Student achievement prediction using deep neural network from multi-source campus data
Finding students at high risk of poor academic performance as early as possible plays an
important role in improving education quality. To do so, most existing studies have used the …
important role in improving education quality. To do so, most existing studies have used the …
Dual path convolutional neural network for student performance prediction
Student performance prediction is of great importance to many educational domains, such
as academic early warning and personalized teaching, and has drawn numerous research …
as academic early warning and personalized teaching, and has drawn numerous research …
Student academic performance prediction using deep multi-source behavior sequential network
X Li, X Zhu, X Zhu, Y Ji, X Tang - … in Knowledge Discovery and Data Mining …, 2020 - Springer
Online education is becoming increasingly popular and often combined with traditional
place-based study to improve learning efficiency for university students. Since students have …
place-based study to improve learning efficiency for university students. Since students have …
Behavior-driven student performance prediction with tri-branch convolutional neural network
Student performance prediction aims to leverage student-related information to predict their
future academic outcomes, which may be beneficial to numerous educational applications …
future academic outcomes, which may be beneficial to numerous educational applications …
Student-performulator: student academic performance using hybrid deep neural network
Educational data generated through various platforms such as e-learning, e-admission
systems, and automated result management systems can be effectively processed through …
systems, and automated result management systems can be effectively processed through …
Predicting high-risk students using learning behavior
T Liu, C Wang, L Chang, T Gu - Mathematics, 2022 - mdpi.com
Over the past few years, the growing popularity of online education has enabled there to be
a large amount of students' learning behavior data stored, which brings great opportunities …
a large amount of students' learning behavior data stored, which brings great opportunities …
SEPN: a sequential engagement based academic performance prediction model
Students' performance prediction is a crucial task in today's online education. By predicting a
student's final grade in an academic examination, intervene can be applied in advance …
student's final grade in an academic examination, intervene can be applied in advance …
Student performance prediction with short-term sequential campus behaviors
X Wang, X Yu, L Guo, F Liu, L Xu - Information, 2020 - mdpi.com
As students' behaviors are important factors that can reflect their learning styles and living
habits on campus, extracting useful features of them plays a helpful role in understanding …
habits on campus, extracting useful features of them plays a helpful role in understanding …
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 …
Deep Learning for Predicting Students' Academic Performance
A Yunita, HB Santoso… - 2019 Fourth International …, 2019 - ieeexplore.ieee.org
The use of Deep Learning to predict what happens in the future becomes more popular
because of great availability of data. This study proposes the power of Deep Learning to …
because of great availability of data. This study proposes the power of Deep Learning to …