[HTML][HTML] Students matter the most in learning analytics: The effects of internal and instructional conditions in predicting academic success
Predictive modelling of academic success and retention has been a key research theme in
Learning Analytics. While the initial work on predictive modelling was focused on the …
Learning Analytics. While the initial work on predictive modelling was focused on the …
DeepLMS: a deep learning predictive model for supporting online learning in the Covid-19 era
Abstract Coronavirus (Covid-19) pandemic has imposed a complete shut-down of face-to-
face teaching to universities and schools, forcing a crash course for online learning plans …
face teaching to universities and schools, forcing a crash course for online learning plans …
Systematic ensemble model selection approach for educational data mining
A plethora of research has been done in the past focusing on predicting student's
performance in order to support their development. Many institutions are focused on …
performance in order to support their development. Many institutions are focused on …
Educational anomaly analytics: features, methods, and challenges
Anomalies in education affect the personal careers of students and universities' retention
rates. Understanding the laws behind educational anomalies promotes the development of …
rates. Understanding the laws behind educational anomalies promotes the development of …
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 …
With the help of this predictive capacity, students may make well-informed decisions about …
Early dropout prediction in online learning of university using machine learning
HS Park, SJ Yoo - JOIV: International Journal on Informatics Visualization, 2021 - joiv.org
Recently, most universities plan to open or open online learning courses, but the problem
of dropout of online learning is still a problem for universities. Online learning has the …
of dropout of online learning is still a problem for universities. Online learning has the …
Predicting student academic performance by means of associative classification
The Learning Analytics community has recently paid particular attention to early predict
learners' performance. An established approach entails training classification models from …
learners' performance. An established approach entails training classification models from …
Using convolutional neural network to recognize learning images for early warning of at-risk students
This article proposes two innovative approaches, the one-channel learning image
recognition and the three-channel learning image recognition, to convert student's course …
recognition and the three-channel learning image recognition, to convert student's course …
A novel methodology using RNN+ LSTM+ ML for predicting student's academic performance
In the profession of education, predicting students' academic success is an essential
responsibility. This study introduces a novel methodology for predicting students' pass or fail …
responsibility. This study introduces a novel methodology for predicting students' pass or fail …
An integrated framework based on latent variational autoencoder for providing early warning of at-risk students
The rapid development of learning technologies has enabled online learning paradigm to
gain great popularity in both high education and K-12, which makes the prediction of student …
gain great popularity in both high education and K-12, which makes the prediction of student …