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The Deferred Acceptance (DA) algorithm is stable and strategy-proof, but can produce outcomes that are Pareto-inefficient for students, and thus several alternative mechanisms have been proposed to correct this inefficiency. However, we…

Theoretical Economics · Economics 2025-06-16 Josue Ortega , Gabriel Ziegler , R. Pablo Arribillaga , Geng Zhao

Contribution: This study examined student effort and performance in an introductory programming course with respect to student-held implicit theories and self-efficacy. Background: Implicit theories and self-efficacy shed a light into…

Computers and Society · Computer Science 2018-09-03 F. Boray Tek , Kristin S. Benli , Ezgi Deveci

We introduce the framework of performative reinforcement learning where the policy chosen by the learner affects the underlying reward and transition dynamics of the environment. Following the recent literature on performative…

Machine Learning · Computer Science 2023-06-08 Debmalya Mandal , Stelios Triantafyllou , Goran Radanovic

This study aims to determine a predictive model to learn students probability to pass their courses taken at the earliest stage of the semester. To successfully discover a good predictive model with high acceptability, accurate, and…

Machine Learning · Computer Science 2023-04-13 Anabella C. Doctor

Student repetition in secondary education imposes significant resource burdens, particularly in resource-constrained contexts. Addressing this challenge, this study introduces a unified machine learning framework that simultaneously…

Artificial Intelligence · Computer Science 2026-03-03 Mwayi Sonkhanani , Symon Chibaya , Clement N. Nyirenda

We propose a new estimation method for heterogeneous causal effects which utilizes a regression discontinuity (RD) design for multiple datasets with different thresholds. The standard RD design is frequently used in applied researches, but…

Econometrics · Economics 2019-05-14 Takayuki Toda , Ayako Wakano , Takahiro Hoshino

Several studies indicate that attracting students to research careers requires to engage them from early undergraduate years. Following this paradigm, our Engineering School has developed an undergraduate research program that allows…

Information Retrieval · Computer Science 2017-06-22 Felipe del-Rio , Denis Parra , Jovan Kuzmicic , Erick Svec

There is debate over whether Asian American students are admitted to selective colleges and universities at lower rates than white students with similar academic qualifications. However, there have been few empirical investigations of this…

Computers and Society · Computer Science 2023-08-10 Joshua Grossman , Sabina Tomkins , Lindsay Page , Sharad Goel

We consider the problem of designing affirmative action policies for selecting the top-k candidates from a pool of applicants. We assume that for each candidate we have socio-demographic attributes and a series of variables that serve as…

Computers and Society · Computer Science 2021-03-10 Michael Mathioudakis , Carlos Castillo , Giorgio Barnabo , Sergio Celis

Using detailed Norwegian data on earnings, education and work histories, we estimate a dynamic structural model of education and sector choices that captures rich life-cycle patterns by ability. We validate the model against variation in…

General Economics · Economics 2024-07-03 Manudeep Bhuller , Philipp Eisenhauer , Moritz Mendel

In this study, we examine how event data from campus management systems can be used to analyze the study paths of higher education students. The main goal is to offer valuable guidance for their study planning. We employ process and data…

Academic performance depends on a multivariable nexus of socio-academic and financial factors. This study investigates these influences to develop effective strategies for optimizing students' CGPA. To achieve this, we reviewed various…

Machine Learning · Computer Science 2025-08-04 Bushra Akter , Md Biplob Hosen , Sabbir Ahmed , Mehrin Anannya , Md. Farhad Hossain

We propose a simple, statistically principled, and theoretically justified method to improve supervised learning when the training set is not representative, a situation known as covariate shift. We build upon a well-established methodology…

Machine Learning · Statistics 2025-03-12 Maximilian Autenrieth , David A. van Dyk , Roberto Trotta , David C. Stenning

Consequential decision-making typically incentivizes individuals to behave strategically, tailoring their behavior to the specifics of the decision rule. A long line of work has therefore sought to counteract strategic behavior by designing…

Machine Learning · Computer Science 2018-11-26 Smitha Milli , John Miller , Anca D. Dragan , Moritz Hardt

The development and deployment of matching procedures that incentivize truthful preference reporting is considered one of the major successes of market design research. In this study, we test the degree to which these procedures succeed in…

Econometrics · Economics 2022-10-12 Alex Rees-Jones , Samuel Skowronek

High school and college graduates seemingly are often battling for the courses they should major in order to achieve their target career. In this paper, we worked on suggesting a career path to a graduate to reach his/her dream career given…

Computers and Society · Computer Science 2015-10-20 Akshay Nagpal , Supriya P. Panda

Longitudinal data tracking repeated measurements on individuals are highly valued for research because they offer controls for unmeasured individual heterogeneity that might otherwise bias results. Random effects or mixed models approaches,…

Applications · Statistics 2009-09-29 J. R. Lockwood , Daniel F. McCaffrey

Strategic incentives may lead to inefficient and unequal provision of public services. A prominent example is school admissions. Existing research shows that applicants "play the system" by submitting school rankings strategically. We…

Designing recommendation systems that serve content aligned with time varying preferences requires proper accounting of the feedback effects of recommendations on human behavior and psychological condition. We argue that modeling the…

Information Retrieval · Computer Science 2022-08-09 Mihaela Curmei , Andreas Haupt , Dylan Hadfield-Menell , Benjamin Recht

Datasets for training recommender systems are often subject to distribution shift induced by users' and recommenders' selection biases. In this paper, we study the impact of selection bias on datasets with different quantization. We then…

Information Retrieval · Computer Science 2022-12-29 Fengyu Li , Sarah Dean