[HTML][HTML] Multi-Output Based Hybrid Integrated Models for Student Performance Prediction
H Xue, Y Niu - Applied Sciences, 2023 - mdpi.com
In higher education, student learning relies increasingly on autonomy. With the rise in
blended learning, both online and offline, students need to further improve their online …
blended learning, both online and offline, students need to further improve their online …
University Admissions Predictor Using Logistic Regression
Students applying for admissions to universities find it difficult to understand whether they
have good chances of getting admission in a university or not. Keeping this in focus, we …
have good chances of getting admission in a university or not. Keeping this in focus, we …
Early prediction of Student academic performance based on Machine Learning algorithms: A case study of bachelor's degree students in KSA
In the current educational landscape, where large amounts of data are being produced by
institutions, Educational Data Mining (EDM) emerges as a critical discipline that plays a …
institutions, Educational Data Mining (EDM) emerges as a critical discipline that plays a …
Student academic performance prediction using educational data mining
DK Arun, V Namratha, BV Ramyashree… - 2021 International …, 2021 - ieeexplore.ieee.org
The field of Educational Data Mining concentrates on prediction more often as compared to
generating exact results for future purpose. In order to keep track of the changes occurring in …
generating exact results for future purpose. In order to keep track of the changes occurring in …
Deep auto encoder based on a transient search capsule network for student performance prediction
Prediction of Student performance through a machine predicts a student's future success. It
can be considered an essential procedure to determine the students' academic excellence …
can be considered an essential procedure to determine the students' academic excellence …
[HTML][HTML] Analysis of machine learning strategies for prediction of passing undergraduate admission test
This article primarily focuses on understanding the reasons behind the failure of
undergraduate admission seekers using different machine learning (ML) strategies. An …
undergraduate admission seekers using different machine learning (ML) strategies. An …
Predicting university dropout by using convolutional neural networks
Based on current trends in graduation rates, 39% of today's young adults on average across
OECD (2014) countries are expected to complete tertiary-type A (university level) education …
OECD (2014) countries are expected to complete tertiary-type A (university level) education …
Predicting students academic performance using a hybrid of machine learning algorithms
R Ayienda, R Rimiru, W Cheruiyot - 2021 IEEE AFRICON, 2021 - ieeexplore.ieee.org
Educational data mining (EDM) has become a very interesting field of study in machine
learning (ML), since it has enabled searchers to mine knowledge from educational …
learning (ML), since it has enabled searchers to mine knowledge from educational …
Prediction of student's academic performance using feedforward neural network augmented with stochastic trainers
The academic performance of students is of great interest to tutors and decision-makers in
educational institutions. The extensive use of information technology systems in education …
educational institutions. The extensive use of information technology systems in education …
[PDF][PDF] Deep Neural Network Model for Identification of Predictive Variables and Evaluation of Student's Academic Performance.
Accepted: 21 October 2021 An important concern for students at all levels, from universities
to colleges to junior high and high school, is predicting academic achievement and …
to colleges to junior high and high school, is predicting academic achievement and …