Updated October 2026 · Prepared by Edhitch’s data and accreditation team
What is AISHE?
The All India Survey on Higher Education (AISHE) is the Ministry of Education’s annual survey of every higher education institution in India — universities, colleges and standalone institutions. Launched in 2010-11, it is the official source of national higher education statistics. Each institution’s nodal officer submits data through the web-based Data Capture Format (DCF) on the AISHE portal, using the institution’s AISHE code.
Why AISHE matters beyond the survey: AISHE is the national baseline for your faculty, enrolment and finance figures. The same data feeds your NAAC SSR and AQAR and your NIRF submission. An institution that reports 412 faculty to AISHE and 438 to NIRF has a problem no amount of documentation will fix.
What the AISHE Data Capture Format collects
| Section | What is reported | Also used in |
|---|---|---|
| Basic details | Institution type, management, location, affiliation, programmes offered | NAAC extended profile, NIRF |
| Teaching staff | Faculty by designation, qualification, gender, social category | NAAC Criterion 2, NIRF TLR |
| Non-teaching staff | Staff by group and category | NAAC extended profile |
| Enrolment | Students by programme, level, gender, social category, minority, PwD, foreign nationals, mode | NAAC Criteria 2 and 5, NIRF TLR and OI |
| Examination results | Final-year appeared and passed, by programme | NIRF GO, NAAC Criterion 2 |
| Finances | Income and expenditure by head | NIRF TLR (financial resources), NAAC Criterion 6 |
| Infrastructure | Facilities and learning resources | NAAC Criterion 4 |
| Scholarships and loans | Students supported, by scheme | NAAC Criterion 5, NIRF OI |
| Accreditation | NAAC and NBA status | NAAC, NBA |
Every enrolment figure is broken down by gender, social category, minority status, disability and foreign nationality — the same breakdowns NIRF’s Outreach and Inclusivity parameter and NAAC’s student-diversity metrics rely on.
The annual AISHE cycle
- Register once on the AISHE portal. The nodal officer enters the institution’s AISHE code, verifies email and mobile by OTP, and the account is approved by the designated authority.
- Prepare data for the reference year. Collect faculty, enrolment, results, finance and infrastructure figures as of the survey’s reference date.
- Fill the web DCF. Enter every section on the portal — the 2024-25 round opened in July 2025 and closed in October 2025.
- Validate before submitting. Reconcile every figure with your NAAC and NIRF data and your audited accounts.
- Submit and archive. Keep the submitted DCF and its source data — next year’s round and your accreditation cycle both start from it.
The latest AISHE figures
| Indicator | 2022-23 | 2023-24 |
|---|---|---|
| Institutions registered | 60,380 | 64,756 |
| Institutions responding | 56,180 | 59,533 |
| Total enrolment | 4.46 crore | 4.50 crore |
| Gross Enrolment Ratio (18–23) | 29.5 | 30.0 |
| Female GER | 30.2 | 31.2 |
AISHE 2022-23 and 2023-24 were released together on 8 July 2026. In 2023-24, 1,278 of 1,289 universities, 46,468 of 48,246 colleges and 11,787 of 15,221 standalone institutions responded. Source: Ministry of Education (PIB).
Where AISHE submissions go wrong
- Figures that do not match NAAC and NIRF. Faculty and enrolment counts differ across the three because each was compiled by a different office.
- Breakdowns rebuilt by hand. Gender, category, PwD and minority splits are tallied from registers every year instead of computed from one student record.
- Finance that does not reconcile. Income and expenditure heads in AISHE do not tie back to audited accounts.
- One-person knowledge. The nodal officer changes and the method for last year’s figures leaves with them.
- Last-week compilation. The DCF is filled in the final days before the deadline, with no validation pass.
Master Data Map’s AISHE module
AISHE is where Master Data Map’s one-record approach pays off first. Every AISHE figure is already in the institutional record that produces your NAAC SSR and AQAR and your NIRF data — so the AISHE return is generated, not compiled, and it matches everything else you report.
| Capability | What it does |
|---|---|
| DCF-ready data | Generates every AISHE DCF section — staff, enrolment, results, finance, infrastructure, scholarships — from the record, ready to enter on the portal. |
| Automatic breakdowns | Computes gender, social category, minority, PwD and foreign-national splits from student and staff records, programme by programme. |
| Cross-framework reconciliation | Flags any AISHE figure that differs from what the institution reports to NAAC or NIRF, before submission. |
| Nodal officer workflow | Assigns sections to departments, tracks completion and keeps the method and source for every number. |
| Year-on-year history | Keeps every submitted return, so each cycle starts from last year’s validated data. |
Frequently asked questions
What is AISHE?
The All India Survey on Higher Education is the Ministry of Education’s annual survey of all higher education institutions in India — universities, colleges and standalone institutions. Launched in 2010-11, it is the official source of national higher education statistics.
How do institutions submit AISHE data?
The institution’s nodal officer registers once on the AISHE portal with the institution’s AISHE code, then fills the web-based Data Capture Format (DCF) for each survey round.
What data does AISHE collect?
Basic institutional details, teaching and non-teaching staff, enrolment by programme with gender, social category, minority, disability and foreign-national breakdowns, examination results, income and expenditure, infrastructure, scholarships and accreditation status.
What do the latest AISHE reports show?
The AISHE 2022-23 and 2023-24 reports were released on 8 July 2026. In 2023-24, 59,533 of 64,756 registered institutions responded, total enrolment was 4.50 crore and the Gross Enrolment Ratio was 30.0.
Why should AISHE data match NAAC and NIRF?
AISHE, NAAC and NIRF ask for the same faculty, enrolment, results and finance data. When the figures differ across them, the institution cannot defend any of them.
How does Master Data Map help with AISHE?
Master Data Map’s AISHE module generates every DCF section from the institutional record, computes all the required breakdowns automatically, and flags any figure that differs from what the institution reports to NAAC or NIRF.
AISHE Data Review
30-minute session with our team. We’ll compare your AISHE figures with your NAAC and NIRF data and show where they disagree.
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