Towards IoT-Big Data architecture for future education
New technology, through the IoT, Big Data and AI ecosystem, is the foundation on which
tomorrow's solutions are created. Improved processes with better decision making are the …
tomorrow's solutions are created. Improved processes with better decision making are the …
Modelos predictivos de riesgo académico en carreras de computación con minería de datos educativos
EA Franco, REL Martínez… - Revista de Educación a …, 2021 - revistas.um.es
Los problemas de bajo rendimiento académico y rezago son recurrentes en instituciones
educativas de nivel superior, especialmente al inicio de los estudios universitarios. En el …
educativas de nivel superior, especialmente al inicio de los estudios universitarios. En el …
Contextualizing the current state of research on the use of machine learning for student performance prediction: A systematic literature review
Today, educational institutions produce large amounts of data with the deployment of
learning management systems. These large datasets provide an untapped potential to …
learning management systems. These large datasets provide an untapped potential to …
Analyzing navigational data and predicting student grades using support vector machine
Abstract The advent of Learning Management System (LMS) has unfolded a unique
opportunity to predict student grades well in advance which benefits both students and …
opportunity to predict student grades well in advance which benefits both students and …
Students' academic performance and engagement prediction in a virtual learning environment using random forest with data balancing
Virtual learning environment (VLE) is vital in the current age and is being extensively used
around the world for knowledge sharing. VLE is helping the distance-learning process …
around the world for knowledge sharing. VLE is helping the distance-learning process …
[HTML][HTML] A systematic literature review: Recent techniques of predicting STEM stream students
Nowadays, fewer students are choosing to enroll in STEM (science, technology,
engineering, and mathematics) fields. STEM students in schools and in higher educational …
engineering, and mathematics) fields. STEM students in schools and in higher educational …
Clustering-based knowledge graphs and entity-relation representation improves the detection of at risk students
The nature of education has been transformed by technological advances and online
learning platforms, providing educational institutions with more options than ever to thrive in …
learning platforms, providing educational institutions with more options than ever to thrive in …
machine learning in higher education: students' performance assessment considering online activity logs
G Latif, SE Abdelhamid, KS Fawagreh… - IEEE …, 2023 - ieeexplore.ieee.org
Machine learning in Education is receiving more attention from researchers as the number
of students at all levels globally is increasing. To ensure students' success in K-12 …
of students at all levels globally is increasing. To ensure students' success in K-12 …
Stacking and voting ensemble methods fusion to evaluate instructor performance in higher education
Abstract Machine learning has emerged as the most widely used tool in resolving
administrative and other educational-related problems like student dropout. Most of the …
administrative and other educational-related problems like student dropout. Most of the …
Fuzzy artificial intelligence—Based model proposal to forecast student performance and retention risk in engineering education: An alternative for handling with small …
A Bressane, M Spalding, D Zwirn, AIS Loureiro… - Sustainability, 2022 - mdpi.com
Understanding the key factors that play an important role in students' performance can assist
improvements in the teaching-learning process. As an alternative, artificial intelligence (AI) …
improvements in the teaching-learning process. As an alternative, artificial intelligence (AI) …