Antecedents of teachers’ professional competencies

Abstract

Non-behavioral factors potentially enhance the development of teachers’ professional competencies. Because there is a lack of research examining the direct relationships between teachers’ professional competencies and these non-behavioral factors, present study aimed to identify the main cognitive, personality and motivational antecedents of professional competencies among Slovak in-service teachers. The relationships between professional competencies, cognitive abilities (including executive functions, cognitive reflection and scientific reasoning), personality and motivation were measured in order to identify the main antecedents of teachers’ professional competencies. A total of 443 in-service teachers (88.7% women) aged 21–70 years old with 0 to 50 years of practice participated in the data collection. The main positive antecedents of professional competencies were having personality traits of agreeableness, conscientiousness and open-mindedness, having intrinsic and altruistic motivation and having developed executive function plans and time management. The main negative antecedent of professional competencies was the personality trait negative emotionality. It follows that these non-behavioral factors should be considered in the selection of student applicants and that more should be done to develop cognitive abilities during teacher training, including social psychological training.

Keywords:

• professional competency
• teacher
• motivation
• personality
• cognition
• executive function

1. Introduction

The teaching profession depends on skills and professional competencies, which can be summarized by the term professional competence. Professional competencies enable a teacher to perform skilled activities on a professional basis. Different views on the definition and classification of professional competencies appear in the literature. In general, teachers’ professional competencies are the skills, dispositions, attitudes and knowledge required for the effective practice of the teaching profession (Moreno-Murcia et al., 2015). This study used the competence model (Kasáčová, 2006; Kasáčová et al., 2006) developed in the cultural and legislative environment in which the presented research was carried out. This competence model includes (1) student-centered competencies, (2) teacher self-development competencies and (3) competences oriented toward educational processes. In our study we focused on didactic competencies (as competences oriented toward educational processes), preferred interaction and teaching style (as student-centered and teacher self-development competencies), as well as cognitive, personal and motivational antecedents.

Teachers’ professional competencies are often mistaken for didactic competencies. However, didactic competencies are specifically related to planning, organizing, managing, evaluating and implementing the teaching process (Rovňanová, 2015). Teachers who have acquired and developed didactic competencies should have knowledge of pedagogy, developmental psychology, didactics and innovative teaching forms and methods; they should be able to design teaching aims, content, methods and forms, and evaluate the educational process (Šuťáková, 2017).

An understanding of teaching methods and forms that support active learning is required to have an individual teaching style. Teaching style represents how a teacher communicates, manages tasks, oversees processes and socializes with students (Ford et al., 2016; Grasha, 2002; Mohanna et al., 2007). Mohanna et al. (2007) analyzed different learning and teaching styles to help future teachers develop teaching strategies and identified six learning styles: a versatile, flexible and adaptable teacher; a sensitive student-centered teacher; an official teacher who adheres to the curriculum; a teacher who prefers direct facts; a conference teacher; and a one-time teacher. Furthermore, the Grasha-Reichmann model (Ford et al., 2016; Grasha, 2002) emphasized the individuality of students and their learning styles and identified five basic styles that prevail in the teaching process: expert, formal authority, personal model, facilitator and delegate. By combining these styles, the teacher can adapt the educational process to the needs of individual groups of students. Based on Mohanna et al. (2007), Ford et al. (2016) and Grasha (2002), the present study examined four teaching styles revealed in previous research (Ballová Mikušková, 2022) as: supportive, goal-oriented, knowledge-oriented and managerial.

Finally, the present study focused on the relatively stable way teachers interact, behave and communicate – the interaction style. We used Leary’s model of personality (Leary, 1957) and derived a model of teacher interaction behavior (Wubbels et al., 1987) in which a teacher’s interactions can be located in a space defined by two basic axes, where one axis shows the degree of cooperation in interaction and the other axis shows the degree of control in communication. The interaction style model defines eight sectors and eight aspects of teacher behavior: organization, help, understanding, responsibility, uncertainty, dissatisfaction, rebuke and severity. Preferred teaching styles, such as leadership, understanding and responsibility, were associated with the self-perceived prosocial behavior of students, whereas other styles, such as strict, uncertain, dissatisfied and admonishing, were associated with a lower self-perceived prosocial behavior of students (Sádovská & Kusý, 2019).

1.1. Possible antecedents of professional competencies

Previous studies have investigated teaching competencies centered on the cognitive, affective and behavioral characteristics and professional, personal and social competences of teachers (Zagyváné Szűcs, 2017), teaching focused on student outcomes, teacher behaviors and classroom processes (Lupascua et al., 2014; Moreno Rubio, 2009), and teaching connected with qualification, societal requests and quality models of teaching (Fenstermacher & Richardson, 2005; van de Grift, 2014). There are also non-behavioral factors that potentially enhance the development of professional competencies, but there is a lack of research examining the direct relationships between teachers’ professional competencies (interaction and teaching styles and didactic competencies) and these non-behavioral factors (like cognitive abilities, personality traits and motivation for teaching profession). So, the present study may bring an original view of teachers’ professional competencies and their possible antecedents based on the real-world characteristics of in-service teachers.

1.1.1. Cognitions

An adequate level of cognition can help avoid labelling, social stereotypes and prejudice toward students and increase teachers’ professional competencies (Huber et al., 2018). Although cognitive ability development is part of pre-gradual training, teachers’ cognitive abilities decline (Čavojová, 2015; Grönqvist & Vlachos, 2016; Kosturková, 2013). The question is whether individual differences in cognition relate to how teachers carry out their professions and professional competencies. Cognitive reflection helps in the development of professional competencies and education (Čavojová & Jurkovič, 2017c; Jursová Zacharová et al., 2019) and prevents cognitive biases, unwarranted beliefs, prejudice and stereotyping (Swami et al., 2014; Trippas et al., 2015). Although cognitive reflection among Slovak pre-service teachers was low to moderate, in-service teachers achieved better results on cognitive reflection tests than pre-service teachers (Ballová Mikušková, 2018; Čavojová & Jurkovič, 2017a, 2017c). Similarly, Janssen et al. (2019) reported that teaching practice was associated with a higher level of cognitive reflection, which was associated with a stronger disposition toward effortful thinking.

There is consensus that promoting scientific reasoning skills should be one of the goals of education (Kuhn et al., 1988). Teachers acquire epistemic knowledge during undergraduate training; however, well-developed scientific reasoning is necessary for in-depth understanding (Krell et al., 2020). Scientific reasoning evaluates whether information is consistent with scientific evidence, which requires an understanding of the methods and principles of science; therefore, scientific knowledge increases with scientific reasoning (Drummond & Fischhoff, 2017). Using well-developed scientific reasoning, one can explain natural phenomena, proceed in the domain, develop at a professional level and be less subject to unwarranted statements, pseudoscience or paranormal beliefs (Čavojová et al., 2020).

Analytic thinking is closely related to executive functions, which are mental processes controlling and working in conjunction with cognitive functions (Burgess, 2010), and the highest executive and self-control bodies with control and integration functions (Brown, 2006). Executive functions are essential for proper and effective information processing, management and academic success and help with planning, organization and the interplay of action and thinking (Strait et al., 2020). Moreover, executive functions prevent inappropriate reactions and job stress and help resist distractions, maintain certain behaviors for a long time, allow the use of multiple sources of information, understand complex situations and plan and proceed comprehensively (Friedman-Krauss et al., 2014). Despite the importance of executive functions in analytical thinking and the teaching profession, research in this domain is limited (Corcoran & O’Flaherty, 2017).

1.1.2. Personality and motivation

Personality traits determine teachers’ performance, including motivation and job retention, level of professionalism and communication skills and the ability to model concepts in their content area (Bastian et al., 2017; Klassen & Tze, 2014) and relate to work engagement and job satisfaction (Kokkinos, 2007). Based on the Big Five model of personality, Costa and McCrae (1992) identified teachers with higher extraversion and lower neuroticism as being effective teachers. Similarly, Aydın et al. (2013) revealed that extraversion was the strongest predictor of teachers’ professional competencies, and neuroticism had a negative effect on all teaching competencies. Other studies found that open-mindedness was not a significant predictor of teachers’ professional competencies (Aydın et al., 2013; Han & Pistole, 2017), and agreeableness and conscientiousness did not explain teacher performance (Aydın et al., 2013; Bastian et al., 2017). Moreover, Sanderson and Kelley (2014) demonstrated that pre-service teachers scored lower on neuroticism and higher on open-mindedness than in-service teachers.

Personality was a predictor of motivation for study-teaching: previous studies (Tomšik, 2019; Tomšik & Verešová, 2016) identified the following possible motivations for becoming a teacher: intrinsic, external, altruistic and alternative career choice. Research on motivations as predictors of professional competencies is rare and focuses on examining teaching career motivations (Giersch et al., 2021; Şahin, 2014; Watt et al., 2012). In another study, a higher level of extraversion and agreeableness predicted intrinsic motivation and satisfaction with the choice of the teaching profession (Jugović et al., 2012). However, Sokolová et al. (2019) compared students with teaching as their first or alternative choice and did not find significant differences in any of the monitored dimensions.

1.2. Present study

The objective of the study is to investigate which personality traits, motivation factors and cognitive abilities support better developed professional competences of teachers. Specifically, we aimed to identify the cognitive, personality and motivational antecedents of professional competencies among Slovak in-service teachers to answer the question whether and how professional competencies relate to cognitive abilities (including cognitive reflection and scientific reasoning), personality traits and motivations for choosing the teaching profession (for the conceptual framework, see Figure 1). As age and practice significantly affect a teacher’s professional development (Corcoran & O’Flaherty, 2017; Dias-Lacy & Guirguis, 2017) and there is feminization of the teaching profession (NÚCEM, 2020), we included age, practice and sex as control variables in the analyses. This study is explanatory and seeks to provide evidence for a better theoretical and practical background in undergraduate training, lifelong learning and self-education.

Figure 1. Conceptual framework.

2. Methods

2.1. Participants and design

All preschool, elementary and secondary schools in Slovakia were invited to participate in the study via email, as lists of email addresses of headmasters are freely available on the (CVTI, 2021). We asked the headmasters to distribute research links among their teachers. Data were collected from October to November 2021 using an online questionnaire (www.survio.com/sk/). As a reward for participation, participants were entered into a drawing for vouchers for the purchase of books worth €30, €20 and €15 and sets of books produced by the department.

A total of 443 in-service teachers (88.7% women) aged 21–70 years (M = 44.29; SD = 10.38) who had been practicing teaching from 0 to 50 years (M = 18.15; SD = 11.43) participated in the data collection. This sample size provided sufficient power (.80) to detect effect sizes of d > .26 in t-tests and correlations of r > .086 based on post-hoc sensitivity analysis conducted in G*Power 3.1.9 (Faul et al., 2007). After signing the informed consent form, participants completed several demographic questions and instruments in the following order: demographics, Executive Skills Questionnaire-Revised, Questionnaire on Teacher Interaction—Self-Assessment, Cognitive Reflection Test, Didactic Competencies Questionnaire, Scientific Reasoning Scale, Slovak Teaching Style Questionnaire, Scale of Motivation for Choosing Teaching Profession and the Big Five Inventory. The study was conducted according to the ethical principles of the American Psychological Association. The data were anonymized and shared using OSF (https://osf.io/p2ekq).

2.2. Instruments

Since the willingness of teachers to participate in research is low in Slovakia, we opted for self-report questionnaires instead of performance tests to collect data from a larger number of in-service teachers. Questionnaires measuring the professional competencies of teachers were tested in a pilot study (Ballová Mikušková, 2022) and achieved acceptable psychometric indicators. Common method bias (Kock, 2020; Tehseen et al., 2017; Widodo et al., 2022) was not present in our study for professional competencies instruments (Harman’s single factor score), and the total variance extracted by one factor was low (23.23%).

Interaction styles were measured using the modified Slovak version of the Questionnaire on Teacher Interaction (QTI). In the original version of the QTI (Gavora et al., 2003; Wubbels & Levy, 2005), students evaluate their teachers, and each teacher receives a score for each of the eight sectors of teacher behavior based on Leary’s personality model: leadership, helpful, understanding, student-teacher responsibility, uncertain, dissatisfied, objecting and strict. The present study used a modified version of the Questionnaire on Teacher Interaction—Self-assessment (QTI-S), adjusted for the self-assessment of teachers (Ballová Mikušková, 2022; Verešová, 2021). This tool includes 40 statements regarding teaching behavior rated on a five-point Likert scale (1 = never; 5 = always).

Teaching styles were measured using the Slovak Teaching Style Questionnaire (STSQ; Ballová Mikušková, 2022), which is a combination of items from the Teaching Style Inventory (Ford et al., 2016; Grasha, 2002) and the Staffordshire Evaluation of Teaching Styles (Mohanna et al., 2007). This tool included 20 items rated on a five-point Likert scale (1 = strongly disagree; 5 = strongly agree). The average scores for the four teaching styles (supporting, goal-oriented, knowledge-oriented, and managerial) were computed.

Finally, didactic competencies were measured using the Didactic Competencies Questionnaire (DCQ; Ballová Mikušková, 2022; Rapsová et al., 2021). This tool included 57 items on teaching behavior in five lesson phases (planning and preparation, realization, classroom climate, diagnostics and evaluation, and self-reflection) rated on a five-point Likert scale (1 = strongly disagree; 5 = strongly agree).

Cognitive reflection was measured using the seven-item version of the Cognitive Reflection Test (CRT (Frederick, 2005; Toplak et al., 2011),; which consists of simple numerical and verbal tasks that lead participants to intuitive but incorrect answers. The correct answer requires suppression of the first intuitive answer and engagement in rational, deliberate thinking. Participants received one point for each correct answer. The total score was computed, and a higher score indicated higher cognitive reflection.

Scientific reasoning was measured using the short Slovak version of the Scientific Reasoning Scale (SRS; Bašnáková et al., 2021; Čavojová et al., 2020; Drummond & Fischhoff, 2017), which consists of six tasks. The SRS measures the ability to evaluate evidence, including blinding, causation versus correlation, confounding variables, construct validity, control group, ecological validity and random assignment to conditions. In each task, participants had to read short texts and select whether they agreed or disagreed with the conclusions. The sum score of the correct answers was computed, and a higher score indicated higher scientific reasoning.

Executive functions were measured using the Executive Skills Questionnaire-Revised (ESQ-R (Strait et al., 2020),; which is based on the Executive Skills Questionnaire (Dawson & Guare, 2018). The ESQ-R measures executive functions as skills rather than abilities using 25 self-assessment items: plan management (the ability of individuals to perform tasks by creating and managing a plan), time management (the ability to manage various aspects of time), organization (the ability to set up and maintain a system to keep track of information and things), emotional regulation (the ability to control emotions to complete tasks and achieve goals), and behavioral regulation (the potential for self-control and ability to anticipate the consequences of one’s actions before the actual behavior). Answers were rated on a five-point scale (1=never, rarely; 5=always). Higher scores indicated problems with that area of executive functions.

We used the short form of the Big Five Inventory (BFI-2-S; Kohut et al., 2020) to measure five personality traits: extraversion, agreeableness, conscientiousness, negative emotionality and open-mindedness. Participants had to assess 30 statements (six items for each trait) on a five-point scale (1 = strongly disagree; 5 = strongly agree). The mean scores for all five domains were computed, with a higher score indicating a stronger personality trait.

Individual career choice motivations were assessed using the Scale of Motivation for Choosing Teaching Profession (SMVUP-4-S; Tomšik & Verešová, 2016). This tool included 48 items rated on a five-point Likert scale (1 = strongly disagree; 5 = strongly agree). The SMVUP-4-S measured 12 types of motivations grouped into four categories: intrinsic motivation (interest, self-perception of teaching skills, work potential and previous experience), extrinsic motivation (benefits, income, social status and significant others), altruistic motivation (prosocial behavior, work with children and work with youth) and alternative choice. A higher score indicated a higher level of motivation.

2.3. Data analyses

Descriptive statistics (mean, standard deviation, skewness and kurtosis) for all measured variables were computed. The internal consistency of all instruments was measured using Cronbach’s alpha and using the Kuder-Richardson formula 21 (a measure of reliability for an instrument with binary variables) in the case of the Cognitive Reflection Test and Scientific Reasoning Scale. Correlations between measured variables were computed using Pearson’s correlation. Finally, a hierarchical regression analysis was conducted with demographics entered as control variables in Step 1 and personality traits, motivations and cognitions entered as independent variables in Steps 2, 3 and 4, respectively.

3. Results

Descriptive statistics and internal consistency coefficients (Cronbach’s alpha for all measures and Kuder-Richardson formula 21 for the cognitive reflection test) are presented in Table 1.

Table 1. Descriptive statistics

	N	α	M	SD	min	max	skewness	kurtosis
age	442	-	44.29	10.38	21	70	−0.07	−0.64
practice	443	-	18.15	11.43	0	50	0.28	−0.83
interaction styles
leadership	443	.74	4.31	0.52	2.6	5	−0.61	−0.02
helpful	443	.75	4.51	0.50	1.8	5	−1.25	2.12
understanding	443	.70	4.37	0.53	2.2	5	−1.14	1.27
student-teacher responsibility	443	.57	4.13	0.55	1.8	5	−0.57	0.30
uncertain	443	.63	1.95	0.72	1	4.5	0.68	−0.01
dissatisfied	443	.65	1.81	0.60	1	4.2	0.85	0.81
objecting	443	.66	1.71	0.54	1	4	0.99	1.24
strict	443	.68	3.02	0.73	1	4.8	−0.16	−0.21
teaching styles
supporting	443	.61	3.65	0.65	1.5	5	0.02	−0.11
goals-oriented	443	.75	3.12	0.79	1.25	5	0.07	−0.28
knowledge-oriented	443	.71	3.74	0.74	1.25	5	−0.29	−0.02
manager	443	.81	4.22	0.68	1.25	5	−0.81	0.79
didactic competencies
planning a preparation	443	.80	4.10	0.51	2.23	5	−0.50	0.27
realization	443	.86	4.09	0.48	2.31	5	−0.48	0.12
climate	443	.75	4.37	0.50	2.88	5	−0.80	0.24
diagnostics and evaluation	443	.87	4.10	0.54	2.14	5	−0.57	−0.09
self-reflection	443	.79	4.16	0.77	0.6	5	−0.96	0.81
personality
extraversion	443	.69	3.77	0.65	1.67	5	−0.22	−0.24
agreeableness	443	.69	4.30	0.54	2.5	5	−0.74	0.02
conscientiousness	443	.71	4.20	0.61	2.17	5	−0.66	−0.03
negative emotionality	443	.79	2.12	0.69	1	4.5	0.43	−0.19
open-mindedness	443	.63	4.03	0.62	2	5	−0.28	−0.63
motivation
intrinsic motivation	443	.86	3.64	0.75	1.25	5	−0.30	−0.53
extrinsic motivation	443	.84	2.28	0.66	1	4.5	0.35	−0.17
altruistic motivation	443	.81	3.67	0.75	1	5	−0.21	−0.25
alternative choice	443	.66	1.65	0.81	1	5	1.50	2.30
cognitions
cognitive reflection	443	.77	3.01	2.25	0	7	0.37	−1.11
scientific reasoning	443	.29	4.31	0.99	1	6	−0.80	0.67
executive functions
plan management	443	.83	1.97	0.54	1	3.82	0.55	0.22
time management	443	.58	2.26	0.63	1	4.5	0.24	0.03
organization	443	.72	1.96	0.82	1	4.67	0.85	0.13
emotional regulation	443	.52	2.33	0.67	1	4.33	0.31	−0.09
behavioral regulation	443	.53	2.62	0.64	1	4.75	−0.02	0.21

Note: N—number; M—mean; SD—standard deviation; α – internal consistency measured as Cronbach’s alpha (for the cognitive reflection test and scientific reasoning scale using Kuder-Richardson formula 21); min—minimum; max—maximum.

All possible antecedents were correlated with professional competencies (Appendix). The interaction styles leadership, helpful, understanding and student-teacher responsibility correlated positively with personality traits (except negative emotionality—there were negative relationships), intrinsic and altruistic motivation (and negatively with extrinsic motivation and alternative choice) and developed executive functions. The uncertain, dissatisfied and objecting interaction styles had relationships in the opposite direction; the strict interaction style correlated positively only with extraversion and conscientiousness (and negatively with agreeableness), altruistic motivation, cognitive reflection, and developed plan management and poorly developed emotional regulation.

A hierarchical regression analysis was conducted with demographics (sex, age and years of practice) entered in Step 1 as control variables, and personality traits, motivations and cognition entered as independent variables in Steps 2, 3 and 4. Table 2a-c present the regression statistics.

Table 2a. Hierarchical regression analysis to predict interaction styles

	leadership	helpful	understanding	student-teacher responsibility	uncertain	dissatisfied	objecting	strict
sex	.018	.008	.018	.044	.009	−.047	−.018	−.106*
age	.067	−.126	−.073	.044	.153*	.003	−.042	.091
practice	−.023	.083	−.003	.085	−.156*	.034	.000	.009
extraversion	.092*	.070	−.060	.011	−.237***	−.075	.038	.077
agreeableness	.105*	.261***	.354***	.202***	.044	−.211***	−.218***	−.237***
conscientiousness	.189**	.050	−.051	.034	.104	.174**	.108	.374***
negative emotionality	−.102	−.041	−.053	−.002	.285***	.330**	.309***	.130*
open-mindedness	.099*	.089	.043	.051	.012	.003	.026	−.043
intrinsic motivation	.229***	.177***	.094	.092	.006	−.089	−.072	.005
extrinsic motivation	−.042	−.106*	−.109*	−.179***	.098*	.082	.043	.083
altruistic motivation	−.039	.014	.085	.098*	−.095	.011	−.010	.115*
alternative choice	.075	.083	.017	.019	.043	−.022	.029	.022
cognitive reflection	.016	−.061	−.010	.014	−.062	.010	.032	.144**
scientific reasoning	.037	.065	.120**	.083	−.035	−.049	−.032	−.085
plan management	−.188**	−.093	−.225***	−.152*	.212***	.156*	.227***	−.108
time management	−.103*	−.072	.000	−.047	.066	.012	−.065	.054
organization	−.025	−.036	.060	.142*	.032	.097	.034	.047
emotional regulation	.203***	.080	.090	.026	.066	.067	.123*	.095
behavioral regulation	.039	.082	.187***	.152**	−.010	−.052	.056	.100*
	R^2=.313; ΔR^2=.022; F(19,421) = 10.083***	R^2=.429; ΔR^2=.043***; F(19,421) = 16.626***	R^2=.290; ΔR^2=.061***; F(19,421) = 9.054***	R^2=.251; ΔR^2=.046***; F(19,421) = 7.439***	R^2=.418; ΔR^2=.058***; F(19,421) = 15.910***	R^2=.394; ΔR^2=.034**; F(19,421) = 14.411***	R^2=.433; ΔR^2=.059**; F(19,421) = 16.944***	R^2=.186; ΔR^2=.045**; F(19,421) = 5.063***

Note: Standardized betas are reported, *p < .05; **p < .01; ***p < .001.

First, hierarchical multiple regression revealed that the personality trait agreeableness was associated with variability in the interaction styles leadership, helpful, understanding and student-teacher responsibility (low agreeableness was associated with variability in dissatisfied, objecting and strict styles); higher negative emotionality together with problem with plan management was associated with variability in uncertain, dissatisfied and objecting styles. Next, low extrinsic motivation was associated with variability in the interaction styles helpful, understanding and student-teacher responsibility, and developed plan management was associated with variability in the interaction styles leadership, understanding and student-teacher responsibility (more details are in Table 2a and in the Appendix).

Second, hierarchical multiple regression revealed that the supporting teaching style was associated with female sex, with variability in low negative emotionality, high open-mindedness and developed time management. The goal-oriented teaching style was associated with variability in conscientiousness, teaching profession as an alternative choice, lower scientific reasoning and developed behavioral regulation. On the other hand, the knowledge-oriented teaching style was associated with higher age, with variability in conscientiousness and intrinsic motivation. Finally, the manager teaching style was associated with variability in extraversion, lower negative emotionality, higher open-mindedness, intrinsic and altruistic motivation and lower cognitive reflection (more details are in Table 2b and in Table A1 in the Appendix).

Table 2b. Hierarchical regression analysis to predict teaching style

	supporting	goal-oriented	knowledge-oriented	manager
sex	.114*	−.022	−.049	.025
age	.034	.106	.236*	.041
practice	.117	−.076	−.177	.026
extraversion	.041	.011	.040	.124*
agreeableness	.085	−.013	.000	.066
conscientiousness	−.098	.227**	.184*	−.064
negative emotionality	−.145*	.046	−.007	−.145*
open-mindedness	.231***	−.056	−.043	.249***
intrinsic motivation	.091	.115	.152*	.195***
extrinsic motivation	.009	.067	.018	−.044
altruistic motivation	.084	.075	.072	.163***
alternative choice	.034	.156**	.088	.022
cognitive reflection	−.024	−.075	−.056	−.100**
scientific reasoning	.017	−.147**	−.139	.016
plan management	.108	.101	.051	−.025
time management	−.125*	−.043	−.018	−.068
organization	.007	−.008	−.063	.029
emotional regulation	.040	.006	.088	.066
behavioral regulation	−.038	−.108*	−.071	.009
	R2=.226; XR2=.012; F(19,421) = 6.452***	R2=.151; XR2=.044**; F(19,421) = 3.932***	R2=.153; XR2=.038*; F(19,421) = 4.005***	R2=.401; XR2=.014; F(19,421) = 14.862***

Note: Standardized betas are reported, *p < .05; **p < .01; ***p < .001.

Third, hierarchical multiple regression revealed that planning and preparation of teaching was associated with female sex, practice, conscientiousness, open-mindedness, intrinsic motivation and problems with behavioral motivation. Realization of teaching was associated with variability in practice, extraversion, open-mindedness, intrinsic and altruistic motivation and problems with emotional regulation. Classroom climate was associated with variability in extraversion, open-mindedness, intrinsic motivation and developed time management. Diagnostics and evaluation were associated with variability in agreeableness, open-mindedness, intrinsic and low extrinsic motivation, plan management and problems with emotional regulation. Finally, self-reflection was associated with variability in female sex, open-mindedness and intrinsic motivation (more details are in Table 2c and in Table A2 in Appendix).

Table 2c. Hierarchical regression analysis to predict didactic competencies

	planning and preparation	realization	climate	diagnostics and evaluation	self-reflection
sex	.104*	.076	.009	.057	.115*
age	−.092	−.076	.077	−.009	.092
practice	.204*	.175**	.024	.132	.019
extraversion	−.015	.129*	.165***	.056	.002
agreeableness	.049	.091	.056	.175**	.109
conscientiousness	.238***	.095	.121	−.007	.109
negative emotionality	.007	−.103	−.128*	−.019	.040
open-mindedness	.217***	.187***	.117*	.207***	.165**
intrinsic motivation	.108*	.205***	.114*	.205***	.119*
extrinsic motivation	−.001	−.055	−.057	−.088**	−.073
altruistic motivation	.085	.088*	.039	.068	.076
alternative choice	−.046	.047	−.054	.031	−.037
cognitive reflection	−.038	.004	−.011	.009	−.001
scientific reasoning	−.042	−.016	.048	−.002	.057
plan management	−.081	−.085	−.062	−.136*	−.075
time management	−.077	−.140	−.173**	−.091	.022
organization	.044	.095	.061	−.038	.089
emotional regulation	.039	.163**	.041	.140**	−.004
behavioral regulation	.092*	−.003	.022	.032	.076
	R2=.369; XR2=.019; F(19,421) = 12.946***	R2=.446; XR2=.029**; F(19,421) = 17.868***	R2=.412; XR2=.027**; F(19,421) = 15.574***	R2=.388; XR2=.025*; F(19,421) = 14.053***	R2=.229; XR2=.015; F(19,421) = 6.577***

Note: Standardized betas are reported, *p < .05; **p < .01; ***p < .001.

4. Discussion

Becoming (or being) a teacher requires a mix of many skills, abilities and competencies. To date, most research has focused on behavioral factors related to teachers’ professional competences; therefore, the aim of the present study was to investigate whether and how non-behavioral factors like cognitive abilities, personality traits and motivations for choosing the teaching profession relate to professional competencies of teachers. We demonstrated that being a woman is strongly associated with a higher level of a supporting interaction style, better didactic competencies in planning and preparation of teaching and self-reflection. In reality, 82% of teachers in Slovakia are women (NÚCEM, 2020), which is similar to other countries (European data, 2014). So, whether being a woman means a higher predisposition to professional competencies remains questionable. The feminization of the teaching profession would not have been a problem if it were not associated with the low social status of teachers and did not contribute to a crisis in teacher recruitment and retention (Richardson & Watt, 2005; Yost, 2006).

Overall, the strongest antecedents of professional competency were personality traits. Higher agreeableness was associated with desirable interaction styles (leadership, helpful, understanding, student-teacher responsibility) whereas negative emotionality was an antecedent of undesirable interaction styles (uncertain, dissatisfied, objecting, strict). Furthermore, open-mindedness was associated with didactic competencies, and together with conscientiousness also teaching styles. Our findings regarding the negative impact of negative emotionality on professional competencies were in line with previous research (Aydın et al., 2013; Costa & McCrae, 1992); for other traits, the findings were less clear. For instance, agreeableness, a higher level of cognitive functions and the results of the undergraduate teacher training state exam have been found to relate to the level of teacher professional competencies (Roloff et al., 2020). Likewise, we found that agreeableness was the strongest antecedent. In our study, extraversion was only one of several antecedents, but Aydın et al. (2013) and Costa and McCrae (1992) identified teachers with higher extraversion as more effective. Moreover, Aydın et al. (2013) and Han and Pistole (2017) did not identify open-mindedness as a significant predictor, whereas it was a significant antecedent in our study.

Therefore, across various studies, only higher negative emotions can be clearly identified as a barrier to the sufficient development of teachers’ professional competencies. This raises the question of whether attempting to identify ideal or typical teacher personality profiles even has merit. Alternatively, we could focus on identifying unsuitable traits for the teaching profession, such as the dark triad traits: Machiavellianism, narcissism and psychopathy (Paulhus & Williams, 2002). Characteristics such as disagreeableness, lack of empathy and interpersonal antagonism are the common bases of these traits (Furnham et al., 2013). However, research on the dark triad traits among teachers is limited. Čopková (2020) examined the dark triad of Slovak pre-service and in-service teachers and found that Machiavellianism is a dominant aversive feature, which is alarming because teachers in their positions can misuse power and authority and manipulate students.

As expected, teachers’ intrinsic and altruistic motivation in particular were associated with a higher level of professional competencies, whereas extrinsic motivation was associated with a lower level of competencies. In Slovakia, the teaching profession appears to be based on intrinsic and altruistic motivations (Tomšik, 2016), which is similar to other countries (Htang, 2019; Kyriacou et al., 1999). According to our findings, being motivated internally and altruistically is a good starting point for a teacher’s career. Although intrinsic and altruistic motivations were more significant for acquiring and developing professional competencies, teachers’ low social status and low salaries can be frustrating. In Slovakia, teachers’ salaries in 2021 accounted for 125.7% of the national average, after considering all surcharges and rewards, including the salaries of school directors and managers; most teachers likely earn less than the average salary (Rehúš, 2022). In Slovakia, being a good teacher requires relatively strong internal motivation that overcomes external barriers.

Finally, professional competencies were associated with using well-developed executive function plans and time management. Planning and time management are necessary not only for proper and optimal lesson management but also for the facilitation of a planned manner rather than using automatic but less appropriate behavior (Friedman-Krauss et al., 2014). Although research on executive functions and their role in the teaching profession is lacking, our findings, which indicated that developed plans and time management as well as organization were associated with better professional competencies, are enriching.

Our finding that cognitive abilities were not related to professional competencies (or were only weak antecedents) was somewhat surprising. However, it is relatively encouraging that the cognitive abilities of Slovak in-service teachers exhibited medium (43% success in cognitive reflection) to advanced levels (72% success in scientific reasoning) (Čavojová & Jurkovič, 2017b). Moreover, cognitive reflection and scientific reasoning were correlated with older age. This finding is important, as older teachers with a higher level of cognitive reflection have been shown to make more patient decisions compared to younger teachers with higher cognitive reflection (Čavojová & Jurkovič, 2017a). This is probably due to the longer practice of older teachers, allowing them to rely on the automation of some cognitive abilities and smoother working memory to solve more complex characteristics of the situation (Hattie, 2003).

Our results suggest that personality, motivation and cognitive factors play a role in the development of professional competences. Therefore, they should be taken into account. For example, motivations could be taken into account in the selection of student applicants (for example, Slovak universities often accept all applicants to study due to low interest in study, in becoming teacher; in addition, many applicants have teacher education only as a fallback plan if they are not accepted to their preferred field of study). More should be done to develop cognitive abilities during the training of future teachers, and students could also receive psychological support (in terms of coping with, for example, negative emotionality on the job) through social psychological training.

4.1. Limitations and future research

The present study has some limitations. Due to the explanatory nature of our study, we could only show the mutual relations of the concepts studied. We cannot say anything about the causality of these relationships. In order to be able to say whether non-behavioral factors (such as personality traits, motivation, and cognitive abilities) really support the development of professional competencies, as we assume, it is necessary to conduct follow-up studies in the future.

Psychological education should offer future teachers the opportunity to develop not only professional competencies, but also psychological literacy, socio-psychological competencies and the connection between psychological theory and school practice (Sokolová et al., 2014). The present study focused on several basic non-behavioral factors potentially related to teachers’ professional competencies. According to recent recommendations (e.g., Sokolová, 2018), another non-behavioral factor may be psychological literacy, i.e., knowledge of psychological research and constructs, as well as adaptive use of this psychological knowledge, and critical psychological thinking (Sokolová, 2018; Sokolová et al., 2017). Thus, future research should focus on teachers’ psychological literacy and the impact of psychological literacy on the development of teachers’ professional competencies.

5. Conclusion

Preparing teachers for practice is the purpose of teachers’ undergraduate training. Knowing the psychological profile of an effective teacher is the basis on which teachers’ education should grow to prepare teachers and attract people to the teaching profession (Corcoran & O’Flaherty, 2016). The present study investigated personality, motivation and cognitive factors supporting better development of teachers’ professional competences. Our findings bring a new perspective on relationships between professional competencies and non-behavioral factors potentially enhancing their development. We identified personality traits (agreeableness, conscientiousness and open-mindedness), intrinsic and altruistic motivation, executive function plans and time management as positive antecedents of teachers’ professional competencies. To improve the quality of teachers and prevent them from leaving the profession, pre-service teachers should be carefully chosen; their intrinsic motivations should be supported, and barriers, such as low social status and salary, should be reduced.

The teaching profession requires experts who possess professional competencies in the educational process, with a focus on students in the relevant developmental framework as well as self-reflection and self-development. Teaching is one of the most complex and demanding of professions, requiring developed professional knowledge, skills and competencies. Teaching requires developed attitudes and values, an attentive approach and empathy toward students and other school stakeholders, effective time management, critical thinking and creative problem solving, personality characteristics such as openness, agreeableness and enthusiasm, and intrinsic and altruistic motivation. Society and education require teachers who are prepared for lifelong learning and developing their professional competencies and able to utilize them effectively in school practice.

Ethics approval and consent to participate

All methods were carried out in accordance with APA standards. Informed consent was obtained from all subjects.

Acknowledgments

The study was supported by the scientific grant agency of the Ministry of Education, Science, Research and Sport of the Slovak Republic as part of the project VEGA 1/0084/21 “Personality, Cognitive and Motivational Predictors of Professional Competencies of Teachers in Pregradual Education and in Practice”.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The datasets generated for this study can be found at: https://osf.io/p2ekq.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/2331186X.2023.2286813

Additional information

Funding

This work was supported by the Vedecká Grantová Agentúra MŠVVaŠ SR a SAV [VEGA 1/0084/21].

Appendix A

Table A1. Hierarchical regression analysis to predict teaching style

		supporting	goal-oriented	knowledge-oriented	manager
1	sex	.169***	.034	.044	.151***
	age	.035	.102	.207*	.021
	practice	.149	−.030	−.108	.099
		R2=.067; XR2=.067***; F(3,437) = 10.465***	R2=.007; XR2=.007; F(3,437) = 1.079	R2=.018; XR2=.018*; F(3,437) = 2.671*	R2=.040; XR2=.040***; F(3,437) = 6.066***
2	sex	.137**	.009	.006	.095*
	age	.039	.112	.217*	.044
	practice	.125	−.058	−.145	.037
	extraversion	.065	.034	.077	.204***
	agreeableness	.060	−.085	−.068	.049
	conscientiousness	−.075	.244***	.257***	−.020
	negative emotionality	−.134*	.061	.040	−.132*
	open-mindedness	.248***	−.021	−.006	.314***
		R2=.196; XR2=.129***; F(8,432) = 13.203***	R2=.046; XR2=.039**; F(8,432) = 2.628**	R2=.075; XR2=.057***; F(8,432) = 4.396***	R2=.319; XR2=.279***; F(8,432) = 25.313***
3	sex	.108*	−.026	−.039	.030
	age	.036	.103	.217*	.041
	practice	.125	−.049	−.149	.028
	extraversion	.039	−.002	.041	.154***
	agreeableness	.063	−.044	−.050	.033
	conscientiousness	−.080	.261***	.258***	−.042
	negative emotionality	−.137*	.050	.031	−.136**
	open-mindedness	.214***	−.067	−.056	.245***
	intrinsic motivation	.097	.142*	.167**	.204***
	extrinsic motivation	.008	.085	.039	−.044
	altruistic motivation	.072	.051	.057	.155***
	alternative choice	.045	.177***	.103*	.038
		R2=.214; XR2=.017; F(12,428) = 9.699***	R2=.107; XR2=.061***; F(12,428) = 4.279***	R2=.115; XR2=.040***; F(12,428) = 4.652***	R2=.387; XR2=.068***; F(12,428) = 22.541***
				***
4	sex	.114*	−.022	−.049	.025
	age	.034	.106	.236*	.041
	practice	.117	−.076	−.177	.026
	extraversion	.041	.011	.040	.124*
	agreeableness	.085	−.013	.000	.066
	conscientiousness	−.098	.227**	.184*	−.064
	negative emotionality	−.145*	.046	−.007	−.145*
	open-mindedness	.231***	−.056	−.043	.249***
	intrinsic motivation	.091	.115	.152*	.195***
	extrinsic motivation	.009	.067	.018	−.044
	altruistic motivation	.084	.075	.072	.163***
	alternative choice	.034	.156**	.088	.022
	cognitive reflection	−.024	−.075	−.056	−.100**
	scientific reasoning	.017	−.147**	−.139	.016
	plan management	.108	.101	.051	−.025
	time management	−.125*	−.043	−.018	−.068
	organization	.007	−.008	−.063	.029
	emotional regulation	.040	.006	.088	.066
	behavioral regulation	−.038	−.108*	−.071	.009
		R2=.226; XR2=.012; F(19,421) = 6.452***	R2=.151; XR2=.044**; F(19,421) = 3.932***	R2=.153; XR2=.038*; F(19,421) = 4.005***	R2=.401; XR2=.014; F(19,421) = 14.862***

Note: Standardized betas are reported, * p < .05; ** p < .01; *** p < .001.

Table A2. Hierarchical regression analysis to predict didactic competencies

		planning and preparation	realization	climate	diagnostics and evaluation	self-reflection
1	sex	.226***	.197***	.114*	.195***	.211***
	age	−.118	−.123	.080	−.044	.081
	practice	.270**	.284**	.104	.210*	.046
		R2=.092; XR2=.092***; F(3,437) = 14.790***	R2=.083; XR2=.083***; F(3,437) = 13.115***	R2=.048; XR2=.048***; F(3,437) = 7.367***	R2=.075; XR2=.075***; F(3,437) = 11.850***	R2=.064; XR2=.064***; F(3,437) = 9.882***
2	sex	.146***	.119**	.025	.116**	.154***
	age	−.108	−.103	.075	−.029	.088
	practice	.220**	.215**	.046	.159*	.022
	extraversion	.052	.215***	.219***	.141**	.045
	agreeableness	.053	.057	.065	.146**	.160**
	conscientiousness	.272***	.137**	.178***	.116*	.066
	negative emotionality	.009	−.071	−.158**	.002	.040
	open-mindedness	.251***	.248***	.146**	.261***	.211***
		R2=.324; XR2=.231***; F(8,432) = 25.829***	R2=.372; XR2=.290***; F(8,432) = 32.005***	R2=.364; XR2=.315***; F(8,432) = 30.851***	R2=.320; XR2=.245***; F(8,432) = 25.411***	R2=.186; XR2=.122***; F(8,432) = 12.336***
3	sex	.109*	.058	−.012	.055	.116*
	age	−.101	−.105	.082	−.029	.090
	practice	.208**	.203**	.027	.143	.008
	extraversion	.028	.171***	.199***	.101*	.021
	agreeableness	.035	.046	.038	.128*	.129*
	conscientiousness	.252***	.121*	.156**	.097	.042
	negative emotionality	.011	−.079	−.159**	−.006	.040
	open-mindedness	.213***	.189***	.115*	.206***	.176***
	intrinsic motivation	.110*	.200***	.117*	.198***	.108
	extrinsic motivation	−.003	−.066	−.072	−.090*	−.086
	altruistic motivation	.092*	.092*	.043	.079	.087
	alternative choice	−.039	.053	−.044	.035	−.044
		R2=.350; XR2=.026**; F(12,428) = 19.184***	R2=.417; XR2=.045***; F(12,428) = 25.518***	R2=.385; XR2=.021**; F(12,428) = 225.314***	R2=.363; XR2=.042***; F(12,428) = 20.294***	R2=.214; XR2=.028**; F(12,428) = 9.729***
4	sex	.104*	.076	.009	.057	.115*
	age	−.092	−.076	.077	−.009	.092
	practice	.204*	.175**	.024	.132	.019
	extraversion	−.015	.129*	.165***	.056	.002
	agreeableness	.049	.091	.056	.175**	.109
	conscientiousness	.238***	.095	.121	−.007	.109
	negative emotionality	.007	−.103	−.128*	−.019	.040
	open-mindedness	.217***	.187***	.117*	.207***	.165**
	intrinsic motivation	.108*	.205***	.114*	.205***	.119*
	extrinsic motivation	−.001	−.055	−.057	−.088**	−.073
	altruistic motivation	.085	.088*	.039	.068	.076
	alternative choice	−.046	.047	−.054	.031	−.037
	cognitive reflection	−.038	.004	−.011	.009	−.001
	scientific reasoning	−.042	−.016	.048	−.002	.057
	plan management	−.081	−.085	−.062	−.136*	−.075
	time management	−.077	−.140	−.173**	−.091	.022
	organization	.044	.095	.061	−.038	.089
	emotional regulation	.039	.163**	.041	.140**	−.004
	behavioral regulation	.092*	−.003	.022	.032	.076
		R2=.369; XR2=.019; F(19,421) = 12.946***	R2=.446; XR2=.029**; F(19,421) = 17.868***	R2=.412; XR2=.027**; F(19,421) = 15.574***	R2=.388; XR2=.025*; F(19,421) = 14.053***	R2=.229; XR2=.015; F(19,421) = 6.577***

Note: Standardized betas are reported, * p < .05; ** p < .01; *** p < .001.