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 …
Self-paced graph memory for learner GPA prediction and it's application in learner multiple evaluation
A scientific and rational evaluation of teaching is essential for personalized learning. In the
current teaching assessment model that solely relies on Grade Point Average (GPA) …
current teaching assessment model that solely relies on Grade Point Average (GPA) …
Multi-level contrastive graph learning for academic abnormality prediction
Y Ouyang, Y Wang, R Gao, Y Zeng, J Liu… - Neural Computing and …, 2024 - Springer
Abstract Academic Abnormality Prediction aims to predict whether students have academic
abnormalities through their historical academic scores. However, existing research methods …
abnormalities through their historical academic scores. However, existing research methods …
Study-GNN: a novel pipeline for student performance prediction based on multi-topology graph neural networks
M Li, X Wang, Y Wang, Y Chen, Y Chen - Sustainability, 2022 - mdpi.com
Student performance prediction has attracted increasing attention in the field of educational
data mining, or more broadly, intelligent education or “AI+ education”. Accurate performance …
data mining, or more broadly, intelligent education or “AI+ education”. Accurate performance …
Graph Neural Network for Senior High Student's Grade Prediction
Senior high school education (SHSE) forms a connecting link between the preceding junior
high school education and the following college education. Through SHSE, a student not …
high school education and the following college education. Through SHSE, a student not …
Aggregating time series and tabular data in deep learning model for university students' gpa prediction
Current approaches of university students' Grade Point Average (GPA) prediction rely on the
use of tabular data as input. Intuitively, adding historical GPA data can help to improve the …
use of tabular data as input. Intuitively, adding historical GPA data can help to improve the …
Graph-based exercise-and knowledge-aware learning network for student performance prediction
Predicting student performance is a fundamental task in Intelligent Tutoring Systems (ITSs),
by which we can learn about students' knowledge level and provide personalized teaching …
by which we can learn about students' knowledge level and provide personalized teaching …
Academic performance estimation with attention-based graph convolutional networks
Q Hu, H Rangwala - arXiv preprint arXiv:2001.00632, 2019 - arxiv.org
Student's academic performance prediction empowers educational technologies including
academic trajectory and degree planning, course recommender systems, early warning and …
academic trajectory and degree planning, course recommender systems, early warning and …
Graph-based Ensemble Machine Learning for Student Performance Prediction
Y Wang, A Ding, K Guan, S Wu, Y Du - arXiv preprint arXiv:2112.07893, 2021 - arxiv.org
Student performance prediction is a critical research problem to understand the students'
needs, present proper learning opportunities/resources, and develop the teaching quality …
needs, present proper learning opportunities/resources, and develop the teaching quality …
Predicting academic performance of students in Chinese-foreign cooperation in running schools with graph convolutional network
P Hai-tao, F Ming-qu, Z Hong-bin, Y Bi-zhen… - Neural Computing and …, 2021 - Springer
To improve students' performance effectively, many Chinese universities are establishing
systems to predict student's academic performance and sending student's academic early …
systems to predict student's academic performance and sending student's academic early …