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 …
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 …
Student performance prediction using technology of machine learning
In the given paper, the main focus of this report is education. Student performance prediction
is our main target. Various factors have been taken into account to create a model used for …
is our main target. Various factors have been taken into account to create a model used for …
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 …
[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 …
Factors affecting student's academic performance
WAIWA Razak, SNAK Akmal, NF Azizan… - … on Perceptive and …, 2021 - journals.iium.edu.my
The educational system measures students' performance using varied assessment methods
such as quizzes, tests, examinations and assignments. Academic performance along with …
such as quizzes, tests, examinations and assignments. Academic performance along with …
Machine learning based student academic performance prediction
MS Ram, V Srija, V Bhargav… - … Inventive Research in …, 2021 - ieeexplore.ieee.org
Every educational system organizational goal is to provide a good and fruitful knowledge to
the students. Now a days most of the educational institutions are spending most of their time …
the students. Now a days most of the educational institutions are spending most of their time …
Prediction of Students Programming Performance Using Naïve Bayesian and Decision Tree
M Sivasakthi, KRA Padmanabhan - Soft Computing for Security …, 2022 - Springer
Abstract Machine learning strategies are faster than ever in the field of education. Machine
learning aims to discover hidden information and students' performance in programming …
learning aims to discover hidden information and students' performance in programming …
Hybrid students' academic performance and dropout prediction models using recursive feature elimination technique
MA Alarape, AO Ameen, KS Adewole - Advances on Smart and Soft …, 2021 - Springer
Predicting students' academic performance (SAP) and dropout are crucial aspects of any
academic institution management. It enhances the close monitoring of students' academic …
academic institution management. It enhances the close monitoring of students' academic …
Literature Review for Educational Data Mining Systems—Fahad Bin Sultan University Case Study
AM Barakeh, MA Mezher, BA Alharbi - Artificial Intelligence-Augmented …, 2024 - Springer
The advancement of the learning environment is significantly facilitated by the critical role
played by Educational Data Mining through its contributions of state-of-the-art methods …
played by Educational Data Mining through its contributions of state-of-the-art methods …