Intrinsic motivation and perceived utility as predictors of student homework engagement

  1. Susana Rodríguez Martínez 2
  2. Isabel Piñeiro Aguín 2
  3. Bibiana Regueiro Fernández 1
  4. Iris Estévez Blanco 2
  1. 1 Universidad Internacional de La Rioja
    info

    Universidad Internacional de La Rioja

    Logroño, España

    ROR https://ror.org/029gnnp81

  2. 2 Universidade da Coruña
    info

    Universidade da Coruña

    La Coruña, España

    ROR https://ror.org/01qckj285

Zeitschrift:
Revista de psicodidáctica

ISSN: 1136-1034

Datum der Publikation: 2020

Ausgabe: 25

Nummer: 2

Art: Artikel

DOI: 10.1016/J.PSICOD.2019.11.001 DIALNET GOOGLE SCHOLAR lock_openOpen Access editor

Andere Publikationen in: Revista de psicodidáctica

Ziele für nachhaltige Entwicklung

Zusammenfassung

The value students place on tasks, including utility, underlies their choices and the extent of their engagement, effort and persistence in learning activities, and ultimately explains academic achievement. This study attempts to verify how far the value students place on homework and their perceptions of its utility can be significant predictors of their behavioural engagement. With a sample of 730 secondary school students, via path analysis, the results generally confirm the hypothesis underlying the model. Intrinsic motivation and the perceived utility of homework were significantly and positively associated with student engagement with them, and this engagement was also positively related to academic achievement. The amount of variance in academic achievement that is explained by the five homework-related variables was only 8.6%. The main contribution of the study is that, when students are interested in working on homework and believe that it is useful for their learning, they are more involved in the homework. The purpose of learning and the perception of utility become explanatory factors for the level of students’ engagement with homework.

Informationen zur Finanzierung

Este trabajo se ha desarrollado gracias a la financiación de los proyectos de investigación EDU2013-44062-P (MINECO) y EDU2017-82984-P (MEIC).

Geldgeber

  • MINECO Spain
    • EDU2013-44062-P
  • MEIC
    • EDU2017-82984-P

Bibliographische Referenzen

  • Arbuckle, J. L. (2013). IBM SPSS AMOS 22 users’ guide. Armonk, NY: IBM Corp.
  • Christenson, S. L., Reschly, A. L., y Wylie, C. (2012). Handbook of research on student engagement. New York, NY: Springer Science + Business Media.
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2. a ed.). Hillsdale, NJ: Erlbaum.
  • Cooper, H., Robinson, J. C., y Patall, E. A. (2006). Does homework improve academic achievement? A synthesis of research, 1987-2003. Review of Educational Research, 76(1), 1–62. http://dx.doi.org/10.3102/00346543076001001
  • Cooper, H., Steenbergen-Hu, S., y Dent, A. L. (2012). Homework. En K. R. Harris, S. Graham, y T. Urdan (Eds.), Educational psychology handbook, Vol. 3: Application to learning and teaching (pp. 475–495). Washington, DC: American Psychological Association. http://dx.doi.org/10.1037/13275-019
  • Dettmers, S., Lüdtke, O., Trautwein, U., Kunter, M., y Baumert, J. (2010). Homework works if homework quality is high: Using multilevel modeling to predict the development of achievement in mathematics. Journal of Educational Psychology, 102(2), 467–482. http://dx.doi.org/10.1037/a0018453
  • Fan, H., Xu, J., Cai, Z., He, J., y Fan, X. (2017). Homework and students’ achievement in math and science: A 30-year meta-analysis, 1986-2015. Educational Research Review, 20, 35–54. http://dx.doi.org/10.1016/j.edurev.2016.11.003
  • Fernández-Alonso, R., Suárez-Álvarez, J., y Mu ̃niz, J. (2015). Adolescents’ homework performance in mathematics and science: Personal factors and teaching practices. Journal of Educational Psychology, 107(4), 1075–1085. http://dx.doi.org/10.1037/edu0000032
  • Hu, L., y Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55.
  • INE. (2016). Encuesta de condiciones de vida 2016. Madrid: Instituto Nacional de Estadística.
  • Ladd, G. W., y Dinella, L. M. (2009). Continuity and change in early school engagement: Predictive of children’s achievement trajectories from first to eighth grade? Journal of Educational Psychology, 101, 190–206. http://dx.doi.org/10.1037/a0013153
  • Lenhard, W., y Lenhard, A. (2016). Calculation of effect sizes. Psychometrica, http://dx.doi.org/10.13140/RG.2.2.17823.92329. Recuperado de https://www.psychometrica.de/effect size.html
  • Murillo, F. J., y Martínez-Garrido, C. (2014). Homework and primary-school students’ academic achievement in Latin America. International Review of Education, 60(5), 661–681. http://dx.doi.org/10.1007/s11159-014-9440-2
  • Núñez, J. C., Suárez, N., Cerezo, R., González-Pienda, J., Rosário, P., Mourão, R., y Valle, A. (2015). Homework and academic achievement across Spanish Compulsory Education. Educational Psychology, 35(6), 726–746. http://dx.doi.org/10.1080/01443410.2013.817537
  • Núñez, J. C., Suárez, N., Rosário, P., Vallejo, G., Cerezo, R., y Valle, A. (2015). Teachers’ feedback on homework, homework-related behaviors and academic achievement. Journal of Educational Research, 118(3), 204–216. http://dx.doi.org/10.1080/00220671.2013.878298
  • Núñez, J. C., Tuero, E., Vallejo, G., Rosário, P., y Valle, A. (2014). Variables del estudiante, del profesor y del contexto en la predicción del rendimiento académico en Biología: análisis desde una perspectiva multinivel. Revista de Psicodidáctica, 19(1), 145–172. http://dx.doi.org/10.1387/RevPsicodidact.7127
  • OCDE (2014), Does homework perpetuate inequities in education?, PISA in Focus, 46, OECD Publishing, Paris, https://doi.org/10.1787/5jxrhqhtx2xt-en.
  • Pan, I., Regueiro, B., Ponte, B., Rodríguez, S., Pi ̃neiro, I., y Valle, A. (2013). Motivación, implicación en los deberes escolares y rendimiento académico. Aula Abierta, 41(3), 13–22.
  • Regueiro, B., Suárez, N., Estévez, I., Rodríguez, S., Pi ̃neiro, I., y Valle, A. (2018). Deberes escolares y rendimiento académico: un estudio comparativo entre el alumnado inmigrante y nativo. Journal of Psychology and Education, 13(2), 92–98. http://dx.doi.org/10.23923/rpye2018.01.160
  • Regueiro, B., Suárez, N., Valle, A., Nú ̃nez, J., y Rosário, P. (2015). La motivación e implicación en los deberes escolares a lo largo de la escolaridad obligatoria. Revista de Psicodidáctica, 20(1), 47–63. http://dx.doi.org/10.1387/RevPsicodidact.12641
  • Su, A. Y. S., Huang, C. S. J., Yang, S. J. H., Ding, T. J., y Hsieh, Y. Z. (2015). Effects of annotations and homework on learning achievement: An empirical study of Scratch programming pedagogy. Educational Technology & Society, 18(4), 331–343.
  • Suárez, N., Regueiro, B., Estévez, I., Ferradás, M. M., Guisande, M. A., y Rodríguez, S. (2019). Individual precursors of student homework behavioral engagement: The role of intrinsic motivation, perceived homework utility and homework attitude. Frontiers in Psychology, 10, 941. http://dx.doi.org/10.3389/fpsyg.2019.00941
  • Trautwein, U. (2007). The homework-achievement relation reconsidered: Differentiating homework time, homework frequency, and homework effort. Learning and Instruction, 17(3), 372–388. http://dx.doi.org/10.1016/j.learninstruc.2007.02.009
  • Trautwein, U., Lüdtke, O., Nagy, N., Lenski, A., Niggli, A., y Schnyder, I. (2015). Using individual interest and conscientiousness to predict academic effort: Additive, synergistic, or compensatory effects? Journal of Personality and Social Psychology, 109, 142–162. http://dx.doi.org/10.1037/pspp0000034
  • Trautwein, U., Lüdtke, O., Schnyder, I., y Niggli, A. (2006). Predicting homework effort: Support for a domain-specific, multilevel homework model. Journal of Educational Psychology, 98(2), 438–456. http://dx.doi.org/10.1037/0022-0663.98.2.438
  • Trautwein, U., Schnyder, I., Niggli, A., Neumann, M., y Lüdtke, O. (2009). Chameleon effects in homework research: The homework-achievement association depends on the measures used and the level of analysis chosen. Contemporary Educational Psychology, 34, 77–88. http://dx.doi.org/10.1016/j.cedpsych.2008.09.001
  • Trautwein, U., y Köller, O. (2003). The relationship between homework and achievement—still much of a mystery. Educational Psychology Review, 15(2), 115–145. http://dx.doi.org/10.1023/A:1023460414243
  • Valle, A., Regueiro, B., Núñez, J. C., Rodríguez, S., Piñeiro, I., y Rosário, P. (2016). Academic goals, student homework engagement, and academic achievement in elementary school. Frontiers in Psychology, 7, 463. http://dx.doi.org/10.3389/fpsyg.2016.00463
  • Xu, J. (2010). Predicting homework time management at the secondary school level: A multilevel analysis. Learning and Individual Differences, 20(1), 34–39. http://dx.doi.org/10.1016/j.lindif.2009.11.001
  • Xu, J., Du, J., y Fan, X. (2017). Self-regulation of mathematics homework behavior: An empirical investigation. The Journal of Educational Research, 110(5), 467–477. http://dx.doi.org/10.1080/00220671.2015.1125837
  • Xu, J., y Yuan, R. (2003). Doing homework: Listening to students’, parents’, and teachers’ voices in one urban middle school community. School Community Journal,13, 25–44.
  • Xu, J., Yuan, R., Xu, B., y Xu, M. (2014). Modeling students’ time management in math homework. Learning and Individual Differences, 34, 33–42. http://dx.doi.org/10.1016/j.lindif.2014.05.011