A survey of machine learning approaches for student dropout prediction in online courses

B Prenkaj, P Velardi, G Stilo, D Distante… - ACM Computing Surveys …, 2020 - dl.acm.org
The recent diffusion of online education (both MOOCs and e-courses) has led to an
increased economic and scientific interest in e-learning environments. As widely …

DeepLMS: a deep learning predictive model for supporting online learning in the Covid-19 era

SB Dias, SJ Hadjileontiadou, J Diniz… - Scientific reports, 2020 - nature.com
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 …

Utilizing grid search cross-validation with adaptive boosting for augmenting performance of machine learning models

M Adnan, AAS Alarood, MI Uddin… - PeerJ Computer Science, 2022 - peerj.com
Abstract Corona Virus Disease 2019 (COVID-19) pandemic has increased the importance of
Virtual Learning Environments (VLEs) instigating students to study from their homes. Every …

Predictive video analytics in online courses: A systematic literature review

OR Yürüm, T Taşkaya-Temizel, S Yıldırım - Technology, Knowledge and …, 2024 - Springer
The purpose of this study was to investigate the use of predictive video analytics in online
courses in the literature. A systematic literature review was performed based on a hybrid …

Analysis of the factors influencing learners' performance prediction with learning analytics

PM Moreno-Marcos, TC Pong, PJ Munoz-Merino… - IEEE …, 2020 - ieeexplore.ieee.org
The advancement of learning analytics has enabled the development of predictive models to
forecast learners' behaviors and outcomes (eg, performance). However, many of these …

Is college students' trajectory associated with academic performance?

H Lim, S Kim, KM Chung, K Lee, T Kim, J Heo - Computers & Education, 2022 - Elsevier
Many higher-education institutions have endeavored to understand students' characteristics
in order to improve the quality of education. To this end, demographic information and …

An exploratory analysis of the latent structure of process data via action sequence autoencoders

X Tang, Z Wang, J Liu, Z Ying - British Journal of Mathematical …, 2021 - Wiley Online Library
Computer simulations have become a popular tool for assessing complex skills such as
problem‐solving. Log files of computer‐based items record the human–computer interactive …

[HTML][HTML] Predicting student achievement based on temporal learning behavior in MOOCs

S Qu, K Li, B Wu, S Zhang, Y Wang - Applied Sciences, 2019 - mdpi.com
With the development of data mining technology, educational data mining (EDM) has gained
increasing amounts of attention. Research on massive open online courses (MOOCs) is an …

Predicting student performance in interactive online question pools using mouse interaction features

H Wei, H Li, M **a, Y Wang, H Qu - Proceedings of the tenth international …, 2020 - dl.acm.org
Modeling student learning and further predicting the performance is a well-established task
in online learning and is crucial to personalized education by recommending different …

[HTML][HTML] Predictive learning analytics in online education: A deeper understanding through explaining algorithmic errors

M Hlosta, C Herodotou, T Papathoma… - … and Education: Artificial …, 2022 - Elsevier
Abstract Existing Predictive Learning Analytics (PLA) systems utilising machine learning
models show they can improve teacher practice and, at the same time, student outcomes …