325 citations · 400 across the 19 of their papers we have counts for
9 papers · 1 filter
Generative AI Produces and Transmits Beauty Bias
AJ Alvero, Deepak Varuvel Dennison, Alexandra Crespin +5
Societies reward people judged to be attractive by standards intertwined with gender and race. In this paper, we examine if and how generative AI may contribute to these dynamics.…
When the Past Misleads: Rethinking Training Data Expansion Under Temporal Distribution Shifts
Chengyuan Yao, Yunxuan Tang, Christopher Brooks +2
Predictive models are typically trained on historical data to predict future outcomes. While it is commonly assumed that training on more historical data would improve model perfor…
Algorithms for College Admissions Decision Support: Impacts of Policy Change and Inherent Variability
Jinsook Lee, Emma Harvey, Joyce Zhou +3
Each year, selective American colleges sort through tens of thousands of applications to identify a first-year class that displays both academic merit and diversity. In the 2023-20…
The Life Cycle of Large Language Models: A Review of Biases in Education
Jinsook Lee, Yann Hicke, Renzhe Yu +2
Large Language Models (LLMs) are increasingly adopted in educational contexts to provide personalized support to students and teachers. The unprecedented capacity of LLM-based appl…
Cultural Differences in Students' Privacy Concerns in Learning Analytics across Germany, South Korea, Spain, Sweden, and the United States
Olga Viberg, René F. Kizilcec, Ioana Jivet +5
Applications of learning analytics (LA) can raise concerns from students about their privacy in higher education contexts. Developing effective privacy-enhancing practices requires…
What Explains Teachers' Trust of AI in Education across Six Countries?
Olga Viberg, Mutlu Cukurova, Yael Feldman-Maggor +9
With growing expectations to use AI-based educational technology (AI-EdTech) to improve students' learning outcomes and enrich teaching practice, teachers play a central role in th…
Should College Dropout Prediction Models Include Protected Attributes?
Renzhe Yu, Hansol Lee, René F. Kizilcec
Early identification of college dropouts can provide tremendous value for improving student success and institutional effectiveness, and predictive analytics are increasingly used…
Algorithmic Fairness in Education
René F. Kizilcec, Hansol Lee
Data-driven predictive models are increasingly used in education to support students, instructors, and administrators. However, there are concerns about the fairness of the predict…
Evaluation of Fairness Trade-offs in Predicting Student Success
Hansol Lee, René F. Kizilcec
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 algor…