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The global surge in social inequalities is one of the most pressing issues of our times. The spatial expression of social inequalities at city scale gives rise to urban segregation, a common phenomenon across different local and cultural…
Data-driven predictive models are increasingly used in education to support students, instructors, and administrators. However, there are concerns about the fairness of the predictions and uses of these algorithmic systems. In this…
Motivated by school admissions, this paper studies screening in a population with both advantaged and disadvantaged agents. A school is interested in admitting the most skilled students, but relies on imperfect test scores that reflect both…
Intuitively, students who start a homework assignment earlier and spend more time on it should receive better grades on the assignment. However, existing literature on the impact of time spent on homework is not clear-cut and comes mostly…
The tendency for individuals to form social ties with others who are similar to themselves, known as homophily, is one of the most robust sociological principles. Since this phenomenon can lead to patterns of interactions that segregate…
Socio-demographic disparities in STEM degree outcomes impact the diversity of the UK's future workforce, particularly in fields essential for innovation and growth. Despite the importance of institution-level, longitudinal analyses in…
In many situations people make sequences of similar, but unrelated decisions. Such decision sequences are prevalent in many important contexts including judicial judgments, loan approvals, college admissions, and athletic competitions. A…
Ensembling is commonly regarded as an effective way to improve the general performance of models in machine learning, while also increasing the robustness of predictions. When it comes to algorithmic fairness, heterogeneous ensembles,…
Predictive models for identifying at-risk students early can help teaching staff direct resources to better support them, but there is a growing concern about the fairness of algorithmic systems in education. Predictive models may…
The lack of an engaging pedagogy and the highly competitive atmosphere in introductory science courses tend to discourage students from pursuing science, technology, engineering, and mathematics (STEM) majors. Once in a STEM field, academic…
The study investigated roles of institutional types and ethnic/racial background on academic credit among the traditionally underrepresented population of the U.S. study abroad program. Using archival data, the study sampled the students'…
In previous work we analyzed databases for 95 classes to show that the percent grade scale was correlated with a much higher student fail rate than the 4.0 grade scale. This paper builds on this work and investigates equity gaps occurring…
We study the design of effort-maximizing grading schemes between agents with private abilities. Assuming agents derive value from the information their grade reveals about their ability, we find that more informative grading schemes induce…
Students interpret grades as signals of their strengths, and grades inform students' decisions about majors and courses of study. Differences in grades that are not related to learning can impact this judgment and have real-world impact on…
We study the role of information and access in capacity-constrained selection problems with fairness concerns. We develop a statistical discrimination framework, where each applicant has multiple features and is potentially strategic. The…
In the context of higher education's evolving dynamics post-COVID-19, this paper assesses the impact of new pedagogical incentives implemented in a first-year undergraduate computing module at University College London. We employ a mixed…
We develop a feedback theory that includes reinforcing and balancing feedback effects that emerge when colleges compete for reputation, applicants, and tuition revenue. The feedback theory is replicated in a formal duopoly model consisting…
Underlying complex systems, there is a rich web of interconnected components that determine the relational properties of the system. Yet, traditional methods used in education sciences often disregard the underlying complexity of the…
We analyze a heterogeneity of the educational system on the basis of one parameter: input grades of university students. We propose a mathematical model based on the construction of universities interval order. We use the Hamming distance…
Creating equitable performance outcomes among students is a focus of many instructors and researchers. One focus of this effort is examining disparities in physics student performance across genders, which is a well-established problem.…