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\setlength{\parindent}{0pt}\raggedright \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt \textcolor{GJBlue}{\large\bfseries\abstractname\space} }{% \vskip8pt \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt } \usepackage[absolute,overlay]{textpos} \makeatother \usepackage{lineno} \linenumbers \begin{document} \author[1]{ Achchuthan} \affil[1]{ Sabaragamuwa University of Sri Lanka} \renewcommand\Authands{ and } \date{\small \em Received: 10 December 2013 Accepted: 1 January 2014 Published: 15 January 2014} \maketitle \begin{abstract} The primary aim of the study is to find out the significant mean difference in pay satisfaction among personal characteristics of the school teachers as gender, age, family size, subjects for teaching, educational qualification, work place and work experience. Further, secondary objective is to suggest the government authoritative bodies to enhance pay satisfaction, which will give the long term value to the Northern Province, Sri Lanka in terms of social, economical and political development. The study employs independent samples t- test and one-way ANOVA (f-test) to test the operational hypotheses. The survey method used in this study is a questionnaire and a total of 360 usable responses were obtained using simple random sampling technique. Findings revealed that, there is a significant mean difference in pay satisfaction among family size, subjects for teaching, educational qualification and working experience. In contrast, we found that, there is no significant mean difference in pay satisfaction among gender, age level and work place. Further, we suggested that, When the drafts on policies in terms of the pay structure and administration of the school teachers especially in the northern part of the Sri Lanka are initiated or designed, governmental bodies like ministry of education should consider the differences in the level of pay satisfaction among personal characteristics. This study would hopefully benefit to the academicians, researchers, policy makers, and practitioners of Sri Lanka as well as other countries. \end{abstract} \keywords{pay satisfaction, personal characteristics, northern province, sri lanka and school teachers .} \begin{textblock*}{18cm}(1cm,1cm) % {block width} (coords) \textcolor{GJBlue}{\LARGE Global Journals \LaTeX\ JournalKaleidoscope\texttrademark} \end{textblock*} \begin{textblock*}{18cm}(1.4cm,1.5cm) % {block width} (coords) \textcolor{GJBlue}{\footnotesize \\ Artificial Intelligence formulated this projection for compatibility purposes from the original article published at Global Journals. However, this technology is currently in beta. \emph{Therefore, kindly ignore odd layouts, missed formulae, text, tables, or figures.}} \end{textblock*} \let\tabcellsep& \section[{I.}]{I.}\par Background of The Study he study on employee's satisfaction with compensation has been initiated and exhibited in the early 1960s, two index measurements as Job Descriptive Index (JDI) and the Minnesota Satisfaction Questionnaire (MSQ) have been utilized in the pay or compensation satisfaction dimension in the literature of the pay satisfaction \hyperref[b18]{(Smith, Kendall, \& Hulin, 1969;}\hyperref[b22]{Williams, McDaniel \& Ford, 2007;}\hyperref[b20]{Velnampy, 2008)}. \hyperref[b3]{Heneman and Schwab (1985)} examined the compensation satisfaction with the help of the four dimensions as satisfaction with pay level, pay raises, benefit level, and pay structure and administration.\par Further, the perception towards pay satisfaction among. employees may differ from person to person. Every person perceives the world differently based on their attitudes and behaviors \hyperref[b0]{(Aloysius, 2011)}. In this context, we have to empirically analyze the facts that, whether personal demographic factors have the influence on the pay satisfaction or not. Due to that, we have selected the school teachers in Northern Province, Sri Lanka.\par Northern Province is considered as the emerging province among other provinces in Sri Lanka. Especially in the post war context, the Northern Province has been already focused by the government for the renovation and development perspective. In this context, education should be viewed as the fundamental need of the community, which will give the value in the long run to get the better society in terms of well organized culture, social status, better income level \& standard of living etc. In the world of education, Teaching is a profession that lies at the heart of both the learning of children and young people and their social, cultural and economic development. It is crucial to transmitting and implanting social values, such as democracy equality, tolerance cultural understanding, and respect for each person's fundamental freedoms \hyperref[b7]{( MacBeath, 2012)}.in this context, Schools today are better places for children with special needs and learning difficulties in countries where teachers have access to research and enjoy opportunities to take part in continuing professional development \hyperref[b7]{( MacBeath, 2012)}. Further, Teachers come into the profession for differing reasons in different country contexts, in differing economic circumstances and with varying expectations of the rewards and challenges of the role The main objective of the study is to find out the significant mean difference in pay satisfaction among personal demographic variables of the school teachers as gender, age, family size, subjects for teaching, educational qualification, work place and work experience. Further, secondary objective is to suggest the government authoritative bodies to enhance pay satisfaction, which will give the long term value to the Northern Province, Sri Lanka in terms of social, economical and political development.\par T significant mean difference in pay satisfaction among personal characteristics of the school teachers as gender, age, family size, subjects for teaching, educational qualification, work place and work experience. Further, secondary objective is to suggest the government authoritative bodies to enhance pay satisfaction, which will give the long term value to the Northern Province, Sri Lanka in terms of social, economical and political development. The study employs independent samples t-test and one-way ANOVA (f-test) to test the operational hypotheses. The survey method used in this study is a questionnaire and a total of 360 usable responses were obtained using simple random sampling technique. Findings revealed that, there is a significant mean difference in pay satisfaction among family size, subjects for teaching, educational qualification and working experience. In contrast, researchers found that, there is no significant mean difference in pay satisfaction among gender, age level and work place. Further, researchers suggested that, When the drafts on policies in terms of the pay structure and administration of the school teachers especially in the northern part of the Sri Lanka are initiated or designed, governmental bodies like ministry of education should consider the differences in the level of pay satisfaction among personal characteristics. This study would hopefully benefit to the academicians, researchers, policy makers, and practitioners of Sri Lanka as well as other countries.\par Reinforcement theory and expectancy theory have been viewed as the earliest theories to give insights on how pay influences employee behavior. Reinforcement theory \hyperref[b17]{(Skinner, 1953)} suggested that, pay acts as a general reinforce. People learn from life experiences that a primary need, such as food or shelter, can be satisfied if money is obtained. \hyperref[b21]{Vroom's (1964)} expectancy theory stated that how pay influences future behavior. According to expectancy theory, three components determine motivation: judgment regarding to the likelihood that an effort leads to a certain level of performance (expectancy); Judgment regarding to the likelihood that this level of performance leads to a certain outcome (Instrumentality); the importance of the outcome to the individual (valence) \hyperref[b2]{( Faulk, 2002)}. Further, Important link between pay and pay satisfaction has been originated by \hyperref[b4]{Herzberg's (1968)} two-factor motivational model, which suggested that, it is the individual's affective reaction to pay, pay satisfaction, which impacts motivation. Further, it suggested that, the pay is a hygiene, or contextual factor, that prevents an employee from being motivated by such things as the work itself.\par The effect of self-esteem and pay satisfaction on adjustment and outcome variables among teachers has been carried by \hyperref[b14]{Richardson , Kirchenheim and Richardson , 2006}. The results revealed that, there is evidence of a relationship between pay satisfaction and other job-related factors, namely job satisfaction and turnover intention. All of the outcome factors correlate positively with adjustment. It should be noted that the pay satisfaction measure used is multi-dimensional. Clearly, then, there is a relationship between perceptions of pay and benefits, overall adjustment, and other work related factors. Findings suggested that, from an organizational perspective, the accurate measurement of some of these identified intrinsic and extrinsic factors may provide valuable information to the employer regarding those applicants that have the greatest probability of adjustment.\par The study on salary differential and managerial job satisfaction in Nigeriaa has been conducted by okpara, 2004. In which gender gap is utilized. Further, In Nigeria, number of women who have entered the banking profession in recent years has been increasing. The population for this study comprised bank managers who were members of the Chartered Institute of Bankers of Nigeria (CIBN). The aim of the mentioned study is to investigate whether there is a male / female salary differential for bank managers. Results indicated that, \hyperref[b8]{(Nakata \& Takehiro, 2002)}.Gender inequality may also be attributed to the socio-cultural environment of the country, which strongly accords the traditional roles of housewife and mother to women. This cultural status may be responsible for some significant gender inequality in the industrial and service sectors of the Nigerian economy. Furthermore, Correlation results also indicated that a significant relationship exists between salary and gender, education, and experience. These variables explain the reasons for salary differential between male and female bank managers in Nigeria. \hyperref[b1]{Baakile (2011)} focused the study on comparative analysis of teachers' perception of equity, pay satisfaction, affective commitment and intention to turnover in Botswana. The purpose of the study was to investigate the relationships between equity, pay satisfaction, affective commitment and intention to turnover among junior and senior secondary school teachers in Botswana. Results revealed that, the relationship between equity and pay satisfaction was strong and significant for both junior and senior secondary school teacher. The relationship between equity and affective commitment, pay satisfaction and intention to turnover, and affective commitment and intention were all significant. The major conclusions are that teachers' perception of these variables is similar regardless of whether they are at a junior or senior school.\par Nguyen, Taylor and Bradley ( {\ref 2003}) conducted the study on the determinants of job satisfaction. It included actual pay, relative pay, hours of work, job autonomy and several personal characteristics. Researchers also investigated the determinants of satisfaction with pay conditional on a worker's satisfaction with other domains of job satisfaction, such as satisfaction with job security. Findings revealed that, income predicted from a wage equation and a worker's prior expected income have the negative effect on satisfaction with pay. The estimated coefficients indicated, however, that the impact of relative income on satisfaction with pay is small compared to the estimated impact of actual income. Current income and hours worked have the expected effect on satisfaction with pay they also found that the major influence on satisfaction with pay is the degree of freedom that workers have over how they do their job. Further, personal characteristics have little effect on satisfaction with pay.\par Based on the review of literature, we can construct the conceptual Model for this study. salary differential does exist between male and female bank managers. Findings are consistent with other empirical works in the west and other industrial nations There is a significant mean difference in the levels of pay satisfaction between male and female school teachers H2: There is a significant mean difference in the levels of pay satisfaction among the age levels of school teachers H3: There is a significant mean difference in the levels of pay satisfaction among the family size of school teachers H4: There is a significant mean difference in the levels of pay satisfaction among the subjects which have been taught by the school teachers H5: There is a significant mean difference in the levels of pay satisfaction among the educational qualification of school teachers H6: There is a significant mean difference in the levels of pay satisfaction among the work experience of school teachers H7: There is a significant mean difference in the levels of pay satisfaction among the of the work place of school teachers II. \section[{Methodology a) Data Sources}]{Methodology a) Data Sources}\par Primary and secondary data were used for this study. Primary data were collected through the questionnaire. Secondary data were collected from, texts, journals and magazines. \section[{b) Research Design and Model}]{b) Research Design and Model}\par Quantitative method is utilized to answer the research question as "To what extent Personal characteristics influence the pay satisfaction among School teachers of the Northern Province, Sri Lanka". \section[{c) Sampling frame work}]{c) Sampling frame work}\par In the quantitative approach, the survey instrument in the form of close-ended questionnaire was developed for the purpose of collecting the main data for the study. The study was limited to school teachers in the Northern Province, Sri Lanka. Therefore, Probability sampling method as simple random sampling has been adopted to select respondents( Zikmund, Babin, Carr and Griffin, 2012). And researcher has taken the details of the school teachers in the Northern Province, Sri Lanka., with the help of the document which is uploaded in the URL of the Ministry of Education, Sri Lanka. In which, the document is named as Sri Lanka Education Information, 2012. According to the document, in the Northern Province, 944 school teachers who are graduate, trained, untrained, and trainee are practicing their profession as teaching. We have used 38 \% to get the adequate sample size (944 * 40 \% = 370) form the population as 944 school teachers. Further, \hyperref[b6]{Krejcie and Morgan (1970)} pointed that, sample size as 274 is adequate for the population size as 950 through the table for determining sample size from a given population. In this study, researchers considered the sample size as 360. Due to that, sample size for this study is adequate.\par In addition, when researchers considered the sample respondents, personal characteristics as gender, age, family size, subjects for teaching, educational qualification, work place and work experience have been considered.\par Researcher has issued Three hundred and eighty (380) questionnaires for selecting the respondents. Out of Three hundred and eighty (380) questionnaires, Three hundred and seventy (370) was returned; the response rate was 97\%. Then, Out of Three hundred and seventy (370), Three hundred and sixty (360) was used for the study purpose. \section[{d) Instrument development}]{d) Instrument development}\par The research instrument used in this study is composed of two parts .The part one included a number of demographic questions such as gender, age, family size, subjects for teaching, educational qualification, Results And Analysis a) Data analysis method Statistical methods have been employed to compare the data collected from 360 respondents. These methods include inferential statistics, which involves in drawing conclusions about a population based only on sample data. It includes t-test and f-test, which was used to identify the significant mean difference between the levels of pay satisfaction across the personal characteristics. \section[{Personal Characteristics}]{Personal Characteristics} \begin{quote} Gender\end{quote} \section[{b) Reliability}]{b) Reliability}\par The internal consistency of the research instrument should be tested by reliability analysis \hyperref[b9]{(Ndubisi 2006}). Nunnally (as cited in Ahsan et al., 2009) suggested that the minimum alpha of 0.6 sufficed for early stage of research. The cronbach's alpha in this study were all much higher than 0.6, the constructs were therefore deemed to have adequate reliability. (Overall Cronbach alpha value was 0.758.) c) Normality of data Normality data should be tested before conducting the inferential statistics (Ahsan et al., 2009).According to the "Test of Normality" all the variables in this research were in 0.05 level significant. Therefore the normality assumption is the valid one. \section[{d) T-Test and F-Test Analysis i. T-Test was used to identify the significant difference}]{d) T-Test and F-Test Analysis i. T-Test was used to identify the significant difference}\par between the two variables. In this research, among the several t-tests, the independent sample t-test was used. The Independents-Samples t-test procedure compares means for two groups of cases. F-Test was also used to identify the significance of differences between sample means where more than two conditions were used, or even when several independent variables were involved (Velnampy, 2012 ; Sivathaasan, Achchuthan,\& Kajananthan, 2013). And also the data analysis for the proposed research was performed with the latest SPSS computer package. ii.\par Independent samples t-test is utilized to indentify the significant mean difference in pay satisfaction between male and female group. According to the Table {\ref .} 5, Results of Independent sample one-way ANOVA test, there is a significant mean difference in pay satisfaction across the family size of school teachers. The significant levels for the dimensions as pay level \& benefit, pay raises and pay structure \& administration are less than the 0.05 levels (P < 0.05). It means that school teachers who hold different family size in their family have dissimilar levels of pay satisfaction in terms of pay level \& benefit, pay raises and pay structure \& administration. \section[{Gender Vs Pay satisfaction}]{Gender Vs Pay satisfaction}\par We can also explain the finding summary through the Mean Plot. \section[{According to the Table. 4,}]{According to the Table. 4,}\par Results of Independent sample one-way ANOVA test, there is no significant mean difference in pay satisfaction across the age levels of school teachers. The significant levels for the dimensions as pay level \& benefit, pay raises and pay structure \& administration are greater than the 0.05 According to the Table {\ref .} 6, Results of Independent sample one-way ANOVA test, there is no significant mean difference in pay satisfaction in terms of pay level \& benefit and pay raises across the subjects for teaching. The significant levels for the dimensions as pay level \& benefit and pay raises are greater than the 0.05 levels (P > 0.05). In contrast, we found that, there is a significant mean difference in pay satisfaction in terms of pay structure \& administration across the subjects for teaching. The significant level for the dimension as pay structure \& administration is less than 0.05 levels (P < 0.05). It means that school teachers who taught different subjects as social studies, business studies and commerce, pure science, fine arts have different level of pay satisfaction in terms of pay structure \& administration.\par We can also explain the finding summary through the Mean Plot. \section[{Mean Plot for Subjects for Teaching Vs Pay Structure and Administration}]{Mean Plot for Subjects for Teaching Vs Pay Structure and Administration}\par According to the mean plot, school teachers , who taught fine arts subjects have high level of pay satisfaction in terms of pay structure and administration than the teachers who taught subjects like social studies, pure science, and business studies \& commerce. Further, teachers who taught social studies According to the Table {\ref .} 7: Results of Independent sample one-way ANOVA test, there is a significant mean difference in pay satisfaction in terms of pay raises and pay structure \& administration across the educational qualification .The significant levels for the dimensions as Pay raises and pay structure \& administration are less than 0.05 levels (P < 0.05). It means that school teachers who hold the educational qualifications as GCE A/L , diploma, Bachelor degree and masters have the different levels of pay satisfaction in terms of pay raises and pay structure and administration. In contrast, we found that, there is no significant mean difference in pay satisfaction in terms of pay level and befits across the educational qualification. The significant level for the dimension as pay level \& benefit is greater than the 0.05 levels (P > 0.05).\par We can also explain the finding summary through the Mean Plot.\par Mean Plot for Educational Qualification Vs Pay raises We can also explain the finding summary through the Mean Plot. According to the Table. 9, Results of Independent sample one-way ANOVA test, there is no significant mean difference in pay satisfaction across the work places of school teachers. The significant levels for the dimensions as pay level \& benefit, pay raises and pay structure \& administration are greater than the 0.05 levels (P > 0.05). It means that school teachers who are in different work places have the same level of pay satisfaction in terms of pay level \& benefit, pay raises and pay structure \& administration approximately. Therefore, H7 is rejected. \section[{IV. Conclusion And Recommendation}]{IV. Conclusion And Recommendation}\par Based on the overall study findings, there is a significant mean difference in pay satisfaction among family size, subjects for teaching, educational qualification and working experience. In the family size, school teachers who have the family size as 1-2 hold the high level of pay satisfaction in terms of pay level \& benefit, pay raises and pay structure \& administration than others. In relation to the subjects for teaching, school teachers, who taught fine arts subjects have high level of pay satisfaction in terms of pay structure and administration than the teachers who taught subjects like social studies, pure science, and business studies \& commerce. In terms of educational qualification, school teachers , who have the educational qualifications as GCE A/L hold high level of pay satisfaction in terms of pay raises and pay structure \& administration. Further, in the working experiences, school teachers, who have the working experience as 1-5 and 21 and above years When the drafts on policies in terms of the pay structure and administration of the school teachers especially in the northern part of the Sri Lanka are initiated or designed, governmental bodies like ministry of education should consider the differences in the level of pay satisfaction among personal characteristics. Finally, this study would hopefully benefit to the academicians, researchers, policy makers, and practitioners of Sri Lanka as well as other countries.\par hold the high level of pay satisfaction in terms of pay structure and administration. In contrast, researchers found that, there is no significant mean difference in pay satisfaction among gender, age level and work place.\begin{figure}[htbp] \noindent\textbf{}\includegraphics[]{image-2.png} \caption{\label{fig_1}A}\end{figure} \begin{figure}[htbp] \noindent\textbf{}\includegraphics[]{image-3.png} \caption{\label{fig_2}100}\end{figure} \begin{figure}[htbp] \noindent\textbf{}\includegraphics[]{image-4.png} \caption{\label{fig_3}}\end{figure} \begin{figure}[htbp] \noindent\textbf{2}\includegraphics[]{image-5.png} \caption{\label{fig_4}Figure 2 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{3}\includegraphics[]{image-6.png} \caption{\label{fig_5}Figure 3 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{4}\includegraphics[]{image-7.png} \caption{\label{fig_6}Figure 4 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{5}\includegraphics[]{image-8.png} \caption{\label{fig_7}Figure 5 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{67}\includegraphics[]{image-9.png} \caption{\label{fig_8}Figure 6 :Figure 7 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{1} \par \begin{longtable}{P{0.5932999999999999\textwidth}P{0.0017\textwidth}P{0.1343\textwidth}P{0.12069999999999999\textwidth}} \multicolumn{2}{l}{Description}\tabcellsep Frequency\tabcellsep Percentage\\ Gender:\tabcellsep \tabcellsep \\ Male\tabcellsep \tabcellsep 175\\ Female\tabcellsep \tabcellsep 185\\ Total\tabcellsep \tabcellsep 360\\ Age:\tabcellsep \tabcellsep \\ 20 -30\tabcellsep \tabcellsep 62\\ 31-40\tabcellsep \tabcellsep 163\\ 41 -50\tabcellsep \tabcellsep 90\\ 51 and above\tabcellsep \tabcellsep 45\\ Total\tabcellsep \tabcellsep 360\\ Family Size\tabcellsep \tabcellsep \\ 1-2\tabcellsep \tabcellsep 51\\ 3-5\tabcellsep \tabcellsep 266\\ 6-\tabcellsep 8\tabcellsep 43\\ \tabcellsep \tabcellsep 360\\ \multicolumn{2}{l}{Educational qualifications:}\tabcellsep \\ G.C.E. (A/L)s\tabcellsep \tabcellsep 105\tabcellsep 26.7\\ Diploma\tabcellsep \tabcellsep 111\tabcellsep 51.3\\ Bachelor Degree\tabcellsep \tabcellsep 104\tabcellsep 13.3\\ Master Degree\tabcellsep \tabcellsep 40\tabcellsep 8.7\\ Total\tabcellsep \tabcellsep 360\tabcellsep 100\\ \multicolumn{2}{l}{Subjects for Teaching :}\tabcellsep \\ Social Studies\tabcellsep \tabcellsep 69\tabcellsep 19.2\\ Pure Science\tabcellsep \tabcellsep 38\tabcellsep 10.6\\ \multicolumn{2}{l}{Business Studies and Commerce}\tabcellsep 51\tabcellsep 14.2\\ Fine Arts\tabcellsep \tabcellsep 43\tabcellsep 11.9\\ Other Subjects\tabcellsep \tabcellsep 159\tabcellsep 44.2\\ Total\tabcellsep \tabcellsep 360\tabcellsep 100\\ Work Place:\tabcellsep \tabcellsep \\ Jaffna\tabcellsep \tabcellsep 150\tabcellsep 41.7\\ Vavuniya\tabcellsep \tabcellsep 60\tabcellsep 16.7\\ Mannar\tabcellsep \tabcellsep 50\tabcellsep 13.9\\ Kilinochchi\tabcellsep \tabcellsep 50\tabcellsep 13.9\\ Mullaitivu\tabcellsep \tabcellsep 50\tabcellsep 13.9\\ Total\tabcellsep \tabcellsep \\ Work Experience:\tabcellsep \tabcellsep \end{longtable} \par \caption{\label{tab_0}Table 1 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{2} \par \begin{longtable}{} \end{longtable} \par \caption{\label{tab_1}Table 2 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{3} \par \begin{longtable}{P{0.4281615302869288\textwidth}P{0.008129649309245484\textwidth}P{0.0027098831030818275\textwidth}P{0.03251859723698194\textwidth}P{0.048777895855472896\textwidth}P{0.14452709883103082\textwidth}P{0.0614240170031881\textwidth}P{0.07948990435706695\textwidth}P{0.03974495217853347\textwidth}P{0.004516471838469713\textwidth}} \multicolumn{2}{l}{t-test variables}\tabcellsep \tabcellsep \tabcellsep t-value\tabcellsep \tabcellsep p-value / sig\tabcellsep \multicolumn{2}{l}{Mean difference}\\ \multicolumn{2}{l}{Pay Level and Benefit}\tabcellsep \tabcellsep \tabcellsep -1.016\tabcellsep \tabcellsep 0.310\tabcellsep -.1398\\ \multicolumn{2}{l}{Pay Raises}\tabcellsep \tabcellsep \tabcellsep -1.747\tabcellsep \tabcellsep 0.081\tabcellsep -.2375\\ \multicolumn{4}{l}{Pay Structure and Administration}\tabcellsep -1.008\tabcellsep \tabcellsep 0.314\tabcellsep -.1288\\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep Std.\tabcellsep Std.\tabcellsep Error\\ \tabcellsep \tabcellsep \tabcellsep Gender\tabcellsep N\tabcellsep \tabcellsep Mean\tabcellsep Deviation\tabcellsep Mean\\ \multicolumn{2}{l}{Pay Level and Benefit}\tabcellsep \tabcellsep Male\tabcellsep \multicolumn{2}{l}{175}\tabcellsep 2.8331\tabcellsep 1.30271\tabcellsep .09848\\ \tabcellsep \tabcellsep \tabcellsep Female\tabcellsep \multicolumn{2}{l}{185}\tabcellsep 2.9730\tabcellsep 1.30814\tabcellsep .09618\\ \multicolumn{2}{l}{Pay Raises}\tabcellsep \tabcellsep Male\tabcellsep \multicolumn{2}{l}{175}\tabcellsep 2.7048\tabcellsep 1.28547\tabcellsep .09717\\ \tabcellsep \tabcellsep \tabcellsep Female\tabcellsep \multicolumn{2}{l}{185}\tabcellsep 2.9423\tabcellsep 1.29344\tabcellsep .09510\\ Pay\tabcellsep Structure\tabcellsep and\tabcellsep Male\tabcellsep \multicolumn{2}{l}{175}\tabcellsep 3.0324\tabcellsep 1.23470\tabcellsep .09333\\ \multicolumn{2}{l}{Administration}\tabcellsep \tabcellsep Female\tabcellsep \multicolumn{2}{l}{185}\tabcellsep 3.1613\tabcellsep 1.19225\tabcellsep .08766\\ \multicolumn{4}{l}{According to the Table. 2,}\tabcellsep Results of\tabcellsep \multicolumn{3}{l}{Therefore, H1 is rejected.}\\ \multicolumn{5}{l}{Independent samples t-test, there is no significant mean difference in pay satisfaction between male and female school teachers (P > 0.05). It means that both male and female school teachers have approximately same level}\tabcellsep \multicolumn{4}{l}{Independent sample one -way ANOVA test. One-way ANOVA test can be used to find out the significant mean difference in pay satisfaction}\\ \multicolumn{5}{l}{of pay satisfaction in terms of pay level \& benefits, pay}\tabcellsep \tabcellsep \tabcellsep \\ \multicolumn{4}{l}{raises and pay structure \& administration.}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par \caption{\label{tab_2}Table 3 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{4} \par \begin{longtable}{P{0.85\textwidth}} Therefore, H2 is rejected.\end{longtable} \par \caption{\label{tab_3}Table 4 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{5} \par \begin{longtable}{P{0.425\textwidth}P{0.32499999999999996\textwidth}P{0.09999999999999999\textwidth}} Sum of Squares df\tabcellsep Mean Square F\tabcellsep Sig.\end{longtable} \par \caption{\label{tab_4}Table 5 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{6} \par \begin{longtable}{P{0.425\textwidth}P{0.32499999999999996\textwidth}P{0.09999999999999999\textwidth}} Sum of Squares df\tabcellsep Mean Square F\tabcellsep Sig.\end{longtable} \par \caption{\label{tab_5}Table 6 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{7} \par \begin{longtable}{P{0.3606060606060606\textwidth}P{0.051515151515151514\textwidth}P{0.33484848484848484\textwidth}P{0.10303030303030303\textwidth}} Sum of Squares\tabcellsep df\tabcellsep Mean Square F\tabcellsep Sig.\end{longtable} \par \caption{\label{tab_6}Table 7 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{8} \par \begin{longtable}{P{0.4591452991452991\textwidth}P{0.034145299145299145\textwidth}P{0.0021794871794871794\textwidth}P{0.06974358974358974\textwidth}P{0.05521367521367521\textwidth}P{0.1758119658119658\textwidth}P{0.03123931623931624\textwidth}P{0.010897435897435897\textwidth}P{0.011623931623931624\textwidth}} \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Sum of Squares df}\tabcellsep \multicolumn{2}{l}{Mean Square F}\tabcellsep Sig.\\ \multicolumn{2}{l}{Pay Level and Benefit}\tabcellsep \tabcellsep Between Groups\tabcellsep 13.237\tabcellsep 4\tabcellsep 3.309\tabcellsep 1.962\tabcellsep .100\\ \tabcellsep \tabcellsep \tabcellsep Within Groups\tabcellsep 598.674\tabcellsep 355\tabcellsep 1.686\tabcellsep \tabcellsep \\ \tabcellsep \tabcellsep \tabcellsep Total\tabcellsep 611.911\tabcellsep 359\tabcellsep \tabcellsep \tabcellsep \\ \multicolumn{2}{l}{Pay Raises}\tabcellsep \tabcellsep Between Groups\tabcellsep 8.828\tabcellsep 4\tabcellsep 2.207\tabcellsep 1.324\tabcellsep .260\\ \tabcellsep \tabcellsep \tabcellsep Within Groups\tabcellsep 591.602\tabcellsep 355\tabcellsep 1.666\tabcellsep \tabcellsep \\ \tabcellsep \tabcellsep \tabcellsep Total\tabcellsep 600.429\tabcellsep 359\tabcellsep \tabcellsep \tabcellsep \\ Pay\tabcellsep Structure\tabcellsep and\tabcellsep Between Groups\tabcellsep 14.170\tabcellsep 4\tabcellsep 3.543\tabcellsep 2.446\tabcellsep .046\\ \multicolumn{2}{l}{Administration}\tabcellsep \tabcellsep Within Groups\tabcellsep 514.135\tabcellsep 355\tabcellsep 1.448\tabcellsep \tabcellsep \\ \tabcellsep \tabcellsep \tabcellsep Total\tabcellsep 528.305\tabcellsep 359\tabcellsep \tabcellsep \tabcellsep \\ \multicolumn{3}{l}{Source: Survey data (2014)}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \tabcellsep \multicolumn{4}{l}{According to the Table. 8 : Results of}\tabcellsep \multicolumn{4}{l}{than 0.05 levels (P < 0.05). It means that school}\\ \multicolumn{5}{l}{Independent sample one-way ANOVA test, there is no}\tabcellsep \multicolumn{4}{l}{teachers who hold the working experience as 1-5, 6-10,}\\ \multicolumn{5}{l}{significant mean difference in pay satisfaction in terms}\tabcellsep \multicolumn{4}{l}{11-15, 16-20 and 21 and above have the different}\\ \multicolumn{5}{l}{of pay level \& benefit and pay raises across the working}\tabcellsep \multicolumn{4}{l}{levels of pay satisfaction in terms of pay structure \&}\\ \multicolumn{5}{l}{experience of school teachers. The significant levels for}\tabcellsep administration.\tabcellsep \tabcellsep \tabcellsep \\ \multicolumn{5}{l}{the dimensions as pay level \& benefit and pay raises are}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \multicolumn{5}{l}{greater than the 0.05 levels (P > 0.05). In contrast, we}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \multicolumn{5}{l}{found that, there is a significant mean difference in pay}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \multicolumn{5}{l}{satisfaction in terms of pay structure \& administration}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \multicolumn{5}{l}{across the working experience. The significant level for}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \multicolumn{5}{l}{the dimension as pay structure \& administration is less}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par \caption{\label{tab_7}Table 8 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{9} \par \begin{longtable}{P{0.425\textwidth}P{0.32499999999999996\textwidth}P{0.09999999999999999\textwidth}} Sum of Squares df\tabcellsep Mean Square F\tabcellsep Sig.\end{longtable} \par \caption{\label{tab_8}Table 9 :}\end{figure} \footnote{© 2014 Global Journals Inc. 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