doi: 10.56294/sctconf2024.1269
ORIGINAL
Factors Impacting Work-Life Balance and Quality of Work Life among Teachers
Factores que afectan el equilibrio entre el trabajo y la vida personal y la calidad de vida Trabajo entre los Profesores
I. Antonyinico1 
*, F. R. Alexander Pravin Durai1 *
1Research Scholar, Department of Commerce, St. Joseph’s College (Autonomous), Affiliated to Bharathidasan University, Tiruchirappalli, Tamilnadu, India.
2Associate Professor, Department of Commerce, St. Joseph’s College (Autonomous), Affiliated to Bharathidasan University, Tiruchirappalli, Tamilnadu, India.
Cite as: Antonyinico I, Pravin Durai FRA. Factors Impacting Work-Life Balance and Quality of Work Life among Teachers. Salud, Ciencia y Tecnología - Serie de Conferencias. 2024; 3:.1269. https://doi.org/10.56294/sctconf2024.1269
Submitted: 12-04-2024 Revised: 31-07-2024 Accepted: 29-10-2024 Published: 30-10-2024
Editor: Dr.
William Castillo-González
Corresponding author: I. Antonyinico *
ABSTRACT
Introduction: a number of circumstances can disrupt the work life balance, and achieving success depends not only on one’s ability to perform at a high level but also on one’s ability to manage professional and personal obligations.
Objectives: to explore the factors impacting Work-life Balance and find out the stress levels that teachers encounter. To assess the Quality of work life among teachers in government-aided and self-financing schools.
Method: a total of 200 samples were selected, and a structured questionnaire was adopted to gather the primary data. The collected data was tested by statistical analysis using various tools, including Mann-Whitney U test, Kruskal-Wallis test, Chi-square, and ANOVA for interpretation.
Results: the findings indicate that teachers in government-aided schools experience lower stress levels and evince higher contentment across various dimensions in quality of work life. However, the teachers in self-financing schools grapple with varying stress levels, ranging from lower to higher stress, reflecting dissatisfaction across all aspects of life.
Conclusion: a collective implantation of strategies from teachers and institutions is required to maintain a healthy and harmonious work life balance in order to augment the quality of work life.
Keywords: Factors; Quality of Work Life; Stress; Work Life Balance; Teachers.
RESUMEN
Introducción: una serie de circunstancias pueden alterar el equilibrio entre la vida trabajo y personal, y alcanzar el éxito depende no solo de la capacidad de una persona para desempeñarse a un alto nivel, sino también de su capacidad para gestionar sus obligaciones profesionales y personales.
Objetivos: explorar los factores que afectan el equilibrio entre el trabajo y la vida personal y determinar los niveles de estrés que enfrentan los profesores. Evaluar la calidad de vida trabajo entre los profesores de los colegios subvencionados por el gobierno y colegios autofinanciados.
Método: se seleccionó un total de 200 muestras y se adoptó un cuestionario estructurado para recopilar los datos primarios. Los datos recopilados se probaron mediante análisis estadístico utilizando varias herramientas, incluida la prueba U de Mann-Whitney, la prueba de Kruskal-Wallis, Chi-cuadrado y ANOVA para la interpretación.
Resultados: los hallazgos indican que los docentes en colegios subvencionados por el gobierno experimentan niveles de estrés más bajos y muestran una mayor satisfacción en varias dimensiones de la calidad de vida trabajo. Sin embargo, los profesores en colegios autofinanciados se enfrentan a diferentes niveles de estrés, que van desde un estrés más bajo a un estrés más alto, lo que refleja insatisfacción en todos los aspectos de la vida.
Conclusión: Es necesaria una implantación colectiva de estrategias desde profesores e instituciones para mantener un equilibrio saludable y armónico entre vida trabajo y personal que permita aumentar la calidad de vida trabajo.
Palabras clave: Factores; Calidad de Vida Trabajo; Estrés; Equilibrio Entre Vida Trabajo y Personal; Profesores.
INTRODUCTION
Teachers in many nations have had to deal with heavy workloads while also being paralysed by threats of increasing class sizes, improved quality indicating additional workload, and layings-off of the teachers.(1) Furthermore, the pervasiveness of technology in all aspects of life, as well as its application in lesson delivery, has visibly expressed the teaching career to hitherto unforeseen realities.(2) After hours, excessive participation in the digital learning environment severely reduces balancing work life and personal life of the teachers.(3)
While empirical evidence demonstrates that increased workload among teachers leads to high stress and other associated difficulties such as poor performance, weak work-life balance, low job satisfaction, and a negative impact on student accomplishment.(4) Many authors analysed the shifting dynamics of teaching phenomenon in India and concluded that the face of education had altered.(5,6,7)
According to certain researchers, work-life balance among school teachers has increasingly diminished as workloads have increased.(8) Unlike these writers, Lahti stated that, while teachers’ workloads in Finland have increased, their work-life balance remains adequate.(9) Likewise, Immanuel discovered that teachers in self-financing schools may manage their professional and personal lives while being contented.(10) Similarly, Blackburn et al. found that teachers are satisfied with their jobs, can balance their workloads, and face less personal interference in their work.(11) According to these findings, Marmol discovered that teachers in the Philippines had a reasonable work-life balance in all aspects, including efficiency, effectiveness, workloads, self-care, family welfare, and support.(12)
As the demands and stresses in the professional sphere escalate, the friction between job obligations and family life intensifies. The evolving landscape of the workforce has significantly spotlighted work-family dynamics.(13) Although the phrase ‘work-life balance’ (WLB) is traditionally connected to the labour force as a whole, there is a noticeable trend of teachers experiencing exhaustion due to the demanding academic responsibilities and professional hurdles. This mounting pressure leads to heightened stress levels among teachers, resulting in an imbalance between their professional commitments and personal lives.(14) Consequently, there emerges a pressing need to delve into and comprehend the intricacies of work-life balance specifically among teachers in both government-aided and self-financing schools. Based on the previous research, the research question is emerged, “What are the factors that impact work life balance of teachers in government-aided and self-financing schools and how it associates with variables related to Quality of work life”
Objectives
1. To explore the factors impacting Work-life Balance (WLB) and find out the stress levels that teachers encounter in government-aided and self-financing schools at Tiruchirappalli District.
2. To assess the Quality of work life (QWL) among teachers in government-aided and self-financing schools at Tiruchirappalli district, considering variables of gender, age, and income.
Hypotheses
H01: A significant association exist between the factors that impact WLB and the level of stress related to teachers in government-aided schools at Tiruchirappalli District.
H02: A significant association exists between the level of satisfaction experienced by the teachers in government-aided schools at Tiruchirappalli District relating to QWL based on gender classification.
H03: A significant association exists between the level of satisfaction experienced by the teachers in government-aided schools at Tiruchirappalli District relating to QWL based on age and income.
H04: A significant association exists between the factors that impact WLB and the level of stress related to teachers in self-financing schools at Tiruchirappalli District.
H05: A significant association exists between the level of satisfaction experienced by the teachers in self-financing schools at Tiruchirappalli District relating to QWL based on gender classification.
H06: A significant association exists between the level of satisfaction experienced by the teachers in self-financing schools at Tiruchirappalli District relating to QWL based on age and income.
METHOD
This study follows a descriptive research method. Since it describes the existing state of affairs, it mainly includes surveys and fact findings. The relationship between the variables is also tested and analysed. The study describes the factors impacting Work-Life Balance and Quality of Work Life among Teachers in Tiruchirappalli district, state of Tamilnadu, India. 200 survey forms were distributed to potential participants within the total population. The researcher adopts simple random sampling method to select the sample respondents from each school. This method ensures that every item of the universe has an equal chance of inclusion in the sample.
The primary data was gathered by the researcher at Tiruchirappalli, a district in the state of Tamilnadu, India. A well-structured questionnaire was prepared for the participants namely teachers working in government-aided and self-financing schools at Tiruchirappalli District and distributed through in-person interviews. This questionnaire was classified into two parts. The first part focused on gathering details related to demographic items by use of a mix of closed- and open-ended enquiries. The part two of the questionnaire comprised Likert scale questions aimed at assessing the the variables impacting Work-Life Balance and Quality of Work Life among Teachers. Secondary data has also been utilized from a variety of sources, such as periodicals, journals, books, and magazines. All the variables in the questionnaire were numerically coded and were entered in excel sheet. The numerically coded data was exported from excel sheet to Statistical Package for Social Sciences (SPSS). The researcher used SPSS 22 version for processing and the analysis of data. Descriptive and analytical tools like Kruskal-Wallis test, ANOVA, Chi-square, and Mann-Whitney U test were used for interpretation.
Informed consent was obtained from the respondents stating that the data collected would be used for academic purposes only. The data collection and analysis were done in adherence to scientific and ethical standards. No fabrication and falsification of data is involved during the research process.
RESULTS
Government-Aided Schools
H01: A significant association exists between the factors that impact WLB and the level of stress related to teachers in self-financing schools at Tiruchirappalli District.
|
Table 1. Factors that Impact WLB and Stress Levels |
||||
|
Factors |
Mean and Standard Deviation (SD) |
Stress Levels |
||
|
Fatigue (Less Stress) |
Committing errors (Medium Stress) |
Biological disorders (More Stress) |
||
|
Commitment towards financial needs |
Mean |
3,22 |
3,32 |
3,83 |
|
Number |
100 |
100 |
100 |
|
|
SD |
1,323 |
1,142 |
1,52 |
|
|
Not Possible to take care of children |
Mean |
3,14 |
3,22 |
3,55 |
|
Number |
100 |
100 |
100 |
|
|
SD |
1,335 |
1,220 |
1,413 |
|
|
More household works |
Mean |
2,32 |
2,22 |
3,76 |
|
Number |
100 |
100 |
100 |
|
|
SD |
1,012 |
1,112 |
1,123 |
|
|
Not spending quality time with family |
Mean |
2,321 |
2,91 |
3,135 |
|
Number |
100 |
100 |
100 |
|
|
SD |
1,014 |
1,211 |
1,152 |
|
|
Work pressure in schools |
Mean |
3,23 |
3,15 |
3,29 |
|
Number |
100 |
100 |
100 |
|
|
SD |
1,126 |
1,213 |
1,445 |
|
|
No recognition from the Management and Leave Problems |
Mean |
3,52 |
3,42 |
3,77 |
|
Number |
100 |
100 |
100 |
|
|
SD |
1,217 |
1,215 |
1,212 |
|
|
No Job Satisfaction and Lower salary |
Mean |
3,31 |
3,44 |
3,62 |
|
Number |
100 |
100 |
100 |
|
|
SD |
1,152 |
1,213 |
1,223 |
|
|
Conflict with Colleagues |
Mean |
2,521 |
2,213 |
3,81 |
|
Number |
100 |
100 |
100 |
|
|
SD |
1,12 |
1,11 |
1,21 |
|
|
Total |
Mean |
3,45 |
3,63 |
3,82 |
|
|
Number |
800 |
800 |
800 |
|
|
SD |
1,123 |
1,212 |
1,228 |
|
|
F Value |
3,262 |
3,432 |
3,753 |
|
|
Sig Value |
,005 |
,004 |
,002 |
|
Source: Author’s Original Data. |
||||
The findings shown in table 1 are of ANOVA examining the relationship between various factors impacting WLB and stress levels of school teachers. The objective is to determine if these factors have a significant influence on the stress levels of teachers.
Key Findings
1. Stress Levels: The stress levels are categorized into three groups: “Fatigue” (Less Stress), “Committing errors” (Medium Stress), and “Biological disorders” (More Stress). The mean stress levels are 3,22, 3,32, and 3,83, respectively, for these three categories. The standard deviations (Std. Deviation) indicate the spread or variability of stress levels within each category.
2. Factors Impacting WLB: Various factors that impact WLB are listed, including commitment towards financial needs, not being able to take care of children, more household works, not spending quality time with family, work pressure in schools, no recognition from the management, leave problems, no job satisfaction and lower salary, and conflicts with colleagues. Each factor is assessed based on its mean score, standard deviation, and the total number of responses (N).
3. Interpretation: The F-Value for each factor represents whether there are significant differences in stress levels associated with that factor. For the “Fatigue” category, the F-Value is 3,623, with a significant p-value of ,003, indicating that there are significant differences in stress levels associated with factors impacting work-life balance in this category. However, for “Committing errors” and “Biological disorders,” the F-Values are 1,321 and 1,442, respectively, with higher p-values (,573 and ,636), indicating that the differences in stress levels are not statistically significant for these categories. Overall, the results suggest that various factors impacting work-life balance significantly influence the stress levels of teachers in government-aided schools, particularly in the “Fatigue” category. These findings can be valuable for understanding the sources of stress and improving work-life balance for teachers.
H02: A significant association exists between the level of satisfaction experienced by the teachers in government-aided schools at Tiruchirappalli District relating to QWL based on gender classification.
|
Table 2. Quality of Work Life based on Gender Classification |
|||||||
|
Factors |
Gender |
Mann Whitney U |
Z |
Sig. (2 tailed) |
Mann Whitney U |
Z |
Asymp Sig (2 tailed) |
|
Job satisfaction |
Male |
1124,000 |
-1,326 |
,153 |
695,000 |
-2,632 |
,002* |
|
Female |
|
|
|
|
|
|
|
|
Total |
100 |
|
|
|
|
|
|
|
Good salary |
Male |
1321,000 |
-,451 |
,625 |
653,000 |
-2,432 |
,004* |
|
Female |
|
|
|
|
|
|
|
|
Total |
100 |
|
|
|
|
|
|
|
Good recognition |
Male |
735 |
-2,274 |
,002* |
784,000 |
-1,543 |
,094 |
|
|
Female |
|
|
|
|
|
|
|
|
Total |
100 |
|
|
|
|
|
|
Family support |
Male |
754,000 |
-2,321 |
,421 |
765,000 |
-1,754 |
,096 |
|
Female |
|
|
|
|
|
|
|
|
Total |
100 |
|
|
|
|
|
|
|
Good Work-life Balance and healthy lifestyle |
Male |
734,000 |
-2,453 |
,006 |
675,000 |
-2,231 |
,027* |
|
Female |
|
|
|
|
|
|
|
|
Total |
100 |
|
|
|
|
|
|
|
Fulfil the family requirements |
Male |
1148,000 |
-,764 |
,253 |
865,000 |
-2,328 |
,015* |
|
Female |
|
|
|
|
|
|
|
|
Total |
100 |
|
|
|
|
|
|
|
More efficient and successful |
Male |
1211,000 |
-,643 |
,259 |
548,000 |
-2,425 |
,024* |
|
Female |
|
|
|
|
|
|
|
|
Total |
100 |
|
|
|
|
|
|
|
Fulfil Social commitment |
Male |
543,000 |
-2,345 |
,001* |
654,000 |
-1,547 |
,095 |
|
Female |
|
|
|
|
|
|
|
|
Total |
100 |
|
|
|
|
|
|
|
Source: Author’s Original Data. Note: * Denotes significance at 5 % level. |
|||||||
The table 2 provides a breakdown of different factors related to QWL, such as job satisfaction, good salary, good recognition, family support, work-life balance, fulfilling family requirements, efficiency, and fulfilling social commitments, and examines the differences between male and female teachers. The table includes the Mann-Whitney U statistic, Z value, and level of significance (two-tailed) for each factor.
Key Findings
1. Job Satisfaction: The Mann-Whitney U statistic for male teachers is 1124,000, “with a Z-score of -1,326 and a p-value of ,153 (not significant)”. The Mann-Whitney U statistic for female teachers is 695,000, “with a Z-score of -2,632 and a p-value of ,002 (significant)”. Result: There is a significant disparity in job satisfaction between male and female teachers, with female teachers expressing lower levels of satisfaction.
2. Good Salary: The Mann-Whitney U statistic for male teachers is 1321,000, “with a Z-score of -0,451 and a p-value of ,625 (not significant)”. The Mann-Whitney U statistic for female teachers is 653,000, “with a Z-score of -2,432 and a p-value of ,004 (significant)”. Result: The perception of good salary differs significantly between male and female teachers, with the former feeling less satisfied.
3. Good Recognition: The Mann-Whitney U statistic for male teachers is 735,000, “with a Z-score of -2,274 and a p-value of ,002 (significant)”. The Mann-Whitney U statistic for female teachers is 784,000, “with a Z-score of -1,543 and a p-value of ,094 (not significant)”. Result: The perception of good recognition differs significantly between male and female teachers, with the former having a lower perception than the latter.
H03: A significant association exists between the level of satisfaction experienced by the teachers in government-aided schools at Tiruchirappalli District relating to QWL based on age and income.
|
Table 3. Quality of Work Life based on Age and Income |
||||||
|
Factors |
Age (years) |
Chi–Square |
Asymp.Sig |
Annual Income (Lakhs) |
Chi- Square |
Asymp.Sig |
|
Job satisfaction |
30-40 |
21,523 |
,000* |
Up to 6 |
8,643 |
,014* |
|
41-50 |
|
|
6 – 7 |
|
|
|
|
51-60 |
|
|
7 – 10 |
|
|
|
|
Good salary |
30-40 |
16,262 |
,000* |
Up to 6 |
6,432 |
,043* |
|
41-50 |
|
|
6 – 7 |
|
|
|
|
51-60 |
|
|
7 – 10 |
|
|
|
|
Good recognition |
30-40 |
4,125 |
,142 |
Up to 6 |
3,572 |
,153 |
|
41-50 |
|
|
6 – 7 |
|
|
|
|
51-60 |
|
|
7 – 10 |
|
|
|
|
Family support |
30-40 |
5,315 |
,063 |
Up to 6 |
2,253 |
,241 |
|
41-50 |
|
|
6 – 7 |
|
|
|
|
51-60 |
|
|
7 – 10 |
|
|
|
|
Good Work-life Balance and healthy life style |
30-40 |
13,525 |
,001* |
Up to 6 |
1,425 |
,045* |
|
41-50 |
|
|
6 – 7 |
|
|
|
|
51-60 |
|
|
7 – 10 |
|
|
|
|
Fulfil the family requirements |
30-40 |
16,413 |
,000* |
Up to 6 |
7,327 |
,012* |
|
41-50 |
|
|
6 – 7 |
|
|
|
|
51-60 |
|
|
7 – 10 |
|
|
|
|
More efficient and successful |
30-40 |
12,434 |
,001* |
Up to 6 |
8,532 |
,011* |
|
41-50 |
|
|
6 – 7 |
|
|
|
|
51-60 |
|
|
7 – 10 |
|
|
|
|
Fulfil Social commitment |
30-40 |
7,243 |
,124 |
Up to 6 |
4,532 |
,064 |
|
41-50 |
|
|
6 – 7 |
|
|
|
|
51-60 |
|
|
7 – 10 |
|
|
|
|
Source: Author’s Original Data. Note: *significant at 5 % level. |
||||||
The table 3 presents the findings of Kruskal-Wallis test examining the relationship between the satisfaction of teachers relating to QWL on the basis of age and income. The Kruskal-Wallis test is used to compare three or more groups and assess whether income levels and age groups differ significantly from one another in terms of various QWL-related factors.
Key Findings
1. Job Satisfaction: The Chi-Square statistic for different age groups (30 to 40 y., 41 to 50 y, 51 to 60 y) is 21,523 with a p-value of ,000*, displaying a significant variance in the degrees of job satisfaction among age groups. The Chi-Square statistic for different income levels (Up to 6 L, 6 to 7 L, 7 to 10 L) is 8,643 with a p-value of ,014*, demonstrating a significant disparity in job satisfaction between various income levels.
2. Good Salary: The Chi-Square values and p-values reveal significant variations in how various age groups and income levels differ in perception of good salary.
3. Good Recognition, Family Support, Work-Life Balance, Fulfilling Family Requirements, Efficiency, and Fulfilling Social Commitment: For some factors (like Good Recognition, Family Support, and Fulfilling Social Commitment), no significant differences exist between age groups or income levels (p-values > ,05). However, for factors like WLB, Fulfilling Family Requirements, and Efficiency, there are significant differences among various age and income groups (p-values < ,05).
Self-Financing Schools
H04: A significant association exists between the factors that impact WLB and the level of stress related to teachers in self-financing schools at Tiruchirappalli District.
|
Table 4. Factors that impact Work-Life Balance and Stress Level |
||||
|
Factors |
Mean and Standard Deviation (SD) |
Stress Levels |
||
|
Fatigue (Less Stress) |
Committing errors (Medium Stress) |
Biological disorders (More Stress) |
||
|
Commitment towards financial needs |
Mean |
3,54 |
2,46 |
2,23 |
|
Number |
100 |
100 |
100 |
|
|
SD |
1,532 |
1,243 |
1,12 |
|
|
Not Possible to take care of children |
Mean |
3,56 |
3,32 |
3,25 |
|
Number |
100 |
100 |
100 |
|
|
SD |
1,324 |
1,131 |
1,136 |
|
|
More household works |
Mean |
2,56 |
2,38 |
2,26 |
|
Number |
100 |
100 |
100 |
|
|
SD |
1,11 |
1,02 |
1,011 |
|
|
Not spending quality time with family |
Mean |
2,746 |
2,04 |
2,12 |
|
Number |
100 |
100 |
100 |
|
|
SD |
1,141 |
1,021 |
1,032 |
|
|
Work pressure in schools |
Mean |
3,54 |
3,12 |
3,07 |
|
Number |
100 |
100 |
100 |
|
|
SD |
1,154 |
1,142 |
1,421 |
|
|
No recognition from the Management and Leave Problems |
Mean |
3,97 |
3,10 |
3,01 |
|
Number |
100 |
100 |
100 |
|
|
SD |
1,425 |
1,143 |
1,112 |
|
|
No Job Satisfaction and Lower salary |
Mean |
3,32 |
3,16 |
3,03 |
|
Number |
100 |
100 |
100 |
|
|
SD |
1,475 |
1,262 |
1,212 |
|
|
Conflict with Colleagues |
Mean |
2,521 |
2,124 |
2,14 |
|
Number |
100 |
100 |
100 |
|
|
SD |
1,473 |
1,142 |
1,017 |
|
|
Total |
Mean |
3,82 |
3,23 |
3,12 |
|
|
Number |
800 |
800 |
800 |
|
|
SD |
1,379 |
1,235 |
1,141 |
|
|
F Value |
3,623 |
1,321 |
1,442 |
|
|
Sig Value |
,003 |
,573 |
,636 |
|
Source: Author’s Original Data. |
||||
The findings shown in table 4 are of ANOVA examining the relationship between various factors impacting WLB and stress levels of school teachers. The objective is to determine if these factors have a significant influence on the stress levels of teachers.
Key Findings
1. Stress Levels: The stress levels are categorized into three groups: “Fatigue” (Less Stress), “Committing errors” (Medium Stress), and “Biological disorders” (More Stress). The mean stress levels are 3,22, 3,32, and 3,83, respectively, for these three categories. The standard deviations (Std. Deviation) indicate the spread or variability of stress levels within each category.
2. Factors Impacting WLB: Various factors that impact WLB are listed, including commitment towards financial needs, not being able to take care of children, more household works, not spending quality time with family, work pressure in schools, no recognition from the management, leave problems, no job satisfaction and lower salary, and conflicts with colleagues. Each factor is assessed based on its mean score, standard deviation, and the total number of responses (N).
3. Interpretation: The F-Values for each factor represent whether there are significant differences in stress levels associated with that factor. For the “Fatigue,” “Committing errors,” and “Biological disorders” categories, the F-Values are 3,262, 3,432, and 3,753, respectively. The corresponding Sig Values are ,005, ,004, and ,002, indicating that there are significant differences in stress levels associated with factors impacting work-life balance for all three categories. Overall, the results suggest that various factors impacting work-life balance significantly influence the stress levels of teachers in self-financing schools, with all three stress categories showing significant associations with these factors. These findings can be valuable for understanding the sources of stress and improving work-life balance for teachers in self-financing schools.
H05: A significant association exists between the level of satisfaction experienced by the teachers in self-financing schools at Tiruchirappalli District relating to QWL based on gender classification.
|
Table 5. Quality of Work Life based on Gender Classification |
|||||||
|
Factors |
Gender |
Mann Whitney U |
Z |
Sig. (2 tailed) |
Mann Whitney U |
Z |
Asymp Sig (2 tailed) |
|
Job satisfaction |
Male |
1132,000 |
-1,423 |
,143 |
693,000 |
-2,543 |
,002* |
|
Female |
|
|
|
|
|
|
|
|
Total |
100 |
|
|
|
|
|
|
|
Good salary |
Male |
1342,000 |
-,624 |
,423 |
647,000 |
-2,537 |
,004* |
|
Female |
|
|
|
|
|
|
|
|
Total |
100 |
|
|
|
|
|
|
|
Good recognition |
Male |
762 |
-3,231 |
,002* |
754,000 |
-1,362 |
,003* |
|
|
Female |
|
|
|
|
|
|
|
|
Total |
100 |
|
|
|
|
|
|
Family support |
Male |
549,000 |
-2,253 |
,462 |
764,000 |
-1,635 |
,005* |
|
Female |
|
|
|
|
|
|
|
|
Total |
100 |
|
|
|
|
|
|
|
Good Work-life Balance and healthy life style |
Male |
654,000 |
-2,742 |
,005 |
764,000 |
-2,240 |
,043* |
|
Female |
|
|
|
|
|
|
|
|
Total |
100 |
|
|
|
|
|
|
|
Fulfil the family requirements |
Male |
1063,000 |
-,654 |
,453 |
786,000 |
-2,327 |
,015* |
|
Female |
|
|
|
|
|
|
|
|
Total |
100 |
|
|
|
|
|
|
|
More efficient and successful |
Male |
1253,000 |
-,684 |
,352 |
743,000 |
-2,215 |
,027* |
|
Female |
|
|
|
|
|
|
|
|
Total |
100 |
|
|
|
|
|
|
|
Fulfil Social commitment |
Male |
642,000 |
-3,253 |
,003* |
825,000 |
-1,647 |
,034* |
|
Female |
|
|
|
|
|
|
|
|
Total |
100 |
|
|
|
|
|
|
|
Source: Author’s Original Data. Note: * Denotes significance at 5 % level. |
|||||||
Table 5 shows that the findings of a Mann-Whitney U test are to assess the relationship between satisfaction of teachers relating to QWL and gender classification. As in the previous analysis, the Mann-Whitney U test is used to determine whether there are significant differences between male and female teachers for a range of QWL-related factors.
Key Findings
1. Job Satisfaction: The Mann-Whitney U statistic for male teachers is 1132,000, “with a Z-score of -1,423 and a p-value of ,143 (not significant)”. The Mann-Whitney U statistic for female teachers is 693,000, “with a Z-score of -2,543 and a p-value of ,002 (significant)”. Result: There is a significant disparity in job satisfaction between male and female teachers, with female teachers expressing lower levels of satisfaction.
2. Good Salary: The Mann-Whitney U statistic for male teachers is 1342,000, “with a Z-score of -0,624 and a p-value of ,423 (not significant)”. The Mann-Whitney U statistic for female teachers is 647,000, “with a Z-score of -2,537 and a p-value of ,004 (significant)”. Result: The perception of good salary differs significantly between male and female teachers, with the former feeling less satisfied.
3. Good Recognition: The Mann-Whitney U statistic for male teachers is 762,000, “with a Z-score of -3,231 and a p-value of ,002 (significant). The Mann-Whitney U statistic for female teachers is 754,000, with a Z-score of -1,362 and a p-value of ,003 (significant)”. Result: The perception of good recognition differs significantly between male and female teachers, with the former having a lower perception than the latter.
H06: A significant association exists between the level of satisfaction experienced by the teachers in self-financing schools at Tiruchirappalli District relating to QWL based on age and income.
|
Table 6. Quality of Work Life based on Age and Income |
||||||
|
Factors |
Age (Years) |
Chi- Square |
Asymp.Sig |
Annual Income (Lakhs) |
Chi- Square |
Asymp.Sig |
|
Job satisfaction |
30-40 |
23,876 |
,000* |
Up to 3 |
8,543 |
,013* |
|
41-50 |
|
|
3 – 4 |
|
|
|
|
51-60 |
|
|
4 – 6 |
|
|
|
|
Good salary |
30-40 |
15,432 |
,000* |
Up to 3 |
6,682 |
,004* |
|
41-50 |
|
|
3 – 4 |
|
|
|
|
51-60 |
|
|
4 – 6 |
|
|
|
|
Good recognition |
30-40 |
4,080 |
,023* |
Up to 3 |
3,425 |
,016* |
|
41-50 |
|
|
3 – 4 |
|
|
|
|
51-60 |
|
|
4 – 6 |
|
|
|
|
Family support |
30-40 |
5,323 |
,054* |
Up to 3 |
2,124 |
,0212* |
|
41-50 |
|
|
3 – 4 |
|
|
|
|
51-60 |
|
|
4 – 6 |
|
|
|
|
Good Work-life Balance and healthy life style |
30-40 |
12,562 |
,001* |
Up to 3 |
1,642 |
,035* |
|
41-50 |
|
|
3 – 4 |
|
|
|
|
51-60 |
|
|
4 – 6 |
|
|
|
|
Fulfil the family requirements |
30-40 |
13,233 |
,000* |
Up to 3 |
6,343 |
,011* |
|
41-50 |
|
|
3 – 4 |
|
|
|
|
51-60 |
|
|
4 – 6 |
|
|
|
|
More efficient and successful |
30-40 |
12,322 |
,001* |
Up to 3 |
8,426 |
,012* |
|
41-50 |
|
|
3 – 4 |
|
|
|
|
51-60 |
|
|
4 – 6 |
|
|
|
|
Fulfil Social commitment |
30-40 |
7,734 |
,035 |
Up to 3 |
4,645 |
,042* |
|
41-50 |
|
|
3 – 4 |
|
|
|
|
51-60 |
|
|
4 – 6 |
|
|
|
|
Source: Author’s Original Data. Note: *significant at 5 % level. |
||||||
The table 6 shows the outcomes of a Chi-Square analysis (Kruskal-Wallis test) examining the connection between school teachers’ satisfaction regarding QWL, concerning age and income levels. This analysis compares the perceptions of various factors associated with Quality of Work Life across different age groups and income brackets.
Key Findings
1. Job Satisfaction: For age groups (30 to 40 y, 41 to 50 y, 51 to 60 y), the Chi-Square values are high, and the p-value (,000*) indicates a significant difference in job satisfaction among different age brackets. The Chi-Square values for various income brackets (Up to 3 L, 3 to 4 L, 4 to 6 L) also exhibit a considerable difference in job satisfaction.
2. Good Salary: Significant differences exist in perceptions of a good salary among different age groups and income brackets, as indicated by the Chi-Square values and associated p-values.
3. Good Recognition, Family Support, Work-Life Balance, Fulfilling Family Requirements, Efficiency, and Fulfilling Social Commitment: There are significant disparities in the perceptions of these factors among different age groups and income levels. Some factors, such as Good Recognition, Family Support, and Fulfilling Social Commitment, are significantly different across age and income brackets, while others, like Work-Life Balance, Fulfilling Family Requirements, and Efficiency, also show significant differences in their associations.
DISCUSSION
Government-Aided Schools
The quality of work life of teachers in government-aided schools differs among male and female teachers in terms of job satisfaction, good salary and good recognition. The female teachers in government-aided schools express lower levels of satisfaction than male teachers. The male teachers in government-aided schools are less satisfied in the salary that they receive and have a low perception for good recognition compared to female teachers. Similarly, the teachers in government-aided schools demonstrates a significant disparity in job satisfaction between various income levels. For some factors like Good Recognition, Family Support, and Fulfilling Social Commitment there is no significant differences exist between age groups or income levels among teachers in government-aided schools. However, for factors like WLB, Fulfilling Family Requirements, and Efficiency, there are significant differences among various age and income groups. The various factors impacting work-life balance significantly influence the stress levels of teachers in government-aided schools, particularly in the “Fatigue” category.
Self-financing Schools
Regarding teachers in self-financing schools, there is a significant disparity in job satisfaction between male and female teachers, with female teachers expressing lower levels of satisfaction. The male teachers in self- financing schools have low perception to good salary and good recognition. Significant differences exist in perceptions of a good salary among different age groups and income brackets. The research also shows that there is a significant disparity in job satisfaction between various income levels. The factors like Good Recognition, Family Support, Work-Life Balance, Fulfilling Family Requirements, Efficiency, and Fulfilling Social Commitment are found be significantly different among age groups and income levels of teachers in self-financing schools. The various factors impacting work-life balance significantly influence the stress levels of teachers in self-financing schools, with all three stress categories showing significant associations with these factors.
CONCLUSION
In today’s dynamic milieu, the perceived importance of work can often overshadow other facets of our lives. Nevertheless, prioritizing work-life balance has been recognized as an avenue toward enhancing overall well-being and fostering sustained success. The statistical analysis discerns that teachers in government-aided schools experience lower stress levels and evince higher contentment across various dimensions of a quality work life, indicative of a more balanced work-life engagement. This cohort enjoys comprehensive facilities, resulting in minimal stress. Conversely, teachers in self-financing schools grapple with varying stress levels, ranging from lower to higher stress, reflecting dissatisfaction across all aspects of a quality work life and a lack of equilibrium. The inadequacies in facilities and support systems for self-financing school teachers culminate in meagre remuneration, limited leaves, restricted social participation, and inadequate recognition despite their substantial commitment, at work and home. At an institutional level, a collective effort to enhance work-life balance is paramount. Institutions focusing on self-financing schools must prioritize and acknowledge the role of teachers within this system. Teachers can initiate incremental changes in their work patterns, commencing with self-reflection and identification of areas for improvement. A supportive environment, inclusive of institutional guidance, is essential. Adhering to these guidelines could pave the way for a positive transformation in work-life balance within society.
REFERENCES
1. Day, C. Teachers in the Twenty-first Century: Time to renew the vision. Teachers and Teaching. 2000;6(1):101-15. https://doi.org/10.1080/135406000114771
2. Wheeler, S. Information and communication technologies and the changing role of the teachers. Journal of Educational Media. 2001;26(1):7-17. https://doi.org/10.1080/135816500120069292
3. Bauwen, R, Muylaert, J, Clarrysse, E, Audenaert, M, Decramer, A. Teachers’ acceptance and use of digital learning environments after hours: Implications for work-life balance and the role of integration preference. Computers in Human Behaviour. 2020;112(2020): 1-9. https://doi.org/10.1016/j.chb.2020.106479
4. Naylor, C, White, M. The work life of BC teachers in 2009: A BCTF study of working and learning conditions. British Columbia Teachers’ Federation. 2010.[Accessed 9 July 2024]. Available from: http://www.bctf.ca/uploadedfiles/public/issues/WorklifeWorkload/2009/fullreport.pdf
5. Dey, B, Dutta, SK. Changing role of teachers. International Journal of Research and Analytical Reviews. 2018;5(3):16-19
6. Gayen, S. Role of teachers in the changing scenario in Indian society. Harvest (Online) Bi-annual. 2017;2: 81-83
7. Husssain, MA, Sultana, S. Changing roles of teachers in the society and the present scenario of teacher education in India. International Journal of Multidisciplinary Research. 2017; 6(3): 90-98
8. Ching, PL, Soek, PB. Challenge hindrance appraisal job and work life balance among teachers: A conceptual paper. Malaysian Journal of Social Sciences and Humanities. 2018;3(3):104-16
9. Lahti, A. The perceived impact of flexible working hours on work-life balance in the education sector in Finland [Bachelor’s thesis]. Aalto University, School of Business. [Internet] 2017. Available from: https://core.ac.uk/download/pdf/84756547.pdf
10. Immanuel, SJD. Work life balance of women teachers in matriculation schools: An empirical investigation. International Journal of Research-Granthaalayah. 2016; 4(7): 5-9
11. Blackburn, JJ, Bunch, JC, Haynes, JC. Assessing the relationship of teachers’ self-efficacy, job satisfaction and perception of work life balance of Louisiana agriculture. Journal of Agricultural Education. 2017; 58 (1): 14-35
12. Marmol, AD. Dimensions of teachers’ work-life balance and school commitment. International Multidisciplinary Research Journal. 2019;1(1):110-20
13. Blackburn, JJ, Bunch, JC, Haynes, JC. Assessing the relationship of teachers’ self-efficacy, job satisfaction and perception of work life balance of Louisiana agriculture. Journal of Agricultural Education. 2017; 58 (1): 14-35
14. Grady, G, McCarthy, A. Work life integration: experiences of mid-career professionals working mothers. Journal of managerial Psychology. 2008;23(5): 599-22
FINANCING
No financing.
CONFLICT OF INTEREST
None.
AUTHORSHIP CONTRIBUTION:
Conceptualization: I. Antonyinico, F. R. Alexander Pravin Durai.
Data curation: I. Antonyinico, F. R. Alexander Pravin Durai.
Formal analysis: I. Antonyinico, F. R. Alexander Pravin Durai.
Research: I. Antonyinico, F. R. Alexander Pravin Durai.
Methodology: I. Antonyinico, F. R. Alexander Pravin Durai.
Drafting – Original Draft: I. Antonyinico, F. R. Alexander Pravin Durai.
Writing - Proofreading and Editing: I. Antonyinico, F. R. Alexander Pravin Durai.