From existing datasets, how do I know the reasons for high dropout rates or low retention and transition rates of specific groups of children?
To identify these reasons, it is essential to delve into the available data and adopt a comprehensive approach.
Begin by analysing datasets that provide detailed information on student demographics, such as the Annual Status of Education Report (ASER) and the Unified District Information System for Education (UDISE+), which may offer insights into dropout patterns and retention rates. Look for trends and patterns specific to the groups you’re interested in, whether it’s economically disadvantaged students (EWS), children with disabilities (CWD), or other specific categories. These datasets may include information on attendance, performance, and sociodemographic characteristics.
To gain a more in-depth understanding of the reasons behind high dropout rates or low retention and transition rates, consider conducting additional research or surveys. Engaging with the affected students, their families, and teachers can provide valuable qualitative insights into the challenges they face.
By combining quantitative data analysis with qualitative feedback, you can develop a more comprehensive perspective on the underlying factors contributing to these educational disparities.