02 SES 14 A, Learning and Working Environments
Academic effort is known to be an antecedent of academic achievement in both school (Trautwein et al., 2009) and vocational education (Schafer, 2018). Kreutzmann, Zander and Hannover (2014) report positive correlations between effort and goal orientation, academic self-efficacy as well as the joy of learning and negative correlations with fear of failure. Fostering students' academic effort can therefore be seen as a necessary aspect of schools, training companies and other teaching facilities.
In Switzerland, about two thirds of adolescents take up an apprenticeship after completing compulsory school after 9th grade. Others choose the general educational path. After the transition to VET, their learning motivation and academic effort often increases (Neuenschwander et al., 2012). Little is known, however, about the role of learning environment and its perception by students in shaping the change in effort during this transition. This begs the question how effort is predicted after the transition from school to upper secondary education. In this paper, it is analyzed in what extent perceptions of learning environments and competence-related beliefs predict adolescents' effort in three different educational contexts: training companies, vocational school in dual VET and Gymnasium (general education).
A well-established approach to explain student motivation is the Self Determination Theory (SDT, Ryan & Deci, 2000). The SDT suggests that an individual's engagement is higher when their environment fulfills basics needs. Three needs have been identified as particularly important: a need for agency and competence, a need for autonomy and a need for belonging. Zimmer-Gembeck et al. (2006) formulated and tested a model based on SDT, describing how students' perception of the school environment influences their academic engagement and achievement. They included student-teacher relationship and person-environment fit (PEF; an indicator of students' perception of their learning environment) as predictors. The results show direct effects of student-teacher relationship on engagement as well as PEF. Students' perceived fit also directly predicts engagement and therefore serves as a mediator. Other studies support this framework: positive relationships with teachers and instructors have been shown to lead to extra effort in both school environment (Larry, 2017) as well as in the workplace (Skiba & Wildman, 2019).
In this paper, we replicated the model of Zimmer-Gembeck et al. (2006) and expanded it by several aspects. While student-teacher relationship serves as an operationalization of the sense of belonging, we also included general self-efficacy as a predictor. Self-efficacy indicates an individual's sense of being able to accomplish a task and can therefore be seen as an indicator of perceived agency. We expect it to be a determinant of effort (Helm, Krumpholz & Heinrichs, 2017) as well as PEF (Zee & Koomen, 2020). Furthermore, we apply the model on a transitional stage in three different domains: training companies, vocational school and general education.
We hypothesize that adolescents' effort in all three environments is directly predicted by their self-efficacy (H1) and their effort before the transition (H2), by their relationship with their teachers or instructors (H3) and their perceived person-environment fit after the transition to upper secondary education (H4a). In line with Zimmer-Gembeck (2006), we also assume that perceived person-environment fit serves as a mediator between relationship and effort (H4b) as well as between self-efficacy and effort (H4c). We further expect a significant increase in effort from 9th grade to upper secondary education for all three contexts (H5).
The models were tested using data from the longitudinal study “Effects of Tracking” (“Wirkungen der Selektion WiSel”). Adolescents from four Swiss cantons were asked to fill out questionnaires at multiple points in their academic career. We used data from Wave 4, conducted in 2015 when the adolescents were in ninth grade, and Wave 5, conducted in 2016, when adolescents were in their first year of post-compulsory education. The models were specified with the hypothesized paths for the transition to dual VET (sample 1, N = 1269) and to general education (sample 2, N = 517). In the case of dual VET, we applied our model to two different learning environments, training companies and vocational school. We will therefore test our hypotheses independently for the transition to three different contexts, training companies, vocational school and general education and assume the models to be equal. Measures: Effort: Adolescents' effort in school (t1) and their training company (t2) was assessed with four items (e.g. "I do my best at (vocational) school / in my training company") based on Rieger et al. (2017). Our samples showed mean values between 4.20 (Wave 4, SD = .96, α = .90) and 5.04 (Wave 5, SD = .69, α = .88). Relationship with instructor: This scale consisted of five items (e.g. "My instructor supports me when I have problems in my training company") and was based on theoretical frameworks by Gerstenmeier (1975). The mean value in our sample was 4.84 (SD = .87, α = .90). Self-efficacy: Adolescents’ self-efficacy was assessed with six items (e.g. “When a problem appears, I usually have more than one idea how to solve it"; Jerusalem & Schwarzer, 2003). In our sample, the mean value was 4.36 (SD = 0.74, α = .87). Perceived person-environment fit: Adolescents' perceived person-environment fit was assessed with five items (e.g. "My current career situation matches my personal interests"). The scale is based on Neuenschwander et al. (2013). In our sample, the mean value was 5.05 (SD = .78, α = .85). The hypotheses were tested with structural equation modelling (SEM) in Mplus 8.1 (H1 – H4) and with t-tests using SPSS 26.0 (H5). Missing values were treated with FIML, implemented in Mplus. The models were calculated independently in all three domains.
All three SEM showed good fits (training companies: χ2(237)=373.76, p<.001, CFI=.98, RMSEA=.02, SRMR=.06); vocational school: χ2(237)=371.44, p<.001, CFI=.98, RMSEA=.02, SRMR=.07); general education: χ2(237)=346.21, p<.001, CFI=.97, RMSEA=.03, SRMR=.09)). Effort t2 was predicted by relationship with teachers/instructions t2 in VET, but not in general education (H3a partially confirmed). In all three contexts the effects were mediated by PEF t2 (H4a and H4b confirmed), with a significant indirect effect on effort t2, after controlling for effort t1 (H2 supported). Self-efficacy t1 predicted PEF t2. PEF mediated the effect of self-efficacy t1 on effort t2 (significant indirect effect, H4c supported). The direct effect of self-efficacy t1 on effort t2 was only significant in training companies (H1 partially supported). Of the three conducted t-tests, only one showed a significant result: adolescents' effort increased from 4.38 in 9th grade to 5.04 in their training companies: t(319)=-12.31, p<.001, two-tailed, Cohen's dz = .69 (H5 confirmed for transition to training companies). In the other two learning environments, the change was not significant. SDT serves as a successful approach to explain the domain specific increase of effort during the transition to upper secondary education, with person-environment fit serving as a mediator. There are only a few differences between the three contexts that seem to require further research. It is interesting to note, that student-teacher relationship is a predictor in VET but not in general education. A possible explanation is that most teachers in general education only teach one subject and very few lessons per week . These findings provide important information on adolescents' change of effort during the transition to dual VET, an important concept in many European countries. Future research should investigate these effects in other countries and age groups. International comparisons might help to inform how VET influences the perception of person-work fit and its effect on effort.
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