From Frustration to Focus: The Link between Iranian EFL Teachers’ Emotional Intelligence and their Classroom Management
الموضوعات :
1 - English Department, Islamic Azad University, Bu.C., Bushehr, Iran
الکلمات المفتاحية: Emotional intelligence, proactive classroom management, reactive classroom management, years of teaching experience ,
ملخص المقالة :
This study delved into the interplay between Iranian EFL teachers' emotional intelligence and their classroom management styles. The study employed the Emotional Quotient Inventory (EQ-i) and the Competency and Behavior Management Survey (CBMS) to assess emotional intelligence and management styles of 110 EFL instructors from The Iran Language Institute. The findings revealed a statistically significant positive association between teachers' emotional intelligence and their preference for proactive classroom management strategies. Conversely, a significant negative correlation emerged between teachers' emotional intelligence and their inclination towards reactive management styles. Furthermore, the study identified a positive association between teachers' experience and both their emotional intelligence and their preference for proactive management. Additionally, teachers with master's degrees exhibited higher emotional intelligence levels, a stronger affinity for proactive strategies, and a weaker tendency for reactive approaches. These results hold significant implications for educators and teacher training programs. The study suggests a link between teachers' emotional intelligence and their successful implementation of classroom management strategies. This underscores the potential value of incorporating emotional intelligence development into teacher training programs, potentially enhancing future educators' ability to effectively manage their classrooms.
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Research Article
From Frustration to Focus: The Link between Iranian EFL Teachers’ Emotional Intelligence and their Classroom Management
Samaneh Imandar
English Department, Islamic Azad University, Bu.C., Bushehr, Iran
*Author: imandarsamaneh@gmail.com
(Received: 2024/12/05; Accepted: 2025/07/20)
Online publication: -----------
Abstract
Employing a correlational design, this study delved into the interplay between Iranian EFL teachers' Emotional Intelligence (EI) and their Classroom Management Strategies (CMSs). The study employed the Emotional Quotient Inventory (EQ-i) and the Competency and Behavior Management Survey (CBMS) to assess EI and CMSs of 110 EFL instructors working in private language institute. The results of Pearson correlation revealed a statistically significant positive association between teachers' EI and their preference for proactive CMSs. Conversely, a significant negative correlation emerged between teachers' EI and their inclination towards reactive management styles. Furthermore, the results of MANOVA identified a positive association between teachers' experience and both their EI and their preference for proactive management. Additionally, compared to teachers with BA degrees, teachers with master's degrees exhibited higher EI levels, a stronger affinity for proactive strategies, and a weaker tendency for reactive approaches. These results hold significant implications for educators and teacher training programs. The study suggests a link between teachers' EI and their successful implementation of CMSs. This underscores the potential value of incorporating EI development into teacher training programs, potentially enhancing future educators' ability to effectively manage their classrooms.
Keywords: EI, proactive CM, reactive CM, years of teaching experience
Introduction
Previous research demonstrates a consistent link between high EI and teacher effectiveness (Halimi et al., 2020). Educators with high EI possess strong social skills and a high degree of empathy, allowing them to effectively navigate the emotional aspects of learning interactions (Mortiboys, 2005). This focus fosters positive classroom environments, making learning more engaging and enjoyable and cultivates positive working relationships (Miri & Pishghadam, 2021).
Jennings and Greenberg (2009) outline a conceptual framework termed the prosocial classroom, which emphasizes the central role of educators’ socioemotional competence and psychological well-being in fostering and sustaining positive teacher-student relationships, implementing effective classroom management practices, and ensuring the successful integration of social and emotional learning initiatives. Strong emotional competencies empower teachers to build positive and productive relationships with students, guide them through complex situations, foster collaboration, and serve as role models for respectful communication and pro-social behavior. Effectively managing a classroom is an undeniably demanding task, laden with emotional complexities (Hofman, 2022). This multifaceted endeavor requires a confluence of intricate and interconnected skills, including establishing an appropriate learning environment, aligning curriculum with student needs, fostering positive student relationships, and addressing disruptive behavior (Woodcock & Reupert, 2023). Classroom Management, as the most valuable skillset a teacher can possess (Landau, 2001), is categorized into proactive and reactive strategies (Hepburn & Beamish, 2019). Proactive strategies prioritize cultivating a positive behavioral ecology by minimizing disruptions (Reddy et al., 2013; Nash et al., 2016; Safran & Oswald, 2003) like establishing clear routines or diversifying instructional methods (Simonsen et al., 2008). Reactive strategies, conversely, address existing disruptions through contingency management (Reddy et al., 2013) such as verbal reprimands, extra assignments, and privilege removal (Mendenhall et al., 2020; Goss et al., 2017; Little & Akin-Little, 2008; Stormont et al., 2011). By fostering these skills, teachers stand a greater chance of creating a rewarding and productive learning environment, ultimately enhancing both their own and their students' experiences (Bar-On, 1997; Mayer et al., 1999).
The role of the modern teacher has undergone a significant shift, becoming progressively more complex (Rapanta et al., 2021). Curating a supportive classroom atmosphere necessitates a teacher's adeptness at navigating the social, emotional, and behavioral dynamics within their classroom (McDaniel et al., 2022). Schools across the globe grapple with the pressure to address perceived increases in classroom disruptions and student behavior problems (Sullivan, 2016; Bennett, 2020). While evidence for a global decline in student behavior remains inconclusive, reports from various countries consistently highlight the ongoing challenges teachers face in managing student misconduct (Madden & Senior, 2017; Sun & Shek, 2012). Building upon the aforementioned considerations, this research endeavor delved into the potential correlation between educators' EI and their Classroom Management Strategies (CMSs).
Literature Review
The construct of EI finds its antecedents in earlier psychological theories. Thorndike’s (1920) concept of social intelligence, emphasizing the ability to navigate interpersonal interactions effectively, can be considered a distant precursor (Bar-On, 2000). Gardner’s (1983) theory of multiple intelligences provided a more proximate foundation, particularly through the constructs of interpersonal and intrapersonal intelligence. Interpersonal intelligence focuses on decoding the intentions and motivations of others, while intrapersonal intelligence centers on self-awareness of one’s emotions and desires, alongside the ability to effectively manage them.
The term EI itself was first introduced by Salovey and Mayer (1990) and gained widespread recognition following the publication of Goleman’s (1995) popular book. Since then, a multitude of prominent models of EI have emerged, including Bar-On’s (2011) Model of Emotional-Social Intelligence (ESI), Goleman’s (2006, 2011) EI model, and Mayer et al.’s (2008) Ability Model of EI. Mayer and Salovey (1990) defined EI as the ability to process emotions accurately, manage emotions in oneself and others, utilize emotions to enhance cognition, and recognize emotions in others. Goleman’s (1996) definition encompasses a broader range of skills, including self-motivation, impulse control, emotional regulation, empathy, and hope. Ameriks et al. (2009) emphasize EI as a psychological characteristic linked to effective emotional identification, comprehension, regulation, and utilization in problem-solving and decision-making.
Within contemporary discourse, EI is conceptualized as the multifaceted ability to perceive, comprehend, regulate, and effectively communicate emotions, both within oneself and in interpersonal interactions (Dogru, 2022). This competency encompasses a core set of skills, including emotional awareness, emotional reasoning, emotional management, and emotional communication. Research endeavors have yielded evidence suggesting that these skills contribute significantly to the establishment and maintenance of positive relationships, the effective management of stress and challenges, and ultimately, the enhancement of well-being and performance across various domains of life (Karimi et al., 2021).
Bar-On (2006) posits a comprehensive framework for EI, encompassing the interrelated facets of emotional and social competencies, facilitators, and skillsets. This framework reflects the degree of effectiveness with which individuals navigate self-understanding, self-expression, comprehension of others, interpersonal interaction, and the management of daily stressors. Building upon the notion of EI as a multifaceted construct (Bar-On, 2006), Bar-On’s model (1997) delves deeper into this concept, identifying five core composite scales, each subdivided into specific competencies.
The first domain, intrapersonal skills, focuses on self-regard, self-awareness, assertiveness, self-actualization, and independence. Individuals with strong intrapersonal skills possess a clear understanding of their emotions, cultivate a positive sense of self-worth, and comfortably express themselves. They demonstrate independence and a strong sense of self-direction. Interpersonal skills, the second scale, emphasize empathy, social responsibility, and interpersonal relations. Individuals with high interpersonal skills are adept at communication, interaction, and building positive relationships, thriving in collaborative environments and teamwork settings.
Adaptability, the third domain, highlights flexibility, realistic thinking, and problem-solving skills. Resilient individuals adapt to challenging situations, think realistically, and generate practical solutions. The fourth scale, stress management, focuses on stress tolerance and impulse control. Individuals with strong stress management skills remain calm under pressure, exhibit minimal impulsivity, and perform effectively in stressful situations. Finally, the general mood domain centers on expressing positive emotions, enthusiasm, and an encouraging attitude. Individuals with high general mood skills appreciate life’s experiences and contribute to a positive work environment (Bar-On, 2004; Bar-On & Parker, 2000).
The significance of EI in education stems from its ability to equip educators with tools to manage their own negative emotions and sentiment (Maamari & Majdalani, 2019). Emotionally intelligent teachers exhibit heightened capacity to comprehend students’ psychological well-being and behavioral communication, fostering a conducive learning environment and motivating academic excellence (Radu, 2014). Furthermore, such educators cultivate positive student-teacher relationships and improve academic achievement (Kostić-Bobanović, 2020). These results support the theoretical link between EI and teacher self-efficacy. Similarly, Barlozek’s (2015) study found a positive correlation between teachers’ EI and student-teacher relationships, with students perceiving high-EI teachers more favorably.
Extending beyond teacher self-efficacy, research explores EI’s influence on student motivation (Rahman et al., 2024). Rahman et al. (2024), investigating Bangladeshi teachers using Goleman’s (2006) framework, found positive correlations between all five EI dimensions (self-awareness, self-regulation, self-motivation, empathy, social skills) and student motivation. Conversely, Amponsah et al. (2024), examining pre-service teachers, identified a significant connection between academic performance and most EI components but found none for self-awareness and self-management. These findings highlight the need for further research into these specific components.
Classroom Management Strategies (CMSs) is a complex and multifaceted construct, with various scholars offering distinct perspectives on its definition. A common definition emphasizes the diverse skills and techniques employed by teachers to maintain order, focus, and academic productivity among students (Abbott, 2014). Expanding on this notion, Ozcan (2017) conceptualizes CM as the dynamic interplay between teachers and students, encompassing all teacher behaviors that cultivate a positive learning environment conducive to effective instruction. This environment is fostered through techniques such as establishing clear rules and procedures, organizing the physical classroom space, capturing student attention, and engaging them in stimulating activities (Ozcan, 2017). Ozcan (2017) emphasizes the pivotal role of CM in fostering both academic achievement and social-emotional development. From this perspective, CM can be conceptualized holistically, encompassing all teacher actions within the classroom environment that facilitate the learning process (Ozcan, 2017; Marzano et al., 2003).
Burden (2005) adopts a broader perspective, defining CM as the teacher’s comprehensive effort to oversee classroom activities, including learning, social interactions, and student behaviors. Doyle (2006) highlights the reciprocal nature of CM, encompassing the perspectives and actions of both teachers and students that shape behavior within the classroom. Similarly, Brophy (1986) views CM as the teacher’s deliberate attempt to create and sustain an environment conducive to effective learning and teaching.
Savage and Savage (2009) introduce a two-tiered approach to CM, emphasizing preventative measures alongside strategies for addressing disruptive behaviors after they occur. Their focus on prevention aligns with research underscoring the critical role of proactive techniques in fostering positive learning environments (Emmer & Stough, 2001). Magableh and Hawamdeh (2007) distinguish between two key components of CM: behavioral management and instructional management. Behavioral management addresses disruptive behaviors that impede the learning environment, such as talking out of turn, inappropriate device use, or bullying (Codding & Smyth, 2008). Instructional management focuses on behaviors hindering the learning process itself, such as disengagement, lack of participation, or incomplete assignments (Codding & Smyth, 2008).
The overarching objective of CM lies in cultivating a secure, supportive learning environment that empowers students with the requisite skillsets to flourish academically and socially (Wong & Wong, 2009). By understanding CM’s multifaceted nature, educators can develop comprehensive approaches to fostering positive learning environments. Despite variations in definitions, research consistently emphasizes CM’s importance for teachers and effective teaching (Brophy & Evertson, 1976; Wang et al., 1993). Landau (2001) even identifies CM as the most valuable skillset a teacher can possess. Empirical studies demonstrate that teachers’ proficiency in CM and instructional organization significantly contributes to teaching success (Brophy, 1988; Emmer et al., 2000). Corroborating this, Wang et al. (1993), in a meta-analysis of five decades of classroom research, identified CM as the most influential variable impacting student learning.
A productive learning environment requires multifaceted Classroom Management Strategies (CMSs), categorized as proactive or reactive (Hepburn & Beamish, 2019). Proactive strategies prioritize cultivating a positive behavioral ecology by minimizing disruptions (Reddy et al., 2013; Nash et al., 2016; Safran & Oswald, 2003). Reactive strategies, conversely, address existing disruptions through contingency management (Reddy et al., 2013). Proactive approaches include optimizing classroom layouts, establishing clear routines, diversifying instructional methods, reinforcing appropriate conduct, and structuring consequences for misconduct (Simonsen et al., 2008). Reactive strategies often involve negative reinforcement, such as verbal reprimands, extra assignments, privilege removal, isolation, punitive measures, or aggression (Mendenhall et al., 2020; Goss et al., 2017; Little & Akin-Little, 2008; Stormont et al., 2011).
Research unequivocally underscores the superiority of proactive strategies (Hepburn & Beamish, 2019). Proactive practices correlate with enhanced student engagement, stronger teacher-student interactions, and reduced behavioral issues (Oliver et al., 2011). Reactive strategies offer transient solutions but lack long-term efficacy (Sugai & Horner, 2002). Frequent punitive or aggressive reactions, such as yelling or sarcasm, harm teacher-student relationships and may escalate misbehavior (Black, 2016). Thus, educators should prioritize proactive approaches over punitive ones.
Emerging research suggests a correlation between educators’ high EI and effective CM practices. Studies indicate that emotionally intelligent teachers navigate complex classrooms—addressing diverse populations, stress, and group dynamics—more effectively (Brackett et al., 2010; Corcoran & Tormey, 2012b; Jennings & Greenberg, 2009). They also design engaging lessons, foster motivation, and cultivate classrooms with fewer disruptions (Nizielski et al., 2012; Richards & Gross, 1999). Sutton et al. (2009) highlight their use of emotional regulation strategies to manage interactions and improve outcomes. Valente et al. (2018), in a study of 559 teachers, found a significant positive correlation between EI and classroom discipline management. Effective discipline management is critical for cognitive learning (Valente, 2015), as poor management impedes teaching and learning. High-EI teachers build supportive relationships, attend to individual needs (Nizielski et al., 2012), and report greater job satisfaction (Anari, 2012). Research further links EI to improved teacher-student relationships, teaching efficacy, and self-efficacy in CM (Fabio & Palazzeschi, 2008; Perry & Ball, 2007; Pugazhenthi & Srinivasan, 2018). Conversely, limited resources and emotional dysregulation harm student behavior and teacher well-being (Becker et al., 2015; Tsouloupas et al., 2010; Keller et al., 2014), reinforcing EI’s importance, as corroborated by Jeloudar et al. (2011).
Although there is strong evidence for the correlation between educators’ high EI and effective CM practices, the majority of these studies have mainly covered Western contexts or general educators (Jeloudar et al., 2011; Marzano et al., 2003). Iranian EFL instructors still face underrepresentation, in spite of different constraints like cultural dynamics, certain lacks of resources and language-specific pedagogical demands. In order to fill this gap, the present research aimed to explore the relationship between EI and CM strategies of Iranian EFL teachers with the following research questions:
1. Is there a statistically significant relationship between EFL teachers’ EI and their preferred CMSs?
2. Are there any significant variations in the EI levels of EFL teachers and their chosen CMSs based on their teaching experience?
3. Do significant differences emerge in the EI levels of EFL teachers and their chosen CMSs when considering their educational qualifications?
Method
This study employed a convenience sampling technique to recruit 110 Iranian EFL teachers currently working in private language institutes. The sample consisted of 77 females and 33 males, ranging in age from 20 to 42 years old. Teaching experience varied from 2 to 14 years. Following Gatboton (1999), teachers with at least five years of experience were classified as "experienced," while those with less than three years were considered "novice." Notably, all participants had previously completed a teacher training course.
Design
This study employed a correlational design to investigate the potential statistical relationships among four key variables: Iranian EFL teachers' EI, CMSs, teaching experience, and educational qualifications. The researcher utilized two established scales to measure these variables. The Emotional Quotient Inventory (EQ-i) developed by Baron (1997) assessed the participants' level of EI. The Competency and Behavior Management Survey (CBMS), developed and validated by Herrera and Little (2005), measured the teachers' preferred CM approaches. This approach allowed the researcher to examine the potential correlations between EI, teaching experience, and CMSs employed by Iranian EFL teachers.
Materials and Instruments
Emotional Intelligence Scale: The Emotional Quotient Inventory (EQ-i) developed by Baron (1997) assessed participants' EI. This 133-item inventory measures five core EI constructs outlined in Bar-On's (1997) model: intrapersonal skills, interpersonal skills, adaptability, stress management, and general mood. Each construct encompasses specific competencies. Soodmand Afshar and Rahimi (2015) did a validation study on this questionnaire with 150 Iranian EFL learners and showed that it had high level of reliability and validity in the context of Iran. The Iranian validated of the EQ-i was employed. The instrument demonstrated good internal consistency (α = .84) in this study, indicating acceptable reliability, as α > .70 is generally considered satisfactory in social science research.
Classroom Management Strategies Scale (CMSS): A shortened and modified version of the Competency and Behavior Management Survey (CBMS) developed by Herrera and Little (2005) was used. This instrument investigates the types of management strategies teachers utilize in response to disruptive behavior. The CBMS comprises 12 items categorized as proactive or reactive management strategies. Participants rated items on a five-point Likert scale ranging from "extremely unlikely" to "extremely likely" (Herrera & Little, 2005). The Iranian-validated version of the EQ-i, as established by Fadaei and Tahriri (2023), was employed in this study. Similar to the EQ-i, the CBMS also exhibited strong internal consistency (α = .87), surpassing the conventional threshold of α > .70, which is widely accepted as indicative of good reliability in social science research.
Procedure
This study employed a voluntary participation approach. After explaining the research objectives, the researcher obtained informed consent from interested EFL teachers. The participants were free to withdraw from the study at any point. The researcher did not provide the participants with an exact set of instructions on how to complete the questionnaires, thus allowing them to answer in their own understanding. This gave the respondents freedom to interpret and fill in the survey on their own. The researcher conducted the surveys via the Internet through Google Forms, which is the most popular and easy-to-use web-based survey tool in the Google Drive suite. The two aforementioned questionnaires (EQ-i and CBMS) were used to collect the data. Upon completion, the participant responses were tabulated and prepared for statistical analysis to address the research questions.
Data Analysis
Pearson correlation coefficients were employed to ascertain statistically significant relationships between the EI of EFL teachers and their CMSs (Research Question 1). To delve deeper into the potential influence of teaching experience on both EI and CMSs (Research Question 2), MANOVA was conducted. MANOVA was replicated for the investigation of potential influences of educational degree on EI and CMSs (Research Question 3).
Results
Table 1
Descriptive Statistics
| Mean | Std. Deviation | N |
Proactive | 24.86 | 2.52 | 110 |
Reactive | 9.04 | 1.36 | 110 |
EI | 412.44 | 24.58 | 110 |
Table 2
Correlation between EI and Proactive and Reactive Strategies
| proactive | reactive | ||
EI | Pearson Correlation | .671** | -.517** | |
Sig. (2-tailed) | .000 | .000 | ||
N | 110 | 110 | ||
**. Correlation is significant at the 0.01 level (2-tailed). | ||||
As Table 2 shows, there was statistically significant strong positive relationship between teacher EI and proactive CMSs (r = .67, p<.01), and there is strong negative correlation between teachers' EI and their reactive CMSs (r = -.51, p<.01).
In order to answer the second research question addressing significant difference among EFL teachers’ degree of EI and choice of CMSs with respect to their teaching experience, MANOVA test was run. The results are presented in Table 3.
Table 3
Descriptive Statistics
| Teaching experience | Mean | Std. Deviation | N |
EI | inexperienced | 395.81 | 14.59 | 48 |
Experienced | 425.32 | 23.02 | 62 | |
Total | 412.44 | 24.58 | 110 | |
Proactive | Inexperienced | 22.62 | 1.39 | 48 |
Experienced | 26.59 | 1.71 | 62 | |
Total | 24.86 | 2.52 | 110 | |
Reactive | Inexperienced | 10.10 | 1.01 | 48 |
Experienced | 8.22 | .98 | 62 | |
Total | 9.04 | 1.36 | 110 |
A multivariate analysis of variance (MANOVA) was conducted to examine the effect of teaching experience on teachers' emotional intelligence (EI), proactive classroom management strategies (CMSs), and reactive CMSs. The results are presented in Table 4.
Table 4
Multivariate Testsa
Effect | Value | F | Hypothesis df | Error df | Sig. | Partial Eta Squared | |||||||||
Teaching experience | Pillai's Trace | .62 | 59.75b | 3.00 | 106.00 | .00 | .62 | ||||||||
Wilks' Lambda | .37 | 59.75b | 3.00 | 106.00 | .00 | .62 | |||||||||
Hotelling's Trace | 1.69 | 59.75b | 3.00 | 106.00 | .00 | .62 | |||||||||
Roy's Largest Root | 1.69 | 59.75b | 3.00 | 106.00 | .00 | .62 | |||||||||
a. Design: Intercept + teaching experience | |||||||||||||||
b. Exact statistic | |||||||||||||||
The results in Table 4 revealed a statistically significant difference between less experienced and more experienced teachers across these dependent variables (Wilks' Λ = .37, F(3, 106) = 59.75, p < .001, partial η² = .62). The small p-value (p < .001) provides strong evidence that teaching experience significantly influences teachers' EI as well as their preferences for both proactive and reactive CMSs. The large effect size (partial η² = .62) further indicates that teaching experience explains a substantial portion of the variance in these outcomes. All four multivariate test statistics—Pillai's Trace, Wilks' Lambda, Hotelling's Trace, and Roy's Largest Root—yielded consistent results (F = 59.75, p < .001), reinforcing the robustness of the findings.
In Table 5, the results of the tests of Between-Subject Effects are presented to indicate which variable scores are different with respect to teachers’ teaching experience.
Table 5
Tests of Between-Subjects Effects
Source | Dependent Variable | Type III Sum of Squares | Df | Mean Square | F | Sig. | Partial Eta Squared | |
Teaching experience | EI | 23560.3 | 1 | 23560.31 | 60.08 | .00 | .35 | |
Proactive | 426.78 | 1 | 426.78 | 170.6 | .00 | .61 | ||
Reactive | 95.45 | 1 | 95.45 | 96.06 | .00 | .47 | ||
a. R Squared = ,357 (Adjusted R Squared = ,352) | ||||||||
b. R Squared = ,612 (Adjusted R Squared = ,609) | ||||||||
c. R Squared = ,471 (Adjusted R Squared = ,466) | ||||||||
As illustrated in Table 5, a statistically significant difference (p < .05) was observed in the F values for mean scores across various years of teaching experience as shown in Table 5. This indicates that EFL teachers with different levels of experience differed significantly in their EI (F = 60.08, sig. = .00, p < .05), proactive CMSs (F = 170.0, sig. = .00, p < .05), and reactive CMSs (F = 96.06, sig. = .00, p < .05). Further analysis of mean scores revealed that teachers with more experience exhibited higher EI (mean = 425.32) compared to their less experienced counterparts (mean = 395.81). Similarly, experienced teachers demonstrated a stronger orientation towards proactive CMSs (mean = 26.59) compared to less experienced ones (mean = 22.62). Conversely, experienced teachers displayed a weaker tendency towards reactive CMSs (mean = 8.42) compared to less experienced teachers (mean = 10.10).
To answer the third research question concerning any significant difference among EFL teachers’ degree of EI and choice of CMSs with respect to educational qualifications, another MANOVA test was calculated, the results of which are shown in Table 6 and 7.
Table 6
Descriptive Statistics
| Educational degree | Mean | Std. Deviation | N |
EI | BA | 403.37 | 21.20 | 64 |
MA | 425.06 | 23.56 | 46 | |
Total | 412.44 | 24.58 | 110 | |
Proactive | BA | 23.71 | 2.36 | 64 |
MA | 26.45 | 1.79 | 46 | |
Total | 24.86 | 2.52 | 110 | |
Reactive | BA | 9.56 | 1.28 | 64 |
MA | 8.32 | 1.13 | 46 | |
Total | 9.04 | 1.36 | 110 |
Table 7
Multivariate Testsa
Effect | Value | F | Hypothesis df | Error df | Sig. | Partial Eta Squared | |
Educational qualifications | Pillai's Trace | .29 | 15.07b | 3.00 | 106.0 | .00 | .299 |
Wilks' Lambda | .70 | 15.07b | 3.00 | 106.0 | .00 | .299 | |
Hotelling's Trace | .42 | 15.07b | 3.00 | 106.0 | .00 | .299 | |
Roy's Largest Root | .42 | 15.07b | 3.00 | 106.0 | .00 | .299 | |
a. Design: Intercept + educational degree | |||||||
b. Exact statistic | |||||||
The results in Table 7 revealed a statistically significant difference between BA- and MA-educated teachers across EI, proactive CMSs, and reactive CMSs (Wilks’ Λ = .70, F(3, 106) = 15.07, p < .001, partial η² = .29). The partial eta-squared value (η² = .29) indicates a moderate to large effect size, suggesting that educational qualifications explain approximately 30% of the variance in these combined dependent variables. In Table 8, tests of Between-Subject Effects are presented to indicate which variable scores are different with respect to teachers’ educational qualifications.
Table 8
Tests of Between-Subjects Effects
Source | Dependent Variable | Type III Sum of Squares | df | Mean Square | F | Sig. | Partial Eta Squared | |
Educational qualifications | EI | 12591.36 | 1 | 12591.36 | 25.5 | .00 | .191 | |
Proactive | 200.60 | 1 | 200.60 | 43.64 | .00 | .288 | ||
Reactive | 40.91 | 1 | 40.91 | 27.3 | .00 | .202 | ||
a. R Squared = ,191 (Adjusted R Squared = ,184) | ||||||||
b. R Squared = ,288 (Adjusted R Squared = ,281) | ||||||||
c. R Squared = ,202 (Adjusted R Squared = ,194) | ||||||||
The results in Table 8 revealed significant differences across all three dependent variables. First, regarding emotional intelligence (EI), MA teachers (M = 425.06, SD = 23.56) demonstrated significantly higher scores than their BA counterparts (M = 403.37, SD = 21.20), F(1, 108) = 25.5, p < .001, with a small to medium effect size (partial η² = .19). Second, for proactive classroom management strategies, MA teachers (M = 26.45, SD = 1.79) reported substantially greater usage compared to BA teachers (M = 23.71, SD = 2.36), F(1, 108) = 43.64, p < .001, showing a moderate to large effect (partial η² = .28). Finally, in reactive strategies, the pattern reversed: BA teachers (M = 9.56, SD = 1.28) employed these approaches more frequently than MA teachers (M = 8.32, SD = 1.13), F(1, 108) = 27.3, p < .001, with a small to medium effect size (partial η² = .20).
Discussion
Furthermore, the positive association between EI and proactive management strategies suggests that emotionally intelligent teachers are adept at anticipating and preventing potential classroom disruptions. This ability can be attributed to several core components of EI, including self-awareness and social awareness. Teachers with high self-awareness can recognize their own emotional triggers and anticipate how their emotional state might impact students (Goleman, 1998). Social awareness allows them to perceive the emotional states of their students and proactively address potential issues before they escalate (Bar-On, 1997). This proactive approach aligns with the “ethic of care” that Isenbarger and Zembylas (2006) identify as a critical professional norm for teachers. By fostering a positive and supportive classroom environment, teachers with high EI can minimize the need for reactive management strategies.
The current study's findings also extend the existing body of research by examining the influence of teaching experience and educational degree on the relationship between EI and CM. Results suggest that teachers with more experience exhibit higher levels of EI and a preference for proactive strategies. This can be interpreted through the lens of experiential learning (Gkonou & Mercer, 2017). Throughout their careers, teachers with extensive experience accumulate a repertoire of effective strategies for managing emotions and student behavior. This acquired knowledge allows them to refine their EI and rely less on reactive approaches. Furthermore, the positive correlation between possessing a Master’s degree and both EI and proactive management strategies aligns with the work of Yahyazadeh-Jeloudar and Lotfi-Goodarzi (2012) and Akbari and Tavassoli (2011). One possible explanation for this phenomenon is Bar-On's (2000) theoretical framework that EI is able to be changed through training. Master’s degree-holding educators typically participate in enhanced pedagogical training and continuing development so it is intuitively more likely that they experienced social learning opportunities which involve building EI skills. These programs also often focus on key dimensions of EI which can provide teachers with reflective practices and adaptive strategies that help them develop increased emotional intelligence over time.
Conclusion
This study also carries significant implications for language pedagogy and teacher education. By acknowledging the multifaceted nature of EI, teacher educators gain a deeper understanding of the factors that truly empower instructors to utilize CMSs effectively. This understanding can inform the development of programs that raise teacher awareness about the importance of EI and its impact on their ability to implement successful CMSs. Ultimately, a focus on EI can lead to a significant enhancement in the overall quality of language learning experiences.
It is important to acknowledge a limitation of this study: the reliance on self-reported data to measure both teacher EI and preferred CMSs. Self-reported information may not always reflect reality with perfect accuracy. Future work could integrate observational protocols (e.g., video recordings analyzed for CMS use) and student evaluations to validate self-reports. Further exploration of the causal relationship between EI and CMSs would also be valuable. By investigating whether interventions designed to improve EI translate into more effective CM, researchers can provide even more robust evidence for the importance of integrating EI development into teacher training programs.
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Biodata
Samaneh Imandar is a PhD candidate in TEFL at the Islamic Azad University, Bushehr Branch, Iran, since 2019. She received her M.A. in TEFL from Shahid Chamran University, Ahvaz, in 2011, and her B.A. in English Language and Literature from Persian Gulf University, Boushehr, in 2007. She has been working as an adjunct instructor of TEFL at Fargangian University, Boushehr Branch, since 2018, and has been an English teacher at the Adults’ Department of the Iran Language Institute in Boushehr since 2011. From 2013 to 2018, she also served as an adjunct instructor of TEFL at Persian Gulf University, Boushehr.
