Predicting Early Childhood Education Attendance From Preschool: a Machine Learning Exploration in the Urban Region of Maharagama, Sri Lanka Among Low-income Families Children

Abstract

"This research aims to delve into the dynamics of early childhood education (ECE) attendance among children from low-income families in the urban area of Maharagama, Sri Lanka. It seeks to understand the multifaceted influences of demographic, socio-economic, and behavioural factors on ECE attendance through a combination of traditional statistical analyses and machine learning exploration.

Key variables under investigation encompass various aspects such as gender, age, religion, race, health status, father's occupation and education, mother's occupation and education, mode of transportation to preschool, and commute time. These factors are crucial in understanding the determinants of ECE attendance among children from low-income backgrounds.

The dependent variable, ECE attendance, is central to the study, while the child's interest and engagement in education are considered as mediating factors, suggesting their role in shaping attendance patterns. Additionally, parental preschool involvement is viewed as a moderating factor, indicating its potential to influence the relationship between other variables and ECE attendance.

Incorporating machine learning techniques into the analysis allows for a comprehensive exploration of intricate patterns within the data, enabling the identification of nuanced relationships that may not be readily apparent through traditional statistical methods alone.

The research framework is deeply rooted in the specific cultural and economic context of Maharagama, Sri Lanka, recognizing the unique challenges and opportunities faced by low-income families in accessing quality preschool education. By acknowledging this context, the study aims to provide insights that are directly applicable to the targeted population, thereby facilitating the development of tailored interventions and policies aimed at promoting equitable access to ECE for vulnerable communities.

Overall, the findings of the research are intended to contribute to the design and implementation of effective strategies that address the barriers hindering ECE attendance among children from low-income families, ultimately striving towards ensuring inclusive and quality early childhood education for all. "