There is substantial evidence of the relationship between household income and
achievement on the standardized tests often required for college admissions, yet little …

Machine Learning (ML) techniques have been increasingly adopted to support various
activities in education, including being applied in important contexts such as college …

Early identification of college dropouts can provide tremendous value for improving student
success and institutional effectiveness, and predictive analytics are increasingly used for this …

Modern machine learning increasingly supports paradigms that are multi-institutional (using
data from multiple institutions during training) or cross-institutional (using models from …

In this article, we argue that automated scoring engines should be transparent and construct
relevant—that is, as much as is currently feasible. Many current automated scoring engines …

University admission at many highly selective institutions uses a holistic review process,
where all aspects of the application, including protected attributes (eg, race, gender) …

US colleges and universities are defined by their exclusivity, and the most prestigious
schools reject most of those who apply. Yet these same schools also widely advertise their …

Committing to a major is a fateful step in an undergraduate education, yet the relationship
between courses taken early in an academic career and ultimate major issuance remains …

Variation in college application materials related to social stratification is a contentious topic
in social science and national discourse in the United States. This line of research has also …

We have dramatically advanced our ability to create rich, complex, and effective
assessments across a range of uses through technology advancement. Artificial Intelligence …