A background note can be accessed here: Lok Sabha Q&A: Government Expands Targeted Support for Women in Higher Education Under NEP 2020
The Government's response highlights a range of initiatives to improve women's participation in higher education under the National Education Policy (NEP) 2020. As enrolment gaps continue to narrow, should policy move beyond expanding access towards strengthening women's agency through higher education?
The latest All India Survey on Higher Education (AISHE) reports indicate that women outnumber men in higher education, with the Gender Parity Index exceeding one in favour of female enrolment in most states. This advantage persists through to graduation, with women accounting for 52.1 percent of all pass-outs, but it is unevenly distributed across disciplines. At the postgraduate level, women make up 60.7 percent of Social Science graduates and 62.7 percent of Science graduates, yet only 39.5 percent of Master of Engineering (M.E.) graduates and 41.4 percent of Master of Computer Applications (MCA) graduates; at the undergraduate level, they account for 29.6 percent of engineering graduates across both Bachelor of Engineering (B.E.) and Bachelor of Technology (B.Tech.) programmes.
This pattern is not confined to only Science, Technology, Engineering and Mathematics (STEM) degrees. In law, women account for 35.3 percent of undergraduate graduates but 47.0 percent of Master of Laws (LL.M.) graduates; in commerce and business, they account for 51.5 percent of Bachelor of Commerce (B.Com.) graduates but 41.8 percent of Bachelor of Business Administration (BBA) graduates, and 65.7 percent of Master of Commerce (M.Com.) graduates compared with 44.8 percent of Master of Business Administration (MBA) graduates. Across both fields, women are concentrated in academically oriented qualifications, while professional, higher-return tracks continue to be dominated by men.
Given these statistics, policy should prioritise de-gendering subject streams across both quantitative and professional tracks through targeted pathways into STEM, explicit counselling against stereotype-based tracking, and incentives for institutions that move more women into high-return fields, including management and other professional degrees. Equally important is institutionalised role-model exposure through structured first-year modules and mentoring with female alumni in STEM, research, public service, and entrepreneurship. Higher education must also build stronger links between degree programmes and labour-market-relevant skills, internships, and digital capabilities, echoing findings from “Smart Skilling” that enhanced training design improves women's sectoral alignment and earnings.
The measures outlined include scholarships, hostels, gender-inclusive infrastructure, and other targeted interventions. How should policymakers balance programme-based support with broader institutional reforms that make higher education inherently more inclusive for women?
While targeted schemes have expanded women's access to education, they often operate within institutions that remain exclusionary. Broad reform succeeds only when its implementation and enforcement can meet the diverse needs of the population it serves. Pairing minimum national standards with competitive, performance-based incentives offers one way forward: inspired by model-village competitions in Tamil Nadu's climate agenda, regions and universities could be ranked and rewarded for measurable improvements in campus safety, grievance redressal, flexible learning options, and women's representation among faculty and in governance.
Ranking institutions, however, requires data that is not currently collected. AISHE reports teachers by gender, designation, social category, institution type and state, but not by discipline. Thus, while the gender composition of engineering students is published annually, that of engineering faculty is not. Adding a discipline field to the teacher module would allow faculty gender composition to be examined in underrepresented fields and enable a comparison between the ratio of female students to female faculty and that of female students to male faculty. Such analysis can inform targeted recruitment initiatives and reveal how mentorship and workload responsibilities, including the additional institutional labour demanded by the implementation of the NEP, are distributed across faculty by gender.
The same gap applies to outcomes. AISHE shows which degrees are offered and pursued in distance mode rather than regular mode, but not what those degrees lead to; tracking employment outcomes by mode would establish whether flexible pathways deliver comparable returns, which is the condition under which they count as genuinely inclusive. With those measures in place, funding for targeted schemes could be partly tied to retention, completion and safe transitions to work, nudging institutions to invest in mentoring, placement services and safe transport in line with lessons from Smart Skilling on the importance of design and complementary inputs for women's outcomes.
The expansion of women's higher education is increasingly becoming an economic as well as a social policy objective. What complementary reforms are needed to ensure that rising educational attainment translates into higher female labour force participation and leadership in India's knowledge economy?
India’s gender dividend hinges on whether rising educational attainment among women translates into sustained labour force participation and leadership, rather than credentialed withdrawal. Many educated women are “missing” from the workforce, often pushed back into low-productivity agricultural jobs because of limited opportunities in manufacturing and a shortage of suitable service-sector jobs.
A key limitation in assessing long-term educational attainment trajectories is the lack of systematic national and state-level data tracking individuals from the classroom to the workplace. For example, datasets from the Ministry of Statistics and Programme Implementation (MoSPI) capture education levels and the highest attainment as of the survey date, but are collected less frequently than labour force data and do not provide degree-level detail or cohort transition data. Assessing the efficacy of the NEP and other skilling initiatives therefore requires nationally representative and state-level data that is collected consistently and tracked over time to monitor outcomes, providing the foundation for more effective targeting of policy initiatives.
Complementary reforms must be undertaken simultaneously. On the supply side, curricula and career services need to be tightly linked to women-intensive growth sectors, with structured apprenticeships that reflect evidence from vocational studies showing that integrated, experiential training improves women’s sectoral alignment and earnings. On the demand side, industrial and urban policy must be intentionally designed to encourage women-friendly manufacturing and knowledge-economy jobs. Financial instruments can support this transition. Preliminary evidence from the study of unconditional cash transfers to women in Maharashtra suggests that such transfers do not discourage work and can strengthen bargaining power. In addition, employment-linked bonuses and entrepreneurship grants for educated women could offset the cost of childcare without reducing labour force participation.