Educational data mining and learning analytics for 21st century higher education: A review and synthesis
The potential influence of data mining analytics on the students' learning processes and
outcomes has been realized in higher education. Hence, a comprehensive review of …
outcomes has been realized in higher education. Hence, a comprehensive review of …
Educational data mining: a review of the state of the art
Educational data mining (EDM) is an emerging interdisciplinary research area that deals
with the development of methods to explore data originating in an educational context. EDM …
with the development of methods to explore data originating in an educational context. EDM …
Participation-based student final performance prediction model through interpretable Genetic Programming: Integrating learning analytics, educational data mining …
Building a student performance prediction model that is both practical and understandable
for users is a challenging task fraught with confounding factors to collect and measure. Most …
for users is a challenging task fraught with confounding factors to collect and measure. Most …
Predicting students' GPA and developing intervention strategies based on self-regulatory learning behaviors
Predicting students' grades has emerged as a major area of investigation in education due
to the desire to identify the underlying factors that influence academic performance. Because …
to the desire to identify the underlying factors that influence academic performance. Because …
Using data mining on student behavior and cognitive style data for improving e-learning systems: a case study
In this research we applied classification models for prediction of students' performance, and
cluster models for grouping students based on their cognitive styles in e-learning …
cluster models for grouping students based on their cognitive styles in e-learning …
Learning styles assessment and theoretical origin in an E-learning scenario: a survey
L Jegatha Deborah, R Baskaran, A Kannan - Artificial Intelligence Review, 2014 - Springer
The performance of the learners in E-learning environments is greatly influenced by the
nature of the posted E-learning contents. In such a scenario, the performance of the learners …
nature of the posted E-learning contents. In such a scenario, the performance of the learners …
Personalized learning in a virtual hands-on lab platform for computer science education
This Innovate Practice full paper presents a cloud-based personalized learning lab platform.
Personalized learning is gaining popularity in online computer science education due to its …
Personalized learning is gaining popularity in online computer science education due to its …
Determining students' academic failure profile founded on data mining methods
VP Bresfelean, M Bresfelean, N Ghisoiu… - ITI 2008-30th …, 2008 - ieeexplore.ieee.org
Exams failure among university students has long fed a large number of debates, many
education experts seeking to comprehend and explicate it, and many statisticians have tried …
education experts seeking to comprehend and explicate it, and many statisticians have tried …
Predicting students' academic performances–A learning analytics approach using multiple linear regression
OD Oyerinde, PA Chia - 2017 - dspace.unijos.edu.ng
Learning Analytics is an area of Information Systems research that integrates data analytics
and data mining techniques with the aim of enhancing knowledge management and …
and data mining techniques with the aim of enhancing knowledge management and …
Proposed S-Algo+ data mining algorithm for web platforms course content and usage evaluation
I Kazanidis, S Valsamidis, E Gounopoulos… - Soft Computing, 2020 - Springer
This paper suggests a novel data mining algorithm for the evaluation of e-learning courses
from a Learning Management System. This new algorithm, which is called S-Algo+ …
from a Learning Management System. This new algorithm, which is called S-Algo+ …