Factors of dropout from MOOCs: a bibliometric review
Purpose Although MOOCs have become a pervasive online learning model, the problem of
high dropout rates still persists. Gathering the reasons for the high dropout rate can help to …
high dropout rates still persists. Gathering the reasons for the high dropout rate can help to …
Application of machine learning in higher education to assess student academic performance, at-risk, and attrition: A meta-analysis of literature
Recently, machine learning (ML) has evolved and finds its application in higher education
(HE) for various data analysis. Studies have shown that such an emerging field in …
(HE) for various data analysis. Studies have shown that such an emerging field in …
Towards predicting student's dropout in university courses using different machine learning techniques
J Kabathova, M Drlik - Applied Sciences, 2021 - mdpi.com
Featured Application The found model with the best values of the performance metrics,
found as the result of comparing several machine learning classifiers, can identify students …
found as the result of comparing several machine learning classifiers, can identify students …
Deep analytic model for student dropout prediction in massive open online courses
AA Mubarak, H Cao, IM Hezam - Computers & Electrical Engineering, 2021 - Elsevier
Predicting students' performance is critical in Massive Open Online Courses (MOOCs) in
order to benefit from many aspects such as students' retention and make timely …
order to benefit from many aspects such as students' retention and make timely …
Utilizing grid search cross-validation with adaptive boosting for augmenting performance of machine learning models
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 …
Virtual Learning Environments (VLEs) instigating students to study from their homes. Every …
Take a MOOC and then drop: A systematic review of MOOC engagement pattern and dropout factor
H Huang, L Jew, D Qi - Heliyon, 2023 - cell.com
Abstract Massive Open Online Course (MOOC) plays an important role in education equity
and lifelong learning without entrance barriers, time limitations, and geographical …
and lifelong learning without entrance barriers, time limitations, and geographical …
Unraveling the mechanisms underlying drug-induced cholestatic liver injury: identifying key genes using machine learning techniques on human in vitro data sets
Drug-induced intrahepatic cholestasis (DIC) is a main type of hepatic toxicity that is
challenging to predict in early drug development stages. Preclinical animal studies often fail …
challenging to predict in early drug development stages. Preclinical animal studies often fail …
Deep learning model to predict students retention using BLSTM and CRF
D Uliyan, AS Aljaloud, A Alkhalil, HS Al Amer… - IEEE …, 2021 - ieeexplore.ieee.org
There is an increasing awareness that predictive analytics helps universities to evaluate
students' performances. Big data analytics, such as student demographic datasets, can …
students' performances. Big data analytics, such as student demographic datasets, can …
Predictive video analytics in online courses: A systematic literature review
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 …
courses in the literature. A systematic literature review was performed based on a hybrid …
Design and implementation of discrete Jaya and discrete PSO algorithms for automatic collaborative learning group composition in an e-learning system
N Gavrilovic, T Sibalija, D Domazet - Applied Soft Computing, 2022 - Elsevier
This paper presents the design and implementation of two discrete metaheuristic algorithms
for automatic student collaborative group creation in an e-learning system by grouping …
for automatic student collaborative group creation in an e-learning system by grouping …