Relationship of workload and academic motivation among high school students
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Published:
Mar 2, 2020
Keywords:
demand-resource model, high school, workload, academic motivation
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Abstract
Student workload is a popular area of research, which is frequently measured by class hours and quantity of school-related tasks. On the other hand, is it possible to grasp students’ psychological strain by using the demand-resource theory, which provides the theoretical background of the present study. This framework can describe the factors leading to heavy demands, such as negative emotions and mental workload. Moreover, it can distinguish those resources (support of teachers, control and personal development) which can counter balance the effects of demands.
329 high school students participated in our survey study, in which the School Demand-Resource Questionnaire and the Academic Motivation Scale were used. The results of correlation analysis showed that the resources are positively linked to both intrinsic and extrinsic motivation. Demands were linked out of the motivational types only to the amotivation scale. Workload, which was defined by the difference between demands and resources, was connected negatively to motivation.
The results of the research could contribute to the understanding of psychological effects, which students face in school. The results could imply making resources available could reduce subjective workload. For example possibility of personal development, autonomy and control during studying, and support of both teachers and parents could be useful methods.
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Jagodics, B., Varga, R., Szénási, S., Nagy, K., & Szabó, Éva. (2020). Relationship of workload and academic motivation among high school students. Iskolakultúra, 30(3), 35–49. https://doi.org/10.14232/ISKKULT.2020.3.35
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References
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Bakker, A. B., Hakanen, J. J., Demerouti, E., & Xanthopoulou, D. (2007). Job resources boost work engagement, particularly when job demands are high. Journal of Educational Psychology, 99(2), 274–284. https://doi.org/10.1037/0022-0663.99.2.274
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Bottiani, J. H., Duran, C. A. K., Pas, E. T., & Bradshaw, C. P. (2019). Teacher stress and burnout in urban middle schools: Associations with job demands, resources, and effective classroom practices. Journal of School Psychology, 77, 36–51. https://doi.org/10.1016/j.jsp.2019.10.002
Brookover, W. B., Schweitzer, J. H., Schneider, J. M., Beady, C. H., Flood, P. K., & Wisenbaker, J. M. (1978). Elementary School Social Climate and School Achievement. American Educational Research Journal, 15(2), 301–318. https://doi.org/10.3102/00028312015002301
Brouwers, A., Tomic, W., & Boluijt, H. (2011). Job demands, job control, social support and self-efficacy beliefs as determinants of burnout among physical education teachers. Europe’s Journal of Psychology, 7(1), 17–39. https://doi.org/10.5964/ejop.v7i1.103
Burnett, P. C., & Fanshawe, J. P. (1997). Measuring School-Related Stressors in Adolescents. Journal of Youth and Adolescence, 26(4), 415–428. https://doi.org/10.1023/A:1024529321194
Cilliers, J. R., Mostert, K., & Nel, J. A. (2017). Study demands, study resources and the role of personality characteristics in predicting the engagement of fist-year university students. South African Journal of Higher Education, 32(1). https://doi.org/10.20853/32-1-1575
Deci, E. L., & Ryan, R. M. (1985). Intrinsic Motivation and Self-Determination in Human Behavior. Springer US. https://doi.org/10.1007/978-1-4899-2271-7
Deci, E. L., & Ryan, R. M. (2000). The „What” and „Why” of Goal Pursuits: Human Needs and the Self-Determination of Behavior. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01
Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli, W. B. (2001). The job demands-resources model of burnout. Journal of Applied Psychology, 86(3), 499–512. https://doi.org/10.1037/0021-9010.86.3.499
Dicke, T., Stebner, F., Linninger, C., Kunter, M., & Leutner, D. (2018). A longitudinal study of teachers’ occupational well-being: Applying the job demands-resources model. Journal of Occupational Health Psychology, 23(2), 262–277. https://doi.org/10.1037/ocp0000070
Dobozy, G. (2015). A diákok mindennapjai, a tanulói munkaterhek vizsgálata az érettségi előtti és utáni 2-2 évfolyamon. Opus et Educatio, 2(3), 123–134.
Eccles, J. S., Wigfield, A., Midgley, C., Reuman, D., Iver, D. M., & Feldlaufer, H. (1993). Negative Effects of Traditional Middle Schools on Students’ Motivation. The Elementary School Journal, 93(5), 553–574. https://doi.org/10.1086/461740
Evers, W. J. G., Tomic, W., & Brouwers, A. (2004). Burnout among Teachers: Students’ and Teachers’ Perceptions Compared. School Psychology International, 25(2), 131–148. https://doi.org/10.1177/0143034304043670
Fiorilli, C., De Stasio, S., Di Chiacchio, C., Pepe, A., & Salmela-Aro, K. (2017). School burnout, depressive symptoms and engagement: Their combined effect on student achievement. International Journal of Educational Research, 84, 1–12. https://doi.org/10.1016/j.ijer.2017.04.001
Folkman, S., Lazarus, R. S., Gruen, R. J., & DeLongis, A. (1986). Appraisal, coping, health status, and psychological symptoms. Journal of Personality and Social Psychology, 50(3), 571–579. https://doi.org/10.1037/0022-3514.50.3.571
Freudenberger, H. J. (1974). Staff Burn-Out. Journal of Social Issues, 30(1), 159–165. https://doi.org/10.1111/j.1540-4560.1974.tb00706.x
Gaffney, H., Ttofi, M. M., & Farrington, D. P. (2019). Evaluating the effectiveness of school-bullying prevention programs: An updated meta-analytical review. Aggression and Violent Behavior, 45, 111–133. https://doi.org/10.1016/j.avb.2018.07.001
Gao, S., Yang, M., Wang, X., Min, W., & Rozelle, S. (2019). Peer relations and dropout behavior: Evidence from junior high school students in northwest rural China. International Journal of Educational Development, 65, 134–143. https://doi.org/10.1016/j.ijedudev.2018.04.001
Garon-Carrier, G., Boivin, M., Guay, F., Kovas, Y., Dionne, G., Lemelin, J.-P., Séguin, J. R., Vitaro, F., & Tremblay, R. E. (2016). Intrinsic Motivation and Achievement in Mathematics in Elementary School: A Longitudinal Investigation of Their Association. Child Development, 87(1), 165–175. https://doi.org/10.1111/cdev.12458
Ghasemi, A., & Zahediasl, S. (2012). Normality Tests for Statistical Analysis: A Guide for Non-Statisticians. International Journal of Endocrinology and Metabolism, 10(2), 486–489. https://doi.org/10.5812/ijem.3505
Henry, K. L., Knight, K. E., & Thornberry, T. P. (2012). School Disengagement as a Predictor of Dropout, Delinquency, and Problem Substance Use During Adolescence and Early Adulthood. Journal of Youth and Adolescence, 41(2), 156–166. https://doi.org/10.1007/s10964-011-9665-3
Hodge, B., Wright, B., & Bennett, P. (2019). Increasing student engagement and reducing exhaustion through the provision of demanding but well-resourced training. Journal of Further and Higher Education, 43(3), 406–417. https://doi.org/10.1080/0309877X.2017.1363385
Huebner, E. S., Gilman, R., & Laughlin, J. E. (1999). A Multimethod Investigation of the Multidimensionality of Children’s Well-Being Reports: Discriminant Validity of Life Satisfaction and Self-Esteem. Social Indicators Research, 46(1), 1–22. https://doi.org/10.1023/A:1006821510832
Inchley, J., Currie, D., Young, T., Samdal, O., Torsheim, T., Augustson, L., Mathison, F., Aleman-Diaz, A., Molcho, M., Weber, M., & Barnekow, V. (2016). Growing up unequal: Gender and socioeconomic differences in young people’s health and well-being. Health Behaviour in School-aged Children (HBSC) study: International report from the 2013/2014 survey. (Health Policy for Children and Adolescents, No. 7). WHO Regional Office for Europe. http://www.euro.who.int/en/publications/abstracts/growing-up-unequal.-hbsc-2016-study-20132014-survey
Kain, J., & Jex, S. (2010). Karasek’s (1979) job demands-control model: A summary of current issues and recommendations for future research. In P. L. Perrewé & D. C. Ganster (Szerk.), Research in Occupational Stress and Well-being (Köt. 8, o. 237–268). Emerald Group Publishing Limited. https://doi.org/10.1108/S1479-3555(2010)0000008009
Karasek, R. A. (1979). Job demand, job decision latitude, and mental strain: Implications for job redesign. Administrative Science Quarterly, 24, 285–309.
Kember, D. (2004). Interpreting student workload and the factors which shape students’ perceptions of their workload. Studies in Higher Education, 29(2), 165–184. https://doi.org/10.1080/0307507042000190778
Konu, A. (2002). Well-being in schools: A conceptual model. Health Promotion International, 17(1), 79–87. https://doi.org/10.1093/heapro/17.1.79
Konu, A. I., Lintonen, T. P., & Autio, V. J. (2002). Evaluation of Well-Being in Schools ? A Multilevel Analysis of General Subjective Well-Being. School Effectiveness and School Improvement, 13(2), 187–200. https://doi.org/10.1076/sesi.13.2.187.3432
Kyndt, E., Dochy, F., Struyven, K., & Cascallar, E. (2011). The direct and indirect effect of motivation for learning on students’ approaches to learning through the perceptions of workload and task complexity. Higher Education Research & Development, 30(2), 135–150. https://doi.org/10.1080/07294360.2010.501329
Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping (11. [print.]). Springer.
Lee, Y. J., & Anderman, E. M. (2020). Profiles of perfectionism and their relations to educational outcomes in college students: The moderating role of achievement goals. Learning and Individual Differences. https://doi.org/10.1016/j.lindif.2019.101813
Long, J. F., Monoi, S., Harper, B., Knoblauch, D., & Murphy, P. K. (2007). Academic Motivation and Achievement Among Urban Adolescents. Urban Education, 42(3), 196–222. https://doi.org/10.1177/0042085907300447
Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job Burnout. Annual Review of Psychology, 52(1), 397–422. https://doi.org/10.1146/annurev.psych.52.1.397
Mayer, J. (2003). A tanulók munkaterheiről. Új Pedagógiai Szemle, 53(7–8), 70–87.
Oktatáskutató és Fejlesztő Intézet. (2019a). Kerettanterv a szakközépiskolák 9-12. Évfolyamára. http://kerettanterv.ofi.hu/06_melleklet_9-12_szki/index_szakkozep.html
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