JOB SATISFACTION AMONG FEMALE TEACHERS IN PUBLIC AND PRIVATE SECTORS (A CROSS-SECTIONAL STUDY)

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1 Volume 2, 2013, Page JOB SATISFACTION AMONG FEMALE TEACHERS IN PUBLIC AND PRIVATE SECTORS (A CROSS-SECTIONAL STUDY) Naila Amjad, Shazia Qasim Department of Statistics, Lahore College for Women University, Lahore, Pakistan. ABSTRACT This is a school based cross-sectional study consisting of both descriptive and analytical mechanism. It includes 366 female teachers who experienced the job satisfaction at seventeen randomly selected private and public schools (four public and thirteen private schools) of Lahore. The objective of this study is to identify the significant factors of job satisfaction among female teachers and to determine the predictive strength of factors. For the 366 female teachers, 323 are cases and 43 are controls and data is collected through questionnaire. Reliability test is applied through Cronbach s Alpha and Multiple Logistic Model is fitted on significant factors. The significant factors are Status, Job, Qualification, Income, Stress and Pay package. 1. INTRODUCTION 1.1 Job Satisfaction Job satisfaction is relevant to human health. In recent years a number of women entered in teaching profession. A satisfy teacher plays a pivotal role in the upliftment of society. A dissatisfy teacher can become irritable and may create tensions which can have negative influence on the student learning process. 1.2 Job Satisfaction among Female Teachers Teaching is the biggest source of employment for women in formal sectors. Only female teachers recruited to teach in girl s school. In teaching it is more important to have mental commitment and loyalty than physical presence. 1.3 Job Satisfaction among Female Teachers in Government Sectors For many public school teachers, teaching is seen as a profession which offers job security. Female head teachers are significantly more satisfied than male head teachers. 1

2 Volume 2, 2013, Page Furthermore, the public sectors rely on expertise of such professionals to effectively implement government policies. 1.4 Job Satisfaction among Female Teachers in Private Sectors Private schools have a long history in Pakistan. In private sector large numbers of female faculty members are rending their services. Private school teachers tend to be satisfied than public school teachers. 1.5 Objective of the Study The objectives of the study are: To determine through cross tabulation which study variables are significantly contributing towards job satisfaction. To construct a statistical model on significant factors. To identify whether the teachers are contented with beneficial prospects. 2. LITERATURE REVIEW Chen (2010) examined in study that Chinese middle school teachers are dissatisfied with job than younger and less-experienced teachers. Akhtar et al. (2010) investigated in comparative study that there is no significant difference between teacher s job satisfaction in public and private schools. Mensah et al. (2010) discussed the issues which influence the teachers satisfaction and concentrated on workload and conditions of services such as salary as part of key element causing teachers dissatisfaction. Chaturvedi.et al. (2009) investigated the role of certain demographic variables in determining stress-coping behavior of female teachers of various schools of Bhopal. Memeon (2009) carried out in the study that head teachers with smaller schools are more satisfied with social status and compensation than head teachers with larger schools in Toba Tek Singh, Punjab and Age, Gender, Experience and School location were found important predictors of job satisfaction. Tasnim et al. (2006) analyzed that female section is more dissatisfied than male teachers in Government primary school Bangladesh. Similarly Shah et al. (2005) wrote an article and examined that female teachers are more satisfied than male teachers but less satisfied with interpersonal relation with colleagues in public universities of Bangladesh. Wiggins (2007) obtained that teachers are significantly correlated with Social, artistic and Realistic Scales of the Vocational Preference Inventory (VPI). Rutebuka (2000) conducted that most (68.8%) of the teachers were dissatisfied their class sizes with specific reference to teaching and learning materials available to 2

3 Volume 2, 2013, Page them in Adventist Schools of U.S. Geigner et al. (2000) conducted job satisfaction among Information Technology Workers in U.S. 3. DATA COLLECTION AND METHOLOGY This is a cross-sectional study which includes female teachers of public and private sectors. It contains 323 cases i.e. the teachers who are satisfied with their job and 43 controls i.e. the teachers who are not satisfied with their job. 3.1 Sample and Sampling Technique The sampling unit was selected from one locality of the city of Lahore. The sample includes female teachers only. Seventeen schools were selected by stratified random sampling which includes four public and thirteen private schools then by using random sampling the schools were selected. All selected schools were completely studied including all female teachers. The total number of female teachers is 366 consisting 323 cases and 43 controls. 17 Public and Private Schools 13 Private Schools 4 Public Schools 3.2 Data Collection and Study Instrument The data was collected from all selected schools. A tool questionnaire was designed to gather information from all female teachers and it was filled from all selected schools. The 3

4 Volume 2, 2013, Page reliability of questionnaire was checked by using Cronbach s Alpha. It normally ranges between 0 and 1 and here the computed value is Study Variables The study variables of the study are: Marital Status Type of School Type of Job Level of Education Educational Qualification Income Spending Time Stress Find the Job Pension Job Satisfaction Pay Package Opportunity Team Spirit Vacation Bonus 4. LOGISTIC REGRESSION Logistic Regression is a type of predictive model that can be used when the target variable is a categorical variable with two categories, for example live/die, has disease/doesn t have disease etc. The specific form of logistic regression model is as follows: The goal is generally to identify a small set of predictor variables that make in terms of theoretical understanding and that does a good job of predicting group membership for most individuals in the sample. 4.1 Multiple Logistic Regression 4

5 Volume 2, 2013, Page Multiple Logistic Regression is a kind of Logistic Regression which has many variables. The multiple logistic regression model is given by the equation In which logistic regression model is 4.2 Odds Ratio The odds ratio is the ratio of the odds of an event occurring in one group to the odds of it occurring in another group. If probabilistic of the event in each of the group are p 1 (first group) and p 2 (second group), then the odds ratio is The odds ratio must be greater than or equal to zero if it is defined. It is undefined if p 2 q 1 equals zero. 4.3 Role of Odds Ratio in Logistic Regression Logistic regression is one to generalize the odds ratio beyond two binary variables. Suppose we have a binary response variable Y and a binary predictor variable X, and in addition we have other predictor variables Z 1,.,Z p that may or may not be binary. If we use multiple logistic regression Y on X, Z 1,.,Z p, then the estimated coefficient for X is related to a conditional odds ratio. Specifically, at the population level So exp(β x ) is an estimate of this conditional odds ratio and the interpretation of exp(β x ) is as an estimate of the odds ratio between Y and X when the values of Z 1,.,Z p are taken fixed. 5

6 Volume 2, 2013, Page Wald s Test The Wald test is obtained by comparing the maximum likelihood estimate of the slope parameter, to an estimate of its standard error. The resulting ratio under the hypothesis that β 1 =0 follows standard normal distribution. Wald test for Logistic Regression Model is And multivariate analog of the Wald test is obtained by the following vector matrix calculation. 4.5 The Hosmer-Lemeshow Statistics ( ) ( ) The Hosmer-Lemeshow test is used frequently in risk prediction models. The test assesses whether or not the obtained the observed event rates match expected event rates in subgroups of the model population. It follows a chi-square distribution with g-1 degree of freedom when fitted model is appropriate; it is leading to a formal test of goodness of fit for ungrouped binary data and p-value of the significance should not be interpreted rigidly. 4.6 Forward Stepwise Likelihood ratio Method In this method model is fitted with a constant only to begin and a single predictor is added on the basis of most significant score statistic and LR statistic is defined as ( ) And LR is asymptotically chi-square distributed with degree of freedom equals to the difference between the numbers of parameters estimated in the two models. 5. ANALYSIS AND CONCLUSIONS In the research all the factors are taken as categorical and complete analysis of data collection is based on descriptive and analytical study. In descriptive study cross tabulation of the factors was used and descriptive study shows that married female teachers are more satisfied than unmarried teachers and semi government school teachers are more satisfied than others. The teachers who have permanent jobs, no 6

7 Volume 2, 2013, Page stress and aptitude of pension showed more tendency towards satisfaction. Similarly beneficial prospects (opportunity, team spirit, vacation and bonus) demonstrated more content of teachers. For analytical analysis Multiple Logistic Regression was fitted which included all the significant variables of job satisfaction. The stepwise likelihood ratio method was used to determine the predictive strength of significant causes of job satisfaction. The fitted model is Job Satisfaction = Status (1) Job (1) Job (2) Job (3) Qualification (1) Income (1) Income (2) Income (3) Income (4) Stress (1) Pay Package (2) Pay Package (3) Pay Package (4) The table 5.1 provides Wald s test for all variables included in the model. The parameter estimates (log odds) are given in the column labeled as B, standard error of the estimates are given in the column labeled S.E and odds are given in the column labeled as Exp(B). In the logistic regression it is hard to interpret log odds, so they are exponentiated to given odds ratios shown in the table Exp(B) and can be interpreted as change in odds as a result of unit change in predictor. The table shows that Status, Job, Qualification, Income, Stress, Pay package are significant factors towards job satisfaction as their p-values are less than Interpretation of Significant factors of the Model The factor Status is taken as categorical variable. Unmarried status is taken as reference group for the factor. Since the coefficient is negative and odds is The married (higher code) female teachers have times less chance of having job satisfaction than unmarried female teachers keeping all other factors constant. The odds ratio for the factor status is less than 1 therefore the factor status has negative association and is statistically significant. Job group (Contract) is positive and odds ratio is which means that contract job has chance of having job satisfaction. Job group (Permanent) is positive and odds ratio is which means that permanent job has times more chance of having job satisfaction. Daily wages group is positive and odds ratio is which means that daily wages job has times chance of having job satisfaction. The odds ratio for job is greater than 1 in all job groups hence job type is statistically significant and has positive association with job satisfaction. Educational Qualification is also taken as categorical variable. Teachers who feel that their job educational level suits their job are taken as reference group. Since coefficient is taken as negative and odds ratio is The teachers who feel that their educational 7

8 Volume 2, 2013, Page qualification does not suit their job have times less chance of having job satisfaction. The odds ratio is less than 1 therefore qualification has negative association with job satisfaction. Income group (<4000) is positive and odds ratio is which means that income has job satisfaction among female teachers. Income group ( ) is positive and odds ratio is which means that increase in income has more job satisfaction among female teachers. Income group ( ) is positive and odds ratio is which means that more increase in income has more job satisfaction among female teachers. Income group ( ) is positive and odds ratio is which means that increase in income has more job satisfaction among female teachers. The overall odds ratio for the income is greater than 1; income is statistically significant and has positive association with job satisfaction. The factor Stress is taken as categorical variable. Stress category is taken as reference group for the factor stress. Since coefficient is negative and odds ratio is which means that increase in stress has times less chance of having job satisfaction keeping all other factors constant. The odds ratio for the factor stress is less than 1 therefore factor no-stress has negative association with job satisfaction and statistically significant. Pay Package group (Highly Satisfied) is positive and odds ratio is which means that high satisfaction with pay package has more job satisfaction among female teachers. Pay package group (Satisfied) is positive and odds ratio is which means satisfaction with pay package there is an increase in job satisfaction. Pay package (Neutral) is positive and odds ratio is which means that with the neutral satisfaction of pay package there is an increase in job satisfaction. Pay package (Dissatisfied) is negative and odds ratio is which means that with the dissatisfaction for pay package there is less satisfaction towards job. 5.2 Significance of the Model To check the adequacy of the logistic regression model Hosmer and Lemeshow test is used to test the hypothesis that the observed data is significantly different from predicted values from the model (goodness of fit; observed value = predicted value). The Hosmer and Lemeshow statistic equals to with degree of freedom (d.f) = 7 and with a nonsignificant p-value=0.954 (table 5.2), which indicates a decent fit. Hence we conclude that the model does not differ significantly from the observed data. Therefore model is appropriate and is adequately fit the data. 8

9 Volume 2, 2013, Page International Journal of Applied Research Volume 2, 2013, Page The Omnibus tests measure how well a model performs. They provide a test for all the explanatory variables affect simultaneously. It gives significant result with p= and demonstrates that we are 95% confident that the model is appropriate/significant. RECOMMENDATION Job satisfaction is a very vital concern in every field, so enormous area can be studied for such type of research. Also find the job satisfaction among female and male teachers can generate more responsiveness about the job satisfaction. Research on job satisfaction can be completed not only taking data from the school teachers but also taking information from college teachers, university teachers as well as from the employees of other sectors/ departments (such as private or government). ACKNOWLEDGEMENT The author is obliged to Ms. Naila for her precious input and supervision for throughout the research process and special thanks to Ms. Rashda for her guidance and help. Also special thanks to Mr. Qasim Abbasi, Mrs. Fozia Abbasi, Ms. Nazia Qasim and Ms. Azra Qasim for encouragement and support. Ms. Ifrah Mahmood, Mr. Shahid Abbasi and Mr. Ghalib are gratefully acknowledged. REFERENCES 1. Akhtar N.S., Hashmi A. M., and Naqvi H. I. S., (2010) A Comparative Study of Job Satisfaction in Public and Private School Teachers at Secondary Level. 2. Geigner L.C., and Crow B.G., (2000). A Comparison of Job Satisfaction among Women in Computing and a More Traditional Female Occupation. 3. Javaid Memeon, (2009). Job Satisfaction of Elementary School Head Teachers (Toba Tek Singh) in the Punjab, PhD thesis; 20:2. 4. Junjun Chen, (2010). Chinese Middle School Teacher Job Satisfaction and its Relationship with Teacher Moving, Journal of Asia Pacific Education Review, Springer Netherlands Publishing Group. 5. Chaturvedi M., and Purushothaman T., (2009). Behavior of Female Teachers and Job Satisfaction D.R.D.O, Selection Centre Central, S.I. Lines, Bhopal, India. 9

10 Volume 2, 2013, Page Table 5.1 Wald Test for all Variables in the Equation Variable B S.E Wald d.f Sig Exp(B) Status(1) Job Job(1) Job(2) Job(3) Qualification(1) Income Income(1) Income(2) Income(3) Income(4) Stress(1) Pay Package Pay Package(1) Pay Package(2) Pay Package(3) Pay Package(4) Constant Table 5.2 Hosmer and Lemeshow Test Hosmer and Lemeshow Test Ho:Observed Value=predicted Value Omnibus Test (Significance of the Model) Chi-Square P-Value Chi-Square P-Value = =