Student retention using educational data mining and predictive analytics: a systematic literature review
Student retention is an essential measurement metric in education, indicated by retention
rates, which are accumulated as students re-enroll from one academic year to the next. High …
rates, which are accumulated as students re-enroll from one academic year to the next. High …
Which log variables significantly predict academic achievement? A systematic review and meta‐analysis
Q Wang, A Mousavi - British Journal of Educational …, 2023 - Wiley Online Library
Technologies and teaching practices can provide a rich log data, which enables learning
analytics (LA) to bring new insights into the learning process for ultimately enhancing …
analytics (LA) to bring new insights into the learning process for ultimately enhancing …
A comparison of undersampling, oversampling, and SMOTE methods for dealing with imbalanced classification in educational data mining
Educational data mining is capable of producing useful data-driven applications (eg, early
warning systems in schools or the prediction of students' academic achievement) based on …
warning systems in schools or the prediction of students' academic achievement) based on …
Distance learning as a resilience strategy during Covid-19: An analysis of the Italian context
A Appolloni, N Colasanti, C Fantauzzi, G Fiorani… - Sustainability, 2021 - mdpi.com
The purpose of this paper is to analyze the strategic model of distance learning adopted by
Italian higher education, showing how the health emergency due to Covid-19 has …
Italian higher education, showing how the health emergency due to Covid-19 has …
Associations between learning analytics dashboard exposure and motivation and self-regulated learning
Learning analytics dashboards (LADs) are intended to give relevant information to students
and other stakeholders to inform potential next steps in the learning process. The current …
and other stakeholders to inform potential next steps in the learning process. The current …
Predicting individual learning performance using machine‐learning hybridized with the teaching‐learning‐based optimization
M Arashpour, EM Golafshani… - Computer …, 2023 - Wiley Online Library
Reliable prediction of individual learning performance can facilitate timely support to
students and improve the learning experience. In this study, two well‐known machine …
students and improve the learning experience. In this study, two well‐known machine …
An early warning system to detect at-risk students in online higher education
Artificial intelligence has impacted education in recent years. Datafication of education has
allowed developing automated methods to detect patterns in extensive collections of …
allowed developing automated methods to detect patterns in extensive collections of …
Standing on the shoulders of giants: Online formative assessments as the foundation for predictive learning analytics models
As universities around the world have begun to use learning management systems (LMSs),
more learning data have become available to gain deeper insights into students' learning …
more learning data have become available to gain deeper insights into students' learning …
Increased digital resource consumption in higher educational institutions and the artificial intelligence role in informing decisions related to student performance
As education is an essential enabler in achieving Sustainable Development Goals (SDGs), it
should “ensure inclusive, equitable quality education, and promote lifelong learning …
should “ensure inclusive, equitable quality education, and promote lifelong learning …
Predicting and understanding student learning performance using multi-source sparse attention convolutional neural networks
Predicting and understanding student learning performance has been a long-standing task
in learning science, which can benefit personalized teaching and learning. This study shows …
in learning science, which can benefit personalized teaching and learning. This study shows …