Chapter V School Choice, Process and Performance: A Comparative Study of the Schools under Different Managements The history of educational development in Kerala showed the following broad features. In the initial stages, education was conceived in its 'enlightening' and 'empowering' role enlightening the individual and the society in general, through its 'neig hbourhood' effects. In the economic world, knowledge is power and therefore, education, a tool for empowerment. The activities of the missionaries, of the social reform movements; of Nairs, Ezhavas and the others, and the intervention of the government itself had this conception as the guiding I motivating force. This largely explains the lead, the government gave in providing facilities for education and of the social and religious organisations acting on the lead and the proliferation of educational institutions in the state. In the new economir: order a marketdetermined, liberalised and privatised economy, the conceptualisation of education also has undergone a metamorphosis from enlightenment human capital a private merit good, it has become a tool for competition in the job market. School has transformed frbm a social institution to a private economic enterprise. Accordingly, rules of the game also have undergone change. While in the former subsidised regime, students invested largely their time (life) only, in the present dispensation scarce material resources are invested involving questions of costs and returns.
On the providers side, since education is considered an enterprise also involves questions of investment and returns. The following chapters (V to VIII) discuss issues relating to school choice and processes, cost of educationprivate and institutional and returns to education, treated as a private business enterprise. Selecting a stream of education at the higher level involves a screening process and a choice involving the cost incurred and the future returns, is well known in the literature on economics of education. However, selecting a school at the primary level also involvesa choice, despite the fact that the schools are not intrinsically dissimilar in terms of the content of curriculum. Yet a large number of students (parents) opt for the nascent fee paying school system deserting a largely subsidised efficient school system'. Education in Kerala is predominantly provided by the state which finances and manages the schooling services. Government and government aided schools constitute 91.3 per cent of total schools in Kerala. (Eco. Review 2001). These schools recover little of the cost of schooling through fees, but offer a variety of incentives such as noonmeals, uniforms, books etc. at a subsidised rate to attract and retain students. But of late, government seems to be slowly withdrawing from the educational scene. The new economic policies favouring private investment have made their presence felt in the form of self > financing institutions or unaided schools. The proportion of unaided high schools has increased from 4.5 per cent in 199091 to 8.5 in 200001 while that of government and aided high schools declined from 39.2 and 56.3 in 199091 to Kerala has achieved universal literacy, maintained high retention ratio and bridged the gender gap in school education almost entirely. This shows the internal efficiency of the educational system (Nair 1999, Thomas 2000).
37.7 and 53.8 in 200001 respectively. (Economic Review 2001) (Table 5.1). It has already been noted that in terms of enrolment unaided schools continues to register an increase from 1990s, while the government and aided schools a declining trend (See Table 3.6 in Ch.lll). Table 5.1: Distribution of Schools in Kerala According to the Types of Management (in per cent) High Schools Schools tp Schools Year w z e 0 a E O 3 0 I 4. 0 5 w E rn c 3 Y 0 k c; > 0 = 0 + @ $ E a + p_ m C 195051 21.0 39.1 39.9 33.1 37.2 29.7 55.8 42.2 2.0 198091 39.9 56.8 3.3 31.5 67.8 0.7 39.5 59.8 0.7 198586 38.5 57 4.5 31.9 65.9 2.2 38.2 59.6 2.1 199091 39.2 56.3 4.5 32.9 64.6 2.5 37.9 60.1 2 1 00 199596 37.9 54.2 7.9 32.4 63.3 4.4 37.5 60 2.5 200001 37.7 53.8 8.5 32,3 63.1 4.5 37.8 59.8 2.4 Source: For the year 195051, statistics since Independence, Department of Economics and Statistics, Government of Kerala 1998, For other years, Economic Review 2001, Government of Kerala. While a number of schools in the government and aided sector are being closed down for want of students, the number of unaided schools which collect fees and other charges is in~reasing.~ 5 Thus, the educational scenario in Kerala is undergoing a change. The policy of liberalisation and privatisation and the continuous complaint regarding The number of uneconomic schools in 2001 is 2244 consisting of 993 government schools and 1251 aided schools. (Eco. Review 2001),
the deterioration of quality in government and aided schools are creating a conducive climate for the unaided schools. In this context, the study attempts to examine the following problems. What are the major factors determining the choice of schools where the coexistence of government, aided and unaided schools is a common phenomenon? How far the socioeconomic factors influence the selection of a school? How far schools vary in quality? Can one identify the real differences in teacher characteristics, school infrastructure and school functioning under different types of management? How far the performance differentials vary among schools under various managements? These and other related problems are being examined and assessed in the three sections of this chapter based on a sample study. The first section deals with the school choice and its determinants. Second section examines the organisational structures and school process and functioning. In section three, a comparative assessment of scholastic performance among schools under various managements is presented. Definitions and Concepts Before presenting the profile of the sample design, we define the various concepts and terms used in this study. I. Management The authority which runs a school determines the type of management for it, namely, government, local body or private body receiving government aid or not receiving it. The schools may therefore, be classified according to their management as government schools, local body schools, private aided and unaided schools. All the schools run by the state or central government and completely financed by the government are treated as government schools. All
the schools run by city and municipal corporations and panchayats are treated as' local body schools. Private Aided Schools A private aided school is the one, which is run by a private organisation or an agency and receives maintenance grant from the government. Salary of the teachers and nonteaching staff in a private aided school is fully paid by the government. Private Schools A school which is managed and funded by a private organisation or agency and does not receive grant either from a government or local body is referred to as a private unaided school. Recognised Schools A recognised school is one in which the course of study is prescribed or recognised by the governme'nt or a board constituted by law or any other agency authorised on their behalf by the central or state government. Unrecognised Schools In the case of unrecognised schools, they function on the basis of a noobjection certificate from the department of education. In Kerala, they are permitted to admit students only upto the 7fi standard. Structure of Schools in Kerala In Kerala there exist public and private schools at elementary and secondary levels. In elementary education both and sections are included. At the
secondary level, classes from the ~ 1 1 1 " standard to the 12'~ standard are included. In the present study, students studying at, and High School levels only are included. (Standard XI and XI1 though part of school education comes under a different administrative set up; earlier it was part of University education under the name 'PreDegree Course'). Public schools are known usually as government schools and they are fully owned and managed by the Education Department of the Government of Kerala. In the private sector, schools are classified as private aided schools, private unaided recog nised schools and private unaided unrecognised schools. Private aided schools are similar to the government schools in a variety of ways. The fee structure, salary of teachers, syllabi, pupilteacher ratio etc. are the same in both government and aided schools. Private aided schools are fully aided by the state but the management has the autonomy in administration as per the government norms. Staff salary and the maintenance cost of schools are fully met by the government but the administration of these schools is vested with private agencies having individual, trust or corporate status. Private unaided schools function with no financial aid from the government. They follow the scheme and syllabus prescribed by the government or other central agencies like C.B.S.E or I.C.S.E. If they get recognition from the government and other central agencies they are usually referred to as private unaided recognised schools. These schools function as per the guidelines and conditions prescribed by the government and other central agencies. There are also private schools labelled as private unaided unrecognised schools. These schools function with a 'noobjection certificate' from the government and they are permitted to give admissions only upto the 7'h standard. Noobjection
certificates are given for a specified period and their legal recognition depends on the government policy on the sanctioning of new schools in the private sector. At present, no official data are available regarding the total number of unaided unrecognised schools in Kerala. But the association of unaided schools puts their number above 3000. Profile of the Sample Design The problems examined and assessed in this chapter are based on a primary survey. The method of selection and the design of the survey are outlined as follows. As per the Educational Statistics 1999, the total number of schools in Kerala was 12310 consisting of 6748 Schools, 2966 U.P schools and 2596 High schools. A district level distribution of these schools by type of management is shown in table 5.2.
Table 5.20: Percentage Distribution of Reported Adequacyllnadequacy of Drinking Water Facilities and Separate Toilets Management Government Aided Recognised Unrecog nised Status Drinking Water Adequacy Inadequacy 66.7 33.3 26.7 73.3 3.3 96.7 32.2 67.8 93.3 6.7 96.7 3.3 73.3 26.7 87.8 12.2 95 90 94.4 87.5 94.4 5 10 5.6 12.5 5.6 : Adequacy 67 20 16.7 31 1 36.7 90 60 62.2 Separate Toilets Inadequacy 33 80 83.3 68.9 63.3 10 40 37.8 1 00 1 00 1 00
Since it is beyond the scope of this work to gather information from all the schools we confine ourself to one district, i.e. Kottayam. Among all the districts, Kottayam has maintained a preeminent position in literacy and educational effoas (Table 5.3). Table 5.3: Literacy Rate in Kerala by District Wise (in per cent) Name of District Alappuzha Kottayarn Ernakulam Kollam Thiruvananthapuram Thrissur Kozhikode Kannur Malappuram Pala kkad ldukki Wayanad Pathanamthitta Kasargod Source: Primary Census Abstract 1991 Literacy Rate Male Female 96.72 91.57 97.41 93,97 94.54 87.52 94.24 86.89 92.00 84.20 93.07 85.83 95.25 85.80 94.45 85.65 92.02 83.91 86.30 74.56 90.63 82.67 87.54 77.64 96.44 93.24 88.22 75.31 94.06 95.68 91.12 90.48 88.00 89.26 90.43 89.97 87.81 80.20 86.70 82.68 94.78 81.66 It is known as the "land of letters", being the headquarters of many newspapers. In 1991, Kottayam stood first in literacy. It has also been the centre of many pioneering efforts in education, of the CMS (Church Missionary Society) since 1830s, of the CMI (Carmelites of Mary Immaculate) since 1870s, the Head Quarters of Nair Service Society (NSS) since 1914 and of the two Syrian Catholic dioceses which spearheaded educational efforts among the Syrian Catholics. Within the district, Changanacherry is taken as the area of study.
since this taluk has the rare distinction of housing the Syrian Catholic Bishop's house and Nair Service Society (NSS) headquarters of the two pioneering agencies in education in the state. In terms of literacy too, the taluk is ranked first in the district as per the census 1991 (Table 5.4). Table 5. 4: Taluk wise Distribution of Literacy Rate in Kottayam District Name of Taluk Kanjirapally Meenachil Kottayam Changanacherry Literacy Rate 95.17 95.73 96.38 96.88 Source: District Census Handbook Kottayam District, Primary Census Abstract, 1991 For the selection of a sample design, information was collected on the existing number of schools in the government, aided and unaided sectors. Table 5.5 shows the distribution of schools in the Changanacherry Taluk. From this. schools functioning in rural and urban areas were identified. Table 5.5: Distribution of Schools in Changanacherry Taluk by Level and Management Management Government 29 8 11 48 Aided 46 25 24 95 18 10 9 37 93 43 44 180
Changanacherry taluk consists of one municipality and eleven panchayats. Of the latter, five of them are special grade. For this study all the five special grade panchayats along with the municipality were treated as urban area and the remaining six panchayats as rural area. The distribution of schools under rural area and urban area is shown in Table 5.6. Table 5.6: Distribution of Schools Under UrbanlRu ral Classification Status Management Rural Urban Government 16 13 29 Aided 14 32 46 2 16 18 Government 4 4 8 Aided 1 I 14 25 3 7 10 Government 5 6 11 Aided 8 16 24 2 7 65 115 9 180 1 A sample design for the survey was selected from the above distribution and information on the various aspects of school education was collected using a detailed and structured questionnaire. The informads were selected on a random basis. Table 5.7 gives the sample size and distribution of population for the household survey.
Status 1 Table 5.7: Sample Size Distribution of Students Management Government Ur;n 1 1 l ; R; I Aided 1 30 1 30 1 60 1.. 1 6o 1 1 Government I 30 I 30 I Aided 30 30 60 30 30 60 Government 30 30 I Aided 1 30 I 30 1 60 1 1 1 30 1 30 1 60 1 1 270 1 270 1 540 1 Objectives The data thus collected were analysed with the following objectives. 1) To identify the major factors determining the household decision on school selection. 2) To examine the various aspects of school functioning and process to capture the qualitative differences between schools. 3) To evaluate the scholastic performance of schools based on SSLC results. Section I School Choice The problem of spatial accessibility to school education both in rural and urban areas has been fairly resolved in the state. Further, the state had been taking legitimate pride in the fact that its educational system provided equal
access irrespective of gender, social class and income (George and Ajith 1999). Tuition fee free education upto xth standard and the cross subsidised transport fares together with the proximity of institution have certainly enhanced the physical access to educational institutions in Kerala. On an average, there were 0.67 high schools, 0.76 upper primary schools and 1.74 lower primary schools per 10 Sq. Km area in 199899 (George et a/. 2003). But it is doubtful whether Kerala's educational system now provides equal opportunities for quality education any longer. With the decline in the quality of the public system of education, a parallel system of education, run purely on commercial lines is evolving in Kerala as unaided schools. Proximity of educational institutions run and managed by various agencies both in the government and private sector is posing problems of choice before households and students. Who joins which school? What are the criteria of student's choice of schools? This section attempts to examine these problems by analysing the socioeconomic background of students joining various managements. Socioeconomic Profile of Students by Type of Management The family background of students, both social and economic influences the selection of school. It is observed that pupils from Hindu backward communities and Muslims prefer government schools. Forward communities prefer aided and unaided private schools. In the sample 22.2 per cent of the students in government schools belong to Muslim community and 47.8 per cent to Hindu backward communities. The share of foward communities in aided schools is 64.4 per cent and it is 87.5 per cent in the unaided schools (Table 5.8).
Table 5. 8: Percentage Distribution of Students Under Different Managements by CommunitylCaste, CommunitylCaste Government...,..... Aided Managements Recognised Unrecognised Hindu General 6.7 32.2 16.7 11.1 Hindu O.B.C. 28.9 4.4 5.6 Hindu S.C. 16.7 3.3 1.4 Hindu S.T. 2.2 4.4 5.6 Christian Catholic 11.1 30 61 66.7 Christian NonCatholic 6.7 2.2 9.7 5.6 Christian O.B.C. 2.2 I.A Muslim 22.2 17.8 5.6 5.6 Others 3.3 4.4 5.6 1 Educational Status and School Selection Can the educational status of the parents influence the selection of schools of the wards? A positive relationship between educational status of parents and school selection may be identified3. It is observed that educated parents prefer aided and unaided schools since these schools have better scholastic record compared to government schools. Educational status of the parents of students in govemment schools are generally very low (Table 5.9). George Psacharpoulos (1 977) in his paper "f arnily background, education and achievement; A path model of earnings determinants in the UK and some alternatives" assess the extent to which differences in personal characteristics explain differences in occupational and economic success. According to this study fam~ly background relates to father's occupation, education and earnings and they are found to be the determinants of adult success in U,K. In the present study also a positive relationship between parents occupation, education and income is identified in school selection too.
Table 5.9. Educational Status of the Head of Households by Management (in per cent) Educational Status of Parents Illiterate Below S.S.L.C. S.S. L.C. P.D.C. Degree P.G. Government 1 48.9 25.6 14.4 8.9 0 Management Aided 16.7 46.7 5.6 12.2 2.8 13.3 25 5.6 43 Unrecognised 5.6 22.2 11.1 38,9 5.6 Professional 1.1 5.6 23.6 16.7 About 50 per cent of the parents have education below matriculation. But in the aided sector 16.7 per cent of parents have education below matriculation level, 46.7 per cent are matriculates and 24.5 per cent have degree or higher educational qualifications. The educational status of parents is of a higher order in the case of unaided sector. About 91 6 per cent of the parents of pupils in unaided schools are either graduates or postgraduates. The professionally qualified contributed 23.6 per cent. It is thus seen that school selection is influenced by the educational status of the parents. While the less educated parents opt for the government schools, the higher educated group send their wards to aided and unaided schools. Parental Occupation and School Selection Occupation and income are the two economic variables that influence the educational level of children. The classification of schooling by economic groups would throw some light on this (Table 5.10).
Table 5.1 0: Percentage Distribution of Occupation of Households Under Different Managements i Occupation Agriculture labour Farmer Industrial labour I Management 1 Government Aided Recognised Unrecognised 21.1 13.3 4.4 2.2 11.1 Industrialist I 1 1 1.4 1 5.6 1 Businessmen 1 5.6 114.4 1 16.7 1 22.2 1 1 Bank staff 1 1 1.1 1 9.7 1 1 Teaching Government employees 1.I 1 Self employed 1 43.3 122.2 1 8.3 1 11.1 1 / Not in labour force 1 6.7 1 I I 1 4.4 1,4 2.8 11.1 1 1 1 1 ( / 5.6 36.1 22.2 1 t Majority of students (60 per cent) in government schools hail from selfemployed and agricultural labour households. In the aided schools the pattern is mixed. Majority of students in unaided schools hail from the families of teachers, government servants and businessmen with high incomes. On the other hand. students in government schools generally come from poor backgrounds. It seems that caste/community has an economic specificity. Majority of those with low birth in the traditional caste parlance haye lowlevel occupation/ income and viceversa. More than half of the Scheduled Castes and twothirds of OBC students hailed from agricultural labour households (Table 5.11).
Table 5.1 I: Percentage Distribution of Households by Occupation and Caste. Occupation Hindu General Hindu OBC Hindu SC Hindu ST Christian Catholic NonCatholic " : ; Ch; Muslim Others Agricultural labour 14.3 20.6 52.6 3.2 66.7 2.4 12.5 Farmer 6.1 2.9 5. 3 14.3 4.3 12.5 7.3 25 Industrial labour 2 2.9 14.3 6.3 9.8 Industrialist 2.2 Businzssmen 18.4 5.9 12.9 2.5 9.8 37.5 Bankstaff 6.1 5 4 Teaching 5.9 34.4 12.5 Government employee 18.4 5.9 10.5 9.7 6.3 17.1 1 Private employee 10.2 14.3 17.2 18.8 33.3 12.2 Self employed 24.5 55.9 31 6 57 10.8 18.8 26.8 25 Not in labour force 14.6 L.
On the other hand, majority of those belonging to the forward communities have regular and high income occupation. Naturally the low income community prefers government schools where education is tuition fee free and subsidised. High income communities due to better occupation opt for aided or unaided schools regardless of the primary difference in schooling. The demand for schooling depends upon the price or cost of schooling and occupation and income are controlling factors of school selection (Duraisamy 2001). Parental Income and School Selection Parental income and student enrolment relation also show the same pattern of observations. Wards from the higher income households opt for unaided private schools and those from poor background eke out in the government sector (Table 5,12).
Table 5.12: Distribution of Students in Schools by Household Income.(in per cent) Management Class of family annual income Aided Recognised Unatded U nrecognised
In other words, except for a handful, the upper income groups do not turn to the government sector at all. The aided sector is a mixed bag. However, wards from poor parental background do have substantial presence in the sections and their presence tapersoff at the high school level. They either terminate their studies at level or migrate to the government sector. Thus a direct relationship between household's economic status and demand for high priced schooling is observed. Other Determinants of School Selection We have already noted the various socioeconomic factors influencing the selection of schools under various managements. It has been observed that school selection is influenced by noneconomic factors as well. This has been examined with the tool of factor analysis. Factor Analysis. Factor analysis is used to identify the major factors influencing the decision of school selection. This method attempts to identify the underlying variables or factors that explain the pattern of correlation within a set of observed variables. It is often used in data reduction to identify a small number of factors that explain most of the variance observed in a large number of manifest variables. The method of analysis and the results obtained in factor analysis are explained as follows. Steps in Factor Analysis There are four main steps in the factor analysis; 1) First step is data screening and testing for sampling adequacy. The correlation on covariance matrix is computed. If a variable has very small correlations with all the others, it is eliminated.
2) The factor loadings are estimated. Here, we decide whether ihe method of factor interaction is principal components (PCA) or any other method of extraction. 3) The loadings are rotated to make the loadings more interpretable. Rotation methods make the loadings for each factor either large or small, not inbetween. 4) For each case, scores can be computed for each factor and saved for use as input variables in other procedures. Results of Factor Analysis Step I The first body of output concerns data screening and testing of sampling adequacy. Examination of the results of factor analysis starts with the univariants descriptives of the statistics of variables used. It is presented in the Table 513. In the present data set, there are 540 observations and there are no missing values. The mean and standard deviations of each and every variable entered for factor analysis are reported in the table.
Table 5.1 3: Descriptive Statistics Factors Mean S.D Analysis N Good Administration 6.22 2.43 540 Well trained and dedicated teachers 5.1 1 2.50 540 Disciplined campus atmosphere 4.39 1.80 540 Individual Attention 5.52 2.25 540 Regular Exams and Assessment 5.94 2.08 540 locational Advantage 5.88 3.56 540 Preference for English Medium 6.93 5.09 540 Preference for ICSEICBSE Scheme 7.98 5.32 540 Cocurricular and Extra curricular activities 9.01 1.78 540 Less Expensive 8.06 4.96 540 Boarding Facilities 11.54 0.99 540 Good ReputationlTradition 5.56 2.71 540 Own CastelCommunity 8.86 2.67 540 The adequacy of data set is examined by correlation matrix (Rmatrix), KaiserMeyerOlkin (KMO) measure and Barlett's Test of sphericity. The correlation matrix contains the Pearson's correlation coefficients between all pairs of variables and their significance levels. We know that to do a factor analysis we need to have variables that correlate fairly well, but not perfectly. Also, any variable that does not correlate with any other should be eliminated. Therefore we can use correlation matrix to check the pattern of relationships. The easiest way to do this is by scanning the significance values and looking for any variable for which the majority of values are greater than
0.05. Examination of R matrix in the present data set shows that it is appropriate for the analysis. KMO and Bartletts's Test Table 5.44: KMO and Bartletts's Test KaiserMeyerOlkin Measure of Sampling Adequacy 0.598 Bartlett's Test of Sphericity Approx ChiSquare d f Sig. 2342.371 78 0.000 The KMO statistic can be calculated for individual and muttiple variables and represents the ratio of the squared correlation between variables to the squared partial correlation between variables. The KMO statistic varies between 0 and 1. A value of 0 indicates that the sum of partial correlations is large relative to the sum of correlations, indicating diffusion in the pattern of correlations (hence, factor analysis is likely to be inappropriate). A value close to 1 indicates that pattern of correlation is relatively compact and so factor analysis should yield distinct and reliable factors. Kaiser (1968) recommends accepting values greater than 0.5 as acceptable. For the present data set, the value is 0.598, so we can be confident that factor analysis is appropriate for these data. Bartlett's measure tests the null hypothesis that the original correlation matrix is an identity matrix. For factor analysis to work we need some relationship between variables and if the Rmatrix were an identity matrix then all
correlation coefficients would be zero. Therefore, we want this test to be significant (ie. to have a significance value less than 0.05). A significant test tells us that the Rmatrix is not an identity matrix; therefore, there are some relationships between the variables we hope to include in the analysis. For these data, Bartlett's test is significant at zero per cent level, and therefore factor analysis is appropriate. Step II In the second step, factor loadings are to be estimated. For estimating them PCA was selected as the extracting method. The results were rotated to get better results. Step Ill The results of the rotated factor analysis contain the following tables. Table 2 shows commonalities before and after extraction. Commonalities are the proportions of common variance within a variable. Principal component analysis works on the initial assumption that all variance is common, therefore. before extraction the commonalities are all 1. In effect, all of the variance associated with a variable is assumed to be common variance. Once factor has been extracted, we have a better idea of how much variance is, in reality. common. The commonalities in the column labelled Extraction reflect this common variance. So, for example, we can say that 62.6 per cent of the variance associated with variable 1 is common, or shared, variance. Another way to look at these commonalities is in terms of the proportion of variance explained by the underlying factors. Before extraction, there are as many factors as there are variables, so all variance is explained by the factors and commonalities are all 1. However, after extraction some of the factors are
In the column labelled, the eigen values for the multivariate space of the original variables are ordered by size. Each value is the total variance explained by a factor. The percentage of the total variance attributable to each factor is displayed in the column labelled % of variance. The first factor accounts for 35.64% of the variance, the second accounts for 10.89% the third accounts for 10.12 /~ and the fourth accounts for 9.63%. Together, the first four factors account for 66.28% of the variability of the original 13 variables. Table 5.16: Variance Explained Component 1 2 3 4 5 6 7 8 9 10 11 12 13 4,633 1.416 1.316 1.253 0.933 0.890 0.782 0.540 0.516 0.455 0.1 85 8059E02 7.689E05 Initial Eigen values % of variance 35.640 10.891 10.120 9.635 7.181 6.842 6.019 4.150 3.970 3.503 1.426 0.620 5.915E04 Extraction method: Principal component analysis Cumulative YO 35.640 46.531 56,652 66.287 73.468 80.310 86.329 90.480 94.450 97.953 99.379 99.999.00 Extraction sums of squared loadings O/O of Cumulative variance % 4.633 35.640 35.640 1.416 10.891 46.531 1.316 40.120 56.652 1.253 9.635 66.287 Step IV > Table 5.17 named Component Matrix displays coefficients or loadings that relate the variables to the four factors (Components). Loadings are the correlations of the variables with the factors, The correlation between Variable I and factor 1 is only 0.377, while the correlation with factor 2 is 0.328, correlation
with factor 3 is 0.335 and correlation with factor 4 is 0.514. Thus, we can say that Variable 1 is associated with factor 4. Continuing with this analysis, we find the different variables correlated with the different factors. These different factors are named accordingly. Factors Good administration Well trained and dedicated teachers Disciplined campus atmosphere Individual attention Regular exams and assessment Locational advantage Table 5.1 7: Component Matrixa 0.377 0.607 0.264 2.20E02 0.704 0.711 Component I I I / Preference for English medium 1 0.920 1 2.532E02 1 1.459E02 1 7.118502 I 1 Preference for ICSEICBSE scheme 1 0.918 1 7.528E02 1 3.99E02 ( 6.27E02 / Cocurricular and extra curricular I 2 0.328 2.88E03 0.504 0.701 0.185 0.208 activities 1 8.77E02 1 0.669 1 7.622E03 1 0.272 1 1 ~ess Boarding facilities Good reputationltradition Own caste/community ~xpensive 1 0.900 1 9.42E02 1 0.152 1 0.155 1 0,468 0,202 0.532 Extraction Method: Principal Component Analysis a. 4 components extracted 0.108 9.20E02 3 0.335 0.387 0.376 0.466 0.236 3.61 E02 7.17E02 0.637 4 0.574 0.410 0.204 0.218 2.17E02 0.259 0.498 4.1 50E02 1 0.449 1 0.369 1 In short, the factors behind school admissions are found as follows: we identify the first factor as preference for English medium as well as preference for CBSEIICSE syllabus. The second factor is found to be individual care students are getting from school. The third factor is found as reputation of the school. Fourth and the last significant factor may be named as administrative setup of the school. Thus it may be concluded that in the school selection process between schools under different managements both socioeconomic factors as well as
quality related factors influence the household choice of schools. Parents appear to prefer to send their children to private unaided and aided schools because they believe that these schools offer better quality education than the government schools. The high ' socioeconomic status provides easy access to these schools. Hence parents are deemed to view education as an investment consistent with the human capital interpretation. Section II Infrastructure Facilities and School Process Studies at a micro level examining the organisational structures and processes of schools suggest that schools do make a difference to the expected performance of pupils (Thomas 1990). In Kerala, it has been reported that the differentiation between government and private aided schools within the public funded school system and the rapid growth of private schools run without any government aid is increasing (Vaidhyanathan and Nair 2001). Hence in this section, an attempt is made to examine the differentiation between the schools in infrastructural facilities, basic amenities, student strength and school processes and performance. How far schools under different managements differ in the provision of these minimum requirements? How far these differentiations affect the quality and performance of these schools? Information on the educational facilities and the variations in educational infrastructure in terms of physical facilities, teachers and their education levels, pupilteacher ratio, school process etc between schools under different managements are also examined.
Physical Facilities and Basic Amenities The sixth All India Educational Survey (1992) has noted that in terms of infrastructural facilities in schools, Kerala is way ahead of all other states in India. The Physical facilities (school buildings, furniture and equipment, sports facilities, toilets, drinking water etc.) in Kerala schools are much better than anywhere else in the country (Nair 1999). The levels of infrastructure and availability and utility of aids have close correlation with learner achievements. lnfrastructural facilities which include physical and academic infrastructure available in a school are identified as one of the factors which have a distinct and related dimension with quality of school education (Govinda and Varghese 1992). Infrastructure facilities do vary between different managements and the highly reputed unaided schools are providing superior infrastructure facilities compared to aided and government schools. The major physical facilities include, class room, library, laboratory, teaching aids and basic amenities like drinking water and separate toilets. It was observed that aided and unaided schools have adequate class room and laboratory facilities compared to government schools (Table 5.18).
Table 5.1 8: Percentage Distribution of Reported Adequacylf nadequacy of Class Room and Laboratory Facilities Management Government Status Adequacy 96.7 93.3 96.7 95.6 Class Room Facility Inadequacy 3.3 6.7 4.4 4.4 1 00 Adequacy 3.3 1.1 Laboratory Facility Inadequacy 96.7 98.9 Aided 6.7 33.3 60 33.3 93.3 67.3 40 67.3 Recognised 95.5 95 96.7 95.8 4.5 5 3.3 4.2 1 00 I 00 95.5 90 96.7 94.4 4.5 10 3.3 5.6 Unrecognised.lo0 87.5 40 61.I 12.5 60 38.9 i
In the matter of laboratory facilities government schools are in a very poor condition. In library facilities unaided schools are in a better position, than aided and government schools. Data show that none of the government schools have library and only one half of the aided schools have this facility. In the case of teaching aids like black board, chalk etc all the schools reported per cent adequacy (Table 5.19).
Table 5.1 9: Percentage Distribution of Reported Adequacy11 nadequacy of Library Facilities and Teaching Aids Management Status Adequacy Library Facility Inadequacy Adequacy Teaching Aids Inadequacy Tota f Government 3.3 7.1 96.7 98.9 Aided 13.3 46 7 56.7 38.9 86.7 53.3 43.3 61 1 I00 Recognised 95.5 90 96.7 94.4 4.5 10 3.3 5.6 I00 300 Unrecognised 87.5 30 55.6 12.5 70 44.4.
Basic Amenities The proper functioning of a school requires the availability of standard infrastructural facilities and basic amenities like separate toilets for boys and girls and drinking water facilities. On both counts unaided schools are better endowed than aided and government schools (Table 5. 20).
I Name of revenue district 1 Thiruvananthapuram Kollam Pathanamthitta Alappuzha Kottayam ldukki Ernakulam Thrissur Palakkad Malappuram Kozhikkode Wayanad Kannore Kasargode Govt 119 75 48 58 59 52 89 79 59 82 67 37 8 1 74 979 Table 5.2: Number of Schools in Kerala, by Level and Management, 19992000 Source: Educational Statistics1 999 Government of Kerala High Schools Schools Schools Aided 95 124 114 125 166 72 172 147. 77 76 97 22 77 33 1397. 27 10 7 7 16 10 36 20 16 30 17 4 I0 10 220 241 209 169 190 241 134 297 246 152 188 181 63 168 117 2596 Govt 97 62 43 67 68 41 92 54 63 112 76 35 77 72 959 Aided 102 139 86 78 129 60 102 164 159 225 241 39 277 72 1873 16 7 14 3 8 3 16 8 14 14 11 4 12 4 134 215 208 143 148 205 104 210 226 236 351 328 78 366 148 2966 Govt 301 270 169 194 169 71 188 120 186 351 185 93 114 141 2552 Aided 181 189 243 198 274 138 278 390 350 480 533 52 614 115 4035 15 17 13 13 22 5 24 10 10 8 6 6 5 7 161 497 476 425 405 465 214 490 520 546 839 724 151 733 263 6748 Govt 517 407 260 319 296 164 369 253 308 545 328 165 272 287 4490 Aided 378 452 443 401 569 270 552 701 586 781 871 113 968 220 7305 58 34 34 23. 46 18 76 38 40 52 34 14 27 21 515 Tdal 953 893 737 743 9111 452 997 992 934 7 378 1233 292 1267 528 12310
In government schools, such facilities are inadequate. Even in the case of drinking water, two third of the government schools do not have that facility. Physical Access to School The availability of schooling facilities in Kerala is such that the state has one school per 3 sq. k.m. (Educational statistics 1999). This clearly indicates that physical accessibility is not a constraint on school education. It was observed that physical accessibility is not a hindrance for school education in this taluk also. Both in rural and urban areas, schools in government, aided and unaided sector function in close proximity. Data show that about 46.7 per cent of students in government schools came from the vicinity of the school and the remaining 53.3 per cent travel less than 5 km to reach school (Table 5. 21). Table 5.21 : Percentage Distribution of Students Under Various Managements by Distance Class of Distance Managements Status <I km 15km 51Okm 10km 8 above 46.7 53.3 Government 50 50 46.7 53.3 30 70 Aided 26.7 73.3 23.3 60 13.3 3.3 Recognised 9 5 31.8 75 54.5 20 4.5, 1 Unrecog nised 13.3 37.5 56.7 50 60 26.7 12.5 30 3.3 10
In aided schools, 30 per cent came from the vicinity and the rest from within a radius of 5 km. But unaided schools have a large catchment area and students from far off places are enrolled. More than 50 per cent of students travel a distance between 5 km to I 0 km and a few even more. Students strength4 In Kerala, enrolment in schools has been on the decline is well known. The decline is particularly sharp in the government and the aided sectors. This leads to 'division fall' and creates the problem of 'protection' in such schools. On the other hand unaided schools experience a heavy rush for admission. Table 5.22 shows that in the government sector 27 per cent of students in and sections, have class strength below 10 students and 65 per cent have student strength between 10 and 20. Enrolment of students in Kerala which stood at 59.07 lakhs in 1991 92 declined to 53.35 lakhs in 199899. (Educational statistics 1 999). Division fall occurs when the actual strength falls below the effective strength. As per the present rules the effective strength for a division is as follows. Effective strength : Upto 50 students 1 division; 51 to 952 divisions; 96 to 14CL3 divisions; 141 to 185 4 divisions For example if the actual strength is 51, then two divisions are permissible thus enhancing the number of teachers. If the effective strength is reduced due to nonenrolment or drop outs at the time of strength verification, then the teacher becomes surplus due to division fall. In such cases government protects the teacher by paying the salary provided he has completed two years of continuous service (V. Rajasekharan Nair.l995),
Table 5.22: Frequency Distribution of the Sample According to Class Strength Frequency Distribution of Pupils According to Classstrength Management Status 110 8 120 12 130 14 I 40 24 150 1 60 2 61 and above 60 Government 8 26 14 8 4 60 6 34 18 2 60 12 22 12 8 6 60 Aided 20 22 2 10 6 60 6 42 12 60 28 12 4 44 recognised 22 18 40. 24 30 6 60 Unrecognised 3 5 4 6 4 5 8 I 16 20
These schools are in the list of uneconomic schoo~s.~ In the case of aided schools, it has been observed that majority of students are studying in classes with an enrolment higher than the minimum effective strength. In the unaided sector, especially the recognised schools have a viable student strength in all the sections. That government schools are generally disfavoured is also evident from class pupil ratio. While the average number of students in section is 26.13 in government schools, it is 32.50 and 41.36 in the aided and the unaided schools respectively (Table 5.23). Table 5.23: Average Student strength in a Class Management Status Minimum Strength Maximum Strength Mean Standard Deviation 7 55 26.1 3 12.10 Government 5 48 21 12.69 25 52 37. I 0 6.60 16 58 32.50 12.21 Aided 23 68 39.57 13.26 23 59 40.73 9.78 Recognised 35 5.82 35 50 38.55 10.35 32 55 42,77 5.86 Unrecog nised 30 6 50 42 * 41.1 3 22.80 9.82 13.06 5 Uneconomic Schools: The minimum effective strength per standard in I and shall be 25. A school shall be deemed to have the minimum strength if the average effective strength per standard is not less than 25. The minimum effective strength per standard in Sanskrit and Arabic school shall be 15. (Rule 22 A of Chapter V KERs). If the minimum effective strength is not maintained, then it is included in the category of uneconomic of schools. (V. Rajasekharan Nair, 1 995).
Although the minimum effective strength is fixed at 25, the teacherpupil ratio prescribed for staff fixation is 1 :45. Recently it has been reduced to 1 :40 to reduce the number of protected teachers. Student enrolment by medium of instruction is shown in Table 5.24.
Table 5.24: Percentage Distribution of Students according to Class Strength by Medium and Level Frequency Distribution of Pupils According to Classstrength Status Medium 11 0 120 130 1 40 150 61 and above Maia yalam 6.7 20 30 30 6.7 6.7 English 6.7 53.3 33.3 6.7 4.4 13.3 22.2 37.8 15.6 67 Malayalam 7 22.8 29.8 26.3 5.3 5.3 3.5 English 12.1 6.1 9.1 33.3 30.3 6.1 3 8.9 16.7 22.2 28.9 14.4 5.6 3.3 Malayalam 10 63.3 18.3 8.3 English.. 40 43.3 16.7 6.7 55.6 26.7 11.1
It is seen that 53.3 per cent of students in English medium schools are in classes with student strength of 31 to 40. However, more than 50 per cent of the students in the Malayalam medium are in classes with a student strength varying between 11 to 30. At the high school level, 90 per cent of pupils in the Malayalam medium schools and all the pupils in the English medium are in classes with 'economic size'. School Process Quality of education, to a large extent is contingent on the school process(thomas 2001). Scholastic achievement and school functioning are the two sides of a coin ie, school quality (Vadakel 1997). In a society where the coexistence of government, aided and unaided schools is a common phenomenon, it is interesting to examine the variations in school functioning or school process between schools. Different categories of schools have reported varying records of scholastic achievements. How far scholastic attainment is related to school functioning? How far school functioning or school process differ between schools under different managements? Study made by Govinda and Varg hese (1992) have identified four distinct but related dimensions on school education. They are (1) infrastructural facilities which include physical and academic infrastructure available in a school. (2) human resources mainly focussing on teachers and administrators. (3) teaching learning process and (4) learner achievement as an outcome of schooling process. Having examined the first, let us examine the teacher characteristics between the schools.
Teachers' Selection Criteria in Schools Selection criteria of teachers in schools differ between managements. In government schools, teachers are recruited by Public Service Commission and the selection process is written test and interview. Generally duly qualified and competent teachers are given placement in government schools. But in aided schools, different procedures are followed for the teacher recruitment. In 47.9 per cent of schools, donation offered was the major criterion for teacher's selection, besides qualification and personal interview (Table 5.25). Certain unaided schools also take donations for appointing teachers.
Table 5.25: Criteria of Teachers Selection Management Test and Interview Performance in Test and Interview by Management Interview only by Management QualificationlDona tionisecurity1 Teaching Experience Government (23) (23) Aided 72.1 (31) 2.3 (1) 25.6 (11) I00 (43) Recognised 45.5 (5) 36.4 (4) 18.2 (2) (1 1) Unrecognised 66.7 (4) 16.7 (1) 16.7 (1) (6)
Age, Experience and Qualification of Teachers Studies on school related factors focus on teacher characteristics like age, qualification, and experience. How far teacher characteristics influence the scholastic performance of students? It is observed that majority of teachers in government schools (84 per cent) are between the age group of 30 to 49, while the percentage of teachers in the age of group of 50 and 60 in aided school is 25.87 per cent (Table 5.26). Table 5.26: Age Distribution of Teachers (in per cent ) Management Government Aided Recognised U nrecognised Status 38.26 42.44 9.00 8.68 58.33 33.33 8.33 50 40.47 9.52 2029 1.82 5.12 1.49 2.08 48.33 35.16 51 85 3039 44.28 34.14 40.18 40.36 33.53 38.46 26.94 30.38 37.33 44.06 38.88 4049 34.28 53.65 46.72 44.03 43.90 34.61 42.21 41.66 10.67 8.47 9.25 5059 21,42 12.19 13.08 15.59 21 42 12.19 13.08 15.59 4 10.16 60 and Above 2.11 1.60 I00 However, in the unaided sector, majority of teachers (80 per cent) are within the age group of 20 to 39. Inexperienced and younger teachers are found in the unaided sector. Teacher's age and scholastic performance does not show any directional relations.
Teacher groups with older or longer service perform less well than average (Thomas 1990). Teaching experience of teachers shows that 45 per cent of teachers in government schools have more than 20 years of teaching experience and in aided schools 70 per cent of teachers have less than 20 years of experience (Table 5.27). Table 5.27: Distribution of Teachers According to Experience (in per cent ) Management Status year 14 Years of Experience 59 1019 2029 > 30 Government 44.28 11.43 17.08 19.63 35.73 41.46 36.45 4.28 41.46 39.25 4,28 4.67 1.38 16.51 37.A6 41.28 3.67 I Aided Tota I 6.71 20.51 5.99 8 6 13,41 14.40 17.37 15.80 37.81 29.49 50.30 43.92 37.20 32.05 20.66 26.91 4.88 3.85 5.69 5.20 Recognised U n recog n ised 60.82 50.42 52.90 66.67 66.67 66.67 17.56 25.42 23.54 16.67 23.80 22.22 16.22 15.25 15.48 16.66 9.52 11.11 5.40 3.81 4.19 5,08 3.87 I00 However, in the unaided sector more than 50 per cent of teachers have less than four years of experience. Although experience of teachers really count in the scholastic performance of students, no such relationship can be identified in the study. Teachers in the government and the aided sector fulfill the qualification requirements stipulated by the government. In government sector, the
percentage of over qualified teachers with postgraduate degree is higher than that of aided schools (Table 5.28). Table 5.28: Distribution of Teachers according to Qualification (in per cent) Management Status Government 4.87 7.31 87.80 66.35 33.64 2,29 32.1 1 49.08 16.51 8,53 73.1 7 15.85 2.43 Aided 8.97 18.86 66.66 18.86 16.66 42.21 7.69 20.05 14.58 40.79 31.25 13.36 tp 1.33 20 30.66 48 Recognised 5.50 2.11 41.10 50.84 0.42 4.50 6.43 38.58 50.16 0.32 16.66 25 58.33 Unrecognised 4.76 45.23 50 3.70 3.70 40.74 51.85 But in the unaided sector more than 50 per cent of teachers were postgraduates and some had even research degrees. Regarding the gender ratio of teachers in schools, it is seen that there is a female domination in all the schools (Table 5.29).
Table 5.29: Gender Ratio Among Teachers Management Government Aided Recognised U nrecognised Level Gender Ratio (M:F) 112.02 1 :2.87 1 :2.41 1 :2.28 1:3.16 1 :3.89 1 :6.75 1 :4.57 1 :3.75 1 :3.26 1 :3.40 1 :5.25 1:6.12 1 :5.68 While in government schools, the ratio is one male for 2.28 female, it is t4.5 in the aided sector. In aided high school the ratio is even higher. 1:6.75. Similar pattern is found in unaided sector too. Most of the schools reported adequacy of teachers. Vacancy of teacher post unfilled is reported only from 3 government schools out of 23 (1 3 per cent) and 6 aided schools out of 43 (1 3.95 per cent) (Table 5.30).
Table 5.30: Distribution of Teacher Vacancy by Managernentllevel Management Status Number of Teachers Post Vacant 0 1 2 92.3(12) 7.7(1) I OO(13) Government 1 OO(4) 66(4) 16.7(1) 16.7(1) 1 OO(4) 1 OO(6) 87(20) 8.7(2) 4.3(1) 1 OO(23) 82.6(19) 4.3(1) 13(3) 1 OO(23) Aided 88.9(8) 90.9(10) 11.1(1) 9.1(1) 1 OO(9) 1 OO(11) 87(37) 1.3(1) 1 1.6(5) 1 OO(43) tp 1 OO(6) I OO(6) Recog nised 1 OO(5) 1 OO(5) loo(11) loo(11) 1 OO(2) 1 1 OO(2) U n recog n ised 50(2) 50(2) 1 OO(4) 66.7(4) 33.3(2) 1 OO(6) (Figure in brackets indicates the number of schools in the sample) Availability of teachers shows that schooling process in these schools is, not affected for want of teachers. Working Hours and Days The usual timing of class is from 10 a.m. to 4 p.m. with a lunch break of one hour. This timing is followed in majority of cases. But some exceptions are found in aided and unaided schools (Table 5. 31).