Text-based open-ended questions in academic formative and summative assessments help
students become deep learners and prepare them to understand concepts for a subsequent …

In this paper, we present the concept of AI Readiness, along with a framework for
developing AI Readiness training.'AI Readiness' can be framed as a contextualised way of …

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

Nowadays, there is an increasing concern in machine learning about the causes underlying
unfair decision making, that is, algorithmic decisions discriminating some groups over …

Equity of educational outcome and fairness of AI with respect to race have been topics of
increasing importance in education. In this work, we address both with empirical evaluations …

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

Word vectors are widely used as input features in natural language processing (NLP) tasks.
Researchers have found that word vectors often encode the biases of society, and steps …

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 …

A subset of undergraduate applicants to the University of California, Berkeley were invited to
submit letters of recommendation as part of their applications. I use scraped text of the …

Predicting students' academic performance is one of the key tasks of educational data
mining (EDM). Traditionally, the high forecasting quality of such models was deemed critical …