BRIDGING THE GENDER GAP IN EDUCATION THROUGH AI
Education is one of the most effective tools, not only for the progress of a nation but also for ushering social equity. However, in India, gender inequality in education is widely prevalent, and especially aggravated, among the socio economically marginalized sections. The reasons for this are multifaceted- primary being the premium placed on marriage of girls, making the family invest in her dowry rather than education. Moreover, domestic duties are considered the primary duty of women, hence parents prefer the daughter to utilize her time in learning them rather than studying. Another major challenge is the lack of functional washrooms for girls leading girls to drop out of school with the onset of menstruation. Lack of adequate infrastructure coupled with wide spread gender-based violence make the commute to school a daily challenge which most families can’t navigate. As a result of this, enrolment in schools, participation in STEM education, and access to higher education continue to be glaringly unequal. The AI technologies in education offer a promising solution to these challenges. In my research, I would be discussing the present state of women's education in India highlighting how even after initiatives like the Right to Education Act, education still remains an elusive dream for many women, analysing the various social and cultural barriers to it. I would then analyse how AI can be harnessed for facilitating education for women and what are the diverse AI-driven solutions available. Finally, I will look at the possibilities of misuse inherent in the technology proceeding to evaluate means to strengthen the system to make it more potent and inclusive. I would evaluate AI-driven insights that can guide policy framing and implementation for ensuring targeted education. Finally, I would discuss the future scope of AI-driven education to assure gender-inclusive learning and enhancing national development.
Authors
- A. Sanyal
Publication Details
- Journal
- The Social Science Review a Multidisciplinary Journal.
- Published
- 2025-09-20
- DOI
- https://doi.org/10.70096/tssr.250307004
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 0.00