The aim of this study is to examine the relationship between collective teacher efficacy (CTE) and teacher self-efficacy (TSE) by a longitudinal and multilevel analysis.

To respond current complex educational circumstances, CTE is one of the most reliable factors of a school’s effectiveness in achieving its objectives as a group by leveraging each other’s strengths and compensating for one another’s limitations (Klassen et al., 2010; Tschannen-Moran & Barr, 2004). CTE is defined as “the collective self-perception that teachers in a given school make an educational difference to their students over and above the educational impact of their homes and communities” (Tschannen-Moran & Barr, 2004, p. 190). Because of the nature of teacher efficacy, previous studies have indicated that CTE is closely related to TSE (Cansoy & Parlar, 2018; Ninković & Knežević Florić, 2018). As many researchers suggest that CTE and TSE are mutually reinforcing, educational organisation research highlights that CTE arises when teachers cooperate to solve problems and act towards the same goals (Goddard, 2001). However, in practice, school leaders and policy makers could be indecisive about whether they should focus on development of individual teachers first or school as an organisation first. This is because the causal relationship between CTE and TSE has not been clearly revealed.

It is easy to assume the path from TSE to CTE. An organisation or a group of individuals with high abilities can create a strong organisation and have confidence in the organisation (Caprara et al., 2003). When members of an organisation act with individual confidence and achieve success, the motivation of the entire organisation can increase, thereby enhancing collective efficacy as well. Therefore, teachers with high TSE may have the potential to form collaborative school organisations, thereby leading to enhancing CTE. 

On the other hand, some researchers argue the path from CTE to TSE (Goddard et al., 2001; Skaalvik & Skaalvik, 2007). Meyer et al. (2020) note that CTE is likely related to teachers' collaborative behaviour. When educational organisations succeed in working together, teachers gain confidence, higher motivation, and engage more effectively in their work (Yada et al., 2022). In addition, it is known that CTE affects individual performance when task interdependency is high in organisational research (Katz-Navon & Erez, 2005), and schools can be considered high interdependency organisations (Moolenaar et al., 2012). TSE is enhanced through the strong belief in the ability of the organisation to accomplish high interdependent tasks that individuals cannot achieve alone. Being part of a collective efficacious school could provide more opportunities to experience professional collective action, which can enhance individual performance and improve TSE. 

However, there some issues have been identified in prior studies on CTE. First, there is a discrepancy regarding whether TSE or CTE predicts the other. Second, there is a paucity of longitudinal and multilevel examinations between CTE and TSE, which enables more precise predictive relationship analyses. Sample design, size and methodological limitations hinder the longitudinal and multilevel examinations although studies have assumed a path from TSE to CTE in previous studies (Cansoy & Parlar, 2018; Ninković & Florić, 2018). Therefore, we set the research questions as follows:

RQ1: How is CTE related to TSE at individual level?

RQ2: How is CTE related to TSE at school level?

A total of 69 schools with 1081 teachers were included in the analyses. The size of schools ranged from 2 to 88 (M = 20.74, SD = 15.81). Due to the limited number of schools at school level (i.e., 69 schools), we used the mean scores of each variable for subsequent multilevel analysis instead of employing latent factors. The intraclass correlations, representing within-school homogeneity (i.e., between variances), of CTE are 21.4% at T1 and 20.0% at T2 of the variability, while 5.5% at T1 and 7.4% at T2 of variances in TSE. Although school level variation was not large in TSE, statistically significant school level variation in all the observed variables was confirmed, and, thus, multilevel analysis was considered as applicable. CTE was assessed using the student discipline subscale (6 items, 9-point Likert-type scales; e.g., To what extent can teachers in your school make expectations clear about appropriate student behavior?) of the Collective Teacher Beliefs Scale (CTBS) (Tschannen-Moran & Barr, 2004). This study had high reliability for the scale at the first (α = .87) and the second time point (α = .89). TSE was measured using one subscale (6 items, 6-point Likert-type scale; e.g., I am able to calm a student who is disruptive or noisy) of the Teacher Efficacy for Inclusive Practices Scale (TEIP) to measure teacher’s self-efficacy in managing behaviour (Sharma et al., 2012). This study had high reliability for the scale at the fist (α = .82) and the second time point (α = .83). The analyses followed the steps. First, longitudinal measurement invariance was tested to examine whether the same constructs were measured across different timepoints. The scalar invariance models, where factor loadings and intercepts were set to be equal across timepoints, achieved acceptable fit, and there were not large differences in the fit indices when compared to the other models. Achieving scalar invariance implies that variations in the latent construct's means account for all variations in the common variance among the items (Putnick & Bornstein, 2016), thus, we could conclude that mean differences across timpoints were comparable in our data. Next, a cross-lagged panel model analysis with a multilevel approach was performed to answer the research questions. The estimated models were examined using three indicators: RMSEA (<.060), standardised root mean square residual (SRMR, <.080), and CFI (>.950) (Hu & Bentler, 1999). The Mplus statistical software was used for all the analyses.

A two-level path model was analysed. The estimated model fit the data well, χ2(7) = 2.711, p = .258, CFI = .999, RMSEA = .018, SRMRwithin = .001, SRMRbetween = .040. The results for individual and school levels indicated that there were statistically significant auto-regressive paths from T1 to T2 between CTE and TSE. In the light of cross-lagged paths at individual level, a statistically significant path was found from CTE at T1 to TSE at T2 (T1–T2: β = .127, p < .01). Regarding school level, the cross-lagged paths worked differently, where only the path from TSE at T1 to CTE at T2 was statistically significant (T1–T2: β = .621, p < .01). The results showed that the relationships between CTE and TSE differed at individual and school levels. First, as many previous studies have shown (e.g., Skaalvik & Skaalvik, 2007), the results supported that CTE predicts TSE at individual level, which answered RQ1. In other words, when a teacher experiences collective action and perceives that colleagues and staff in the school have high collective capability beliefs, the teacher will be influenced by this and increase their own TSE. This motivational extension could be explained by motivational sources and school atmosphere that are created by highly motivated colleagues, which are sources of efficacy (Bandura, 1997). At school level, the relationship between CTE and TSE showed an inverse direction, which is regarding RQ2. The higher the TSE of a teacher, the higher the CTE of the school, rather than supporting previous’ results (Goddard & Goddard, 2001). This suggests that a group of teachers with high TSE could generate CTE when the individual teachers are aware of collective action, in which they have opportunities to use their expertise. The results enhance current debates and theories on teacher efficacy.

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