Application of machine learning in higher education to assess student academic performance, at-risk, and attrition: A meta-analysis of literature
Recently, machine learning (ML) has evolved and finds its application in higher education
(HE) for various data analysis. Studies have shown that such an emerging field in …
(HE) for various data analysis. Studies have shown that such an emerging field in …
A comparison of undersampling, oversampling, and SMOTE methods for dealing with imbalanced classification in educational data mining
Educational data mining is capable of producing useful data-driven applications (eg, early
warning systems in schools or the prediction of students' academic achievement) based on …
warning systems in schools or the prediction of students' academic achievement) based on …
Predicting student academic performance at higher education using data mining: A systematic review
Recently, educational institutions faced many challenges. One of these challenges is the
huge amount of educational data that can be used to discover new insights that have a …
huge amount of educational data that can be used to discover new insights that have a …
Educational data mining to predict students' academic performance: A survey study
Educational data mining is an emerging interdisciplinary research area involving both
education and informatics. It has become an imperative research area due to many …
education and informatics. It has become an imperative research area due to many …
An explainable model for identifying at-risk student at higher education
Nowadays, researchers from various fields have shown great interest in improving the
quality of learning in educational institutes in order to improve student achievement and …
quality of learning in educational institutes in order to improve student achievement and …
Use of data mining for the analysis of consumer purchase patterns with the fpgrowth algorithm on motor spare part sales transactions data
TAD Lael, DA Pramudito - IAIC Transactions on Sustainable …, 2023 - aptikom-journal.id
This study aims to analyze consumer purchasing patterns for motorcycle parts using data
mining methods and FP-Growth algorithms on motorcycle parts sales transaction data. This …
mining methods and FP-Growth algorithms on motorcycle parts sales transaction data. This …
[HTML][HTML] Perspectives on the challenges of generalizability, transparency and ethics in predictive learning analytics
A Mathrani, T Susnjak, G Ramaswami… - Computers and Education …, 2021 - Elsevier
Educational institutions need to formulate a well-established data-driven plan to get long-
term value from their learning analytics (LA) strategy. By tracking learners' digital traces and …
term value from their learning analytics (LA) strategy. By tracking learners' digital traces and …
An improved early student's academic performance prediction using deep learning
Nowadays due to technological revolution huge amount of data is generated in every fields
including education as well. Extracting the useful insights from consequential data is a very …
including education as well. Extracting the useful insights from consequential data is a very …
Predicting student academic performance using support vector machine and random forest
L H. Alamri, R S. Almuslim, M S. Alotibi… - Proceedings of the …, 2020 - dl.acm.org
The use of machine learning and data mining in the educational field to predict student
performance, known as educational data mining, which has always been an important study …
performance, known as educational data mining, which has always been an important study …
Educational data mining in the academic setting: employing the data produced by blended learning to ameliorate the learning process
Purpose The purpose of this paper is to introduce an interactive system that relies on the
educational data generated from the online Universities services to assess, correct and …
educational data generated from the online Universities services to assess, correct and …