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Objectives
Research on emotions in education has focused on using a between-person paradigm that links individual differences in emotions to differences in outcomes and antecedents. We argue that this paradigm needs to be complemented by a within-person perspective. We examined achievement outcomes and appraisal origins of achievement emotions using two within-person modeling approaches: The random-intercept cross-lagged panel model (RI-CLPM) and dynamic structural equation modeling (DSEM; see Hamaker et al., 2015, 2018). In two longitudinal studies, we used these models to systematically compare within- and between-person relations between achievement emotions and students’ academic achievement and appraisals.
Theoretical Framework
We used Pekrun’s (2006, 2021) control-value theory as a theoretical framework. We hypothesized that achievement emotions are reciprocally related to students’ academic achievement, with positive reciprocal links for positive emotions and negative links for negative emotions. We also hypothesized that control and value appraisals influence these emotions, and that emotions, in turn, influence these appraisals. We left as an exploratory question whether between- and within-person relations between the constructs would be equivalent or not.
Methods and Data Sources
Study 1 used data from the longitudinal Project for the Analysis of Learning and Achievement in Mathematics (PALMA; N=3,425 German students; annual assessments from Year 5 to 9; 50% female) to examine relations between emotions and achievement in mathematics. Emotions were assessed with the Achievement Emotions Questionnaire-Mathematics (Bieleke et al., 2022), achievement with grades and test scores. Study 2 is based on data from a 42-wave intensive longitudinal study (N=525 participants, United Kingdom; 51% female) that included monthly assessments of achievement emotions and control-value appraisals (Likert-type rating scales).
Results
Based on the RI-CLPM, Study 1 confirms that students’ emotions and their achievement are reciprocally related over the school years, with positive relations for positive emotions and negative relations for negative emotions. For Study 2, preliminary DSEM results document reciprocal relations between achievement emotions and perceived control as well as intrinsic value of achievement activities. Importantly, the Study 1 relations between within-person factors of emotions and achievement were largely equivalent to the between-person correlations of the random intercepts. Similarly, in Study 2, correlations between emotions and appraisals were largely equivalent at the within- and between-person levels. The correlations of random intercepts for emotions and achievement in Study 1 (around |r| = .45) suggest that individual differences in emotions explain similar amounts of variance in students’ performance as cognitive variables like intelligence (i.e., substantially more than previously thought; e.g., Barroso et al., 2019; Camacho-Morles et al., 2021).
Significance
The findings document the usefulness of decomposing between- and within-person variance in exploring outcomes and antecedents of achievement emotions. They confirm the importance of these emotions for students’ performance and the role of perceived control and value for their development. As such, the findings indicate that educational practitioners are well advised to attend to students’ emotions. Furthermore, based on within-person analysis, the findings suggest that supporting students in developing adaptive control and value perception can be a primary way to both promote their achievement and their affective wellbeing.
Reinhard Pekrun, University of Essex
Herbert W. Marsh, Australian Catholic University
Andrew J. Elliot, University of Rochester
Kristina Stockinger, University of Augsburg
Anne C. Frenzel, University of Munich
Thomas Goetz, University of Vienna
Stephanie Lichtenfeld, University of Hamburg
Elisabeth Vogl, Ludwig Maximilian University of Munich
Raymond P. Perry, University of Manitoba
Wijnand van Tilburg, University of Essex
Oliver Lüdtke, Leibniz Institute for Science and Mathematics Education