A scalable machine learning-based ensemble approach to enhance the prediction accuracy for identifying students at-risk

S Verma, RK Yadav, K Kholiya - International Journal of …, 2022 - search.proquest.com
Among the educational data mining problems, the early prediction of the students' academic
performance is the most important task, so that timely and requisite support may be provided …

Predicting students performance using supervised machine learning based on imbalanced dataset and wrapper feature selection

S Alija, E Beqiri, AS Gaafar, AK Hamoud - Informatica, 2023 - informatica.si
For learning environments like schools and colleges, predicting the performance of students
is one of the most crucial topics since it aids in the creation of practical systems that, among …

Comparing different resampling methods in predicting students' performance using machine learning techniques

R Ghorbani, R Ghousi - IEEE access, 2020 - ieeexplore.ieee.org
In today's world, due to the advancement of technology, predicting the students' performance
is among the most beneficial and essential research topics. Data Mining is extremely helpful …

Even-odd crossover: a new crossover operator for improving the accuracy of students' performance prediction

SA Shams, AH Omar, AS Desuky… - Bulletin of Electrical …, 2022 - beei.org
Prediction using machine learning has evolved due to its impact on providing valuable and
intuitive feedback. It has covered a wide range of areas for predicting student'performance …

[PDF][PDF] Managing student performance: A predictive analytics using imbalanced data

U Ashfaq, PM Booma, R Mafas - International Journal of Recent …, 2020 - researchgate.net
Big data has revolutionized every field of life, which accumulates human learning as well.
The field of education has progressed in past couple of decades, and addition to that, rapid …

Efficient hyperparameter tuning for predicting student performance with Bayesian optimization

S Albahli - Multimedia Tools and Applications, 2024 - Springer
Higher education is crucial as it introduces students to various fields and then guides them
to the next steps. Student's academic performance is critical and could lead to failure if it is …

Improve imbalanced multiclass classification based on modified SMOTE and feature selection for student grade prediction

S Dianah, A Selamat, O Krejcar - … in Artificial Life, AI, and Machine …, 2022 - igi-global.com
In higher education institutions (HEI), the ability to predict student grades as an early
warning system is one of the important areas that gained attention to improve educational …

Ensemble Model for Educational Data Mining Based on Synthetic Minority Oversampling Technique

R Manoharan, MS Stalin, GB Loganathan - 2023 - researchsquare.com
Data mining in the classroom is a well-known field that involves data mining concepts,
statistical analysis, and machine learning concepts, all of which are applied to educational …

[PDF][PDF] Improving SVM classification performance on unbalanced student graduation time data using SMOTE

A Anggrawan, H Hairani, C Satria - International Journal of …, 2023 - researchgate.net
 Abstract—Student graduation accuracy is one of the indicators of the success of higher
education institutions in carrying out the teaching and learning process and as a component …

The role of machine learning in identifying students at-risk and minimizing failure

RZ Pek, ST Özyer, T Elhage, T Özyer, R Alhajj - IEEE Access, 2022 - ieeexplore.ieee.org
Education is very important for students' future success. The performance of students can be
supported by the extra assignments and projects given by the instructors for students with …