- 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

Enhancing peer instruction in physics: Understanding cognitive processes and refining rules

Vegard Gjerde and Sivert Hagane

  • Department of Physics and Technology, University of Bergen, 5007 Bergen, Norway

PDF

Phys. Rev. Phys. Educ. Res. 20, 010134 – Published 3 May, 2024

DOI: https://doi.org/10.1103/PhysRevPhysEducRes.20.010134

Abstract

Peer Instruction gives practice in the abstract language of physics, addresses common misconceptions among students, and is more effective than traditional lecturing. However, it is not clear what makes Peer Instruction effective nor how we might improve the method. An emerging perspective is that what makes Peer Instruction effective is how it stimulates certain cognitive processes. Research also indicates that providing rules for discussion may improve the effect of peer instruction. Hence, we wanted to answer two research questions in this study: (i) What cognitive learning processes occur during peer discussions? (ii) How do students follow discussion rules? To answer our research questions, we recorded and thematically analyzed peer discussions during Peer Instruction in an introductory physics course. The most prevalent cognitive process during peer discussions was decoding the problem. The most prevalent type of explanation was explanations with physics concepts, which usually led the students to an incorrect answer. The next most prevalent type of explanation was explanation with physics models, which usually led the students to the correct answer. The students also explained with reference to their experience or examples—intuitive or analogical explanations—and it usually added little to the conversation, was wrong, or created confusion. Some discussion rules had limited impact, prompting suggestions for rule improvements to optimize Peer Instruction. Our work contributes to the literature on Peer Instruction with a cognitively based description of the learning processes and how we might further improve and ensure the effectiveness of Peer Instruction.

View figure in article

Physics Subject Headings (PhySH)

Article Text

References (86)

  1. C. Angell, Ø. Guttersrud, E. K. Henriksen, and A. Isnes, Physics: Frightful, but fun—Pupils’ and teachers’ views of physics and physics teaching, Sci. Educ. 88, 683 (2004).
  2. F. Örnek, W. R Robinson, and M. Haugan, What makes physics difficult, Int. J. Environ. Sci. Educ. 3, 30 (2008).
  3. I. A. Halloun and D. Hestenes, Common-sense concepts about motion, Am. J. Phys. 53, 1056 (1985).
  4. J. Clement, Students preconceptions in introductory mechanics, Am. J. Phys. 50, 66 (1982).
  5. H. S. Kizilcik, M. Aygün, E. Şahin, N. Önder-Çelikkanl𝚤, O. Türk, T. Taşk𝚤n, and B. Güneş, Possible misconceptions about solid friction, Phys. Rev. Phys. Educ. Res. 17, 023107 (2021).
  6. M. T. H. Chi, J. D. Slotta, and N. De Leeuw, From things to processes: A theory of conceptual change for learning science concepts, Learn. Instr. 4, 27 (1994).
  7. E. Kim and S.-J. Pak, Students do not overcome conceptual difficulties after solving 1000 traditional problems, Am. J. Phys. 70, 759 (2002).
  8. E. Mazur, Peer Instruction: A user’s manual, in Prentice Hall Series in Educational Innovation (Prentice Hall, Upper Saddle River, 1997), xv, p. 253.
  9. T. Vickrey, K. Rosploch, R. Rahmanian, M. Pilarz, M. Stains, and D. Barnard, Research-based implementation of peer instruction: A literature review, CBE Life Sci. Educ. 14, es3 (2015).
  10. C. H. Crouch and E. Mazur, Peer instruction: Ten years of experience and results, Am. J. Phys. 69, 970 (2001).
  11. C. Turpen and N. D. Finkelstein, The construction of different classroom norms during Peer Instruction: Students perceive differences, Phys. Rev. ST Phys. Educ. Res. 6, 020123 (2010).
  12. S. Freeman, S. L. Eddy, M. McDonough, M. K. Smith, N. Okoroafor, H. Jordt, and M. P. Wenderoth, Active learning increases student performance in science, engineering, and mathematics, Proc. Natl. Acad. Sci. U.S.A. 111, 8410 (2014).
  13. R. R. Hake, Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses, Am. J. Phys. 66, 64 (1998).
  14. L. Deslauriers, E. Schelew, and C. Wieman, Improved learning in a large-enrollment physics class, Science 332, 862 (2011).
  15. J. A. Schell and A. C. Butler, Insights from the science of learning can inform evidence-based implementation of peer instruction, Front. Educ. 3, 1 (2018).
  16. P. Strelan, A. Osborn, and E. Palmer, The flipped classroom: A meta-analysis of effects on student performance across disciplines and education levels, Educ. Res. Rev. 30, 100314 (2020).
  17. D. Kuhn, Thinking together and alone, Educ. Res. 44, 46 (2015).
  18. C. Howe, A. Tolmie, A. Thurston, K. Topping, D. Christie, K. Livingston, E. Jessiman, and C. Donaldson, Group work in elementary science: Towards organisational principles for supporting pupil learning, Learn. Instr. 17, 549 (2007).
  19. S. J. DeLozier and M. G. Rhodes, Flipped classrooms: A review of key ideas and recommendations for practice, Educ. Psychol. Rev. 29, 141 (2017).
  20. A. Lucas, Using peer instruction and i-clickers to enhance student participation in calculus, PRIMUS 19, 219 (2009).
  21. C. Wecker and F. Fischer, Where is the evidence? A meta-analysis on the role of argumentation for the acquisition of domain-specific knowledge in computer-supported collaborative learning, Comput. Educ. 75, 218 (2014).
  22. F. M. van Blankenstein, D. H. J. M. Dolmans, C. P. M. van der Vleuten, and H. G. Schmidt, Which cognitive processes support learning during small-group discussion? The role of providing explanations and listening to others, Instr. Sci. 39, 189 (2011).
  23. J. D. Karpicke and P. J. Grimaldi, Retrieval-based learning: A perspective for enhancing meaningful learning, Educ. Psychol. Rev. 24, 401 (2012).
  24. M. T. H. Chi et al., Self-explanations—How students study and use examples in learning to solve problems, Cogn. Sci. 13, 145 (1989).
  25. N. Kornell, R. A. Bjork, and M. A. Garcia, Why tests appear to prevent forgetting: A distribution-based bifurcation model, J. Mem. Lang. 65, 85 (2011).
  26. J. Samani and S. C. Pan, Interleaved practice enhances memory and problem-solving ability in undergraduate physics, npj Sci. Learn. 6, 32 (2021).
  27. J. R. Anderson, D. Bothell, M. D. Byrne, S. Douglass, C. Lebiere, and Y. Qin, An integrated theory of the mind, Psychol. Rev. 111, 1036 (2004).
  28. J. R. Anderson, J. M. Fincham, and S. Douglass, The role of examples and rules in the acquisition of a cognitive skill, J. Exp. Psychol. Learn. Mem. Cogn. 23, 932 (1997).
  29. J. R. Anderson, J. M. Fincham, and S. Douglass, Practice and retention: A unifying analysis, J. Exp. Psychol. Learn. Mem. Cogn. 25, 1120 (1999).
  30. J. R. Anderson and C. Lebiere, The Atomic Components of Thought (Lawrence Erlbaum Associates, Mahwah, NJ, 1998) xi, p. 490.
  31. J. R. Anderson and C. D. Schunn, Implications of the ACT-R learning theory: No magic bullets, in Advances in Instructional Psychology, Volume 5: Educational Design and Cognitive Science, edited by R. Glaser (Routledge, London, 2000), pp. 1–34.
  32. B. S. Stein, J. Littlefield, J. D. Bransford, and M. Persampieri, Elaboration and knowledge acquisition, Mem. Cogn. 12, 522 (1984).
  33. V. Gjerde, B. Holst, and S. D. Kolstø, Retrieval practice of a hierarchical principle structure in university introductory physics: Making stronger students, Phys. Rev. Phys. Educ. Res. 16, 013103 (2020).
  34. J. C. K. Chan, C. A. Meissner, and S. D. Davis, Retrieval potentiates new learning: A theoretical and meta-analytic review, Psychol. Bull. 144, 1111 (2018).
  35. C. A. Rowland, The effect of testing versus restudy on retention: A meta-analytic review of the testing effect, Psychol. Bull. 140, 1432 (2014).
  36. J. Dunlosky, K. A. Rawson, E. J. Marsh, M. J. Nathan, and D. T. Willingham, Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology, Psychol. Sci. Publ. Interest 14, 4 (2013).
  37. J. Anderson and L. Reder, An elaborative processing explanation of depth processing, in Levels of Processing in Human Memory, edited by L. S. Cermak and F. I. M. Craik (Lawrence Erlbaum Associates, Hillsdale, NJ, 1979).
  38. B. S. Stein and J. D. Bransford, Constraints on effective elaboration—Effects of precision and subject generation, J. Verb. Learn. Verb. Behav. 18, 769 (1979).
  39. J. D. Novak, Concept maps and Vee diagrams: Two metacognitive tools to facilitate meaningful learning, Instr. Sci. 19, 29 (1990).
  40. V. Gjerde, B. Holst, and S. D. Kolstø, Integrating effective learning strategies in basic physics lectures: A thematic analysis, Phys. Rev. Phys. Educ. Res. 17, 010124 (2021).
  41. V. Gjerde, Short introductory videos for elaborative encoding of physics principles (to be published).
  42. J. Lim and J. Park, Self-study enhances the learning effect of discussions, J. Learn. Sci. 32, 455 (2023).
  43. A. C. Butler, Repeated testing produces superior transfer of learning relative to repeated studying, J. Exp. Psychol. Learn. Mem. Cogn. 36, 1118 (2010).
  44. S. K. Carpenter, Testing enhances the transfer of learning, Curr. Dir. Psychol. Sci. 21, 279 (2012).
  45. T. Zu, J. Munsell, and N. S. Rebello, Comparing retrieval-based practice and peer instruction in physics learning, Phys. Rev. Phys. Educ. Res. 15, 010105 (2019).
  46. V. Gjerde, V. H. Paulsen, B. Holst, and S.  D. Kolstø, Problem solving in basic physics: Effective self-explanations based on four elements with support from retrieval practice, Phys. Rev. Phys. Educ. Res. 18, 010136 (2022).
  47. M. C. Lovett, L. Z. Daily, and L. M. Reder, A source activation theory of working memory: Cross-task prediction of performance in ACT-R, Cognit. Syst. Res. 1, 99 (2000).
  48. L. M. Reder, X. L. Liu, A. Keinath, and V. Popov, Building knowledge requires bricks, not sand: The critical role of familiar constituents in learning, Psychon. Bull. Rev. 23, 271 (2016).
  49. T. v. Gog, N. Rummel, and A. Renkl, Learning how to solve problems by studying examples, in The Cambridge Handbook of Cognition and Education (Cambridge University Press, New York, NY, 2019), pp. 183–208.
  50. N. A. Taatgen and F. J. Lee, Production compilation: A simple mechanism to model complex skill acquisition, Human Factors 45, 61 (2003).
  51. A. Renkl, Learning from worked-out examples: A study on individual differences, Cogn. Sci. 21, 1 (1997).
  52. M. T. H. Chi, Constructing self-explanations and scaffolded explanations in tutoring, Appl. Cogn. Psychol. 10, S33 (1996).
  53. N. M. Webb, Peer interaction and learning in small groups, Int. J. Educ. Res. 13, 21 (1989).
  54. M. K. Smith, W. B. Wood, W. K. Adams, C. Wieman, J. K. Knight, N. Guild, and T. T. Su, Why peer discussion improves student performance on in-class concept questions, Science 323, 122 (2009).
  55. J. Heller and F. Reif, Prescribing effective human problem-solving processes: Problem description in physics, Cognit. Instr. 1, 177 (1984).
  56. J. Larkin, The role of problem representation in physics, in Mental Models Conference (University of California, San Diego, 1981).
  57. J. P. Mestre, R. J. Dufresne, W. J. Gerace, P. T. Hardiman, and J. S. Touger, Promoting skilled problem-solving behavior among beginning physics students, J. Res. Sci. Teach. 30, 303 (1993).
  58. E. W. Burkholder, J  K. Miles, T. J. Layden, K. D. Wang, A. V. Fritz, and C. E. Wieman, Template for teaching and assessment of problem solving in introductory physics, Phys. Rev. Phys. Educ. Res. 16, 010123 (2020).
  59. J. R. Anderson and J. M. Fincham, Extending problem-solving procedures through reflection, Cogn. Psychol. 74, 1 (2014).
  60. J. R. Anderson, H. S. Lee, and J. M. Fincham, Discovering the structure of mathematical problem solving, NeuroImage 97, 163 (2014).
  61. J. D. Karpicke and M. A. Smith, Separate mnemonic effects of retrieval practice and elaborative encoding, J. Mem. Lang. 67, 17 (2012).
  62. A. Renkl and R. K. Atkinson, Structuring the transition from example study to problem solving in cognitive skill acquisition: A cognitive load perspective, Educ. Psychol. 38, 15 (2003).
  63. B. J. Brooks and M. D. Koretsky, The influence of group discussion on students’ responses and confidence during Peer Instruction, J. Chem. Educ. 88, 1477 (2011).
  64. N. Lasry et al., When talking is better than staying quiet, AIP Conf. Proc. 1179, 181 (2009).
  65. C. Singh, Impact of peer interaction on conceptual test performance, Am. J. Phys. 73, 446 (2005).
  66. J. K. Knight, S. B. Wise, and K. M. Southard, Understanding clicker discussions: Student reasoning and the impact of instructional cues, CBE Life Sci. Educ. 12, 645 (2013).
  67. C. Turpen and N. D. Finkelstein, Not all interactive engagement is the same: Variations in physics professors’ implementation of Peer Instruction, Phys. Rev. ST Phys. Educ. Res. 5, 020101 (2009).
  68. R. Wegerif, N. Mercer, and L. Dawes, From social interaction to individual reasoning: An empirical investigation of a possible socio-cultural model of cognitive development, Learn. Instr. 9, 493 (1999).
  69. V. Braun and V. Clarke, Using thematic analysis in psychology, Qual. Res. Psychol. 3, 77 (2006).
  70. QSR International, NVivo 12 Pro, 2018.
  71. V. Gjerde, Integrating cognitive learning strategies into physics instruction: Developing students’ approaches to physics and learning, Ph.D. thesis, Department of Physics and Technology, University of Bergen, Bergen, 2021.
  72. A. K. Wood, R. K. Galloway, J. Hardy, and C. M. Sinclair, Analyzing learning during Peer Instruction dialogues: A resource activation framework, Phys. Rev. ST Phys. Educ. Res. 10, 020107 (2014).
  73. J. Tuminaro and E. F. Redish, Elements of a cognitive model of physics problem solving: Epistemic games, Phys. Rev. ST Phys. Educ. Res. 3, 020101 (2007).
  74. N. Mercer, Words and Minds: How We Use Language to Think Together (Routledge, London, New York, 2000), xiii, p. 206.
  75. Y. S. Lincoln and E. G. Guba, Naturalistic Inquiry (Sage Publications, Beverly Hills, CA, 1985), p. 416.
  76. W. A. Firestone, Alternative arguments for generalizing from data as applied to qualitative research, Educ. Res. 22, 16 (1993).
  77. R. K. Yin, Case Study Research: Design and Methods (Sage Publications, London, 1989).
  78. K. VanLehn and R. M. Jones, What mediates the self-explanation effect? Knowledge gaps, schemas or analogies?, in Proceedings of the Fifteenth Annual Conference of the Cognitive Science Society (Erlbaum, Hillsdale, NJ, 1993).
  79. J. J. Williams and T. Lombrozo, Explanation and prior knowledge interact to guide learning, Cogn. Psychol. 66, 55 (2013).
  80. Fiorella S. Kuhlmann, Creating drawings enhances learning by teaching, J. Educ. Psychol. 112, 811 (2020).
  81. H. S. Lee, S. Betts, and J. R. Anderson, Embellishing problem-solving examples with deep structure information facilitates transfer, J. Exp. Educ. 85, 309 (2017).
  82. N. A. Taatgen et al., The acquisition of robust and flexible cognitive skills, J. Exp. Psychol. 137, 548 (2008).
  83. N. M. Webb, P. Ender, and S. Lewis, Problem-solving strategies and group processes in small-groups learning computer programming, Am. Educ. Res. J. 23, 243 (1986).
  84. T. M. Haladyna, S. M. Downing, and M. C. Rodriguez, A review of multiple-choice item-writing guidelines for classroom assessment, Appl. Meas. Educ. 15, 309 (2002).
  85. M. J. Rudolph et al., Best practices related to examination item construction and post-hoc review, Am. J. Pharm. Educ. 83, 1492 (2019).
  86. I. D. Beatty, W. J. Gerace, W. J. Leonard, and R. J. Dufresne, Designing effective questions for classroom response system teaching, Am. J. Phys. 74, 31 (2006).

Outline

Information

Phys. Rev. Phys. Educ. Res. 20, 010134– Published 3 May, 2024
  • Received 7 December 2023
  • Accepted 3 April 2024
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