Academic grit modulates school performance evolution over timea latent transition analysis

  1. Álvaro Postigo 1
  2. Marcelino Cuesta 1
  3. Rubén Fernández-Alonso 2
  4. Eduardo García-Cueto 1
  5. José Muniz 3
  1. 1 Universidad de Oviedo
    info

    Universidad de Oviedo

    Oviedo, España

    ROR https://ror.org/006gksa02

  2. 2 Departmento de Educación del Gobierno del Principado de Asturias
  3. 3 Universidad Nebrija
    info

    Universidad Nebrija

    Madrid, España

    ROR https://ror.org/03tzyrt94

Revista:
Revista de psicodidáctica

ISSN: 1136-1034

Año de publicación: 2021

Volumen: 26

Número: 2

Páginas: 87-95

Tipo: Artículo

DOI: 10.1016/J.PSICOE.2021.03.001 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Revista de psicodidáctica

Objetivos de desarrollo sostenible

Resumen

La tenacidad académica, conocida como la pasión y la perseverancia por objetivos escolares a largo plazo, ha sido ampliamente estudiada en el contexto educativo. Sin embargo, pocos son los estudios que analizan esta variable como dominio específico y de manera longitudinal. El objetivo del presente trabajo es analizar en qué medida la tenacidad académica influye en el rendimiento académico evaluado longitudinalmente. Se utiliza una muestra de 4.853 estudiantes evaluados en tenacidad en dos momentos temporales, separados por cuatro años: cuarto curso de educación primaria (M = 9.9 años, DT = 0.41), y segundo curso de educación secundaria obligatoria (M = 13.87 años, DT = 0.82). También se evalúa el rendimiento académico a través de las notas escolares en Lengua Castellana y Matemáticas en tres momentos temporales. Se utiliza un Análisis de Clases Latentes para identificar grupos subyacentes, y un Análisis de Transiciones Latentes para estudiar las transiciones entre los grupos latentes en los diferentes momentos temporales. Además, se realiza un ANOVA de medidas repetidas para analizar la influencia de la tenacidad académica en el rendimiento académico. Se identifican tres grupos diferenciados en función del nivel de tenacidad académica: Grupo gritty, diligente y descuidado. Con el paso del tiempo (10 a 14 años), se observa una transición clara de los estudiantes hacia los grupos de menor nivel de tenacidad. El rendimiento académico disminuye entre los 10 y los 14 años, si bien no lo hace linealmente, viniendo modulado el cambio por el nivel de tenacidad académica. Promover la tenacidad académica desde la etapa primaria podría amortiguar el fracaso escolar en las etapas posteriores.

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Referencias bibliográficas

  • Abrahams, L., Pancorbo, G., Primi, R., Santos, D., Kyllonen, P., John, O. P., & De Fruyt, F.(2019). Social-emotional skill assessment in children and adolescents: Advances and challenges in personality, clinical, and educational contexts. Psychological Assessment, 31(4), 460–473. https://doi.org/10.1037/pas0000591
  • Akos, P., & Kretchmar, J. (2017). Investigating grit at a non-cognitive predictor of college success. The Review of Higher Education, 40(2), 163–186. https://doi.org/10.1353/rhe.2017.0000
  • Areepattamannil, S., & Khine, M. S. (2017). Evaluating the psychometric properties of the original Grit Scale using rasch analysis in an arab adolescent sample. Journal of Psychoeducational Assessment, 36(8), 856–862. https://doi.org/10.1177/0734282917719976
  • Bauman, Z. (2017). Liquid times. Living in an age of uncertainty. Tusquets. Calderón, C., Navarro, D., Lorenzo-Seva, U., &
  • Ferrando, P. (2019). Multidimensional or essentially unidimensional? A multi-faceted factor-analytic approach for assessing the dimensionality of tests and items. Psicothema, 31(4), 450–457. https://doi.org/10.7334/psicothema2019.153
  • Castejón, J. L., Gilar, R., Miñano, P., & González, M. (2016). Latent class cluster analysis in exploring different profiles of gifted and talented students. Learning and Individual Differences, 50, 166–174. https://doi.org/10.1016/j.lindif.2016.08.0
  • Chittum, J. R., Jones, B. D., & Carter, D. M. (2019). A person-centered investigation of patterns in college students’ perceptions of motivation in a course. Learning and Individual Differences, 69, 94–107. https://doi.org/10.1016/j.lindif.2018.11.007
  • Clark, K. N., & Malecki, C. K. (2019). Academic Grit Scale: Psychometric properties and associations with achievement and life satisfaction. Journal of School Psychology, 72, 49–66. https://doi.org/10.1016/j.jsp.2018.12.001
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Erlbaum.
  • Collins, L. M., & Lanza, S. T. (2010). Latent class and latent transition analysis. With applications in the social, behavioral, and health sciences. Wiley.
  • Cormier, D. L., Dunn, J. G. H., & Dunn, J. C. (2019). Examining the domain specificity of grit. Personality and Individual Differences, 139, 349–354. https://doi.org/10.1016/j.paid.2018.11.026
  • Credé, M., Tynan, M. C., & Harms, P. D. (2017). Much ado about grit: A meta-analytic synthesis of the grit literature. Journal of Personality and Social Psychology, 113(3), 492–511. https://doi.org/10.1037/pspp0000102
  • Duckworth, A. L. (2016). Grit – The power of passion and perseverance. Scribner.
  • Duckworth, A. L, & Quinn, P. D. (2009). Development and validation of the Short Grit Scale (GRIT-S). Journal of Personality Assessment, 91(2), 166–174. https://doi.org/10.1080/00223890802634290
  • Duckworth, A. L., & Yeager, D. S. (2015). Measurement matters: Assessing personal qualities other than cognitive ability for educational purposes. Educational Researcher, 44(4), 237–251. https://doi.org/10.3102/0013189X15584327
  • Duckworth, A. L., Peterson, C., Matthews, M. D., & Kelly, D. R. (2007). Grit: Perseverance and passion for long-term goals. Journal of Personality and Social Psychology, 92(6), 1087–1101. https://doi.org/10.1037/0022-3514.92.6.1087
  • Dumfart, D., & Neubauer, A. C. (2016). Conscientiousness is the most powerful noncognitive predictor of school achievement in adolescents. Journal of Individual Differences, 37(1), 8–15. https://doi.org/10.1027/1614-0001/a000182
  • Dweck, C. (2012). Mindset: Changing the way you think to fulfil your potential. Random House.
  • Eurydice. (2018). Home education policies in europe: Primary and lower secondary education. Eurydice report. Publications Office of the European Union. https://doi.org/10.2797/04352
  • Farrington, C. A., Roderick, M., Allensworth, E., Nagaoka, J., Keyes, T. S., Johnson, D. W., & Beechum, N. O. (2012). Teaching adolescents to become learners. The role of noncognitive factors in shaping school performance: A critical literature review. University of Chicago Consortium on Chicago School Research.
  • Flunger, B., Trautwein, U., Nagengast, B., Lüdtke, O., Niggli, A., & Schnyder, I. (2017). A person-centered approach to homework behavior: Students’ characteristics predict their homework learning type. Contemporary Educational Psychology, 48, 1–15. https://doi.org/10.1016/j.cedpsych.2016.07.002
  • Fong, C. J., & Kim, Y. W. (2019). A clash of constructs? Re-examining grit in light of academic buoyancy and future time perspective. Current Psychology, https://doi.org/10.1007/s12144-018-0120-4. Advance online publication
  • García, E. (2014). The need to address noncognitive skill in the education policy agenda (EPI Briefing Paper No. 386). Economic Policy Institute.
  • García-Crespo, F. J., Fernández-Alonso, R., & Muñiz, J. (2019). Resilient and low performer students: Personal and family determinants in European countries. Psicothema, 31(4), 363–375. https://doi.org/10.7334/psicothema2019.245
  • Gillet, N., Morin, A. J., & Reeve, J. (2017). Stability, change, and implications of students’ motivation profiles: A latent transition analysis. Contemporary Educational Psychology, 51, 222–239. https://doi.org/10.1016/j.cedpsych.2017.08.006
  • González, O., Canning, J. R., Smyth, H., & MacKinnon, D. P. (2020). A psychometric evaluation of the Short Grit Scale. European Journal of Psychological Assessment, 36, 646–657. https://doi.org/10.1027/1015-5759/a000535 Government of the Principality of Asturias (2018). https://www.educastur.es/-/evaluacion-de-diagnostico-educacion-primaria-y-eso-2018-2019
  • Grunschel, C., Patrzek, J., & Fries, S. (2013). Exploring different types of aca-demic delayers: A latent profile analysis. Learning and Individual Differences, 23, 225–233. https://doi.org/10.1016/j.lindif.2012.09.014
  • Heckman, J. J., & Kautz, T. (2012). Hard evidence on soft skills. Labour Economics, 19, 451–464. https://doi.org/10.1016/j.labeco.2012.05.014
  • Howard, M. C., & Hoffman, M. E. (2018). Variable-centered, person-centered, and person-specific approaches: Where theory meets the method. Organizational Research Methods, 21(4), 846–876. https://doi.org/10.1177/109442811774402
  • IBM Corp. (2016). IBM SPSS statistics for windows, version 24.0 [Computer software]. Jiang, W., Xiao, Z., Liu, Y., Guo, K., Jiang,
  • J., & Du, X. (2019). Reciprocal relations between grit and academic achievement: A longitudinal study. Learning and Individual Differences, 71, 13–22. https://doi.org/10.1016/j.lindif.2019.02.004
  • Kirchgasler, C. (2018). True grit? Making a scientific object and pedagogical tool. American Educational Research Journal, 55(4), 693–720. https://doi.org/10.3102/0002831217752244
  • Lanza, S. T., & Cooper, B. R. (2016). Latent class analysis for developmental research. Child Development Perspectives, 10, 59–64. https://doi.org/10.1111/cdep.12163
  • Lanza, S. T., Patrick, M. E., & Maggs, J. L. (2010). Latent transition analysis: Benefits of a latent variable approach to modeling transitions in substance use. Journal of Drug Issues, 40(1), 93–120. https://doi.org/10.1177/002204261004000106
  • Meyers, L. S., Gamst, G., & Guarino, A. J. (2016). Applied multivariate research: Design and interpretation (3rd ed.). Sage Publications.
  • Morales-Vives, F., Camps, E., & Due ̃nas, J. M. (2020). Predicting academic achievement in adolescents: The role of maturity, intelligence and personality. Psicothema, 32(1), 84–91. https://doi.org/10.7334/psicothema2019.262
  • Muthén, L. K., & Muthén, B. O. (2017). Mplus user’s guide (8th edn.). Muthén y Muthén.
  • OECD. (2013). Programme International for Student Assessment (PISA) 2012. Assessment and analytical framework: Mathematics, reading, science, problem solving and financial literacy. OECD Publishing. https://doi.org/10.1787/9789264190511-e
  • OECD. (2016). Programme International for Student Assessment (PISA) 2015. Assessment and analytical framework: Science, reading, mathematic and financial literacy. OECD Publishing. https://doi.org/10.1787/9789264255425-en
  • OECD. (2019a). OECD skills strategy 2019: Skills to shape a better future. OECD Publishing. https://doi.org/10.1787/9789264313835-en
  • OECD. (2019b). Programme International for Student Assessment (PISA) 2018. Assessment and analytical framework. OECD Publishing. https://doi.org/10.1787/b25efab8-en
  • Park, D., Yu, A., Baelen, R. N., Tsukayama, E., & Duckworth, A. L. (2018). Fostering grit: Perceived school goal-structure predicts growth in grit and grades. Contemporary Educational Psychology, 55, 120–128. https://doi.org/10.1016/j.cedpsych.2018.09.007
  • Pellegrino, J., & Hilton, M. L. (2012). Education for life and work. Transferable knowledge and skills for the 21st Century. National Research Council.
  • Peña, P. A., & Duckworth, A. L. (2018). Economics of education review the effects of relative and absolute age in the measurement of grit from 9th to 12th grade. Economics of Education Review, 66, 183–190. https://doi.org/10.1016/j.econedurev.2018.08.009
  • Postigo, Á., Cuesta, M., Fernández-Alonso, R., García-Cueto, E., & Muñiz, J. (2021). Temporal stability of grit and school performance in adolescents: A longitudinal perspective. Psicología Educativa, 27(1), 77–84. https://doi.org/10.5093/psed2021a4
  • Postigo, Á., Cuesta, M., García-Cueto, E., Menéndez-Aller, Á., González-Nuevo, C., & Muñiz, J. (2020). Grit assessment: Is one dimension enough? Journal of Personality Assessment, https://doi.org/10.1080/00223891.2020.1848853. Advance online publication
  • Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of university students’ academic performance: A systematic review and meta-analysis. Psychological Bulletin, 138(2), 353–387. https://doi.org/10.1037/a0026838
  • Robbins, S. B., Lauver, K., Le, H., Davis, D., Langley, R., & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological Bulletin, 130(2), 261–288. https://doi.org/10.1037/0033-2909.130.2.261
  • Schmidt, F. T. C., Lechner, C. M., & Danner, D. (2020). New wine in an old bottle? A facet-level perspective on the added value of grit over BFI–2 conscientiousness. PLoS One, 15(2), Article e0228969 https://doi.org/10.1371/journal.pone.0228969
  • Smithers, L. G., Sawyer, A. C. P., Chittleborough, C. R., Davies, N. M., Smith, G. D., & Lynch, J. W. (2018). A systematic review and meta-analysi of effects of early life non-cognitive skills on academic, psychosocial, cognitive and health outcomes. Nature Human Behaviour, 2, 867–880. https://doi.org/10.1038/s41562-018-0461-x
  • Steinmayr, R., Weidinger, A. F., & Wigfield, A. (2018). Does students’ grit predict their school achievement above and beyond their personality, motivation, and engagement? Contemporary Educational Psychology, 53, 106–122. https://doi.org/10.1016/j.cedpsych.2018.02.004
  • Tang, X., Wang, M., Guo, J., & Salmela-Aro, K. (2019). Building grit: The longitudinal pathways between mindset, commitment, grit, and academic outcomes. Journal of Youth and Adolescence, 48, 850–863. https://doi.org/10.1007/s10964-019-00998-0
  • Tang, X., Wang, M. T., Parada, F., & Salmela-Aro, K. (2021). Putting the goal back intogrit: Academic goal commitment, grit, and academic achievement. Journal of Youth and Adolescence, 50, 470–484. https://doi.org/10.1007/s10964-020-01348-1
  • Usher, E. L., Li, C. R., Butz, A. R., & Rojas, J. P. (2019). Perseverant grit and self-efficacy: Are both essential for children’s academic success? Journal of Educational Psychology, 111(5), 877–902. https://doi.org/10.1037/edu0000324
  • Vermunt, J. K., & Magidson, J. (2002). Latent class cluster analysis. In J. Hagenaars, & A. McCutcheon (Eds.), Applied latent class analysis (pp. 89–106). Cambridge University Press.
  • Vigil-Colet, A., Navarro-González, D., & Morales-Vives, F. (2020). To reverse or to not reverse Likert-type items: That is the question. Psicothema, 32(1), 108–114. https://doi.org/10.7334/psicothema2019.286
  • West, M. R., Kraft, M. A., Finn, A. S., Martin, R. E., Duckworth, A. L., Gabrieli, C. F., & Gabrieli, J. D. (2016). Promise and paradox: Measuring students’ non-cognitive skills and the impact of schooling. Education Evaluation and Policy Analysis, 38(1), 148–170. https://doi.org/10.3102/0162373715597298
  • Yeager, D. S., & Dweck, C. (2012). Mindsets that promote resilience: When students believe that personal characteristics can be developed. Educational Psychologist, 47(4), 302–314. https://doi.org/10.1080/00461520.2012.722805
  • Yeager, D. S., Romero, C., Paunesku, D., Hulleman, C. S., Schneider, B., Hinojosa, C., O’Brien, J., Flint, K., Roberts, A., Trott, J., Greene, D., Walton, G. M., & Dweck, C. (2016). Using design thinking to improve psychological interventions: The case of the growth mindset during the transition to high school. Journal of Educational Psychology, 108(3), 374–391