Roles of School-Context and Goal Orientation on Emotion Regulation amongst Turkish Middle-school STEM Teachers. A Structural Equation Modeling Study

doi:10.21203/rs.3.rs-4982652/v1

Background

Emotion regulation addresses how individuals regulate and monitor their emotion. Although the role of personal characteristics on emotion regulation has been well studied, there is a need for examination the role of school-contextual variables including support, discipline problems, autonomy and recognition and goal orientation in emotion regulation.

Methods

Data from 242 STEM teachers in fifty middle schools in Turkey were collected through Teacher Emotional Control Scale, Teacher Goal Orientation scale and School Contextual Scale in the spring 2022 semester. A Structural Equation Modelling approach, allows examining the direct and indirect causal relations among variables, was used to address the research questions.

Results

Results of SEM showed that the hypothesized model had an acceptable fit with data. The hypothesized model could be accounted for 52.2% of variance in emotion regulation. Whereas mastery goal orientation positively predicted emotion regulation, performance goal orientation negatively contributed to emotion regulation. School contextual variables were directly related to goal orientation and indirectly emotion regulation through goal orientation.

Conclusion

The socio-cultural environment in the schools are important determinants of how teachers regulate and control their emotions. Moreover, the path coefficients between goal orientation and emotion regulation underscore that what teachers want to accomplish in their work greatly contribute to how they regulate their emotions.

Emotion regulation

goal orientation

School environment

Structural equation modelling

Being a teacher is a very emotional job. When they teach in the classroom, teachers can experience emotions that influence their practice and their students [1]. For instance, teachers may experience anxiety when their abilities are questioned, sadness when a lack of effort is shown, annoyance when concepts are not comprehended, and irritation when pupils triumph. Therefore, teacher emotions are associated with their well-being, stress and burnout.

Some emotions can be maladaptive [2]. Thus, teachers frequently attempt to manage these emotions because they believe it aids them in reaching their objectives [3], [4]. That makes emotion regulation a hot topic in educational and psychological research. However, research on how teachers regulate their emotions is still in its early stages, and much more study is needed to grasp the fundamental processes, cultural factors, and classroom impacts [5]. For instance, in a recent meta-analysis study, Wang et al [4] argued that many studies has been focused on teachers’ emotion regulation and their personal characteristics and thus, there is a need for more studies to examine the role of socio cultural and contextual factors on teachers’ emotion regulation. Based on Bandura’s Socio-cognitive Theory, it is reasonable to assume that social environments in schools can relate to how teachers regulate their emotion. Moreover, there is a few studies been investigated teachers’ emotion regulation in Turkey. What is more, Science, Technology, Engineering, Mathematics (STEM) teacher shortage has become an important issue for most developed and developing countries [6]. The interplay between emotion regulation, job satisfaction and teacher burnout [7] underscore the importance of emotion regulation in teachers’ well-being. Thus, we believe it is important to examine the related factors affecting STEM teachers’ emotion regulation.

Emotion regulation

Emotion regulation is defined as the process by which individuals influence which emotions they have, when they have them, and how they experience and express these emotions [2]. Emotion regulation can target both positive and negative emotional states and consists of conscious or unconscious efforts to influence which emotions one has, when one has them, and how one experiences or expresses them [8], [9]. Emotion regulation occurs when an emotion is evaluated as good or bad, prompting a change in the emotion [10].

The goal of emotion regulation is to maintain positive emotions and reduce unpleasant emotions [11]. Emotions are regulated to achieve various goals, and different strategies can be used to reach these goals. There is significant uncertainty about why and how teachers regulate their emotions in the classroom. Considering the emotional demands of teaching [12] and its subsequent effects on teachers' mental health [13], teachers need to regulate their emotions throughout the school day [5], [14]. Teachers face intense stress today [15], often leading to feelings of frustration and anxiety in the classroom. Regulating these emotions is crucial for the success of education [16]. According to Taxer and Frenzel [17], teachers usually control their emotions through a method known as emotion regulation. This variable, key to personal and social development, can be conceptualized as a conscious and unconscious process that affects individuals' emotions, when they experience them, and how they experience and express them [8].

Goal Orientation

A prominent feature in motivation theory is the role of goals. Goals are the targets individuals strive to achieve. Goal orientation theory, also known as achievement goal theory, has been the focus of many educational studies due to its assumed impact on student performance. Goal orientation theorists define achievement goals as the reasons individuals engage in a task [18], [19]. Goal orientations concern why and how people strive to achieve various goals, rather than focusing on the content of the goals themselves [20].

Goal orientation generally refers to the reasons behind individuals’’ actions. Goal setting typically concerns what individuals aim to achieve. Goal structures refer to the messages about prominent goals within the classroom, including motivational climates [20], [21]. Goal orientation theory seeks to understand why some individuals are motivated to overcome obstacles while others easily give up or avoid trying [19]. It examines what motivates people to achieve success in school and other settings [18], [22]. Goal orientation theorists study the types of goals that are most productive for students, and which lead to cognitive strategies, emotional responses, and behaviors that result in student success [23].

School-context

Schools are social structures involving teachers, students, parents, and administrators. The school environment (variables like interactions with stakeholders, values, attitudes, and behaviors) can affect teachers' emotions, motivation, and behaviors. Studies have shown that school environment variables are related to teachers' professional motivation and job satisfaction [24], [25]. Literature reviews indicate that different school environment variables have been defined in research, and their relationships with teachers' emotions and practices have been examined. For instance, Rubie-Davies et al [26] identified school environment variables as class level, time pressure, and the school's economic level. Brault et al [27] selected the school's expectations of teachers, the value placed on education, the purpose of education, the school's economic status, and the number of students as school environment variables. Skaalvik and Skaalvik [25] defined the school-context as a safe learning environment, peer communication, administrative support, colleague support, and school belonging as school environment variables. Similarly, Kıran and Sungur [24] defined the school context variables as communication with parents, discipline problems, administrative support, and relationships with colleagues, and the school's internal and external goals. Considering both international and national studies, this study selected discipline problems, autonomy, recognition, and supports from parents, manager, and colleagues as school-contextual variables.

Recognition

Recognition is defined as recognizing the value and significance of an object, event, or person and establishing an emotional bond with it [28]. Recognition supports an individual's well-being both directly and indirectly through increased spirituality or enhanced social relationships [29]. Studies have shown that recognition develops and maintains interpersonal social bonds and relationships, strengthens trust, and promotes kindness and helpfulness [30]. Recognition is also related to teachers' job satisfaction and motivation [31].

Discipline Problems

One of the necessary conditions for effective teaching in a classroom environment is a disciplined and orderly learning environment [25]. Discipline problems in the classroom are one of the factors that hinder teachers from conducting effective and efficient teaching. Studies have shown that discipline problems affect teachers' feelings of burnout [32].

Autonomy

Autonomy is one of the basic psychological needs of an individual [33].Teacher autonomy is defined as being free in professional decision-making, planning, and implementation processes [34]. Teacher autonomy is one of the important factors affecting the quality of education [35]. Teacher autonomy influences the adoption of new approaches, professional development, and risk-taking situations. Studies have shown that teacher autonomy is positively related to job satisfaction and self-efficacy [25].

Support

Support is defined as the physical, emotional, etc., help a person perceives from their social environment. Support includes numerous social interactions with one's spouse, relatives, friends, and others [36]. Since teaching is a stressful job, it is important for teachers to receive support from their school environment. Research has shown that social support is an important factor in teachers' competence and psychological well-being [37]. For example, Karaçoban-Tuna and Aslan [38] found that support positively predicted organizational commitment among primary school teachers (β = .165, p < .05).

Support is seen as a process that enhances social relationships. Additionally, support encompasses the social resources provided to an individual by a social environment [39]. Recently, support has been seen as especially important in teacher education. It is stated that the support teachers receive from family, school administrators, and colleagues is crucial for professional continuity [40], [41]. Supported teachers are found to be effective and enjoy their work [42]. Additionally, teachers are reported to resolve their professional problems with the support of colleagues and better fulfill the requirements of their profession [43]. Teachers who receive support in areas such as planning and classroom management often transition to teaching more easily [44].

Relations amongst Variables and the Hypothesized Model

Previous studies have reported that teacher emotion regulation has been associated with goal orientation and school-contextual variables. Achievement Goal Theory assumes that different goal orientations lead to different behavioral outcomes [22]. Studies have provided evidence for causal associations between goal orientation and emotion regulation. For instance, Wang and Yang [45] examined the relations between goal orientation, emotion regulation and job search behavior among 1639 university students. Correlational analysis showed that both mastery and performance goal orientations were correlated to emotion regulation (Pearson r from .10 to .33, p < .05). In the recent meta-analytic study, Wang et al. [4] teachers’ emotion regulation and seven related environmental, personal, instructional, and well-being factors. After reviewing 87 articles, they found that school contexts (support from family, supervisor and colleagues, recognition, autonomy etc.) were associated positively with antecedent-focused emotion regulation (effect size r = .161, p < .05) and negatively response-focused emotion regulation (effect size r = − .209, p < .05). Moreover, motivational factors including goal orientation were related to antecedent-focused emotion regulation (effect size r = .206, p < .05).

Based on the previous studies, we hypothesized that support from family, supervisor and colleagues predicted autonomy, recognition and discipline problems because social support was an important factor in teachers' competence and psychological well-being [37]. Then, we assumed that autonomy, recognition and discipline problems contributed to teachers’ goal orientation since goal orientations have been shaped by social interaction with others [22]. The third hypothesis was that goal orientation predicted teachers’ emotion regulation because individuals’ goals directed their behavior and emotion. Finally, we hypothesized that school-contextual variables indirectly influence teacher emotion regulation through goal orientation.

Research Questions

In this study, we sought to address the following research questions:

RQ1- How well does the hypothesized model fit with the data?

RQ2- What proportion of variance of emotion regulation can be explained by the hypothesized model?

RQ3- Do goal orientation predict emotion regulation?

RQ4- Do school contextual variables contribute to goal orientation?

RQ5- Do school contextual variables indirectly relate to emotion regulation through goal orientation?

This research employed a relational research method with a quantitative approach. The relational research method enables the researcher to examine the causal relations between variables without manipulating any variable. Data from 281 STEM teachers who worked at middle schools in Turkey were collected through the Teacher Self-regulation Scale and School Climate Scale. Structural equation modeling (SEM) was employed to test causal relations among variables. SEM has several advantages over other statistical techniques including regression analysis, dealing with different directions of the relation, and assessing the fit indices of the model. Thus, SEM technique was chosen to examine the causal relations among variables.

Participants and Context

Turkey has a centralized education system governed by the Ministry of Turkish National Education (MTNE). All teachers at state schools were appointed by the MTNE. Therefore, Muğla province located in the Southwestern Turkey was chosen as the accessible population to represent the STEM teachers in Turkey. At the time of data collection, there were 1323 STEM teachers (129 computer, 453 science, 550 mathematics and 191 technology) from 198 state middle schools in 13 districts in Muğla province. Fifty middle schools were randomly selected for data collection. From 50 schools, 242 STEM teachers voluntarily participated in the study. Descriptive characteristics of the participants were given in See Table 1. Of these teachers, 68.2% were female and 82.6% worked at urban schools. Some teachers reported that they taught two subjects (computer and mathematics or science and design and technology; thus, the total number of teachers was higher than 242). Majority of the participants (36.0%) were teaching mathematics.

Table 1

Descriptive characteristics of the sample
		n	%
Gender	Male	77	31,8
	Female	165	68,2
School location	Urban	200	82.6
	Rural	42	17.4
Courses teachers taught	Computer	62	0.256
	Mathematics	87	0.360
	Science	55	0.269
	Design and technology	60	0.248
Teaching experience	1–10 years	63	26,0
	11–20 years	100	41,3
	21 year and more	79	32,6

Data Collection Tools

In this study, we used the following instruments because of the fact that a) they covered interested variables, and b) had been validated in Turkish context.

Teacher Emotional Control Scale

We used the emotional control dimension of Teacher Self-regulation Scale by developed by Çapa-Aydın et al [46]. This scale was previously used to measure teacher emotion regulation [47]. The scale consisted of five items in a six-point Likert-type (1: strongly disagree, 6: strongly agree). A higher score indicates that the teacher tends to regulate and control her mood and emotions in teaching practices. Çapa-Aydın et al [46] reported the internal consistency score as .73 in the Turkish context. In this study, we tested its validity with CFA and its reliability with Cronbach’s alphas. Cronbach’s alphas coefficient was found to be .84, higher than .70 acceptable cutoff value. The CFA yielded the χ² (5) = 9.09, RMSEA = .05, CFI = .95, and TLI = .94. Factor loadings were between .60 and .81. These results indicated that the Teacher Emotional Control Scale was reliable and valid.

Teacher Goal Orientation Scale

For the study purposes, we used two dimensions of Teacher Self-regulation Scale by developed by Çapa-Aydın et al [46]. Performance goal orientation (five items) was about goals to perform better than others did whereas mastery goal orientation (four items) measured goals to improve their competence for self-set standards. Çapa-Aydin et al [46] reported the internal consistency score for performance goal orientation as .78 and for mastery goal orientation as .67 in the Turkish context. In this study, we found the internal consistency coefficient of Cronbach alphas as .82 for mastery goal orientation and .85 for performance goal orientation. The results of CFA were χ² (26) = 68.7, RMSEA = .06, CFI = .94, and TLI = .94. Factor loadings were between .50 and .88 for mastery goal orientation and between .60 and .82 for performance goal orientation. These results indicated that the Teacher Goal Orientation Scale was reliable and valid.

School Contextual Scale

We developed the School Contextual Scale to measure teachers’ views on school contextual variables. The scale consisted of six dimensions as discipline (3 items), support from colleague (3 items), support from supervisor (3 items), autonomy (3 items), support from parents (3 items) and recognition (4 items). We used discipline problems items developed by Skaalvik and Skaalvik [40] to measure to what level discipline problems teachers encountered affected their teaching. Support from supervisor, colleague and parents, developed by Skaalvik and Skaalvik [40], measure how much support teachers perceive from their environment. Autonomy, developed by Skaalvik and Skaalvik [46], measures teachers’ feeling of freedom to implement their way of teaching in their practice. Recognition, developed by Pietarinen et al [48], is about how much their teaching are recognized by their environment. Kıran and Sungur [24] adapted the School Context Scale into Turkish with a sample of 134 science teachers. They reported that expect for autonomy, Cronbach alphas of dimensions were higher than .70 cut-off value. In this study, the CFA test results in acceptable fit indices as χ² (137) = 348.0, RMSEA = .07, CFI = .93, and TLI = .92. Cronbach’s alphas were between .65 and .92. These results indicated that the School Contextual Scale was reliable and valid.

Data Collection and Analysis

Once the IRB permission for data collection was granted from Muğla Sitki Kocman University, data were collected from fifty middle school during the spring 2022. Data, first, were examined for missing and outlier cases. Thirteen cases were removed because of highly missing responses. Then, we checked the interval consistency of the data (Cronbach’s alphas). Similar to Kıran and Sungur’s [24] studies, Cronbach value for autonomy was less than the .70 cut-off value. We decided to keep autonomy factor in analysis as the SEM approach with latent variable helps us ignore the low reliability coefficient [49]. To address research question, we utilized structural equation modeling, which allows researchers to test the causal relations between more than two variables. Rather than observed variables, in SEM analysis, we treated variables as latent variables, which enable us to test relations between variables by removing unreliability of the variable [49]. To determine estimation methods in SEM analysis, first, we checked the normality of data. The skewness and kurtosis values of variables indicated that data were non-normally distributed (exceeding − 2.00 and + 2.00 range; see Table 2). Therefore, weighted least squares - mean and variance adjusted (WLSMV) was used as the estimation method [50]. SEM approach allows research to evaluate the hypothesized model using fit indices (indicating how the hypothesized model fits with data). Recommended fit indices for good fit are χ²/df less than 2.5, RMSEA value less than .06, or CFI and TLI values higher than .95 [51]. Based on these fit indices, before evaluating the causal relations among variables, we examined the fit indices. In addition, we examined modification indices to obtain a better fit. SEM analyses were done via Mplus 8.4 statistics software.

To validate the hypothesized model, some researchers suggested that rather than relying on one model, different models should be compared with one other to obtain the best fitting model [52]. This comparison would allow the researcher to look from different angle to better explore the complex the nature of social variables. For this purpose, we structured a competing model that assumes goal orientations predicted school-contextual variables and then teacher emotion regulation. We run both models and check their fit indices. As seen in Table 2, the original model yielded a better fit indices with lower chi-square and RMSEA values and higher CFI and TLI values. Thus, we stuck to the original model to examine the relations between teacher emotion regulation, goal orientation and school-contextual variables [52].

Table 2

Fit indices of the models
Model	χ (df)	RMSEA	CFI	TLI	SRMR
Original	992.47 (476)	.067	.950	.943	.075
Competing	1198.61 (476)	.079	.928	.920	.090

Descriptive results (mean, standardized deviation, Cronbach’s alphas, and skewness, kurtosis, and Pearson moment correlation coefficients) were given in Table 3. First, mean value for emotional regulation indicated that the teachers in the sample reported that they highly control and regulated their emotion and mood (in six-point Likert type, 1.00–2.66 for low, 2.67–4.33 for moderate, and 4.34-6.00 for high). The mean values for mastery goal orientation was at high level whereas for performance goal orientation was at moderate. Mean values for all support types, autonomy and recognition were at high level while discipline problems were at moderate level. Pearson correlation coefficients showed that all variables were statistically significantly related to emotional regulation. Mastery goal orientation and autonomy were positively and strongly correlated to emotional regulation while discipline problems had a weak and negative correlation with emotional regulation. Pearson correlation coefficients were less .80 cut-off value for multi-collinearity.

Table 3

Statistics for the Variables
	ER	MGO	PGO	COL	SUP	PAR	DIS	AUT	REC
ER	–
MGO	.52**	–
PGO	.15*	.33**	–
COL	.27**	.27**	.23**	–
MAN	.29**	.31**	.19**	.56**	–
PAR	.33**	.18**	.20**	.28**	.23**	–
DIS	− .14*	.01	.42**	.03	.14*	− .10	–
AUT	.40**	.38**	.15*	.51**	.54**	.40**	.02	–
REC	.34**	.32**	.19**	.62**	.52**	.46**	− .06	.64**	–
M	5.08	5.28	3.56	5.10	5.19	4.94	3.69	5.05	4.98
SD	0.85	0.82	1.31	1.05	1.06	0.97	1.48	0.82	0.93
α	.84	.82	.85	.87	.89	.84	.88	.65	.92
Skewness	-1.71	-3.02	0.02	-1.42	-1.71	-1.11	-0.04	-1.54	-1.51
Kurtosis	-1.12	2.87	2.83	1.86	3.22	-0.83	3.00	1.16	2.99
Note: * p < .05, ** p < .01, ER: Emotional regulation, MGO: Mastery goal orientation, PGO: Performance goal orientation, COL: Support from colleague, MAN: Support from manager, PAR: Support from parents, DIS: Discipline problems, AUT: Autonomy, REC: Recognition

Results of SEM

The first run of SEM yielded as χ² (476) = 992.47, p < .05. Although the chi-square test showed a significant difference between the hypothesized model and data, this interpretation could be misleading because the chi-square test was affected by the sample size (Kline, 2015). Some researchers recommended the ratio of chi-square to degree of freedom (less than 2.5) might indicate a sign of good fit. Other absolute fit indices, RMSEA value and Standardized Root Mean Square Residual (SRMR), was found to be .067 [.063, .071] and .075, respectively. These values were in acceptable fit indices range. Although CFI value was equal to the acceptable fit, .95, TLI was found to be .93, less than .95 good fit cut-off value. Therefore, we examined the modification indices and added covariance between support from mastery goal orientation and performance goal orientation. This covariance was reasonable because individual might have both types of goal orientation. The results of the rerun SEM were test χ² (475) = 915.32, p < .05, RMSEA = .062 [.056, .068], SRMR = .069, CFI = .96 and TLI = .95. These values were in acceptable fit indices range [51].

Figure 1 depicted the path coefficients and explained variance by the hypothesized model. It was found that the hypothesized model could explain 55.2% of variance in emotion regulation. In other words, the hypothesized model alone can explain more than half of variance in emotion regulation. Addition to this, the model successfully can explain 15.3% of variance in discipline, 52.8% in autonomy, 50.6% in recognition, 33.1% in performance goal orientation, and 47.4% mastery goal orientation. These variances explained by the hypothesized model indicated a large effect size (.01 for small effect, .09 for medium effect, and over .25 for large effect) [53].

In Fig. 1, arrows represent the casual relations, and the number does its strength in standardized form (β). Standardized coefficients showed that support from colleagues significantly and positively predicted recognition (β = .46, p < .01) and autonomy (β = .20, p < .05). The path between support from colleagues to discipline problems was not statistically significant (β = − .03, p = .79), Support from parents statistically significantly predicted discipline (β = − .16, p < .05), autonomy (β = .41, p < .01), and recognition (β = .41, p < .01). Support from manager was significantly related to discipline (β = .21, p < .01), autonomy (β = .41, p < .01), and recognition (β = .16, p < .01). Autonomy significantly and positively contributed to mastery goal orientation (β = .29, p < .01). Similarly, recognition positively predicted mastery goal orientation (β = .15, p < .05). Discipline problems were only statistically significantly associated with performance goal orientation (β = .43, p < .01). Emotion regulation was significantly and positively associated with mastery goal orientation (β = .55, p < .01), and negatively with performance goal orientation (β = − .38, p < .01).

We examined the indirect effects of school-contextual variables to emotion regulation through goal orientations. The indirect path coefficients were presented in Table 4. Support from colleagues indirectly effected the emotion regulation through autonomy (β = .111, p < .01), and recognition (β = .069, p < .05) through mastery goal orientation. Similarly support from parents indirectly predicted emotion regulation through (β = .238, p < .01), and recognition (β = .063, p < .05) through mastery goal orientation. Support from manager indirectly contributed to emotion regulation through autonomy (β = .217, p < .01) through mastery goal orientation and discipline problems (β = − .041, p < .05 through performance goal orientation.

Table 4

Indirect effects of variables in the model to emotion regulation
	MGO			PGO
	DIS	AUT	REC	DIS	AUT	REC
COL	.001	.111*	.069*	.005	− .011	− .024
PAR	.001	.238*	.063*	.032	− .024	− .023
MAN	− .001	.217*	.023	− .041*	− .022	− .008
* p < .05

The purpose of this study was to explore the complex interplay between teacher emotion regulation, goal orientation and school-contextual variables. For this purpose, quantitative data from 242 STEM teachers in Turkey were analyzed through SEM.

The results of study showed that teacher emotion regulation was at high level, indicating that in their classroom practices teachers often control and monitor their emotion. Goal orientation mean scores showed that the teachers were highly motivated for self-standards and moderately inspired to demonstrate their abilities to others. Mean values for supports demonstrated that teachers felt the most support from their supervisor whereas they did the least from parents. Teachers in the sample reported their teaching practices were moderately interrupted by discipline problems. Mean values for autonomy and recognition showed that teachers highly felt autonomy in their practices and recognition for their practices. In another study, Uzuntiryaki-Kondakci et al [47] reported that a mean score of 5.01 (0.61), at high level, for emotion regulation for Turkish science teachers. However, Moafian and Ostovar [54] reported that their sample of 817 Iranian EFL teachers had a moderate level of emotion regulation. This difference can be due to the cultural and contextual differences.

One important finding of this study was that mastery goal orientation was positively associated with emotion regulation while performance goal orientation did negatively with emotion regulation. In other words, the results of this study showed that high motivational goals to improve teaching skill for self-development yielded a high emotion regulation; however, high motivational goal to do better than others led to a less regulation of emotion. Previous studies reported that teachers regulated and managed their emotions to increase their effectiveness or positive expected outcomes [3]. In other words, teachers tend their emotions to not interfere with their teaching, had to control their anger to avoid it disrupting their lessons, or felt that too much emotion could lead to becoming overly focused on themselves [3]. Therefore, it is plausible to assume that mastery goal-oriented teacher who motivate themselves to enhance their skills and foster a positive classroom culture [55] tend to control their emotion. On the other hand, teachers who motivated themselves to do better than others are inclined to less control their emotions.

The results of this study showed that recognition and autonomy were positively associated with mastery goal orientation. That is, recognizing the teacher and giving autonomy for her teaching practices led to the teacher got motivated to improve her teaching skills in her practices. The reason might be that recognition advocates teachers’ well-being and autonomy affects teachers’ adaptations of new approach and professional development [29]. Consistent with the results of this study, Ertem et al [56] reported that teacher autonomy associated with Turkish teachers’ goal orientation. Similarly, Garvin's [57] study revealed that teachers experienced greater autonomy in schools where principals fostered an environment that encouraged professional development and collaboration among teachers. On the other hand, discipline problems were positively associated with performance goal orientation. That indicates that teachers who deal with more discipline problems in their classrooms tend to be oriented with doing better than others. Previous studies reported that discipline problems were positively associated with emotional exhaustion and depersonalization, and negatively with personal accomplishment. Moreover, performance-oriented teachers are more likely to adopt teacher-focused instructions [58]. Thus, it can be reasonable to assume that any discipline problems teachers encountered causes teachers to get motivated to do better than other in their teaching.

In this study, it was found that support from colleagues, parents and managers were related to discipline problems, recognition, and autonomy. The sign of the coefficients between supports from colleagues and recognition, and autonomy were positive, indicating that teachers who received more supports from their colleagues and managers felt recognition and autonomy in their practices of teachings. Similarly, teachers who received more support from the parents were more likely to feel more recognized and be autonomous. Also, support from parents negatively predicted discipline problems. In other words, when teachers got less support from parent, they encountered more discipline problems. This finding showed evidence for the importance of collaboration between teachers and parents to reduce discipline problems. One interesting finding was that support from manager positively predicted discipline problems. In other words, when they received more supports from managers they encounter more discipline problems. This might be since teachers who wanted to solve discipline problems were more likely to ask their managers’ help. Consistent with the results of this study, Skaalvik and Skaalvik [25] found that there was a negative correlation between support from parent and discipline problems.

The results of this study showed that supports from colleagues, parents and managers indirectly contributed to emotion regulation through goal orientations. The mediation path from supports to emotion regulation was through first autonomy and recognition and then mastery goal orientation. The positive sign indicated that the more supports from parents, colleagues and managers first led to more autonomy and recognition and then mastery goal orientation and finally the more emotion regulation teachers used. It has been observed that supports from colleagues had positive effects on individuals’ psychological well-being and performance [59]. For example, one study showed that individuals who receive high levels of colleague support have higher levels of mastery goals and that these individuals achieve more successful learning outcomes [60]. To better understand and strengthen this relationship, it is recommended to develop strategies to increase colleague support in educational and work environments [33]. Likewise, family and manager support help individuals feel independent and competent, reinforcing their sense of autonomy [61]. This support supports the processes of individuals making their own decisions, setting personal goals, and achieving these goals. Similarly, family and manager support also strengthen individuals' sense that their efforts are recognized and appreciated [62].

The other mediation path was only support from manager to emotion regulation, through first discipline problems and then performance goal orientation. The negative sign implies that the more teachers have received manager supports tend to have more discipline problems and then, more performance goal oriented but finally less emotion regulation in their teaching practices Discipline problems can weaken individuals' sense of independence and autonomy because it usually requires a controlling and authoritarian approach [63].

The results of this study indicated that school-contextual variables significantly contributed to emotion regulation. The hypothesized model successfully explained more than half of variance (55.2%) in emotion regulation. These results show that the socio-cultural environment in the schools are important determinants of how teachers regulate and control their emotions. Moreover, the path coefficients between goal orientation and emotion regulation underscore that what teachers want to accomplish in their work greatly contribute to how they regulate their emotions. The results of this study highlight that the interplay between teachers and parents and managers direct their goal orientation and then how they behave in their classroom.

Limitation

There are several limitations of the study. First, a great attention was paid to choose a comprehensive and representative sample for data collections to generalize the results for Turkey. Thus, fifty schools were included in data collection. However, Mugla Province is located in the Southwestern region of Turkey, which have highly experienced teachers profile from the Middle and East regions of Turkey in terms of teaching experience, may affect teacher emotion regulation. Thus, this caution should be considered in generalizing the findings of this study. Also, although 55.2% of variance of emotion regulation was explained, 44.8% still remains unexplained. Self-efficacy, teaching competence, motivation, etc are the other important variables that research has provided evidence of their effects on emotion regulation [7]. A more comprehensive model should be studied in different contexts.

Ethics approval and consent to participate

The research protocol underwent a thorough evaluation and received approval from the Scientific Research and Publication Ethics Committee in Mugla Sıtkı Kocman University (Protocol ID: 30). This study was done in accordance with the Declaration of Helsinki. All participants provided their written informed consent before taking part and retained the option to withdraw from the survey at any point before submission.

Funding

This research received no specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author Contribution

O.U. and MMA desinged the study.O. U. wrote the introduction, literature review, reviewed the manuscript and collected data.M. M. A. analyzed data, wrote the manuscript.

Acknowledgement

The research protocol underwent a thorough evaluation and received approval from the Scientific Research and Publication Ethics Committee in Mugla Sıtkı Kocman University (Protocol ID: 30). This study was done in accordance with the Declarationof Helsinki. All participants provided their written informed consent before taking part and retained the option to withdraw from the survey at any point before submission.

Data Availability

Data are available if any research contacts the corresponding author with a statement how data will be used.

Gkonou C, Miller ER. Relationality in language teacher emotion regulation: Regulating emotions through, with and for others. System. 2023;115:103046.
Gross JJ. The emerging field of emotion regulation: An integrative review. Rev Gen Psychol. 1998;2:271–299.
Sutton RE. Emotional regulation goals and strategies of teachers. Soc Psychol Educ. 2004;7(4):379–398.
Wang H, Burić I, Chang ML, Gross JJ. Teachers’ emotion regulation and related environmental, personal, instructional, and well-being factors: A meta-analysis. Soc Psychol Educ. 2023;26(6):1651-1696.
Sutton RE, Harper E. Teachers' emotion regulation. In: Saha LJ, Dworkin AG, editors. International handbook of research on teachers and teaching. Boston, MA: Springer US; 2009. p. 389-401.
Hutchison LF. Addressing the STEM teacher shortage in American schools: Ways to recruit and retain effective STEM teachers. Action Teach Educ. 2012;34(5-6):541-550.
Yang X, Du J. The effect of teacher self-efficacy, online pedagogical and content knowledge, and emotion regulation on teacher digital burnout: a mediation model. BMC Psychol. 2024;12(1):51.
Gross JJ. Emotion regulation: Current status and future prospects. Psychol Inq. 2015;26(1):1–26. https://doi.org/10.1080/1047840X.2014.940781.
Ochsner KN, Gross JJ. Thinking makes it so: A social cognitive neuroscience approach to emotion regulation. In: Vohs KD, Baumeister RF, editors. Handbook of self-regulation: Research, theory, and applications. New York: Guilford Press; 2004. p. 229–255.
Gross JJ, Sheppes G, Urry HL. Emotion generation and emotion regulation: A distinction we should make (carefully). Cogn Emot. 2011;25:765–781.
Gross JJ. Emotion regulation: Conceptual and empirical foundations. In: Gross JJ, editor. Handbook of emotion regulation. 2nd ed. Guilford; 2014. p. 3–20.
Jennings PA, Greenberg MT. The prosocial classroom: Teacher social and emotional competence in relation to student and classroom outcomes. Rev Educ Res. 2009;79(1):491–525. https://doi.org/10.3102/0034654308325693.
Baker CN, Peele H, Daniels M, Saybe M, Whalen K, Overstreet S, The New Orleans TISLC. The experience of COVID-19 and its impact on teachers’ mental health, coping, and teaching. Sch Psychol Rev. 2021;50(4):491–504.
Taxer JL, Gross JJ. Emotion regulation in teachers: The “why” and “how.” Teach Teach Educ. 2018;74:180–189. https://doi.org/10.1016/j.tate.2018.05.008.
Robinson LE, Valido A, Drescher A, Woolweaver AB, Espelage DL, LoMurray S, et al. Teachers, stress, and the COVID-19 pandemic: A qualitative analysis. Sch Ment Health. 2023;15(1):78–89.
Rauterkus H, Hennemann T, Hagen T, Krull J, Nitz J, Eiben K, et al. Teachers’ ability to regulate their emotions predicts their levels of stress in primary schools in Germany. J Curric Stud. 2024;1-12.
Taxer JL, Frenzel AC. Facets of teachers' emotional lives: A quantitative investigation of teachers' genuine, faked, and hidden emotions. Teach Teach Educ. 2015;49:78-88. https://doi.org/10.1016/j.tate.2015.03.003.
Ames C. Achievement attributions and self-instructions under competitive and individualistic goal structures. J Educ Psychol. 1984;76:478–487.
Dweck CS. Self-theories: Their role in motivation, personality, and development. Philadelphia: Psychology Press; 1999.
Anderman EM, Wolters CA. Goals, values, and affect: Influences on student motivation. In: Alexander PA, Winne P, editors. Handbook of educational psychology. Mahwah, NJ: Erlbaum; 2006. p. 369–89.
Maehr ML, Zusho A. Achievement goal theory: The past, present, and future. In: Wentzel KR, Wigfield A, (ed). Handbook of motivation at school. New York: Routledge; 2009. p. 77–104.
Elliot A, Dweck CS, (ed). The handbook of competence and motivation. New York: Guilford Press; 2005.
Was CA. Academic achievement goal orientation: Taking another look. Electron J Res Educ Psychol. 2006;10:529-550.
Kıran D, Sungur S. Science teachers' motivation and job satisfaction in relation to perceived school context. Educ Sci. 2018;43:61-80.
Skaalvik EM, Skaalvik S. Teacher self-efficacy and teacher burnout: A study of relations. Teach Teach Educ. 2010;26(4):1059-1069.
Rubie-Davies CM, Flint A, McDonald LG. Teacher beliefs, teacher characteristics, and school contextual factors: What are the relationships?. Br J Educ Psychol. 2012;82(2):270-288.
Brault MC, Janosz M, Archambault I. Effects of school composition and school climate on teacher expectations of students: A multilevel analysis. Teach Teach Educ. 2014;44:148–159.
Adler MG, Fagley NS. Appreciation: individual differences in finding value and meaning as a unique predictor of subjective well-being. J Pers. 2005;73:79–114.
Algoe SB, Gable SL, Maisel NC. It's the little things: Everyday gratitude as a booster shot for romantic relationships. Pers Relatsh. 2010;17(2):217-233.
Fagley NS, Adler MG. Appreciation: a spiritual path to finding value and meaning in the workplace. J Manag Spiritual Relig. 2012;9:167-187.
Zembylas M, Papanastasiou EC. Modeling teacher empowerment: The role of job satisfaction. Educ Res Eval. 2005;11:433-459.
Durak HY, Seferoğlu SS. Examination of teachers’ sense of burnout in terms of various variable. Gazi Univ J Gazi Educ Fac. 2017;37(2):759-788.
Deci EL, Ryan RM. The "what" and "why" of goal pursuits: Human needs and the self-determination of behavior. Psychol Inq. 2000;11(4):227-268.
Öztürk İH. Teacher’s role and autonomy in instructional planning: the case of secondary school history teachers with regard to the preparation and implementation of annual instructional plans. Educational Sciences: Theory & Practice. 2012;12(1):271-299.
Çolak İ, Altınkurt Y. The relationship between school climate and teacher autonomy behaviors. Kuram ve Uygulamada Eğitim Yönetimi. 2017;23(1):33-71.
Siklos S, Kerns KA. Assessing need for social support in parents of children with autism and Down syndrome. J Autism Dev Disord. 2006;36(7):921-933.
Field LK, Buitendach JH. Work engagement, organisational commitment, job resources and job demands of teachers working within disadvantaged high schools in KwaZulu-Natal. South Afr J Psychol. 2012;22:87–95.
Karaçoban-Tuna S, Aslan H. The relationship between perceived social support and organizational commitment levels of primary and secondary school teachers. Univ J Educ Res. 2018;6(5):983-993.
Cohen S, Gottlieb B, Underwood L. Social relationships and health. In: Cohen S, Underwood L, Gottlieb B, editors. Measuring and intervening in social support. New York: Oxford University Press; 2000. p. 3–25.
Skaalvik EM, Skaalvik S. Teacher job satisfaction and motivation to leave the teaching profession: Relations with school context, feeling of belonging, and emotional exhaustion. Teach Teach Educ. 2011;27(6):1029-1038.
Song S, Alpaslan MM. Factors impacting on teachers' job satisfaction related to science teaching: A mixed methods study. Sci Educ Int. 2015;26(3):358-375.
Hobson AJ. On being bottom of the pecking order: Beginner teachers’ perceptions and experiences of support. Teach Dev. 2009;13(4):299-320.
Soini T, Pyhältö K, Pietarinen J. Pedagogical well‐being: reflecting learning and well‐being in teachers’ work. Teach Teach. 2010;16(6):735-751.
Gersten R, Keating T, Yovanoff P, Harniss MK. Working in special education: Factors that enhance special educators' intent to stay. Except Child. 2001;67(4):549-567.
Wang L, Yan F. Emotion regulation strategy mediates the relationship between goal orientation and job search behavior among university seniors. J Vocat Behav. 2018;108:1-12.
Çapa‐Aydin Y, Sungur S, Uzuntiryaki E. Teacher self‐regulation: examining a multidimensional construct. Educ Psychol. 2009;29(3):345-356.
Uzuntiryaki-Kondakci E, Kirbulut ZD, Sarici E, Oktay O. Emotion regulation as a mediator of the influence of science teacher emotions on teacher efficacy beliefs. Educ Stud. 2022;48(5):583-601.
Pietarinen J, Pyhältö K, Soini T, Salmela-Aro K. Reducing teacher burnout: A socio-contextual approach. Teach Teach Educ. 2013;35:62-72.
Hoyle RH, Gottfredson NC. Structural equation modeling with latent variables. In: Cooper H, Coutanche MN, McMullen LM, Panter AT, Rindskopf D, Sher KJ, editors. APA handbook of research methods in psychology: Research designs: Quantitative, qualitative, neuropsychological, and biological. 2nd ed. Washington, DC: American Psychological Association; 2023. p. 459-490.
DiStefano C, Morgan GB. A comparison of diagonal weighted least squares robust estimation techniques for ordinal data. Struct Equ Model Multidiscip J. 2014;21(3):425-448.
Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct Equ Model Multidiscip J. 1999;6(1):1-55.
Kline RB. Principles and practice of structural equation modeling. New York: Guilford Publications; 2015.
Cohen J. Statistical power analysis for the behavioral sciences. Routledge; 2013.
Moafian F, Ostovar S. Validation of the English version of the teacher self-regulation scale in an EFL context. Middle-East J Sci Res. 2012;12(6):774-782.
Butler EA. Emotion regulation in cultural context. In Barnow S, Balkir N, editors. Cultural variations in psychopathology: From research to practice. Hogrefe Publishing, Boston 2012;9-114.
Ertem HY, Arslan A, Özenir Üren E. The role of teacher autonomy and school climate on goal orientations for teaching. Psycho-Educational Res Rev. 2021;10(2):203–212.
Garvin NM. Teacher autonomy: Distinguishing perceptions by school cultural characteristics. University of Pennsylvania; 2007.
Yin H, Han J, Lu G. Chinese tertiary teachers’ goal orientations for teaching and teaching approaches: The mediation of teacher engagement. Teach High Educ. 2017;22(7):766-784.
Rosen B, Harris N, Kacmar KM. The impact of coworker support on employee turnover in the face of downsizing. J Bus Psychol. 2010;25(3):441-455.
Karabenick SA, Dembo MH. Dynamics of academic help-seeking: The role of self-regulation. In: Zimmerman BJ, Schunk DH, (ed). Handbook of self-regulation of learning and performance. Routledge; 2011. p. 268-82.
Grolnick WS, Ryan RM. Parent styles associated with children’s self-regulation and competence in school. J Educ Psychol. 1989;81(2):143-154.
Wang MT, Chen FF, Zhang Q. Parental support for autonomy and child development: A longitudinal study from middle childhood to adolescence in China. J Adolesc. 2016;50:52-63.
Gurland ST, Grolnick WS. Perceived threat, controlling parenting, and children’s achievement orientations. Motiv Emot. 2005;29(2):103-121.

No competing interests reported.

Roles of School-Context and Goal Orientation on Emotion Regulation amongst Turkish Middle-school STEM Teachers. A Structural Equation Modeling Study

Status:

Version 1

Abstract

Figures

Introduction

Emotion regulation

Goal Orientation

School-context

Recognition

Discipline Problems

Autonomy

Support

Relations amongst Variables and the Hypothesized Model

Research Questions

Methodology

Participants and Context

Data Collection Tools

Teacher Emotional Control Scale

Teacher Goal Orientation Scale

School Contextual Scale

Data Collection and Analysis

Results

Results of SEM

Discussion and Conclusion

Conclusion

Limitation

Declarations

Ethics approval and consent to participate

Funding

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

Status:

Version 1