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Early prediction of learners at risk in self-paced education: A neural network approach
To address the demands of modern education and increase flexibility, many higher
education institutions are considering self-paced education programs. However, student …
education institutions are considering self-paced education programs. However, student …
Predictive learning analytics using deep learning model in MOOCs' courses videos
AA Mubarak, H Cao, SAM Ahmed - Education and Information …, 2021 - Springer
Abstract Analysis of learning behavior of MOOC enthusiasts has become a posed challenge
in the Learning Analytics field, which is especially related to video lecture data, since most …
in the Learning Analytics field, which is especially related to video lecture data, since most …
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 …
Utilizing Student Time Series Behaviour in Learning Management Systems for Early Prediction of Course Performance.
F Chen, Y Cui - Journal of Learning Analytics, 2020 - ERIC
Predictive analytics in higher education has become increasingly popular in recent years
with the growing availability of educational big data. Particularly, a wealth of student activity …
with the growing availability of educational big data. Particularly, a wealth of student activity …
A deep learning model to predict Student learning outcomes in LMS using CNN and LSTM
AS Aljaloud, DM Uliyan, A Alkhalil… - IEEE …, 2022 - ieeexplore.ieee.org
Learning Management Systems (LMSs) are increasingly utilized for the administration,
tracking, and reporting of educational activities. One such widely used LMS in higher …
tracking, and reporting of educational activities. One such widely used LMS in higher …
Virtual learning environment to predict withdrawal by leveraging deep learning
The current evolution in multidisciplinary learning analytics research poses significant
challenges for the exploitation of behavior analysis by fusing data streams toward advanced …
challenges for the exploitation of behavior analysis by fusing data streams toward advanced …
[HTML][HTML] Predicting at-risk students using clickstream data in the virtual learning environment
In higher education, predicting the academic performance of students is associated with
formulating optimal educational policies that vehemently impact economic and financial …
formulating optimal educational policies that vehemently impact economic and financial …
Predictive model using a machine learning approach for enhancing the retention rate of students at-risk
HS Brdesee, W Alsaggaf, N Aljohani… - International Journal on …, 2022 - igi-global.com
Student retention is a widely recognized challenge in the educational community to assist
the institutes in the formation of appropriate and effective pedagogical interventions. This …
the institutes in the formation of appropriate and effective pedagogical interventions. This …
Impact of practical skills on academic performance: A data-driven analysis
Most academic courses in information and communication technology (ICT) or engineering
disciplines are designed to improve practical skills; however, practical skills and theoretical …
disciplines are designed to improve practical skills; however, practical skills and theoretical …
A state‐of‐the‐art survey of predicting students' performance using artificial neural networks
W **ao, J Hu - Engineering Reports, 2023 - Wiley Online Library
Predicting students' performance is one of the most important issue in educational data
mining. In order to investigate the state‐of‐the‐art research development in predicting …
mining. In order to investigate the state‐of‐the‐art research development in predicting …