Work – Life Balance among Female Lecturers in Tamil Nadu, India: A Synthetic Data Approach

Abstract

Work-life balance (WLB) is an important issue of wellbeing, particularly for women in professions such as teaching. The aim of this study is to present innovative ways of using synthetic sources to analyse real-world challenges at the intersection of professional duties and personal responsibilities. This research explores the use of artificially generated information and computational techniques to assess the WLB stability of female teachers in higher education institutions. Using this enhanced dataset, a series of machine learning (ML) classifiers are constructed and evaluated to predict WLB outcomes.
This research makes a significant contribution to the fields of educational administration and data science in the Kumbakonam district of Tamil Nadu and illustrates the value of synthetic data in social science research, providing insights into improving the WLB of women in higher education. It also provides recommendations for legislative and institutional reforms that can be implemented to improve women's WLB.