Quantifying holistic review: a multimodal approach to college admissions prediction

This paper introduces the Comprehensive Applicant Profile Score (CAPS), a novel multi-modal framework designed to quantitatively model and interpret holistic college admissions evaluations. CAPS decomposes applicant profiles into three interpretable components: academic performance (Standardized Academic Score, SAS), essay quality (Essay Quality Index, EQI), and extracurricular engagement (Extracurricular Impact Score, EIS). Leveraging transformer-based semantic embeddings, LLM scoring, and XGBoost regression. CAPS provides transparent and explainable evaluations aligned with human judgment. Experiments on a synthetic but realistic dataset demonstrate strong performance, achieving an EQI prediction 𝑅2 of 0.80, classification accuracy over 75%, and a macro F1 score of 0.69, and weighted F1 score of 0.74. CAPS addresses key limitations in traditional holistic review—particularly the opacity, inconsistency, and anxiety faced by applicants—thus paving the way for more equitable and data-informed admissions practices.