How does learning analytics contribute to prevent students' dropout in higher education: A systematic literature review

CF de Oliveira, SR Sobral, MJ Ferreira… - Big Data and Cognitive …, 2021‏ - mdpi.com
Retention and dropout of higher education students is a subject that must be analysed
carefully. Learning analytics can be used to help prevent failure cases. The purpose of this …

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 …

[HTML][HTML] Uplift Modeling for preventing student dropout in higher education

D Olaya, J Vásquez, S Maldonado, J Miranda… - Decision support …, 2020‏ - Elsevier
Uplift modeling is an approach for estimating the incremental effect of an action or treatment
at the individual level. It has gained attention in the marketing and analytics communities …

[PDF][PDF] Towards a students' dropout prediction model in higher education institutions using machine learning algorithms

K Oqaidi, S Aouhassi, K Mansouri - International Journal of …, 2022‏ - learntechlib.org
Using machine learning to predict students' dropout in higher education institutions and
programs has proven to be effective in many use cases. In an approach based on machine …

Integrating LA and EDM for improving students Success in higher Education using FCN algorithm

M Hooda, C Rana, O Dahiya, JP Shet… - Mathematical …, 2022‏ - Wiley Online Library
EDM and LA are two fields that study how to use facts to get more academic learning and
enhance the students' entire performance. Both areas are concerned with a broad range of …

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 …

[HTML][HTML] Factors and conditions that affect the goodness of machine learning models for predicting the success of learning

L Bognár, T Fauszt - Computers and Education: Artificial Intelligence, 2022‏ - Elsevier
The process for building effective machine learning models that predict the learning success
of university students, the competences of the actors involved in model building, and the …

Classification academic data using machine learning for decision making process

E Haerani, F Syafria, F Lestari… - Journal of Applied …, 2023‏ - repository.uin-suska.ac.id
One of the qualities of higher education is determined by the success rate of student
learning. Assessment of student success rates is based on students' graduation on time. The …

A machine learning approach to Predict the Engineering Students at risk of dropout and factors behind: Bangladesh Perspective

SA Ahmed, SI Khan - 2019 10th international conference on …, 2019‏ - ieeexplore.ieee.org
Dropout rate in Bangladeshi universities getting high day by day. Especially in engineering
subjects. Massive number of students taking various engineering subjects for their under …