Admissions Management for Universities

Each platform's API and data model configures independently — Common App data, UCAS UCAS-CCG (Course Choice Graph) and Personal Statement, UAC undergraduate or VTAC choice data, CUET-UG NTA-released score data, JAMB UTME-released score data — all flow into the same prospective-student record. Universities operating across multiple intake platforms (a US university with international branch operating UCAS intake; an Indian university with international applicants via direct / Common App for International) handle them in one workflow. Decision letters, financial aid offers, and downstream SIS enrollment all reference the same prospective record regardless of intake platform.

Yes. Graduate admissions workflow handles per-program faculty review committees: each program (Mechanical Engineering MS, Mechanical Engineering PhD, Public Policy MA, Computer Science PhD) assigns its own admissions committee, reads applications independently, scores against program-specific rubrics, and makes per-program admissions and funding decisions. GRE / GMAT / LSAT / MCAT scores intake from ETS / GMAC / LSAC / AAMC. Funding decisions (TA, RA, fellowship) tie to admissions decisions; some programs admit-with-funding, others admit-then-funding-decided-separately. Interview scheduling, often required for PhD admissions, integrates with calendar systems.

Predicted-yield models train on historical admitted-applicant cohort data, predicting per-segment likelihood-to-enroll based on demographics, financial aid offer, demonstrated interest signals (campus visit, application early-decision, supplementary essay completed), geography, and peer-overlap admit data (where available). Yield dashboards show cycle progress against prediction by segment through April. Summer melt — per NACAC research, 10-20% of admitted-and-deposited students nationally don't enroll by orientation — tracks per cohort segment, with melt-mitigation outreach (financial aid Q&A, advisor outreach, peer-mentor matching) targeting at-risk students before melt occurs. First-generation and low-income melt rates run 15-30% absent intervention; targeted outreach typically cuts melt by 30-50%.

Yes. Following the SFFA v. Harvard / UNC decision (June 2023), university admissions workflows must implement race-blind decision processes while preserving holistic review of context, character, life experience, and individual narrative. Reader workflow rubrics configure per university's post-SFFA policy: rubric dimensions (academic strength, essay quality, recommendation quality, demonstrated interest, fit, individual contextual factors) align with the policy each university adopts. Audit trails on reader scoring support compliance review. Universities seeking guidance from American Council on Education (ACE) and AACRAO post-SFFA policy briefs configure aligned workflows.

IPEDS Admissions component (Fall enrollment, Admitted, Yielded, Test scores 25th/50th/75th percentiles, Geographic origin distribution) exports from source admissions data at IPEDS keyholder closing dates each fall. HESA Student return (UK) exports admissions data including HESA Standard Registration Population, course-level admissions data, and HEDIIP-aligned data definitions during the Data Futures transition. UGC Mandatory Disclosure (India), AICTE EOA admissions section (where applicable), and NAAC SSR admissions metrics generate from source. Universities operating across multiple regulatory regimes (e.g., Indian universities with foreign collaboration; UK universities with offshore programs) export per regime without parallel reporting databases.