Abstract
Data from 10 years of ASER (Annual Status of Education Report) surveys in India reveal two clear trends. First, a steady increase in private school enrollment is visible across rural India. Second, children’s ability to read simple text and do basic arithmetic is extremely poor and has not improved over time. ASER data show that the learning gap is widening between government and private schools but that a larger proportion of this gap is attributable to household factors rather than to private schools themselves. This means that the most disadvantaged children, those who study in government schools, are falling further behind. Data from the India Early Childhood Education Impact (IECEI) study also suggests that although the majority of children in the IECEI study spent between 1 and 2 years in an early childhood education program prior to entering primary school, the impact of this participation on their school readiness and subsequent early grade learning is attributable more to their family background than to the institutions that they attended, which varied very little within a given state in terms of quality. However, variations across states suggest that uptake of developmentally appropriate policies and programs at the state level is likely to influence not only government but also private providers of early childhood services.
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Notes
- 1.
UNESCO’s Global Monitoring Report estimates that 250 million children around the world are not learning the basics, of whom about 50% have spent at least 4 years in school (UNESCO, 2015).
- 2.
See https://sustainabledevelopment.un.org/sdgs for information on specific goals and targets.
- 3.
See Ashley et al. (2014) for a comprehensive review of the role and impact of private schooling in developing countries.
- 4.
According to Census 2011, India has 158.7 million children in the age group 0–6 years of which about 48% of children are covered under the government’s Integrated Child Development Services (ICDS) scheme. There is also a burgeoning private ECCE sector which remains largely unregulated, for which no reliable estimates exist of either number or coverage.
- 5.
For more information on how ASER is designed and implemented as well as on its findings, see www.asercentre.org.
- 6.
For more information on the IECEI study, see Kaul et al. (2017) and Chapter 2 in this volume.
- 7.
ASER is currently the only source of annual data on learning outcomes available on scale in India.
- 8.
These numbers refer to basic reading in primary grades.
- 9.
The “controlled” estimates are obtained from a regression that controls for the child’s age, gender , and whether she gets any supplementary help in the form of private tuition; her parents’ education level; her household characteristics that proxy for affluence like type of house, presence of a TV, mobile, etc., as well as those that proxy for her home learning environment like presence of reading materials in the home; and characteristics of the village she lives in.
- 10.
ASER collects information on various household assets. Among these is the type of home the child lives in. Following other large-scale surveys, like DHS, ASER classifies the house type into three categories: “kutcha,” “semi-pukka,” and “pukka,” A “pukka” house is one which has walls made of burnt bricks, stones (packed with lime or cement), cement, concrete, timber, etc. and roof made of tiles, GCI (galvanized corrugated iron) sheets, asbestos cement sheet, RBC (reinforced brick concrete), RCC (reinforced cement concrete), timber, etc. A “kutcha house has walls and/or roof made of material other than those mentioned above, such as unburnt bricks, bamboos, mud, grass, reeds, thatch, loosely packed stones, etc. A “semi-pukka” house has fixed walls made up of pukka material, but the roof is made up of the material other than those used for pukka house. This variable works as a good proxy for wealth with poor households being classified as those living in “kutcha” houses.
- 11.
See also Chapters 3, 10, and 11 in this volume for different perspectives on the relationship between age and grade in Indian preschools and primary schools.
- 12.
It is instructive to look at both sources of data – ASER and IECEI. ASER is nationally representative but cross-sectional in nature and given its rapid assessment architecture is lean on explanatory variables. However, it useful to look at broad trends and set up hypotheses. IECEI, on the other hand, is longitudinal and has far more detailed information on young children. However, it was conducted in only three states and is not nationally representative. But given the wealth of information available in the study, the data can be used to answer more detailed and interesting questions. In this section, we report results based on the first six visits of the study.
- 13.
As discussed in Chapter 3 of this volume and the IECEI study report (Kaul et al., 2017, p. 30), the IECEI study used a broader definition of “participation” that goes beyond enrollment to capture the extent of children’s actual exposure to ECE, whether formal or informal.
- 14.
Provision of ECE centers was universal with a government Anganwadi center in every sampled village and about half of all sampled villages also having a private ECE center.
- 15.
- 16.
Table 5.9 does not differentiate between government and private schools and ECE centers. However, disaggregating these data further by management type reveals a fair amount of movement between government and private ECE centers as well.
- 17.
The assessment examined children’s foundational cognitive, language, and arithmetic abilities that children age 6 were expected to have achieved. See Kaul et al. (2017) for details.
- 18.
Therefore, children with six ECE center participations were still in an ECE center when the early grade assessment was administered.
- 19.
Unlike the more detailed indicators used in the smaller Strand B of the study, the ECE quality indices used in this analysis were based on a rapid institutional assessment that was conducted in all ECE centers attended by children in the larger Strand A of the IECEI study. This survey format aimed to collect data on key aspects of each institution, such as infrastructure, staff and student enrollment and attendance, and selected elements of classroom processes . The quality index for each sampled child is an average based on all ECE centers she attended. Details of the quality indices are provided in Table 5.12.
- 20.
These tests were administered twice—at the beginning of the study (September–December 2011) and at the end of the first year of the study (October–December 2012).
- 21.
The IECEI study report (Kaul et al., 2017) indicates that four rounds of ECE participation is optimal (Table 6.4). If children continue to participate beyond an optimal number of visits, the returns are negative.
- 22.
See Table 5.12 for the indicators used to construct these indices. As mentioned earlier, these were collected during a rapid assessment of each facility, entirely separate from the much longer and more detailed quality assessments done in the smaller Strand B of the study.
- 23.
The school readiness assessment tested children’s preliteracy, prenumeracy, and cognitive abilities at age 4 and again at age 5. For more details see Kaul et al. (2017).
- 24.
The first year of the study comprised a baseline survey, which included the baseline administration of the school readiness test, two rounds of tracking visits, and an end line administration of the school readiness test.
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Wadhwa, W., Bhattacharjea, S., Banerji, M. (2019). Does Participation in Preschool Help Children’s Early Grade Learning?. In: Kaul, V., Bhattacharjea, S. (eds) Early Childhood Education and School Readiness in India. Springer, Singapore. https://doi.org/10.1007/978-981-13-7006-9_5
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