A systematic literature review of student'performance prediction using machine learning techniques
Educational Data Mining plays a critical role in advancing the learning environment by
contributing state-of-the-art methods, techniques, and applications. The recent development …
contributing state-of-the-art methods, techniques, and applications. The recent development …
Deep learning in electron microscopy
JM Ede - Machine Learning: Science and Technology, 2021 - iopscience.iop.org
Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …
microscopy. This review paper offers a practical perspective aimed at developers with …
How to design AI for social good: Seven essential factors
Abstract The idea of Artificial Intelligence for Social Good (henceforth AI4SG) is gaining
traction within information societies in general and the AI community in particular. It has the …
traction within information societies in general and the AI community in particular. It has the …
Interpretable decision sets: A joint framework for description and prediction
One of the most important obstacles to deploying predictive models is the fact that humans
do not understand and trust them. Knowing which variables are important in a model's …
do not understand and trust them. Knowing which variables are important in a model's …
[HTML][HTML] Explainable artificial intelligence in education
There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics
(FATE) of educational interventions supported by the use of Artificial Intelligence (AI) …
(FATE) of educational interventions supported by the use of Artificial Intelligence (AI) …
Predicting at-risk university students in a virtual learning environment via a machine learning algorithm
KT Chui, DCL Fung, MD Lytras, TM Lam - Computers in Human behavior, 2020 - Elsevier
A university education is widely considered essential to social advancement. Ensuring
students pass their courses and graduate on time have thus become issues of concern. This …
students pass their courses and graduate on time have thus become issues of concern. This …
Escaping the impossibility of fairness: From formal to substantive algorithmic fairness
B Green - Philosophy & Technology, 2022 - Springer
Efforts to promote equitable public policy with algorithms appear to be fundamentally
constrained by the “impossibility of fairness”(an incompatibility between mathematical …
constrained by the “impossibility of fairness”(an incompatibility between mathematical …
Empirical observation of negligible fairness–accuracy trade-offs in machine learning for public policy
The growing use of machine learning in policy and social impact settings has raised
concerns over fairness implications, especially for racial minorities. These concerns have …
concerns over fairness implications, especially for racial minorities. These concerns have …
The impacts of remote learning in secondary education during the pandemic in Brazil
The transition to remote learning in the context of coronavirus disease 2019 (COVID-19)
might have led to dramatic setbacks in education. Taking advantage of the fact that São …
might have led to dramatic setbacks in education. Taking advantage of the fact that São …
Reimagining the machine learning life cycle to improve educational outcomes of students
Machine learning (ML) techniques are increasingly prevalent in education, from their use in
predicting student dropout to assisting in university admissions and facilitating the rise of …
predicting student dropout to assisting in university admissions and facilitating the rise of …