Imbalanced classification methods for student grade prediction: a systematic literature review
Student success is essential for improving the higher education system student outcome.
One way to measure student success is by predicting students' performance based on their …
One way to measure student success is by predicting students' performance based on their …
Multiclass prediction model for student grade prediction using machine learning
Today, predictive analytics applications became an urgent desire in higher educational
institutions. Predictive analytics used advanced analytics that encompasses machine …
institutions. Predictive analytics used advanced analytics that encompasses machine …
Educational data mining techniques for student performance prediction: method review and comparison analysis
Y Zhang, Y Yun, R An, J Cui, H Dai… - Frontiers in psychology, 2021 - frontiersin.org
Student performance prediction (SPP) aims to evaluate the grade that a student will reach
before enrolling in a course or taking an exam. This prediction problem is a kernel task …
before enrolling in a course or taking an exam. This prediction problem is a kernel task …
Predicting and understanding student learning performance using multi-source sparse attention convolutional neural networks
Predicting and understanding student learning performance has been a long-standing task
in learning science, which can benefit personalized teaching and learning. This study shows …
in learning science, which can benefit personalized teaching and learning. This study shows …
Graph-regularized federated learning with shareable side information
This study focuses on specifying local models in federated learning (FL), which allows a
large number of clients to improve their corresponding models by training a shared global …
large number of clients to improve their corresponding models by training a shared global …
Anchor-based collaborative filtering
Modern-day recommender systems are often based on learning representations in a latent
vector space that encode user and item preferences. In these models, each user/item is …
vector space that encode user and item preferences. In these models, each user/item is …
Undergraduate grade prediction in Chinese higher education using convolutional neural networks
Y Zhang, R An, J Cui, X Shang - LAK21: 11th International Learning …, 2021 - dl.acm.org
Prediction of undergraduate grades before their course enrollments is beneficial to the
student's learning plan on selective courses and failure warnings to compulsory courses in …
student's learning plan on selective courses and failure warnings to compulsory courses in …
Federated learning-outcome prediction with multi-layer privacy protection
Y Zhang, Y Li, Y Wang, S Wei, Y Xu… - Frontiers of Computer …, 2024 - Springer
Learning-outcome prediction (LOP) is a longstanding and critical problem in educational
routes. Many studies have contributed to developing effective models while often suffering …
routes. Many studies have contributed to developing effective models while often suffering …
Self-paced graph memory network for student GPA prediction and abnormal student detection
Student learning performance prediction (SLPP) is a crucial step in high school education.
However, traditional methods fail to consider abnormal students. In this study, we organized …
However, traditional methods fail to consider abnormal students. In this study, we organized …
Research on Abnormal Behavior Prediction by Integrating Multiple Indexes of Student Behavior and Text Information in Big Data Environment
With the wide application of information technologies such as big data, the Internet of
Things, and cloud computing, college students have accumulated a large amount of …
Things, and cloud computing, college students have accumulated a large amount of …