Student retention using educational data mining and predictive analytics: a systematic literature review
Student retention is an essential measurement metric in education, indicated by retention
rates, which are accumulated as students re-enroll from one academic year to the next. High …
rates, which are accumulated as students re-enroll from one academic year to the next. High …
Prediction of student academic performance using a hybrid 2D CNN model
Opportunities to apply data mining techniques to analyze educational data and improve
learning are increasing. A multitude of data are being produced by institutional technology, e …
learning are increasing. A multitude of data are being produced by institutional technology, e …
Predicting Students' Performance Using Machine Learning Algorithms: A Review
SO Oppong - Asian Journal of Research in Computer …, 2023 - eprints.go2submission.com
Educational Data Mining is a discipline focused on developing ways for studying the unique
and increasingly large-scale data generated by educational settings and applying those …
and increasingly large-scale data generated by educational settings and applying those …
Early detection of students at risk of poor performance in Rwanda higher education using machine learning techniques
The prediction of student performance is one of the major issues in many higher education
institutions throughout the world. This issue is lately detected due to the lack of a proper …
institutions throughout the world. This issue is lately detected due to the lack of a proper …
Transforming educational insights: Strategic integration of federated learning for enhanced prediction of student learning outcomes
Numerous educational institutions utilize data mining techniques to manage student
records, particularly those related to academic achievements, which are essential in …
records, particularly those related to academic achievements, which are essential in …
Machine learning and deep learning-based students' grade prediction
Predicting student performance in a curriculum or program offers the prospect of improving
academic outcomes. By using effective performance prediction methods, instructional …
academic outcomes. By using effective performance prediction methods, instructional …
Prediction of students' performance with artificial neural network using demographic traits
AJ Kehinde, AE Adeniyi, RO Ogundokun… - Recent Innovations in …, 2022 - Springer
Many researchers have studied student academic performance in supervised and
unsupervised learning using numerous data mining techniques. Neural networks often need …
unsupervised learning using numerous data mining techniques. Neural networks often need …
Teaching and learning tools for introductory programming in university courses
J Figueiredo, F García-Peñalvo - … International Symposium on …, 2021 - ieeexplore.ieee.org
Difficulties in teaching and learning introductory programming have been studied over the
years. The students' difficulties lead to failure, lack of motivation, and abandonment of …
years. The students' difficulties lead to failure, lack of motivation, and abandonment of …
A predictive analytics model for students grade prediction by supervised machine learning
Research on predictive analytics has increasingly evolved due to its impact on providing
valuable and intuitive feedback that could potentially assist educators in improving student …
valuable and intuitive feedback that could potentially assist educators in improving student …
Comprehensive evaluations of student performance estimation via machine learning
Success in student learning is the primary aim of the educational system. Artificial
intelligence utilizes data and machine learning to achieve excellence in student learning. In …
intelligence utilizes data and machine learning to achieve excellence in student learning. In …