Educational data mining and learning analytics for 21st century higher education: A review and synthesis

H Aldowah, H Al-Samarraie, WM Fauzy - Telematics and Informatics, 2019 - Elsevier
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 …

A review on predicting student's performance using data mining techniques

AM Shahiri, W Husain - Procedia Computer Science, 2015 - Elsevier
Predicting students performance becomes more challenging due to the large volume of data
in educational databases. Currently in Malaysia, the lack of existing system to analyze and …

An artificial intelligence approach to monitor student performance and devise preventive measures

I Khan, AR Ahmad, N Jabeur, MN Mahdi - Smart Learning Environments, 2021 - Springer
A major problem an instructor experiences is the systematic monitoring of students'
academic progress in a course. The moment the students, with unsatisfactory academic …

[PDF][PDF] Comparison of supervised and unsupervised learning algorithms for pattern classification

R Sathya, A Abraham - International Journal of Advanced Research in …, 2013 - Citeseer
This paper presents a comparative account of unsupervised and supervised learning
models and their pattern classification evaluations as applied to the higher education …

Educational data mining: a review of the state of the art

C Romero, S Ventura - … on Systems, Man, and Cybernetics, Part …, 2010 - ieeexplore.ieee.org
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 …

Educational data mining techniques for student performance prediction: method review and comparison analysis

Y Zhang, Y Yun, R An, J Cui, H Dai… - Frontiers in psychology, 2021 - frontiersin.org
Student performance prediction (SPP) aims to evaluate the grade that a student will reach
before enrolling in a course or taking an exam. This prediction problem is a kernel task …

Artificial neural network analysis of the academic performance of students in virtual learning environments

A Rivas, A Gonzalez-Briones, G Hernandez, J Prieto… - Neurocomputing, 2021 - Elsevier
Educational institutions continually strive to improve the services they offer, their aim is to
have the best possible teaching staff, increase the quality of teaching and the academic …

Predicting students' academic performance by using educational big data and learning analytics: evaluation of classification methods and learning logs

AYQ Huang, OHT Lu, JCH Huang, CJ Yin… - Interactive Learning …, 2020 - Taylor & Francis
In order to enhance the experience of learning, many educators applied learning analytics in
a classroom, the major principle of learning analytics is targeting at-risk student and given …

Improving accuracy of students' final grade prediction model using optimal equal width binning and synthetic minority over-sampling technique

ST Jishan, RI Rashu, N Haque, RM Rahman - Decision Analytics, 2015 - Springer
There is a perpetual elevation in demand for higher education in the last decade all over the
world; therefore, the need for improving the education system is imminent. Educational data …

Increased digital resource consumption in higher educational institutions and the artificial intelligence role in informing decisions related to student performance

A Jokhan, AA Chand, V Singh, KA Mamun - Sustainability, 2022 - mdpi.com
As education is an essential enabler in achieving Sustainable Development Goals (SDGs), it
should “ensure inclusive, equitable quality education, and promote lifelong learning …