Predicting academic success in higher education: literature review and best practices

E Alyahyan, D Düştegör - … Journal of Educational Technology in Higher …, 2020 - Springer
Student success plays a vital role in educational institutions, as it is often used as a metric for
the institution's performance. Early detection of students at risk, along with preventive …

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 …

Precision education with statistical learning and deep learning: a case study in Taiwan

SC Tsai, CH Chen, YT Shiao, JS Ciou… - International Journal of …, 2020 - Springer
The low birth rate in Taiwan has led to a severe challenge for many universities to enroll a
sufficient number of students. Consequently, a large number of students have been admitted …

Factors influencing dropout students in higher education

Nurmalitasari, Z Awang Long… - Education Research …, 2023 - Wiley Online Library
Dropout students are a severe problem in higher education (HE) in many countries. Student
dropout has a tremendous negative impact not only on individuals but also on universities …

Analysis of enrollment criteria in secondary schools using machine learning and data mining approach

Z Abideen, T Mazhar, A Razzaq, I Haq, I Ullah… - Electronics, 2023 - mdpi.com
Out-of-school children (OSC) surveys are conducted annually throughout Pakistan, and the
results show that the literacy rate is increasing gradually, but not at the desired speed …

A neuro-fuzzy model for predicting and analyzing student graduation performance in computing programs

R Mehdi, M Nachouki - Education and Information Technologies, 2023 - Springer
Predicting student's successful completion of academic programs and the features that
influence their performance can have a significant effect on improving students' completion …

University dropout prediction through educational data mining techniques: A systematic review

F Agrusti, G Bonavolontà, M Mezzini - Journal of e-learning and knowledge …, 2019 - je-lks.org
The dropout rates in the European countries is one of the major issues to be faced in a near
future as stated in the Europe 2020 strategy. In 2017, an average of 10.6% of young people …

Implementation of data mining for drop-out prediction using random forest method

M Utari, B Warsito… - 2020 8th International …, 2020 - ieeexplore.ieee.org
Accreditation is one of the quality measurements for a University. Some elements of these
measurements are students and graduate students. Prevention of students to drop out is a …

Cross-cultural comparisons of the factors influencing the high reading achievement in Turkey and China: Evidence from PISA 2018

S Kılıç Depren, Ö Depren - The Asia-Pacific Education Researcher, 2022 - Springer
The motto “if you can't measure it, you can't manage it” is the basic idea of innovation in
every area of business life. In education, governments get involved in many studies such as …

Data Visualization in Data Science

SMN Sakib - 2022 - cambridge.org
A lot of the important theoretical and practical issues that need to be addressed when
developing data visualizations have been covered in the chapters that precede them. I also …