AI and Holistic Review: Informing Human Reading in College Admissions
College admissions in the United States is carried out by a human-centered method of evaluation known as holistic review, which typically involves reading original narrative essays submitted by each applicant. The legitimacy and fairness of holistic review, which gives human readers significant discretion over determining each applicant's fitness for admission, has been repeatedly challenged in courtrooms and the public sphere. Using a unique corpus of 283,676 application essays submitted to a large, selective, state university system between 2015 and 2016, we assess the extent to which applicant demographic characteristics can be inferred from application essays. We find a relatively interpretable classifier (logistic regression) was able to predict gender and household income with high levels of accuracy. Findings suggest that data auditing might be useful in informing holistic review, and perhaps other evaluative systems, by checking potential bias in human or computational readings.
Code (0)
등록된 구현이 없습니다.
Tasks
FairnessSimilar Papers 제목 키워드 기반
Quantifying Holistic Review: A Multi-Modal 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 prof…
Reading-strategy Inspired Visual Representation Learning for Text-to-Video Retrieval
This paper aims for the task of text-to-video retrieval, where given a query in the form of a natural-language sentence, it is asked to retrieve videos which are semantically relevant to the given query, from a great num…
Representation LearningRetrievalSemantic SimilaritySemantic Textual Similarity+3KRISTEVA: Close Reading as a Novel Task for Benchmarking Interpretive Reasoning
Each year, tens of millions of essays are written and graded in college-level English courses. Students are asked to analyze literary and cultural texts through a process known as close reading, in which they gather text…
BenchmarkingMMLUMultiple-choiceMultimodal Methods for Analyzing Learning and Training Environments: A Systematic Literature Review
Recent technological advancements have enhanced our ability to collect and analyze rich multimodal data (e.g., speech, video, and eye gaze) to better inform learning and training experiences. While previous reviews have …
Systematic Literature ReviewIntegrating HCI Datasets in Project-Based Machine Learning Courses: A College-Level Review and Case Study
This study explores the integration of real-world machine learning (ML) projects using human-computer interfaces (HCI) datasets in college-level courses to enhance both teaching and learning experiences. Employing a comp…