Session Information
08 SES 02 A, School Performance, Learning and Wellbeing
Paper Session
Contribution
Student’s well-being (SWB) is an important educational goal (e.g., Kanonire, Federiakin, & Uglanova, 2020; van Petegem, Aelterman, Rossell, & Creemers, 2006) and a prerequisite for academic success (e.g., Hascher & Hagenauer, 2011). However, despite agreement that SWB is a multidimensional construct, a clear and acknowledged definition is missing (Hascher, Morinaj, & Waber, 2018). Multi-component approaches to comprehensively measure SWB differ regarding selection of its components. However, most approaches refer to the concept of subjective well-being (Diener, 1984) which separates a cognitive and an affective component. Furthermore, social and physical aspects play a crucial role for SWB and are therefore often included to provide a differentiated view on SWB (e.g., Hascher, 2004; Tobia, Greco, Steca, & Marcchozi, 2019). To date, there are only few studies which empirically tested multidimensional models of SWB (e.g., Kanonire et al., 2019). Within the German national extension of the Progress in International Reading Literacy Study (PIRLS), a multi-component model of SWB was derived based on prior theoretical models. It contained five key dimensions: Cognitions towards school, positive and negative emotions concerning school, school-related physical well-being and social inclusion. Medium-sized correlations have been previously reported between these facets of SWB (cf. Hascher, 2004; Kanonire et al., 2020).
Due to the significance of SWB, it is important to identify variables that may influence it. Besides individual factors like gender (e.g., Hascher & Hagenauer, 2011) or academic achievement (e.g., Kleinkorres, Stang, & McElvany, 2020; Rodriguez et al., 2020), factors in students’ environment (e.g., school, family) can affect their well-being. A factor that can be located in the academic and in the extra-mural environment of children (e.g., Deb, Strodl, & Sun, 2015) and has been investigated only sparsely is performance pressure applied on students. Most studies focused on academic performance pressure and found negative associations with SWB (e.g., Hascher, 2004; Torsheim & Wold, 2001). Regarding parental performance pressure one study found positive associations with symptoms of anxiety and depression in Chinese adolescents (Quach, Epstein, Riley, Falconier, & Fang, 2015). Another study considered academic and parental pressure in separate models and found that only academic pressure was significantly negatively related to the mental health in 16- to 18-year-olds (Deb et al., 2015). The finding was robust, when the impact of gender was controlled for. Relations between performance pressure and well-being have been investigated primarily in secondary schools. In terms of the theory of socialization (e.g., Hurrelmann & Bauer, 2015), parents play the most important role for children in early childhood and are later replaced in influence by school and peer-group. It is, therefore, conceivable that performance pressure exerted by parents is more important for well-being of primary school students than pressure exerted by school. Moreover, in Germany, curricular differentiation (i.e., tracking) begins after fourth grade in most federal states, so parents might have a strong interest in ensuring that their children do well at the end of primary school in order to qualify for higher educational pathways. This could lead to high performance pressure applied by parents that is negatively perceived by students and thus affects their well-being.
Based on theory and previous findings, the following research questions were formulated:
1) Can the theoretically derived multicomponent model of SWB be empirically supported?
2a) Is students’ well-being negatively associated with academic and parental performance pressure?
2b) Are the results from 2a) robust when controlling for the influence of gender and academic achievement?
3a) When considered simultaneously, is the association of SWB with parental performance pressure more strongly pronounced than its relation with academic performance pressure?
3b) Are the results from 3a) robust when controlling for the influence of gender and academic achievement.
Method
The sample comprised 342 fourth graders (45.9% female) distributed among 17 classes from two different federal states in Germany who participated in the PIRLS 2020 field test. Students worked on reading tasks at the computer and filled out digital and paper-based questionnaires regarding socio-demographics and variables of interest. For the conceptualization of SWB, we used established instruments measuring satisfaction with school (1 item), joy at school (3 items), worries about school (4 items), physical complaints about school (4 items) and social integration in school (3 items). Furthermore, we used two largely parallelized scales to measure academic and parental performance pressure (4 items each). Reliabilities in terms of Cronbach’s α were acceptable to good (.71 - .83). For the measurement of academic achievement, we calculated WLE scores for the participants based on their performance on the reading tasks. The analyses were computed in R Studio with the package “lavaan” (Rosseel, 2012). In order to examine our first research question confirmatory factor analyses (CFA) were conducted. More precisely, a model with five first-order factors (i.e., the different components of SWB) was compared to a model in which these factors loaded on a second-order factor (global factor of SWB). To test the second and third research questions, structure equation models (SEM) were specified with regressions from SWB on performance pressure measures. As part of the third research question the strength of the relation between academic performance pressure and SWB was compared with the relation between parental performance pressure and SWB by restricting the regression coefficients to being equal in an additional model. This model was subsequently compared to the unrestricted model. Research questions 2b and 3b were examined by including academic achievement and gender as predictors of SWB. All psychological constructs were modeled as latent variables. Because the χ²-difference-test is vulnerable in case of large samples, we used ΔCFI for the comparison of nested models instead. We followed the suggestions by Cheung and Rensvold (2002) to prefer the restricted model if ΔCFI is equal to or greater than -.01. The hierarchical structure of the data was taken into account (ICCs within classes ranged from .00 to .11). For this purpose, the identification number of the students’ classes was considered in our analyses to compute cluster-robust standard errors of the parameters estimated in the SEMs (Rosseel, 2012). Finally, missing data was handled within the SEMs through full information maximum likelihood method (FIML).
Expected Outcomes
We found that the first-order model and the second-order model of SWB fit the data equally well (ΔCFI = -.006) and therefore preferred the less complex second-order model. Thus, concerning our first research question we found evidence that the theoretically derived multi-component model can be supported empirically. Furthermore, the regression analyses to investigate research questions 2a) and 2b) revealed an insignificant negative association between academic performance pressure and SWB (β = -.28, p = .086), but a significant negative association between parental performance pressure and SWB (β = -.44, p < .001). These findings were robust when gender and academic achievement were included in the models, even though the strengths of the relations decreased. Simultaneous consideration of the performance pressure measures regarding their relation with SWB (research question 3a)) revealed that only parental performance pressure was significantly associated with the criterion (β = -.37, p = .023). When gender and academic achievement were included in this model (research question 3b)), neither academic nor parental performance pressure were significantly associated with SWB anymore. The present study reveals new insights in the structure of SWB and its relation to different measures of performance pressure. Results concerning the important role parental performance pressure is playing for SWB in primary school can be interpreted in light of socialization theory (Hurrelmann & Bauer, 2015). Due to relevance of SWB, teachers’ and parents’ awareness for the well-being of school children should be raised, for example, by integrating the topic in teacher training. Moreover, both agents of socialization should become aware of the negative impact that the pressure they put on children in primary school can have on their well-being and academic achievement.
References
Cheung, G. W., & Rensvold, R. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9, 233-255. Deb, S., Strodl, E., & Sun, J. (2015). Academic stress, parental pressure, anxiety and mental health among Indian high school students. International Journal of Psychology and Behavioral Sciences, 5(1), 26-34. Diener, E. (1984). Subjective well-being. Psychological Bulletin, 95, 542-575. Hascher, T. (2004). Wohlbefinden in der Schule [Well-being in school]. Münster, Germany: Waxmann Verlag. Hascher, T., & Hagenauer, G. (2011). Schulisches Wohlbefinden im Jugendalter – Verläufe und Einflussfaktoren [Scholastic well-being during adolescence – time course and impact factors]. In A. Ittel, H. Merkens, & L. Stecher (Eds.), Jahrbuch Jugendforschung 2010 [Yearbook of adolescence 2010] (p. 15-45), Wiesbaden, Germany: VS Verlag. Hascher, T., Morinaj, J., & Waber, J. (2018). Schulisches Wohlbefinden: Eine Einführung in Konzept und Forschungsstand [Schoolish well-being: An introduction to concept and research]. In K., Rathmann & K. Hurrelmann (Eds.), Leistung und Wohlbefinden in der Schule: Herausforderung Inklusion [Performance and well-being at school: the challenge of inclusion] (pp. 66-82). Weinheim, Germany: Beltz. Hurrelmann, K., & Bauer, U. (2015). Einführung in die Sozialisationstheorie [Introduction to socialization theory] (10th Edition). Weinheim, Germany: Beltz Juventa. Kanonire, T., Federiakin, D. A., & Uglanova, I. L. (2020). Multicomponent framework for students’ subjective well-being in elementary school. School Psychology, 35, 321-331. Kleinkorres, R., Stang, J., & McElvany, N. (2020). A longitudinal analysis of reciprocal relations between students' well-being and academic achievement. Journal for educational research online, 12(2), 114-165. Quach, A. S., Epstein, N., Riley, P., Falconier, M., & Fang, X. (2015). Effects of parental warmth and academic pressure on anxiety and depression symptoms in Chinese adolescents. Journal of Child and Family Studies, 24(1), 106-116. Rodríguez, S., Regueiro, B., Piñeiro, I., Valle, A., Sánchez, B., Vieites, T., & Rodríguez-Llorente, C. (2020). Success in Mathematics and Academic Wellbeing in Primary-School Students. Sustainability, 12(9), 3796. Rosseel, Y. (2012). “lavaan: An R Package for Structural Equation Modeling.” Journal of Statistical Software, 48(2), 1-36. http://www.jstatsoft.org/v48/i02/. Tobia, V., Greco, A., Steca, P., & Marzocchi, G. M. (2019). Children’s wellbeing at school: a multi-dimensional and multi-informant approach. Journal of Happiness Studies, 20(3), 841-861. Torsheim, T., & Wold, B. (2001). School-related stress, support, and subjective health complaints among early adolescents: a multilevel approach. Journal of adolescence, 24(6), 70-713. van Petegem, K., Aelterman, A., Rossell, Y., & Creemers, B. (2006). Student perception as moderator for student well-being. Social Indicators Research, 83, 447-463.
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