State of the art and practice in AI in education
Abstract Recent developments in Artificial Intelligence (AI) have generated great
expectations for the future impact of AI in education and learning (AIED). Often these …
expectations for the future impact of AI in education and learning (AIED). Often these …
Student performance analysis and prediction in classroom learning: A review of educational data mining studies
Student performance modelling is one of the challenging and popular research topics in
educational data mining (EDM). Multiple factors influence the performance in non-linear …
educational data mining (EDM). Multiple factors influence the performance in non-linear …
Enhancing prediction of student success: Automated machine learning approach
H Zeineddine, U Braendle, A Farah - Computers & Electrical Engineering, 2021 - Elsevier
Students' success has recently become a primary strategic objective for most institutions of
higher education. With budget cuts and increasing operational costs, academic institutions …
higher education. With budget cuts and increasing operational costs, academic institutions …
Using data mining techniques to predict student performance to support decision making in university admission systems
HA Mengash - Ieee Access, 2020 - ieeexplore.ieee.org
An admissions system based on valid and reliable admissions criteria is very important to
select candidates likely to perform well academically at institutions of higher education. This …
select candidates likely to perform well academically at institutions of higher education. This …
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 …
Multiclass prediction model for student grade prediction using machine learning
Today, predictive analytics applications became an urgent desire in higher educational
institutions. Predictive analytics used advanced analytics that encompasses machine …
institutions. Predictive analytics used advanced analytics that encompasses machine …
Predicting student dropout in subscription-based online learning environments: The beneficial impact of the logit leaf model
Online learning has been adopted rapidly by educational institutions and organizations.
Despite its many advantages, including 24/7 access, high flexibility, rich content, and low …
Despite its many advantages, including 24/7 access, high flexibility, rich content, and low …
Classification technique and its combination with clustering and association rule mining in educational data mining—A survey
SM Dol, PM Jawandhiya - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Educational data mining (EDM) is the application of data mining in the educational field.
EDM is used to classify, analyze, and predict the students' academic performance, and …
EDM is used to classify, analyze, and predict the students' academic performance, and …
Big educational data & analytics: Survey, architecture and challenges
KLM Ang, FL Ge, KP Seng - IEEE access, 2020 - ieeexplore.ieee.org
The proliferation of mobile devices and the rapid development of information and
communication technologies (ICT) have seen increasingly large volume and variety of data …
communication technologies (ICT) have seen increasingly large volume and variety of data …
[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 …