Complementing previous research on the role of individual characteristics in occupational change, the present study used three well-established personality traits to predict the degree of teachers’ behavioral reactions to an educational reform, operationalized by the degree of use of competence-oriented teaching and data feedback for classroom development. The results of this study support three main conclusions: First, in line with the body of previous research some personal dispositions, in particular positive affectivity and self-efficacy proved to be important for building openness to the reform and thereby supporting the individuals’ cooperation in the change processes. Teachers who make use of the reform and show the behavior intended by the reform seem to be primarily characterized by high levels of occupational satisfaction. To a lesser degree, also self-efficacy predicts change behavior: Those who consider themselves capable of mastering (difficult) situations build openness to the reform which in turn facilitates implementation behavior. Second, in contradiction to previous findings, perceived control does not contribute to individuals behavioral reactions in this study. Third, contrary to our hypothesis and to the main thrust of literature, we were not able to demonstrate the predicted context-specific effects on openness to change. Neither the use of social nor external support predict openness to change, only occupational burdens are negatively associated with openness to change. Teachers experiencing high levels of occupational demands were less likely to develop a positive attitude towards the reform.
4.1 Theoretical considerations
In the present study, only two of three dispositions predicted the formation of “openness to change.” There are several theoretical as well as methodological reasons to be considered. Locus of control has been shown to be influenced by frequency, length, and intensity of experiences in specific contexts (most prominently in health context; Lohaus
1992): The longer, the more intense and the more often someone is exposed to unpleasant experiences, the higher the probability that the person will perceive low levels of control and consequently care less about situations. Since teaching and the work in classrooms and schools are frequently undergoing changes which are controlled by external actors (i.e., administration or politics), teachers may perceive low levels of control and, in consequence, care less about the reform (which would be indicated by negative or neutral attitudes to the reform). This interpretation is partly supported by the data since the majority of teachers report high levels of perceived pressure to change their behavior and low levels of acceptance of the reform. If this interpretation makes sense, one would also expect that teachers with long-time work experience report less control (contrary to a “work socialisation hypothesis” which would expect that “perceived control” grows with experience).
The idea that long-term exposure to change in the educational system might diminish perceived control could also be transferred to the contextual variables and give some explanation to the lack of effects of support structures in our data. Given the fact that teachers had already been confronted with educational standards for 3 years, the supportive power of social interaction might have regressed after long exposition to the reform and its support structure. On the other hand, there have been mixed results also in previous studies: Rieß and Zuber (
2014) found that external support did not enhance participation in Austrian educational standard reform, while there is also evidence that support structures facilitate the implementation of educational reforms (Schildkamp and Ehren
2012). In a long-term perspective, one would expect that implementation support is conducive for the overall goal of the policy, for the improvement of teaching and learning processes and of student results.
Second, the study at hand has measured the influence of person factors on the effects intended by the performance standard policy. However, the literature suggests that there may also be several unintended effects (e.g., strategic and symbolic use of this policy). Possibly, the amount of perceived control would be more important for predicting behavior when it comes to unintended effects rather than intended effects. Previous studies support this argument: it has been shown that unintended use of feedback data is most likely when the perceived pressure is very high (von der Embse
2017). Exploring this issue constitutes a worthwhile goal for future research.
Third, also methodical issues need to be considered regarding the influence of perceived pressure. With respect to dispositional characteristics for change, we assume that the scales self-efficacy, positive affectivity, and perceived pressures are highly relevant for the context of our study. Moreover, self-efficacy and affectivity are correlated, as predicted by the literature (Gu and Day
2007). However, perceived pressure as measured in this study may not represent the broader construct of locus of control as proposed by Rotter (
1966). According to previous research, one would expect that all these variables are correlated as they index “resilience” (Gu and Day
2007; Major et al.
1998). Since perceived control was not correlated with self-efficacy and did not predict openness to change, future studies should test a different approach to the measurement of locus of control constructs (such as the scales of Rotter
1966). Even though the applied scale achieved good reliability, the construct is either more heterogeneous than expected or is not optimally assessed by those eight items suggested by the scale authors.
4.2 Limitations
The study at hand has certain limitations that provide opportunities for future research. Another look at the variables included in the study may be worthwhile. The low explanations of variances (
R2 from .11 to .30), in particular, the low levels of variance explaining openness to change (
R2 = .11), suggest that additional information is required to explain “openness to change” within the context of educational reforms. First, it seems useful to include a broader concept of positive affectivity and locus of control. Since positive affectivity was only indexed by occupational satisfaction—as one indicator of positive affectivity—including broader scales, encompassing optimism etc. might increase variance. Second, even though cognitive adaption theory has been shown to be a valid predictor of behavior in change contexts, previous studies point to further variables that could also be considered: First, implementation studies of changes in teaching found that teacher beliefs are important predictors as well. According to Zeitler et al. (
2012), understanding and implementing the concept of competence-based teaching was easier for teachers with a constructivist understanding of teaching and learning, while teachers with instructionist views were more likely to avoid competence-based changes. This is also backed by results of Wan (
2015), who reported that the implementation of differentiated instruction was strongly associated with attitude formation which, in turn, facilitated implementation.
Second, attitudes towards educational reforms have been reported to be predominantly negative and/or highly ambivalent (e.g., Ungar
2016) which is driven by the fact that elements and role changes of educational reforms are often evaluated as ambiguous. Judge et al. (
1999) suggested that the disposition “tolerance for ambiguity” (the tendency to perceive ambiguous situations as tolerable) is related to several aspects of coping with changes (e.g., Rush et al.
1995) whereas intolerance for ambiguity is related to the perception of ambiguous situations as sources of threat. It is quite likely that “tolerance for ambiguity” might add to the explanatory power of dispositions on attitude and behavior in educational reforms.
Third, studies focussing on coping with educational reforms, in particular, with reforms including high accountability pressure, suggest that, besides self-efficacy, individual coping strategies predict how change is dealt with. However, these variables do not necessarily influence the formation of attitudes such as openness to change; rather, they influence cognitive-emotional evaluation processes which predict behavior. For example, Callan et al. (
1994) found that ineffective (emotion-focussed) copers were more prone to anxiety in the wake of organizational change, while successful coping with organizational change was positively related to job performance (Judge et al.
1999). Moreover, coping has been found to mediate the relationship between personality and job performance in educational reforms (von der Embse et al.
2016) and also in other fields (Judge et al.
1999).
Fourth, “perceived pressure” has also been studied under the concept of attribution. Attributions refer to perceived causes that individuals select or construct for events in their lives (Weiner
1994). Attributions are made along three causal dimensions; locus of control (internal vs. external causes), controllability (controllable causes such as skills vs. luck), and stability (do causes change over time?). A basic assumption of attribution theory is that a person’s understanding of the causes of events influences his or her future actions. Motivation for action will increase if the causes are perceived to be internal and controllable. There are first indications that attribution might also play a critical role in educational standard policy, in particular for data feedback use. Teachers and school supervisors tend to attribute student performance to external factors (e.g., students’ lack of competence; Schneewind
2007; Kohler
2004). Tresch (
2007) provided some differentiation of this argument by showing that teachers mainly used external attribution for below-average outcomes, while above-average results were given both internal and external attributions. This corresponds to the theoretical expectation that internal attribution will be preferred after success, while external attributions are given after failures (e.g., Musch and Bröder
1999). External attribution may provide some emotional relief, but may also inhibit further reflection on possible courses of action when it comes to making use of data feedback (Koch
2011). Therefore, it seems worthwhile including this concept in further studies.
Another important methodological point has to be taken into account when interpreting the findings of this study. The data used in this study is solely based on teachers’ self-reported perceptions. While this is a reasonable approach for several constructs portrayed in the model (i.e., individual characteristics), this may not be the case for the measurement of behaviors and competences. In our results, this became visible as “data literacy,” a previous identified key variable for data use (e.g., Schildkamp and Ehren
2012), could not be included in the model, since teacher self-reports produced massive ceiling effects. A potential explanation is that this finding reflects the true situation (i.e., teachers’ high data literacy and/or easily readable data feedback reports). This argument could be supported by the sampling error in this study. As only 27% of teachers responded, the sample might comprise only those teachers who understand the feedback best, the other who did not understand the feedback did not respond). However, previous studies suggest otherwise: Teachers seem to overestimate their data literacy in self- reports (for an overview, see Koch
2011). The study at hand captured data literacy with eight items, focussing on different aspects of the Austrian data feedback report. Nevertheless, this scale did not turn out to be sufficiently valid to avoid ceiling effects. Further studies on educational change processes should therefore use different approaches for measuring goal behavior and competences (e.g., by externally observing goal behavior or externally assessing data competences).
Finally, limitations in the interpretation of the outcome scales need to be considered. Teachers were asked to indicate to what extent they took up educational standard reform, indicated by their amount of competence-based teaching and data-use. However, within this operationalization of behavior, the reasons teachers implement changes remain unclear. When teachers responded that they had paid more attention to competence-based teaching as opposed to content-based teaching, they might simply react to policy waves (since they are more open to these waves). But, they might have also positively responded to this change because it is deeply in line with their beliefs about teaching practices. Thus, the interpretation of the current findings remains on a superficial level. Dispositions, occupational demands, and openness to change contribute to behavioral reactions; however, we do not know which level of underlying behavioral motivation is addressed.
4.3 Implications
The study at hand constitutes a first step of linking several person characteristics to the intended outcomes of a specific educational reform, the performance standards policy. The results clearly underline that it is worthwhile to include person factors of teachers into studying processes and effects of implementing performance standards and data feedback. The study suggests that, in line with previous research, teachers’ behavioral reactions to educational reforms are at least to some extent dependent on factors that are difficult to change as dispositions are relatively stable over time. Teachers who have a positive self-concept and high levels of positive affectivity will be more likely to build up a positive attitude towards an educational reform and more likely to show changes in teaching behavior according to the intentions of the reform. One potential consequence lies in the question whether it would be useful to test and select teachers more carefully before entering training, or, at least, before determining the pilot groups of a reform. Although there is an extensive body of literature supporting the reliability and validity of the personal dispositions included in this study, few of these characteristics have been studied in a selection context. Thus, although the results of the present study are suggestive for applying these variables in selection processes for teacher training or pilot group selection, they do not directly demonstrate the validity of these dispositions in selection processes in the educational context. Moreover, those characteristics that predict positive behavior during change might not be equally valid for predicting constructive behavior during periods of less change (however, there is some evidence for at least some correlation between typical job performance and self-efficacy; see Pierce et al.
1989).
Is it impossible to successfully develop the—comparatively stable—dispositions considered in this study during teacher careers, e.g., through teacher training programs etc.? Education, in particular higher education (Dahmann and Anger
2014), has been found to crucially influence personality characteristics by fostering favorable characteristics with regard to the specific profession. Thus, one might hypothesize that also teacher education can have some leeway for developing favorable dispositions which enhance coping with change. The study at hand is certainly limited with respect to explaining the origins of dispositions; nevertheless, it seems to be worthwhile exploring the influence of teacher education on teachers’ personal dispositions and on their coping with reforms. In sum, educational reforms are pursued in all countries and no change to this situation is expected. While previous research on educational change has often focussed on the policy and organizational level, this paper links educational change to individual characteristics as suggested by cognitive adaption theory. However, further research is needed to account for individual difference and contextual factors related to change in more detail and to asses and extend the generalizability of the results of the current study.