A systematic literature review of student'performance prediction using machine learning techniques
Educational Data Mining plays a critical role in advancing the learning environment by
contributing state-of-the-art methods, techniques, and applications. The recent development …
contributing state-of-the-art methods, techniques, and applications. The recent development …
Early prediction of student learning performance through data mining: A systematic review
J López Zambrano, JA Lara Torralbo… - …, 2021 - redined.educacion.gob.es
Abstract Resumen Background: Early prediction of students' learning performance using
data mining techniques is an important topic these days. The purpose of this literature …
data mining techniques is an important topic these days. The purpose of this literature …
Student Engagement Predictions in an e‐Learning System and Their Impact on Student Course Assessment Scores
Several challenges are associated with e‐learning systems, the most significant of which is
the lack of student motivation in various course activities and for various course materials. In …
the lack of student motivation in various course activities and for various course materials. In …
Predicting at-risk students at different percentages of course length for early intervention using machine learning models
Online learning platforms such as Massive Open Online Course (MOOC), Virtual Learning
Environments (VLEs), and Learning Management Systems (LMS) facilitate thousands or …
Environments (VLEs), and Learning Management Systems (LMS) facilitate thousands or …
Applying learning analytics for the early prediction of Students' academic performance in blended learning
Blended learning combines online digital resources with traditional classroom activities and
enables students to attain higher learning performance through well-defined interactive …
enables students to attain higher learning performance through well-defined interactive …
AI in education: Learner choice and fundamental rights
B Berendt, A Littlejohn, M Blakemore - Learning, Media and …, 2020 - Taylor & Francis
This article examines benefits and risks of Artificial Intelligence (AI) in education in relation to
fundamental human rights. The article is based on an EU scoping study [Berendt, B., A …
fundamental human rights. The article is based on an EU scoping study [Berendt, B., A …
[HTML][HTML] Models for early prediction of at-risk students in a course using standards-based grading
F Marbouti, HA Diefes-Dux, K Madhavan - Computers & Education, 2016 - Elsevier
Using predictive modeling methods, it is possible to identify at-risk students early and inform
both the instructors and the students. While some universities have started to use standards …
both the instructors and the students. While some universities have started to use standards …
The role of demographics in online learning; A decision tree based approach
Research has shown online learners' performance to have a strong association with their
demographic characteristics, such as regional belonging, socio-economic standing …
demographic characteristics, such as regional belonging, socio-economic standing …
Using machine learning to predict student difficulties from learning session data
The student's performance prediction is an important research topic because it can help
teachers prevent students from dropping out before final exams and identify students that …
teachers prevent students from dropping out before final exams and identify students that …
A large-scale implementation of predictive learning analytics in higher education: The teachers' role and perspective
By collecting longitudinal learner and learning data from a range of resources, predictive
learning analytics (PLA) are used to identify learners who may not complete a course …
learning analytics (PLA) are used to identify learners who may not complete a course …