An analysis of dropout in Karnataka G. Nagendra Prasad , 03-07-2012

1. Methodological concerns on measuring dropout in schools in the context of universal elementary education An analysis of dropout in Karnataka G. Nagendra Prasad , 03-07-2012

2. Table of Contents • Why analysis on dropout? • Objectives & Hypothesis to be verified • Nature of dropout • Constituents of dropout • Notations: Dropout & Retention • Variations in enrollment • Variations in Dropout • Influence of net dropout in total dropout • Regression Coefficients • Conclusions from the analysis

3. Why analysis on dropout? • Education Management and Information System (EMIS) collect data on dropout. • Reporting high percentage of dropout is considered failure of schooling system in a village or in a locality. • There are variations in actual and reported enrollment & dropout • To have access to schooling for all eligible children, precise data on dropout is required. • This necessitates for a precise data on ‘Net dropout’ as a component in total or ‘Gross dropout’ • This analysis is to understand variations in reported figures on enrollment & dropout, thereby the net dropout at school level • Net dropout was arrived at by observing school records and actual number of children present on the day of visit. • It considers variations between actual numbers and those as per school records • Statistically significant variations are noted and inferences are drawn.

4. Objectives • To understand variations between actual and reported data on enrollment, dropout and thereby retention. • Variations analyzed are expected to be useful for policy decision making on dropout and enrollment to address the issue of educational access. • Estimate composition of net dropout in total or gross dropout, based on actual data collected from the sample. • Analysis of data suggests a new methodology to separate ‘net dropout’ from total dropout •  Hypotheses: • There is no significant difference in variations between school enrollment and that reported to the department during 3 year period, from 2003-2004 to 2005-06 • There is no significant difference between total class enrollment (no of children in classes) and the names entered in the attendance register • There is no difference between attendance marked by teachers in the attendance register and the number of children in the class by head count. • Net dropout is not a significant constituent in the total or gross dropout

5. Nature of dropout • This analysis looks at data available in school records on dropout of selected sample schools and tries to suggest ways to ascertain realistic data • Dropout is generally defined as exit of a child from school for a continuous period of 30 to 45 days. • Dropout is ratio between number of children at the beginning of an academic year and those at the end of an academic year in a class or in all classes of a school. • Generally, it is concerned with one academic year and is expressed in percentage for easy understanding. • Policy makers & managers are interested to understand the differentials between initial figures of enrollment and those at the terminal year, which is ‘Retention’. The residual is called ‘Dropout’ • This method does not consider various components in total dropout • Purpose of analysis is to understand various constituents in dropout and suggest precise measures on dropout.

6. Constituents of dropout • Following factors generally influence dropout in schools. Educational system • alone cannot change immediately these factors in the short-run • (i) Socio-economic and psychological factors (ii) School environment • (iii) Prevalence of child labor (iv) Age of a child • (vi) Attitude of parents towards school and education • (vii) Need for earning livelihood at an early age of life. • Another kind of independent factors that influence Dropout are: • (viii) Family migrations • (ix) Changes in residence. • (x) Failures • (xi) Admission repetition in a year influence ‘Retention’ rates of a school. • Dropout due to above reasons is manageable, because this can be addressed, in one way or the other. • Dropout other than the above factors is called ‘Net dropout’ for the present purpose. • Thus ‘Net dropout’ is one of the constituents of total dropout, which is voluntary & it is specified as one of the components in in total dropout

7. Notations: Dropout & Retention Where: = Total dropout in year t = Total number of repeaters in year t = Total number of children taken TC in year t = Total number of children migrated to other places in year t = Total net dropout of children in year t, which is ‘voluntary’ Retention rate (%) Where: Generally, dropout is calculated & expressed in percentage 100 - =

8. Variations in enrolment • To understand significant variations in school enrollment for 3 years and that reported from 2003-04 to 05-06 through MMR, paired t test was used, as the sample comes from the related group. • Variations between school enrollment and that reported through the MMR for three years are very marginal. • Calculated t values at 95% significance for 3 years are: • Pair 1 t (93) = 0.330, P> 0.05 (Sig is 0.742) • Pair 2 t (93) = 0.863, P> 0.05 (Sig is 0.390) • Pair 3 t (93) = 0.264, P> 0.05 (Sig is 0.792) • Confidence intervals affected by the selected sample are very minimal at 95% significance level with high probability (more than 0.05) • The null hypothesis that there is no significant difference between school enrollment and that reported during 3 year period is accepted Source: Data from school records- 2003-04 to 2005-08

9. Variations in Dropout • To understand observed difference in means represent a true difference in population, from which the samples were selected, paired t test was conducted, as the samples are related to each other. • While applying t test, the following pairs are separately considered • Pair-1 • Enrollment as per attendance from 1st to 8th standards • Total class enrollment(1st to 8th) and the names entered in the attendance register • Pair-2 • Attendance, marked by teachers for all classes from 1st to 8th standards on the day of visit • Actual numbers of children in the class, as per head count, on the day of visit. • Analysis provided a significant t values (pair-1) between ‘enrollment as per enrollment register’ and ‘names entered in attendance register by teachers’ on the day of visit’ • (t (97) =7.101, p < .0001) is significant at 99%. • Calculated t value between ‘attendance given by teachers’ and the ‘actual attendance’ of children in class, as per head count (pair-2) is t (97) = 5.368 P < 0001) and is significant. Source: Data from school records- 2003-04 to 2005-08

10. Influence of net dropout in total dropout • Another area of enquiry was to understand composition of ‘net dropout’ in ‘total or gross dropout'. • Correlation between number of children taken TC and number of repeaters is significant • Similarly, correlation between number of repeaters and net dropout is significant at 95% confidence level • A multiple regression analysis was conducted to understand influence of net dropout in the overall dropout. • Regression Model included 4 variables, which are the constituents of total dropout. The linear regression model set for the purpose is • Where: • a = Intercept & the rest of denotations are: as used earlier • Total dropout was treated as dependent variable and the variables (i) repeaters (ii) Children taken TC (iii) Children migrated and (iv) Net dropout are considered independent variables or predictors. • About 85% (Adjusted R square) of variations in dropout is explained when adjusted for the error associated with multiple independent variables. • Calculated F value and the corresponding p value of .000 tells that the independent variables explain a statistically significant proportion of variance in total dropout, indicating overall regression model is statistically significant.. Source: Data from school records- 2003-04 to 2005-08

11. Non- standardized Coefficients Standardized Coefficients B Std. Error Beta t Sig. (Constant) . 673 .613 1.097 .275 No of failures 1.236 .120 .461 10.332 .000 Nos taken TC 1.064 .120 .391 8.860 .000 Migration 1.574 .242 .266 6.507 .000 Net dropout 1.070 .134 .330 7.977 .000 Source: Data from school records- 2003-04 to 2005-08 Regression coefficients • All regression coefficients are positive and are significantly determining total dropout. • All 4 variables included in the model are important, as they are statistically significant (p = .000). • Among the independent variables included ‘children migrated to other places along with parents’ and ‘Repeaters’ have high coefficient values. • Next constituent is ‘net dropout’ in the equation. • In standardized terms, the influence of net dropout in the combined influence of variables is 33%, • The variables ‘repeaters’ and issuance of TC due to change of residence is to the tune of 46% and 39% respectively. • Measuring dropout should take into consideration the above variables. By which one can arrive at net dropout which bears 33% influence in total dropout.

12. Conclusions from analysis • Reported enrollment and that existing at the school level have not exhibited statically significant variations. Hence the null hypothesis of no significant difference is accepted • Variations between number of children in a class and appearance of names in attendance register have variations, which are statistically significant.. The null hypothesis of no significant difference is rejected • Attendance marked by teachers on the day of visit and number of children in classes have statistically significant variations. Hence, the null hypothesis of no significant difference is rejected. • Null hypothesis that net dropout is not a significant constituent in the total dropout is rejected as net dropout is one of the statistically significant factors in total dropout. • Net dropout requires initiation of external measures to address the issue. • Suggested methodology requires careful collection of data and meticulas analysis. • Simple head count method along with empirical data collected from school records provides a good base for estimation of a reliable net dropout rate. Source: Data from school records- 2003-04 to 2005-08

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