A survey on datasets for fairness‐aware machine learning
As decision‐making increasingly relies on machine learning (ML) and (big) data, the issue
of fairness in data‐driven artificial intelligence systems is receiving increasing attention from …
of fairness in data‐driven artificial intelligence systems is receiving increasing attention from …
Algorithmic bias in education
In this paper, we review algorithmic bias in education, discussing the causes of that bias and
reviewing the empirical literature on the specific ways that algorithmic bias is known to have …
reviewing the empirical literature on the specific ways that algorithmic bias is known to have …
Leveraging class balancing techniques to alleviate algorithmic bias for predictive tasks in education
Predictive modeling is a core technique used in tackling various tasks in learning analytics
research, eg, classifying educational forum posts, predicting learning performance, and …
research, eg, classifying educational forum posts, predicting learning performance, and …
They shall be fair, transparent, and robust: auditing learning analytics systems
K Simbeck - AI and Ethics, 2024 - Springer
In the near future, systems, that use Artificial Intelligence (AI) methods, such as machine
learning, are required to be certified or audited for fairness if used in ethically sensitive fields …
learning, are required to be certified or audited for fairness if used in ethically sensitive fields …
Assessing algorithmic fairness in automatic classifiers of educational forum posts
Automatic classifiers of educational forum posts are essential in helping instructors
effectively implement their teaching practices and thus have been widely investigated …
effectively implement their teaching practices and thus have been widely investigated …
Moral machines or tyranny of the majority? A systematic review on predictive bias in education
Machine Learning (ML) techniques have been increasingly adopted to support various
activities in education, including being applied in important contexts such as college …
activities in education, including being applied in important contexts such as college …
Bigger data or fairer data?: augmenting BERT via active sampling for educational text classification
Abstract Pretrained Language Models (PLMs), though popular, have been diagnosed to
encode bias against protected groups in the representations they learn, which may harm the …
encode bias against protected groups in the representations they learn, which may harm the …
Is it time we get real? A systematic review of the potential of data-driven technologies to address teachers' implicit biases
Data-driven technologies for education, such as artificial intelligence in education (AIEd)
systems, learning analytics dashboards, open learner models, and other applications, are …
systems, learning analytics dashboards, open learner models, and other applications, are …
Revealing factors influencing students' perceived fairness: A case with a predictive system for math learning
Educational researchers have examined artificial intelligence (AI) to automatically support
students' learning at a large scale. However, it has been broadly identified that AI models …
students' learning at a large scale. However, it has been broadly identified that AI models …
Are algorithms biased in education? Exploring racial bias in predicting community college student success
KA Bird, BL Castleman, Y Song - Journal of Policy Analysis and …, 2024 - Wiley Online Library
Predictive analytics are increasingly pervasive in higher education. However, algorithmic
bias has the potential to reinforce racial inequities in postsecondary success. We provide a …
bias has the potential to reinforce racial inequities in postsecondary success. We provide a …