A survey on educational data mining methods used for predicting students' performance
W Xiao, P Ji, J Hu - Engineering Reports, 2022 - Wiley Online Library
Predicting students' performance is one of the most important issues in educational data
mining (EDM), which has received more and more attention. By predicting students' …
mining (EDM), which has received more and more attention. By predicting students' …
Contributions of machine learning models towards student academic performance prediction: a systematic review
Machine learning is emerging nowadays as an important tool for decision support in many
areas of research. In the field of education, both educational organizations and students are …
areas of research. In the field of education, both educational organizations and students are …
The factors affecting acceptance of e-learning: A machine learning algorithm approach
DN Lu, HQ Le, TH Vu - Education Sciences, 2020 - mdpi.com
The Covid-19 epidemic is affecting all areas of life, including the training activities of
universities around the world. Therefore, the online learning method is an effective method …
universities around the world. Therefore, the online learning method is an effective method …
A brief review of explainable artificial intelligence in healthcare
XAI refers to the techniques and methods for building AI applications which assist end users
to interpret output and predictions of AI models. Black box AI applications in high-stakes …
to interpret output and predictions of AI models. Black box AI applications in high-stakes …
Data clustering using moth-flame optimization algorithm
A k-means algorithm is a method for clustering that has already gained a wide range of
acceptability. However, its performance extremely depends on the opening cluster centers …
acceptability. However, its performance extremely depends on the opening cluster centers …
Contextualizing the current state of research on the use of machine learning for student performance prediction: A systematic literature review
Today, educational institutions produce large amounts of data with the deployment of
learning management systems. These large datasets provide an untapped potential to …
learning management systems. These large datasets provide an untapped potential to …
A review of clustering models in educational data science toward fairness-aware learning
Ensuring fair access to quality education is essential for every education system to fully
realize every student's potential. Nowadays, machine learning (ML) is transforming …
realize every student's potential. Nowadays, machine learning (ML) is transforming …
The mediation role of the organizational memory in the relationship between knowledge capturing and learning organization
Learning organization became an imperative issue to be flexible and adaptable for meeting
ever-changing needs in today's turbulent business environment. This study's major purpose …
ever-changing needs in today's turbulent business environment. This study's major purpose …
RnkHEU: A hybrid feature selection method for predicting students' performance
W Xiao, P Ji, J Hu - Scientific Programming, 2021 - Wiley Online Library
Predicting students' performance is one of the most concerned issues in education data
mining (EDM), which has received more and more attentions. Feature selection is the key …
mining (EDM), which has received more and more attentions. Feature selection is the key …
Predicting students' academic performance using machine learning techniques: a literature review
A Nabil, M Seyam… - International Journal of …, 2022 - inderscienceonline.com
The amount of students' data stored in educational databases is increasing rapidly. These
databases contain hidden patterns and useful information about students' behaviour and …
databases contain hidden patterns and useful information about students' behaviour and …