Explainable student performance prediction models: a systematic review
R Alamri, B Alharbi - IEEE Access, 2021 - ieeexplore.ieee.org
Successful prediction of student performance has significant impact to many stakeholders,
including students, teachers and educational institutes. In this domain, it is equally important …
including students, teachers and educational institutes. In this domain, it is equally important …
A survey of machine learning approaches for student dropout prediction in online courses
The recent diffusion of online education (both MOOCs and e-courses) has led to an
increased economic and scientific interest in e-learning environments. As widely …
increased economic and scientific interest in e-learning environments. As widely …
[HTML][HTML] The impacts of remote learning in secondary education during the pandemic in Brazil
The transition to remote learning in the context of coronavirus disease 2019 (COVID-19)
might have led to dramatic setbacks in education. Taking advantage of the fact that São …
might have led to dramatic setbacks in education. Taking advantage of the fact that São …
Interpretable deep learning for university dropout prediction
The early identification of college students at risk of dropout is of great interest and
importance all over the world, since the early leaving of higher education is associated with …
importance all over the world, since the early leaving of higher education is associated with …
Predicting dropout in higher education based on secondary school performance
M Nagy, R Molontay - 2018 IEEE 22nd international conference …, 2018 - ieeexplore.ieee.org
Predicting student performance, preventing failure and identifying the factors influencing
student dropout are issues that have attracted a great deal of research interest recently. In …
student dropout are issues that have attracted a great deal of research interest recently. In …
A survey of machine learning approaches and techniques for student dropout prediction
School dropout is absenteeism from school for no good reason for a continuous number of
days. Addressing this challenge requires a thorough understanding of the underlying issues …
days. Addressing this challenge requires a thorough understanding of the underlying issues …
Towards a students' dropout prediction model in higher education institutions using machine learning algorithms
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 …
programs has proven to be effective in many use cases. In an approach based on machine …
[HTML][HTML] Student dataset from Tecnologico de Monterrey in Mexico to predict dropout in higher education
J Alvarado-Uribe, P Mejía-Almada, AL Masetto Herrera… - Data, 2022 - mdpi.com
High dropout rates and delayed completion in higher education are associated with
considerable personal and social costs. In Latin America, 50% of students drop out, and only …
considerable personal and social costs. In Latin America, 50% of students drop out, and only …
Diagnosis of learner dropout based on learning styles for online distance learning
L Heidrich, JLV Barbosa, W Cambruzzi, SJ Rigo… - Telematics and …, 2018 - Elsevier
The amount of data generated by computer systems in Online Distance Learning (ODL)
contains rich information. One example of this information we define as the Learner …
contains rich information. One example of this information we define as the Learner …
The role of machine learning in identifying students at-risk and minimizing failure
Education is very important for students' future success. The performance of students can be
supported by the extra assignments and projects given by the instructors for students with …
supported by the extra assignments and projects given by the instructors for students with …