INTERDISCIPLINARY JOURNAL OF ENVIRONMENTAL AND SCIENCE EDUCATION
Research Article
Jul 12, 2022 247 85

Metacognitive Regulation of Essentialism in the Teaching of Evolution

Gaston Perez 1 * ,
Alma Adrianna Gómez Galindo 2,
Leonardo González Galli 1 3
1 Instituto de Investigaciones CeFIEC, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, ARGENTINA2 Unidad Monterrey, Cinvestav, MEXICO3 Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, ARGENTINA* Corresponding Author
Interdisciplinary Journal of Environmental and Science Education, 2022, 18(4), e2295, https://doi.org/10.21601/ijese/12223
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ABSTRACT

Essentialism is a way of reasoning that implies assuming that the members of a group share an immutable essence, and that the variation among the members of the group is negligible. Although this way of reasoning is useful for people in their everyday lives, it may pose difficulties in the learning of scientific models, particularly those of evolutionary biology. Essentialism, understood as an epistemological obstacle, requires some didactic work encouraging the development of metacognitive vigilance, in other words, the awareness and regulation of this way of thinking. In this article, we will characterize the processes of metacognitive regulation of essentialism that took place during a didactic sequence to teach evolution. The sequence was implemented in a secondary school in Argentina with 80 students. We will present some of the possibilities and difficulties of carrying out metacognitive regulation of essentialism in biology classrooms. From the use of thematic analysis, we have found that students seem to regulate essentialism in an implicit way during discussions with their classmates, at both the individual and social levels. Moreover, in the case of evolution learning, we distinguished two types of specific regulations: the regulation of ‘typologism’ and that of ‘noise’. In this sense, we consider that essentialism is not regulated as a whole, but instead through some of its assumptions. This work will allow further thinking about the possibilities of promoting the metacognitive regulation of epistemological obstacles in biology classes.

KEYWORDS

essentialism metacognition epistemological obstacle metacognitive vigilance teaching of evolution

CITATION (APA)

Perez, G., Gómez Galindo, A. A., & González Galli, L. (2022). Metacognitive Regulation of Essentialism in the Teaching of Evolution. Interdisciplinary Journal of Environmental and Science Education, 18(4), e2295. https://doi.org/10.21601/ijese/12223
Harvard
Perez, G., Gómez Galindo, A. A., and González Galli, L. (2022). Metacognitive Regulation of Essentialism in the Teaching of Evolution. Interdisciplinary Journal of Environmental and Science Education, 18(4), e2295. https://doi.org/10.21601/ijese/12223
Vancouver
Perez G, Gómez Galindo AA, González Galli L. Metacognitive Regulation of Essentialism in the Teaching of Evolution. INTERDISCIP J ENV SCI ED. 2022;18(4):e2295. https://doi.org/10.21601/ijese/12223
AMA
Perez G, Gómez Galindo AA, González Galli L. Metacognitive Regulation of Essentialism in the Teaching of Evolution. INTERDISCIP J ENV SCI ED. 2022;18(4), e2295. https://doi.org/10.21601/ijese/12223
Chicago
Perez, Gaston, Alma Adrianna Gómez Galindo, and Leonardo González Galli. "Metacognitive Regulation of Essentialism in the Teaching of Evolution". Interdisciplinary Journal of Environmental and Science Education 2022 18 no. 4 (2022): e2295. https://doi.org/10.21601/ijese/12223
MLA
Perez, Gaston et al. "Metacognitive Regulation of Essentialism in the Teaching of Evolution". Interdisciplinary Journal of Environmental and Science Education, vol. 18, no. 4, 2022, e2295. https://doi.org/10.21601/ijese/12223

REFERENCES

  1. Anderson, D., & Nashon, S. (2006). Predators of knowledge construction: Interpreting students’ metacognition in an amusement park physics program. Science Education, 91(2), 298-320. https://doi.org/10.1002/sce.20176
  2. Anderson, D., Fisher, K., & Norman, G. (2002). Development and evaluation of the conceptual inventory of natural selection. Journal of Research in Science Teaching, 39(10), 952-978. https://doi.org/10.1002/tea.10053
  3. Astolfi, J. P. (1994). El trabajo didáctico de los obstáculos, en el corazón de los aprendizajes científicos [The educational work of obstacles, at the heart of scientific learning]. Enseñanza de las Ciencias [Science Education], 12(2), 206-216. https://doi.org/10.5565/rev/ensciencias.4442
  4. Astolfi, J. P. (1999). El tratamiento didáctico de los obstáculos epistemológicos [The didactic treatment of epistemological obstacles]. Revista Educación y Pedagogía [Education and Pedagogy Magazine], 11(25), 151-171.
  5. Astolfi, J. P. (2002). L’École pour apprendre [The school learns]. ESF.
  6. Astolfi, J., & Peterfalvi, B. (1997). Stratégies de travail des obstacles: dispositifs et resorts [Strategies to work on obstacles: devices and resorts]. Aster Recherchers en Didactique des Sciences Expérimentales [Aster Research in Didactics of Experimental Sciences], 25, 193-216. https://doi.org/10.4267/2042/8685
  7. Atran, S., Medin, D., & Ross, N. (2006). Thinking about biology: Modular constraints on categorization and reasoning in the everyday life of Americans, Maya, and scientists. In R. Viale, D. Andler, & L. Hirschfeld (Eds.), Biological and cultural bases of human inference (pp. 97-130). Psychology Press.
  8. Atran, S., Medin, D., Lynch, E., Vapnarsky, V., Ucan Ek, E., & Sousa, P. (2001). Folkbiology doesn’t come from folkpsychology: Evidence from Yukatek Maya in cross-cultural perspective. Journal of Cognition and Culture, 1(1), 3-42. https://doi.org/10.1163/156853701300063561
  9. Avargil, S., Lavi, R., & Dori, Y. (2018). Students’ metacognition and metacognitive strategies in science education. In Y. Dori, Z. Mevarech, & D. Baker (Eds.), Cognition, metacognition, and culture in STEM education (pp. 33-64). Springer. https://doi.org/10.1007/978-3-319-66659-4_3
  10. Borges, J. L. (1944). Ficciones [Fictions]. Emecé.
  11. Braun, V., & Clarke, V. (2013). Successful qualitative research: A practical guide for beginners. SAGE.
  12. Cho, M., Lankford, D., & Wescott, D. (2011). Exploring the relationships among epistemological beliefs, nature of science, and conceptual change in the learning of evolutionary theory. Evolution: Education and Outreach, 4, 313-322. https://doi.org/10.1007/s12052-011-0324-7
  13. Clement, J., & Rea-Ramirez, M. (2008). Model based learning and instruction in science. Springer. https://doi.org/10.1007/978-1-4020-6494-4
  14. Coley, J., & Tanner, K. (2012). Common origins of diverse misconceptions: Cognitive principles and the development of biology thinking. CBE—Life Sciences Education, 11, 209-215. https://doi.org/10.1187/cbe.12-06-0074
  15. Creswell, J. (2012). Educational research. Planning, conducting, and evaluating quantitative and qualitative research. Pearson.
  16. Dar-Nimrod, I., & Heine, S. (2011). Genetic essentialism: on the deceptive determinism of DNA. Psychological Bulletin, 137(5), 800-818.https://doi.org/10.1037/a0021860
  17. Darwin, C. (1859). On the origin of species by means of natural selection, or the preservation of favoured races in the struggle for life. John Murray. https://doi.org/10.5962/bhl.title.82303
  18. Dawkins, R. (2017). Science in the soul: Selected writings of a passionate rationalist. Bantam Press.
  19. Del Río, M., & Strasser, K. (2007). ¿Tienen los niños una teoría esencialista acerca de la pobreza? [Do children have an essentialist theory about poverty?] Psykhe, 16(2), 139-149. http://dx.doi.org/10.4067/S0718-22282007000200012
  20. Dennett, D. (1995). Darwin´s dangerous idea: Evolution and the meanings of life. Simon and Schuster.
  21. Donovan, B., & Nehm, R. (2020). Genetics and identity. Science & Education, 29, 1451-1458. https://doi.org/10.1007/s11191-020-00180-0
  22. Donovan, B., Stuhlsatz, M., Edelson, D., & Buck Bracey, Z. (2019). Gendered genetics: How reading about the genetic basis of sex differences in biology textbooks could affect beliefs associated with science gender disparities. Science Education, 103(4), 719-749. https://doi.org/10.1002/sce.21502
  23. Emmons, N., & Kelemen, D. (2015). Young children’s acceptance of within-species variation: Implications for essentialism and teaching evolution. Journal of Experimental Child Psychology, 139, 148-160. https://doi.org/10.1016/j.jecp.2015.05.011
  24. Evans, E. (2008). Conceptual change and evolutionary biology: A developmental analysis. In S. Vosniadou (Ed.), International handbook of research on conceptual change (pp. 263-294). Routledge.
  25. Flick, U. (2018). Designing qualitative research. SAGE.
  26. Futuyma, D. (2009). Evolution. Sinauer. https://doi.org/10.1016/B978-0-12-374144-8.00060-6
  27. Gaskins, I. & Elliot, T. (1991). Implementing cognitive strategy instruction across the school: The benchmark manual for teachers. Brookline Books.
  28. Gelman, S., & Legare, C. (2011). Concepts and folk theories. Annual review of anthropology, 40, 379-398. https://doi.org/10.1146/annurev-anthro-081309-145822
  29. Gelman, S., & Rhodes, M. (2012). Two-thousand years of stasis. How psychological essentialism impedes evolutionary understanding. In K. Rosengren, S. Brem, E. Evans, & G. Sinatra (Eds.), Evolution challenges. Integrating research and practice in teaching and learning about evolution (pp. 3-21). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199730421.003.0001
  30. Gelman, S., Coley, J., & Gottfried, G. (1994). Essentialist beliefs in children: The acquisition of concepts and theories. In L. Hirschfeld, & S. Gelman (Eds.), Mapping the mind. Domain specificity in cognition and culture (pp. 128-160). Cambridge University Press. https://doi.org/10.1017/CBO9780511752902.014
  31. Giere, R. (1999). Using models to represent reality. In L. Magnani, N. Nersessian, & P. Thagard (Eds), Model-based reasoning in scientific discovery (pp. 41-57). Springer. https://doi.org/10.1007/978-1-4615-4813-3_3
  32. Giere, R. (2004). How models are used to represent reality. Philosophy of Science, 71(5), 742-752. https://doi.org/10.1086/425063
  33. González Galli, L. (2011). Obstáculos para el aprendizaje del modelo de evolución por selección natural [Obstacles to learning the model of evolution by natural selection] [PhD thesis, Universidad de Buenos Aires].
  34. González Galli, L., & Meinardi, E. (2017). Obstáculos para el aprendizaje del modelo de evolución por elección natural en estudiantes universitarios de biología [Obstacles to learning the model of evolution by natural choice in university biology students]. Revista Eureka sobre Enseñanza y Divulgación de las Ciencias [Eureka Magazine on Teaching and Popularization of Sciences], 14(3), 535-549. https://doi.org/10.25267/Rev_Eureka_ensen_divulg_cienc.2017.v14.i3.03
  35. González Galli, L., Pérez, G., & Gómez Galindo, A. (2020). The self-regulation of teleological thinking in natural selection learning. Evo Edu Outreach, 13(6). https://doi.org/10.1186/s12052-020-00120-0
  36. González Galli, L., Pérez, G., Alegre, C., & Joelson, S. (2018). Explicaciones, concepciones y obstáculos sobre el origen de las especies en estudiantes de escuela secundaria de Argentina [Explanations, conceptions and obstacles about the origin of species in high school students from Argentina]. Ciência & Educação [Science and Education], 24(3), 741-758. https://doi.org/10.1590/1516-731320180030013
  37. Gregory, T. (2009). Understanding natural selection: essential concepts and common misconceptions. Evolution: Education and Outreach, 2(2), 156-175. https://doi.org/10.1007/s12052-009-0128-1
  38. Harms, U., & Reiss, M. (2019). Evolution education re-considered. Understanding what works. Springer. https://doi.org/10.1007/978-3-030-14698-6
  39. Hirschfeld, L. (1994). Is the acquisition of social categories based on domain-specific competence or on knowledge transfer? In L. Hirschfeld, & S. Gelman (Eds.), Mapping the mind. Domain specificity in cognition and culture (pp. 285-328). Cambridge University Press. https://doi.org/10.1017/CBO9780511752902.009
  40. Iiskala, T., Vauras, M., Lehtinen, E., & Salonen, P. (2011). Socially shared metacognition of dyads of pupils in collaborative mathematical problem-solving processes. Learning and Instruction, 21(3), 379-393. https://doi.org/10.1016/j.learninstruc.2010.05.002
  41. Inagaki, K., & Hatano, G. (2006). Young children’s conception of the biological world. Current Directions in Psychological Science, 15(4), 177-181. https://doi.org/10.1111%2Fj.1467-8721.2006.00431.x
  42. Janssen, J., Erkens, G., Kirschner, P., & Kanselaar, G. (2012). Task-related and social regulation during online collaborative learning. Metacognition and Learning, 7(1), 25-43. https://doi.org/10.1007/s11409-010-9061-5
  43. Jorba, J., & Sanmartí, N. (1996). Enseñar, aprender y evaluar: Un proceso de evaluación continua. Propuesta didáctica para las áreas de ciencias de la naturaleza y las matemáticas [Teaching, learning and evaluating: a process of continuous evaluation. Didactic proposal for the areas of natural sciences and mathematics]. Ministerio de Educación y Cultura.
  44. Kampourakis, K. (2014). Understanding evolution. Cambridge University Press. https://doi.org/10.1017/CBO9781139542357
  45. Levins, R., & Lewontin, R. (1985). The dialectical biologist. Harvard University Press.
  46. Malmberg, J., Järvelä, S., Järvenoja, H., & Panadero, E. (2015). Promoting socially shared regulation of learning in CSCL: Progress of socially shared regulation among high-and low-performing groups. Computers in Human Behavior, 52, 562-572. https://doi.org/10.1016/j.chb.2015.03.082
  47. Mayr, E. (1997). This is biology. The science of the living world. Harvard University Press.
  48. Mayr, E. (2004). What makes biology unique? Considerations on the autonomy of a scientific discipline. Cambridge University Press. https://doi.org/10.1017/CBO9780511617188
  49. Nehm, R., & Reilly, L. (2007). Biology majors’ knowledge and misconceptions of natural selection. BioScience, 57(3), 263-272. https://doi.org/10.1641/B570311
  50. Neuendorf, K. (2019). Content analysis and thematic analysis. In P. Brough (Ed.), Research methods for applied psychologists: Design, analysis and reporting (pp. 211-223). Routledge. https://doi.org/10.4324/9781315517971-21
  51. Passmore, C., Svoboda, J., & Giere, R. (2014). Models in science and in learning science: Focusing scientific practice on sense-making. In R. Matthews (Ed.), International handbook of research in history, philosophy and science teaching (pp. 1171-1202). Springer. https://doi.org/10.1007/978-94-007-7654-8_36
  52. Perez, G. (2021). La regulación metacognitiva de los obstáculos epistemológicos en la construcción de modelos de biología evolutiva en la escuela media [The metacognitive regulation of epistemological obstacles in the construction of evolutionary biology models in middle school] [PhD thesis, Universidad de Buenos Aires].
  53. Pérez, G., Gómez Galindo, A. A., & González Galli, L. (2018). Enseñanza de la evolución: Fundamentos para el diseño de una propuesta didáctica basada en la modelización y la metacognición sobre los obstáculos epistemológicos [Teaching of evolution: Foundations for the design of a didactic proposal based on modeling and metacognition about epistemological obstacles]. Revista Eureka sobre Enseñanza y Divulgación de las Ciencias [Eureka Magazine on Teaching and Popularization of Sciences], 15(2), 2102. https://doi.org/10.25267/Rev_Eureka_ensen_divulg_cienc.2018.v15.i2.2102
  54. Pérez, G., Gómez Galindo, A., & González Galli, L. (2021). La regulación de los obstáculos epistemológicos en la enseñanza y el aprendizaje de la evolución [The regulation of epistemological obstacles in the teaching and learning of evolution]. Enseñanza de las Ciencias [Science Education], 39(1), 27-44. https://doi.org/10.5565/rev/ensciencias.2968
  55. Peterfalvi, B. (1997). Enseignants et élèves face aux obstacles [Teachers and students facing obstacles]. Aster Recherchers en Didactique des Sciences Expérimentales [Aster Research in Didactics of Experimental Sciences], 25, 193-216. https://doi.org/10.4267/2042%2F8677
  56. Pinker, S. (2002). The blank slate: The modern denial of human nature. Viking Books.
  57. Pintrich, P., Wolters, C., & Baxter, G. (2000). Assessing metacognition and self-regulated learning. In G. Schraw, & J. Impara (Eds.), Issues in the measurement of metacognition (pp. 43-97). Buros Institute of Mental Measurements.
  58. Pozo, J. (2016) Aprender en tiempos revueltos. La nueva ciencia del aprendizaje [Learn in troubled times. The new science of learning]. Alianza.
  59. Ritchhart, R., Church, M., & Morrison, K. (2011). Making thinking visible: How to promote engagement, understanding, and independence for all learners. Jossey-Bass Ltd.
  60. Ronfard, S., Brown, S., Doncaster, E., & Kelemen, D. (2021). Inhibiting intuition: Scaffolding children’s theory construction about species evolution in the face of competing explanations. Cognition, 211, 104635. https://doi.org/10.1016/j.cognition.2021.104635
  61. Rosengren, K., Brem, S., Evans, E., & Sinatra, G. (2012). Evolution challenges: Integrating research and practice in teaching and learning about evolution. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199730421.001.0001
  62. Saab, N. (2012). Team regulation, regulation of social activities or co-regulation: Different labels for effective regulation of learning in CSCL. Metacognition and Learning, 7(1), 1-6. https://doi.org/10.1007/s11409-011-9085-5
  63. Saldaña, D., & Aguilera, A. (2003). La evaluación de los procesos metacognitivos: Estrategias y problemática actuales [The evaluation of metacognitive processes: Current strategies and problems]. Estudios de Psicología [Psychology Studies], 24(2), 189-204. https://doi.org/10.1174/021093903765762901
  64. Salomon, G. (1993). Distributed cognitions. Cambridge University Press.
  65. Samarapungavan, A., & Wiers, R. W. (1997). Children’s thoughts on the origin of species: A study of explanatory coherence. Cognitive Science, 21(2), 147-177. https://doi.org/10.1016/S0364-0213(99)80021-4
  66. Sawyer, K. (2006). The Cambridge handbook of the learning science. Cambridge University Press. https://doi.org/10.1017/CBO9780511816833
  67. Schraw, G., & Gutierrez, A. (2015). Metacognitive strategy instruction that highlights the role of monitoring and control processes. In A. Peña-Ayala (Ed.), Metacognition: Fundaments, applications, and trends. A profile of the current state-of-the-art (pp. 3-16). Springer. https://doi.org/10.1007/978-3-319-11062-2_1
  68. Shtulman, A., & Schulz, L. (2008). The relation between essentialist beliefs and evolutionary reasoning. Cognitive Science, 32(6), 1049-1062. https://doi.org/10.1080/03640210801897864

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