“Work engagement and individual performance of teachers: The role of job demands and job resources”

This study aims to investigate factors impacting work engagement and individual performance of teachers. The survey-based quantitative approach was used. The sample comprised 455 teachers working in lower and upper secondary education institutions in Lithuania. The findings show that work engagement is a full mediator of the relationship between managerial support (β = 0.319), organizational support (β = 0.432), control (β = 0.374), colleague support (β = 0.456), work pressure (β = –.587), and task performance as the effect of work engagement on task performance is significant (β = 0.229). Furthermore, the analysis demonstrates that remote work moderates the relationships between managerial support (β = 0.560***), organizational support (β = 0.332**), colleague support (β = 0.234*), work pressure (β = 0.456***), control (β = 0.443**), and work engagement. Finally, remote work moderates the relationships between managerial support (β = 0.453***), organizational support (β = 0.332*), col-league support (β = 0.441*), work pressure (β = 0.456***), control (β = 0.444**), and task performance. These insights are valuable to school principals, as they provide a deeper understanding of the factors that determine the task performance of teachers. Remote work requires more job resources to increase engagement and task performance. School principals should focus on increasing engagement through feedback and consultations, psychological safety and development opportunities, and contributing to the individual job performance of teachers. The study supplements the JD-R model with remote work perceived as a contextual factor and thus extends the scientific debate on the application of this model in the teaching occupation.


INTRODUCTION
Teachers are significant stakeholders in education system, and thus their knowledge, motivation, and emotional well-being are critical.They often face a multitude of challenges, including navigating through educational reforms, coping with stressful job conditions, and grappling with feelings of disengagement (Gemmink et al., 2020).Despite the rewarding nature of the teaching job, these difficulties can impact teachers' ability to perform optimally and engage meaningfully in their work.Schools face the ongoing challenge of high teacher turnover rates, particularly notable within the first five years of their careers (Herman et al., 2020).This turnover contributes to a persistent shortage of teachers, placing additional strain on current staff members and leading to increased workloads, which alter work engagement.resources, which reduce the negative impact of student misbehavior (Bakker et al., 2007), contribute to the dedication to work, and subsequently increase individual work performance (Bakker et al., 2004).The COVID-19 pandemic has fostered remote work mode, which, on the other hand, has increased the demands for teachers and has disrupted the balance of job resources and demands (Sokal et al., 2020).Remote work, as a contextual factor, has a direct effect on fatigue and burnout, leads to cynicism (Sokal et al., 2020), stress (Robinson et al., 2023), anxiety, and lower well-being and negatively impacts individual work performance (Šimunović et al., 2023).
Following the pandemic, remote work remains a viable option for some schools, particularly during periods like flu seasons.This continued utilization of remote work underscores the importance of adaptability within educational settings.Exploring how remote work affects teachers' engagement and performance remains essential for navigating the changing landscape of education.However, school principals fail to take the most valid interventions fostering engagement and individual work performance of teachers.This justifies the importance of investigating what factors influence work engagement, further leading to individual work performance in the public sector and, in particular, in the teaching sphere.Furthermore, incorporating remote work into regular practice requires an understanding of its impact on teacher work engagement and individual work performance.Despite the growing body of research on job demands, resources, and work performance, there is limited understanding of how these factors interact in remote work settings, specifically within the educational sector.Additionally, the potential mediating role of work engagement and the moderating effect of remote work on these relationships remain underexplored.

LITERATURE REVIEW AND HYPOTHESES
Work conditions are essential in understanding employee-related outcomes in any organization.
Based on the job demands-resources (JDR) perspective, two broad categories of work conditions, which help to explain organizational processes and employee-related outcomes, are distinguished (Demerouti & Bakker, 2023;Mazzetti et al., 2023).These categories include job demands, which refer to sustained physical and/or emotional effort, and job resources, which refer to the aspects related to the job and contribute to the achievement of goals and reduction of job demands (Bakker & Demerouti, 2017).Employee work engagement is essential in a highly dynamic educational environment and offers insight into their functioning.Work engagement refers to 'a positive, fulfilling, and work-related state of mind' (Bakker et al., 2007), which contributes to the effectiveness of both employee and organization.The literature suggests that work engagement mediates the relationships between job demands, resources, and job performance (Borst et al., 2019).For example, job resources initiate a motivational process and increase employee engagement and performance at work (Demerouti & Bakker, 2023).Previous studies conducted in education settings revealed the relationship between work engagement and job performance (Bakker & Bal, 2010).Hence, the JDR model appears to be suitable for investigating engagement, which in turn leads to job performance.The explanation is that high employee engagement is tied to positive emotions, which broaden thought-action settings and arousal or activation caused by emotions (Bakker & Bal, 2010).Therefore, highly engaged teachers tend to demonstrate greater commitment, productivity, and effectiveness in fulfilling their professional responsibilities.However, the studies are not conclusive and provide mixed results.Some studies revealed that interpersonal and social relations with colleagues and principals (E.When working from home, sufficient job resources maintain satisfactory work performance.Job resources encompass various supportive factors within the work environment, such as managerial support, organizational support, and colleague support, along with the autonomy to control one's work.For instance, job control acts as a basic psychological need, leading to higher performance through feelings of significance reflected in work engagement (Albrecht et al., 2014).Thus, employee job control can increase individual work performance due to the ability of employees to control the surrounding environment while working from home.Job demands, com-prising aspects like workload and time pressure, may inspire teachers to enhance their performance in response to the challenges they present.Thus, work pressure can lead to the willingness of employees to invest more effort and increase individual work performance.Although some studies did not reveal a direct positive impact between work pressure and performance (Prem et al., 2018), recent studies revealed a positive relationship under stressful conditions (Hetland et al., 2022). This

METHOD
The Work engagement was measured by using a scale (Schaufeli & Bakker, 2004) ranging from "never" (0) to "always" (6).An example item for managerial support is "At my work, I feel bursting with energy." Individual work performance was measured using a task performance scale (Koopmans et al., 2014), which aimed to determine the ability to perform tasks, ranging from "seldom" (1) to "always" (5).An example item for task performance is "I managed to plan my work so that it was done on time." Managerial support was measured by using a scale to reveal adequate managerial support at the workplace (Cousins et al., 2004) ranging from "never" (1) to "always" (5).An example item for managerial support is "I am given supportive feedback on my work." Colleague support was measured by using a scale to reveal adequate colleague support at the workplace (Cousins et al., 2004) ranging from "never" (1) to "always" (5).An example item for managerial support is "If work gets difficult, my colleagues will help me." Organizational support was measured by using a scale to reveal adequate organizational support at the workplace (Eisenberger et al., 1986) ranging from "strongly disagree" (1) to "strongly agree" (7).An example item for organizational support is "The organization strongly considers my goals and values." Control was measured by using a scale to reveal opportunities for control and decision-making of a person (Cousins et al., 2004) ranging from "strongly disagree" (1) to "strongly agree" (5).An example item is "I can decide when to take a break." Work pressure was measured by using a scale to reveal stressors at the work place (Cousins et al., 2004) ranging from "never" (1) to "always" (5 In order to guarantee the model's reliability, the average variance extracted must be higher than 0.50, and the composite reliability value must be greater than 0.6.By using the square root of the AVE values, discriminant validity was evaluated to ensure that the model is devoid of duplicated elements.When a model satisfies the criteria for discriminate validity, it is devoid of redundant data.It is necessary for the correlation between exogenous constructs to be less than 0.85 in order to attain discriminating validity.Standardized and non-standard regression weights were examined for the proposed model for the structural model.Regression estimation is used to link exogenous and endogenous components with fitness indices in structural models.In the structural model, the value that needs to be focused on is the usual regression weight value R2, which is placed on the endogenous individual work performance construct (Hair et al., 2014).

RESULTS
Common method variance (CMV) was calculated using Harman's single factor test because the study was cross-sectional and only one data source was utilized for data collection (Podsakoff et al., 2003).Because common methods were utilized for data collection, the study evaluated the extent of erroneous covariance shared among constructs.The top three factors, which together accounted for 59.198% of the variance in the construct according to an exploratory factor analy-sis of all construct items, were the first factor (31.498%), the second factor (16.554%), and the third factor (11.146%).As a result, the single component could not account for the vast majority of variance, proving that prevalent biases have no impact on the data.

Mediational Effect
In a structural model, direct and indirect effects were measured (Table 2).The results revealed that managerial support is positively linked with work engagement (β = 0.319, p-value < 0.001).In contrast, managerial support has an insignificant link with individual work performance (β = 0.192, p-value < 0.234), which measures the direct effect, so the full mediation prevails between the relationship of managerial support and individual performance as the direct effect is insignificant.Therefore, the hypothesis H1 is supported.Secondly, perceived organizational support is positively linked with work engagement (β = 0.432, p-value < 0.001), whereas perceived organizational support has an insignificant link with individual work performance (β = -.009,p-value < 0.634), which measures the direct effect, so the full mediation prevails between the relationship of perceived organizational support and individual performance as the direct effect is insignificant.Therefore, the hypothesis H2 is supported.
Thirdly, colleague support is significant ( β = 0.456, p-value < 0.001), whereas the direct effect of colleague support is insignificantly linked with individual work performance (β = .045,p-value < 0.076), which measures the direct effect.Thus, full mediation prevails between the relationship of colleague support and individual performance mediated by work engagement.The effect of work engagement on individual work performance is significant (β = 0.229, p-value < 0.001).Therefore, the hypothesis H3 is supported.Fourthly, an indirect effect of work pressure effect on work engagement is significant (β = -.587,p-value < 0.001), and direct effect of work pressure on individual work performance is insignificant (β = -.001,p-value < 0.311), so full mediation prevails between the relationship of work pressure and individual performance mediated by work engagement.The effect of work engagement on individual work performance is significant (β = 0.229, p-value < 0.001).Therefore, the hypothesis H4 is supported.
Fifthly, control is positively associated with work engagement (β = 0.374, p-value <0.001), and control is not significantly associated with individual work performance (β = 0.091, p-value < 0.116).Therefore, full mediation prevails between the relationships of control and individual work performance mediated by work engagement.The effect of work engagement on individual work performance is significant (β = 0.229, p-value < 0.001).Therefore, the hypothesis H5 is supported.

Moderation effect
The moderation effect for remote work is presented in Table 3.The results revealed that hypotheses H6, H7, H8, H9, H10 are supported.The remote work moderates between managerial support, organizational support, colleague support, work pressure, control and work engagement.Finally, the hypotheses H11, H12, H13, H14, H15 are supported.The remote work moderates between managerial support, perceived organizational support, colleague support, work pressure, control and individual work performance.

DISCUSSION
The study contributes to the prevailing literature.The analysis revealed that work engagement fully mediates the association between managerial support, organizational support, colleague support, work pressure, the possibility of controlling one's work, and task performance.The results are consistent with other studies focused on the mediating effect of engagement between job demands and resources and individual work performance (Borst et al., 2019).The study also revealed that task performance was impacted by the indirect effect of work engagement rather than the direct effect of investigated job resources and demands.
In other words, the level of work engagement demonstrated by teachers had a greater impact on their individual work performance in completing tasks than the direct pressure they experienced in their work.
Moreover, engaged teachers strive to exceed the expectations of principals and fully understand their role in achieving better performance.They not only make efforts to improve task performance but also contribute to school performance.Thus, the assumption can be made that the contributions of teachers are recognized by principals through or-

CONCLUSION
This study aimed to investigate factors affecting work engagement and individual performance of teachers.The findings highlight that work engagement fully mediates the relationship between managerial support, organizational support, colleague support, work pressure, and task performance.This mediation effect underscores the significant role of work engagement in linking job resources and demands to individual performance outcomes.Furthermore, the study demonstrated that remote work moderates the associations between job resources, job demands, work engagement, and task performance.Specifically, teachers working remotely require additional job resources to sustain their engagement and maintain task performance.The results indicated that work pressure is significantly related to both work engagement and task performance, while job resources exhibit motivational potential to help teachers cope with the pressures of remote work.
These insights are valuable for practitioners, particularly school principals, as they offer a deeper understanding of the factors determining individual teacher performance.Firstly, remote work necessitates increased job resources to foster engagement and enhance task performance.Secondly, emphasizing work engagement during remote work is crucial, as it positively affects task performance.This can be achieved through feedback, counseling, psychological safety, suitable work environments, personal development opportunities, social support, and praise.Thirdly, increased employee support is essential for enhancing work engagement.Principals should support, care for, and treat employees fairly.Providing workplace autonomy, creative autonomy, and decision-making power can further bolster engagement and performance.
Several limitations of this study need to be outlined.First, all measurements are based on self-reported data and represent the subjective perceptions of respondents.Broader results can be achieved by using more objective measures to examine the association between the dimensions examined in this study.
Second, the research data are geographically and culturally limited as the sample is represented only by Lithuanian teachers.Therefore, the results obtained from other Eastern European countries may reveal more persuasive aspects of this problem.Third, this study has examined employee engagement as a single concept without distinguishing its individual components.Future research may focus on individual components and associations with job demands and resources, individual work performance, and remote work intensity.Fourth, this study examined individual performance as task performance.Future research can address individual components and associations with job demands and resources, engagement, and intensity of remote work.Fifth, not all job demands and resources were included in the research model.Future research may include more factors for job resources and demands and their associations with engagement, individual performance outcomes, and intensity of remote work.
study seeks to fill a research gap and extend the existing research in the management field by investigating factors linked to work engagement and individual performance of teachers.First, this study investigates what factors influence work engagement in the public sector, particularly in the teaching sphere.Second, the study expands the understanding of the factors that affect individual work performance.The insights into contextual job demands such as remote work and their interactions with other factors enable principals of schools to take the most valid interventions.Finally, the study expands the prevailing discussion on mediating effects of work engage-ment and individual work performance among school employees.The conceptual framework is presented in Figure 1.The study is based on the following hypotheses: Mediational Hypotheses: H1: Work engagement mediates the relationship between managerial support and individual work performance.H2: Work engagement mediates the relationship between perceived organizational support and individual work performance.H3: Work engagement mediates the relationship between colleague support and individual work performance.H4: Work engagement mediates the relationship between work pressure and individual work performance.H5: Work engagement mediates the relationship between control and individual work performance.

Figure 1 .
Figure 1.Conceptual framework (Biron & Van Veldhoven, 2016) is "I am pressured to work long hours."Remoteworkwasmeasured by asking for an estimate of the average time per week the employees worked remotely during the last three months(Biron & Van Veldhoven, 2016).AMOS-26.For the mediation estimate, the maximum likelihood bootstrapping method was employed.The value of the Tucker-Lewis index (TLI), comparative fit index (CFI), normed fit index, and root mean square was used to evaluate the model fitness of the measurement model.
tablish the mediational effect.The CB-SEM approach was utilized to investigate the underlying link between observable variables and latent constructs.SEM analysis was performed using IBM-

Table 3 .
Moderation effects of remote work