Advertisement

The Role of Inhibition in Conceptual Learning from Refutation and Standard Expository Texts

  • Lucia MasonEmail author
  • Sonia Zaccoletti
  • Barbara Carretti
  • Sara Scrimin
  • Irene-Anna N. Diakidoy
Article

Abstract

Text is the primary tool to learn disciplinary knowledge in school. Text-based learning is shaped by a complex interplay between the text and reader characteristics. This study examined the role of text structure and inhibition in conceptual learning about energy. Inhibition implies the ability to block dominant but inappropriate responses automatically activated. Eighty-five fourth and fifth graders were randomly assigned to the condition of standard expository text, or the condition of refutation text in a pre-test, post-test, and delayed post-test design. Findings revealed that students progressed from pre- to post-test and maintained the gained knowledge at delayed post-test regardless of text read. Moreover, only for refutation-text readers inhibition, as measured by response times, uniquely predicted conceptual learning at delayed post-test over and above reading comprehension, prior knowledge, and short-term conceptual learning. The study deepens our understanding of the refutation text effect by revealing its association with the ability to activate inhibitory control and suggesting a previously unexplored benefit of the refutation text for learning science concepts.

Keywords

Conceptual change Expository text Inhibition Refutation text Science learning 

Notes

Acknowledgements

The authors are very grateful to all the students involved in the study, their parents and teachers, and the school principals.

Supplementary material

10763_2017_9874_MOESM1_ESM.docx (14 kb)
ESM 1 (DOCX 14.4 kb)

References

  1. Ariasi, N., Hyönä, J., Kaakinen, J., & Mason, L. (2016). An eye-movement analysis of the refutation effect in reading science text. Journal of Computer Assisted Learning, 33, 202–221.  https://doi.org/10.1111/jcal.12151.CrossRefGoogle Scholar
  2. Ariasi, N., & Mason, L. (2011). Uncovering the effect of text structure in learning from a science text: An eye-tracking study. Instructional Science, 39, 581–601.  https://doi.org/10.1007/s11251-010-9142-5.
  3. Babai, R., & Amsterdamer, A. (2008). The persistence of solid and liquid naive conceptions: A reaction time study. Journal of Science Education and Technology, 17, 553–559.  https://doi.org/10.1007/s10956-008-9122-6.
  4. Babai, R., Eidelman, R., & Stavy, R. (2012). Preactivation of inhibitory control mechanisms hinders intuitive reasoning. International Journal of Science and Mathematics Education, 10, 763–775.  https://doi.org/10.1007/s10763-011-9287-y.
  5. Borella, E., Carretti, C., & Pelegrina, S. L. (2010). The specific role of inhibitory efficacy in good and poor comprehenders. Journal of Learning Disabilities, 43, 541–552.  https://doi.org/10.1177/0022219410371676.CrossRefGoogle Scholar
  6. Borella, E., Carretti, B., & Lanfranchi, S. (2013). Inhibitory mechanisms in Down syndrome: Is there a specific or general deficit? Research in Developmental Disabilities, 34, 65−71.  https://doi.org/10.1016/j.ridd.2012.07.017.
  7. Borella, E., & de Ribaupierre, A. (2014). The role of working memory, inhibition, and processing speed in text comprehension in children. Learning and Individual Differences, 34, 86–92.  https://doi.org/10.1016/j.lindif.2014.05.001.CrossRefGoogle Scholar
  8. Braasch, J. L. G., Goldman, S. R., & Wiley, J. (2013). The influences of text and reader characteristics on learning from refutations in science texts. Journal of Educational Psychology, 105, 561–578.  https://doi.org/10.1037/a0032627.CrossRefGoogle Scholar
  9. Brault-Foisy, L. M., Potvin, P., Riopel, M., & Masson, S. (2015). Is inhibition involved in overcoming a common physics misconception in mechanics? Trends in Neuroscience and Education, 4, 26–36.  https://doi.org/10.1016/j.tine.2015.03.001.CrossRefGoogle Scholar
  10. Broughton, S. H., Sinatra, G. M., & Reynolds, R. E. (2010). The nature of the refutation text effect: An investigation of attention allocation. Journal of Educational Research, 103, 407–423.  https://doi.org/10.1080/00220670903383101.CrossRefGoogle Scholar
  11. Carretti, B., Borella, E., Cornoldi, C., & De Beni, R. (2009). Role of working memory in explaining the performance of individuals with specific reading comprehension difficulties: A meta-analysis. Learning and Individual Differences, 19, 246–251.  https://doi.org/10.1016/j.lindif.2008.10.002.CrossRefGoogle Scholar
  12. Chi, M. T. H., Slotta, J. D., & de Leeuw, N. (1994). From things to processes: A theory of conceptual change for learning science concepts. Learning and Instruction, 4, 27–43.  https://doi.org/10.1016/0959-4752(94)90017-5.
  13. Cornoldi, C., & Colpo, G. (2011). Prove di lettura MT2 per la scuola elementare 2 [MT2 tests of reading comprehension for the elementary school]. Florence, Italy: Organizzazioni Speciali.Google Scholar
  14. Danielson, R. W., Sinatra, G. M., & Kendou, P. (2016). Augmenting the refutation text effect with analogies and graphics. Discourse Processes, 53, 392–414.  https://doi.org/10.1080/0163853X.2016.1166334.CrossRefGoogle Scholar
  15. Dempster, F. N. (1991). Inhibitory processes: A neglected dimension of intelligence. Intelligence, 15, 157–173.  https://doi.org/10.1016/0160-2896(91)90028-C.
  16. Diakidoy, I. N., Kendeou, P., & Ioannides, C. (2003). Reading about energy: The effects of text structure in science learning and conceptual change. Contemporary Educational Psychology, 28, 335–356.  https://doi.org/10.1016/S0361-476X(02)00039-5.
  17. Diakidoy, I. N., Mouskounti, T., Fella, A., & Ioannides, C. (2016). Comprehension processes and outcomes with refutation and expository texts and their contribution to learning. Learning and Instruction, 41, 60–69.  https://doi.org/10.1016/j.learninstruc.2015.10.002.CrossRefGoogle Scholar
  18. Diakidoy, I. N., Mouskounti, T., & Ioannides, C. (2011). Comprehension and learning from refutation and expository texts. Reading Research Quarterly, 46, 22–38.  https://doi.org/10.1598/RRQ.46.1.2.CrossRefGoogle Scholar
  19. Dole, J. A., & Sinatra, G. M. (1998). Reconceptualizing change in the cognitive construction of knowledge. Educational Psychologist, 33, 109–128.  https://doi.org/10.1080/00461520.1998.9653294.CrossRefGoogle Scholar
  20. Dunbar, K., Fugelsang, J., & Stein, C. (2007). Do naïve theories ever go away? Using brain and behavior to understand changes in concept. In M. C. Lovett & P. Shah (Eds.), Thinking with data: 33rd Carnegie symposium on cognition (pp. 193–206). Mahwah, NJ: Erlbaum.Google Scholar
  21. Friedman, N. P., & Miyake, A. (2004). The relations among inhibition and interference control functions: A latent-variable analysis. Journal of Experimental Psychology: General, 133, 101–135.  https://doi.org/10.1037/0096-3445.133.1.101.
  22. Goldberg, R. F., & Thompson-Schill, S. L. (2009). Developmental “roots” in mature biological knowledge. Psychological Science, 20, 480–487.  https://doi.org/10.1111/j.1467-9280.2009.02320.x.
  23. Guzzetti, B. J., Snyder, T. E., Glass, G. V., & Gamas, W. S. (1993). Promoting conceptual change in science: A comparative meta-analysis of instructional interventions from reading education and science education. Reading Research Quarterly, 28, 117–159.CrossRefGoogle Scholar
  24. Hynd, C. (2003). Conceptual change in response to persuasive messages. In G. M. Sinatra & P. R. Pintrich (Eds.), Intentional conceptual change (pp. 291–315). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  25. Kelemen, D., Rottman, J., & Seston, R. (2013). Professional physical scientists display tenacious teleological tendencies: Purpose-based reasoning as a cognitive default. Journal of Experimental Psychology: General, 142, 1074–1083.  https://doi.org/10.1037/a0030399.CrossRefGoogle Scholar
  26. Kendeou, P., & O’Brien, E. J. (2014). The Knowledge Revision Components (KReC) framework: Processes and mechanisms. In D. N. Rapp & J. L. G. Braasch (Eds.), Processing inaccurate information: Theoretical and applied perspectives from cognitive science and the educational sciences (pp. 353–377). Cambridge, MA: MIT Press.Google Scholar
  27. Kendeou, P., & van den Broek, P. (2007). The effects of prior knowledge and text structure on comprehension processes during reading of scientific texts. Memory and Cognition, 35, 1567–1577.  https://doi.org/10.3758/BF03193491.CrossRefGoogle Scholar
  28. Kindt, M., Bierman, D., & Brosschot, J. F. (1996). Stroop versus Stroop: Comparison of a card format and a single-trial format of the standard color-word Stroop task and the emotional Stroop task. Personality and Individual Differences, 21, 653–661.  https://doi.org/10.1016/0191-8869(96)00133-X.
  29. Ludwig, C., Borella, E., Tettamanti, M., & de Ribaupierre, A. (2010). Adult age differences in the Stroop-color test: A comparison between an item-by-item and a blocked version. Archives of Gerontology and Geriatrics, 51, 135–114.  https://doi.org/10.1016/j.archger.2009.09.040.CrossRefGoogle Scholar
  30. Marzocchi, G. M., Re, A. M., & Cornoldi, C. (2010). Batteria Italiana per l’ADHD [Italian battery for assessing ADHD]. Trento, Italy: Erickson.Google Scholar
  31. Mason, L., & Gava, M. (2007). Effects of epistemological beliefs and learning text structure on conceptual change. In S. Vosniadou, A. Baltas, & X. Vamvakoussi (Eds.), Reframing the conceptual change approach in learning and instruction (pp. 165–196). Oxford: Elsevier.Google Scholar
  32. Mason, L., Gava, M., & Boldrin, A. (2008). On warm conceptual change: The interplay of text, epistemological beliefs, and topic interest. Journal of Educational Psychology, 100, 291–309.  https://doi.org/10.1037/0022-0663.100.2.291.
  33. Masson, S., Potvin, P., Riopel, M., & Brault Foisy, L.-M. (2014). Differences in brain activation between novices and experts in science during a task involving a common misconception in electricity. Mind, Brain, and Education, 8, 44–55.  https://doi.org/10.1111/mbe.12043.CrossRefGoogle Scholar
  34. McNamara, D., & Kintsch, W. (1996). Learning from texts: Effects of prior knowledge and text coherence. Discourse Processes, 22, 247–288.  https://doi.org/10.1080/01638539609544975.CrossRefGoogle Scholar
  35. Mikkilä-Erdmann, M. (2001). Improving conceptual change concerning photosynthesis through text design. Learning and Instruction, 11, 241–257.  https://doi.org/10.1016/S0959-4752(00)00041-4.
  36. Nichelli, F., Scala, G., Vago, C., Riva, D., & Bulgheroni, S. (2005). Age related trends in Stroop and conflicting motor response task findings. Child Neuropsychology, 11, 431–443.  https://doi.org/10.1080/09297040590951569.CrossRefGoogle Scholar
  37. Nigg, J.T. (2000). On inhibition/disinhibition in developmental psychopathology: Views from cognitive and personality psychology and a working inhibition taxonomy. Psychological Bulletin, 126, 220–246.  https://doi.org/10.1037/0033-2909.126.2.220.
  38. Nunnally, J.C. (1978). Psychometric theory. New York, NY: McGraw Hill.Google Scholar
  39. Otero, Leon, J. A., & Graesser, A. C. (Eds.). (2002). The psychology of science text comprehension. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  40. Palladino, P., Cornoldi, C., De Beni, R., & Pazzaglia, F. (2001). Working memory and updating processes in reading comprehension. Memory & Cognition, 29, 344–354.  https://doi.org/10.3758/BF03194929.CrossRefGoogle Scholar
  41. Potvin, P., Masson, S., Lafortune, S., & Cyr, G. (2015). Persistence of the intuitive conception that heavier objects sink more: A reaction time study with different levels of interference. International Journal of Science and Mathematics Education, 13, 21–43.  https://doi.org/10.1007/s10763-014-9520-6.
  42. Qian, G., & Pan, J. (2002). A comparison of epistemological beliefs and learning from science text between American and Chinese high school students. In B. K. Hofer & P. R. Pintrich (Eds.), Personal epistemology. The psychology of beliefs about knowledge and knowing (pp. 365–385). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  43. Salo, R., Henik, A., & Robertson, L. C. (2001). Interpreting Stroop interference: An analysis of differences between task versions. Neuropsychology, 15, 462–471.  https://doi.org/10.1037/0894-4105.15.4.462.
  44. Shallice, T., Marzocchi, G. M., Coser, S., Del Savio, M., Meuter, R. F., & Rumiati, R. (2002). Executive function profile of children with attention deficit hyperactivity disorder. Developmental Neuropsychology, 21, 43–71.  https://doi.org/10.1207/S15326942DN2101_3.CrossRefGoogle Scholar
  45. Shtulman, A., & Valcarcel, J. (2012). Scientific knowledge suppresses but does not supplant earlier intuitions. Cognition, 124, 209–215.  https://doi.org/10.1016/j.cognition.2012.04.005.CrossRefGoogle Scholar
  46. Sinatra, G. M., & Broughton, S. W. (2011). Bridging reading comprehension and conceptual change in science education: The promise of refutation text. Reading Research Quarterly, 46, 374–393.  https://doi.org/10.1002/RRQ.005.CrossRefGoogle Scholar
  47. Tippett, C. D. (2010). Refutational text in science education. A review of two decades of research. International Journal of Science and Mathematics Education, 8, 951–970.  https://doi.org/10.1007/s10763-010-9203-x.
  48. van den Broek, P., & Kendeou, P. (2008). Cognitive processes in comprehension of science texts: The role of co-activation in confronting misconceptions. Applied Cognitive Psychology, 22, 335–351.  https://doi.org/10.1002/acp.1418.CrossRefGoogle Scholar
  49. Vosniadou, S. (1994). Capturing and modeling the process of conceptual change. Learning and Instruction, 4, 45–69.  https://doi.org/10.1016/0959-4752(94)90018-3.
  50. Vosniadou, S., Pnevmantikos, D., Makris, N., Ikospentaki, K., Lepenioti, D., Chountala, A., & Kyrianakis, G. (2015). Executive functions and conceptual change in science and mathematics learning. In R. Dale, C. Jennings, P. P. Maglio, T. Matlock, D. C. Noelle, A. Warlaumont, & J. Yoshimi (Eds.), Proceedings of the 37th annual meeting of the Cognitive Science Society: Mind, Technology, and Society. Pasadena, CA (pp. 2529–2534). Merced, CA: University of California.Google Scholar
  51. Wright, I., Waterman, M., Prescott, H., & Murdoch-Eaton, D. (2003). A new Stroop-like measure of inhibitory function development: Typical developmental trends. Journal of Child Psychology and Psychiatry, 44, 561–575.  https://doi.org/10.1111/1469-7610.00145.
  52. Zaitchik, D., Iqbal, Y., & Carey, S. (2014). The effect of executive function on biological reasoning in young children: An individual differences study. Child Development, 85, 160–175.  https://doi.org/10.1111/cdev.12145.CrossRefGoogle Scholar

Copyright information

© Ministry of Science and Technology, Taiwan 2018

Authors and Affiliations

  1. 1.Department of Developmental Psychology and SocializationUniversity of PaduaPaduaItaly
  2. 2.Department of General PsychologyUniversity of PaduaPaduaItaly
  3. 3.Department of PsychologyUniversity of CyprusNicosiaCyprus

Personalised recommendations