Practical and ethical challenges of large language models in education: A systematic sco** review

L Yan, L Sha, L Zhao, Y Li… - British Journal of …, 2024 - Wiley Online Library
Educational technology innovations leveraging large language models (LLMs) have shown
the potential to automate the laborious process of generating and analysing textual content …

Promises and challenges of generative artificial intelligence for human learning

L Yan, S Greiff, Z Teuber, D Gašević - Nature Human Behaviour, 2024 - nature.com
Generative artificial intelligence (GenAI) holds the potential to transform the delivery,
cultivation and evaluation of human learning. Here the authors examine the integration of …

Moral machines or tyranny of the majority? A systematic review on predictive bias in education

L Li, L Sha, Y Li, M Raković, J Rong… - … learning analytics and …, 2023 - dl.acm.org
Machine Learning (ML) techniques have been increasingly adopted to support various
activities in education, including being applied in important contexts such as college …

[HTML][HTML] Investigating algorithmic bias in student progress monitoring

JA Idowu, AS Koshiyama, P Treleaven - Computers and Education …, 2024 - Elsevier
This research investigates bias in AI algorithms used for monitoring student progress,
specifically focusing on bias related to age, disability, and gender. The study is motivated by …

[HTML][HTML] Fairness for machine learning software in education: A systematic map** study

N Pham, PN Hung, A Nguyen-Duc - Journal of Systems and Software, 2024 - Elsevier
The integration of machine learning (ML) systems into various sectors, notably education,
has great potential to transform business workflows and decision-making processes …

[HTML][HTML] Lessons from debiasing data for fair and accurate predictive modeling in education

L Sha, D Gašević, G Chen - Expert Systems with Applications, 2023 - Elsevier
The past few years have witnessed an explosion of attention given to the bias displayed by
Machine Learning (ML) techniques towards different groups of people (eg, female vs. male) …

Towards automated analysis of rhetorical categories in students essay writings using Bloom's taxonomy

S Iqbal, M Rakovic, G Chen, T Li… - … Learning Analytics and …, 2023 - dl.acm.org
Essay writing has become one of the most common learning tasks assigned to students
enrolled in various courses at different educational levels, owing to the growing demand for …

[HTML][HTML] Enhancing Feedback Quality at Scale: Leveraging Machine Learning for Learner-Centered Feedback

AA Aldino, YS Tsai, RF Mello, D Gašević… - Computers and Education …, 2024 - Elsevier
In higher education, delivering effective feedback is pivotal for enhancing student learning
but remains challenging due to the scale and diversity of student populations. Learner …

Whither bias goes, I will go: An integrative, systematic review of algorithmic bias mitigation.

L Hickman, C Huynh, J Gass, B Booth… - Journal of Applied …, 2024 - psycnet.apa.org
Abstract Machine learning (ML) models are increasingly used for personnel assessment and
selection (eg, resume screeners, automatically scored interviews). However, concerns have …

Predicting university student graduation using academic performance and machine learning: a systematic literature review

LR Pelima, Y Sukmana, Y Rosmansyah - IEEE Access, 2024 - ieeexplore.ieee.org
Predicting university student graduation is a beneficial tool for both students and institutions.
With the help of this predictive capacity, students may make well-informed decisions about …