Teacher Motivation and Teaching Quality: Differential Associations for Perspective-Specific Versus Common Teacher-Student Ratings of Quality

• In Event: Bifactor Models to Improve Theoretical and Analytical Precision and the Opportunity to Study Motivational Processes

Abstract

Introduction
Research on teachers’ motivational beliefs—in particular, teachers’ self-efficacy and enthusiasm for teaching—has proposed that these beliefs can function as key antecedents of teaching quality (Zee & Koomen, 2016), which has been defined in terms of three basic dimensions (Praetorius et al., 2018): classroom management (teachers’ effectiveness in dealing with disruptions), student support (attentiveness to students‘ socio-emotional and learning needs), and cognitive activation (fostering students‘ thinking about content). However, empirical evidence testing these associations is mixed: Some studies report positive links between teacher motivation and both teacher- and student-rated teaching quality (Kunter et al., 2008; Holzberger et al., 2013), others only with teacher-rated but not student-rated quality (Lauermann & Berger, 2021; Schiefele & Schaffner, 2015), or mixed results (Lazarides et al., 2021). Teachers’ self-serving biases and students’ insufficient pedagogical expertise to provide valid ratings of teaching quality have been discussed as possible contributors to these inconsistent findings. However, no study to date has differentiated between shared versus perspective-specific ratings of teaching quality in these analyses, and we know little about the differential associations of teachers‘ motivations with shared versus rater-specific (and potentially biased) perceptions of teaching quality. Thus, we examined the links between teacher motivation and teaching quality based on a bi-factor model that differentiates a common student-teacher factor of teaching quality and teacher-/student-specific perceptions (Bauer et al., 2013).
Methods
Data from 72 math teachers and their 1745 ninth-grade students were analyzed. Students and teachers rated the three basic dimensions of instructional quality with similar items (Table 1). Students’ math achievement, socio-economic status (SES), teachers’ teaching experience, self-efficacy, and enthusiasm were included as covariates in all analyses (Figures 1-2).
Results and Discussion
Two- and bi-factor multilevel models were estimated for each dimension of teaching quality (Figures 1-2). For “classroom disruptions” and “social-emotional support,” a bi-factor model with a common student-teacher factor (C) and a student-specific factor (PFS) was supported based on changes in model fit (Table 2) and significant factor loadings (Model#3; Table 3). In contrast, a common student-teacher factor (C) failed to emerge for “learning support” and “cognitive activation” (Model#5; Table 3). Two-factor multilevel models indicated that teachers’ and students’ ratings were not significantly correlated in this case (Model#1; Table 2).
Models including two correlated factors for teachers’ and students’ ratings of teaching quality (Figure 1) revealed significant positive correlations between teacher motivation and all dimensions of teaching quality, rated either by teachers or students (Table 4). In contrast, bi-factor models that separated student-specific factors (PFS) from common student-teacher ratings (C) of “classroom disruptions” and “socio-emotional support” indicated that teachers‘ motivational beliefs were positively correlated only with the common factor (C) but not with the student-specific factor (PFS). Thus, failure to differentiate between shared versus idiosyncratic, student-specific ratings may be a contributing factor to the inconsistent associations between teacher motivation and teaching quality reported in prior research. For dimensions for which a common factor failed to emerge, teachers’ and students’ ratings appear to reflect different aspects of the instructional process so that both perspectives should be considered.

Authors

• Annika Luisa Koch, TU Dortmund University

• Fani Lauermann, TU Dortmund University

• Hanna Gaspard, TU Dortmund University