Tate, and C. A. Manogue, Integrating computational activities into the upper-level paradigms in physics curriculum at Oregon State University, Am. J. Phys. 76, 340 (2008).
  10. D. M. Cook, Computation in the Lawrence physics curriculum, Available at https://www2.lawrence.edu/dept/physics/ccli/compatlu.pdf (2006) [accessed July 11, 2025]
  11. PhysPort, Available at https://www.physport.org/ [accessed July 9, 2025]
  12. M. D. Caballero, M. A. Kohlmyer, and M. F. Schatz, Implementing and assessing computational modeling in introductory mechanics, Phys. Rev. Phys. Educ. Res. 8, 020106 (2012).
  13. H. C. Sabo, T. O. B. Odden, and M. D. Caballero, How do we assess computation in physics?, arXiv:2308.15983.
  14. A. Gavrin, G. Vemuri, and D. Maric, Preliminary efforts to evaluate an initiative introducing computation across the undergraduate physics curriculum., presented at PER Conf. 2021, Virtual Conference, 10.1119/perc.2021.pr.Gavrin.
  15. I. A. Halloun and D. Hestenes, The initial knowledge state of college physics students, Am. J. Phys. 53, 1043 (1985).
  16. D. Hestenes, M. Wells, and G. Swackhamer, Force Concept Inventory, Phys. Teach. 30, 141 (1992).
  17. National Research Council, Adapting to a Changing World: Challenges and Opportunities in Undergraduate Physics Education (The National Academies Press, Washington, DC, 2013).
  18. J. L. Docktor and J. P. Mestre, Synthesis of discipline-based education research in physics, Phys. Rev. Phys. Educ. Res. 10, 020119 (2014).
  19. L. Bao and K. Koenig, Physics education research for 21st century learning, Discip. Interdiscip. Sci. Educ. Res. 1, 2 (2019).
  20. L. J. Cronbach and L. Furby, How should we measure “change”—or should we?, Psychol. Bull. 74, 68 (1970).
  21. G. S. Howard and P. R. Dailey, Response-shift bias: A problem in evaluating interventions with pre/post self-report measures, Eval. Rev. 4, 93 (1980).
  22. G. S. Howard, K. M. Ralph, N. A. Gulanick, S. E. Maxwell, and S. K. Gerber, Internal invalidity in pretest-posttest self-report evaluations and a re-evaluation of retrospective pretests, Appl. Psychol. Meas. 3, 1 (1979).
  23. J. Kruger and D. Dunning, Unskilled and unaware of it: How difficulties in recognizing one’s own incompetence lead to inflated self-assessments, J. Pers. Soc. Psychol. 77, 1121 (1999).
  24. C. C. Pratt, W. M. McGuigan, and A. R. Katzev, Measuring program outcomes: Using retrospective pretest methodology, Am. J. Eval. 21, 341 (2000).
  25. S. V. Chasteen and R. Chattergoon, Evaluating impact using post-then-pre methodology, presented at PER Conf. 2019, 10.1119/perc.2019.pr.Chasteen.
  26. K. Miller, T. Espinosa, I. Araujo, and I. Gallegos, Response-shift bias in student self-efficacy during an actively taught physics course, Phys. Rev. Phys. Educ. Res. 19, 020167 (2023).
  27. A. Gavrin, G. Gallagher, D. Maric, and G. Vemuri, An exploratory factor analysis of a survey measuring undergraduate student attitudes of computational methods in physics, presented at PER Conf. 2024, Boston, MA, 10.1119/perc.2024.pr.Gavrin.
  28. G. Gallagher, G. Vemuri, A. Gavrin, and D. Maric, Evaluating students’ self-efficacy with respect to computational methods in the undergraduate physics curriculum, presented at PER Conf. 2024 .10.1119/perc.2024.pr.Gallagher
  29. L. Tabachnik, Using Multivariate Statistics (Pearson Education Limited, New York, NY, 2012).
  30. D. L. Bandalos and S. J. Finney, Factor analysis exploratory and confirmatory, in The Reviewer’s Guide to Quantitative Methods in the Social Sciences (Routledge, Boston, MA, 2018).
  31. E. Knekta, C. Runyon, and S. Eddy, One size doesn’t fit all: Using factor analysis to gather validity evidence when using surveys in your research, CBE Life Sci. Educ. 18, 1 (2019).
  32. M. W. Watkins, Exploratory factor analysis: A guide to best practice, J. Black Psychol. 44, 219 (2018).
  33. B. P. O’Connor, SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s map test, Behav. Res. Methods Instrum. Comput. 32, 396 (2000).
  34. Z. Karimian and F. Chahartangi, Development and validation of a questionnaire to measure educational agility: A psychometric assessment using exploratory factor analysis, BMC Med. Educ. 24, 1284 (2024).
  35. S. Sovey, K. Osman, and M. E. Mohd-Matore, Exploratory and confirmatory factor analysis for disposition levels of computational thinking instrument among secondary school students, Eur. J. Educ. Res. 11, 639 (2022).
  36. R. C. MacCallum, K. F. Widaman, S. Zhang, and S. Hong, Sample size in factor analysis, Psychol. Methods 4, 84 (1999).
  37. B. G. Tabachnick and L. S. Fidell, Using Multivariate Statistics, 5th ed. (Pearson Education, Boston, MA, 2007).
  38. K. S. Taber, The use of Cronbach’s alpha when developing and reporting research instruments in science education, Res. Sci. Educ. 48, 1273 (2018).

Outline

Information

Phys. Rev. Phys. Educ. Res. 22, 010138– Published 28 April, 2026
  • Received 19 December 2025
  • Accepted 30 March 2026
Crossmark - Check for updates button
Creative Commons Logo

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

Published by the American Physical Society

Sign In to Your Journals Account

Filter

Filter

Article Lookup

Enter a citation