Analyzing and predicting students' performance by means of machine learning: A review
JL Rastrollo-Guerrero, JA Gómez-Pulido… - Applied sciences, 2020 - mdpi.com
Predicting students' performance is one of the most important topics for learning contexts
such as schools and universities, since it helps to design effective mechanisms that improve …
such as schools and universities, since it helps to design effective mechanisms that improve …
The role of usability on e-learning user interactions and satisfaction: a literature review
Purpose The purpose of this study is to review the effect of usability factors on e-learning
user relationships, namely, student–student interaction (SSI), student–instructor interaction …
user relationships, namely, student–student interaction (SSI), student–instructor interaction …
A deep learning approach to detecting engagement of online learners
Online learning environments enable learning for the online learners. The motivational
factors, like engagement, play an important role in effective learning. However, the learning …
factors, like engagement, play an important role in effective learning. However, the learning …
Diagnosis of learner dropout based on learning styles for online distance learning
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 …
Identifying at-risk students in online learning by analysing learning behaviour: A systematic review
As the development of online learning is growing, a large amount of log data on student
activity is available and accumulated in Learning Management Systems (LMS). This …
activity is available and accumulated in Learning Management Systems (LMS). This …
Prediction of Students’ Performance in E-Learning Environment Using Random Forest
The need for advancement in e-learning technology causes educational data to become
very huge and increase rapidly. The data is generated on daily basis as a result of …
very huge and increase rapidly. The data is generated on daily basis as a result of …
[PDF][PDF] Neural networks to predict dropout at the universities
The university student's dropout is a problem that affects the governments, institutions and
students. It has negative effects on the high expenditure in the administrative and academic …
students. It has negative effects on the high expenditure in the administrative and academic …
Discovering learning behavior patterns to predict dropout in MOOC
B Hong, Z Wei, Y Yang - 2017 12th International Conference on …, 2017 - ieeexplore.ieee.org
High dropout rate of MOOC is criticized while a dramatically increasing number of learners
are appealed to these online learning platforms. Various works have been done on analysis …
are appealed to these online learning platforms. Various works have been done on analysis …
A Systematic Review on Predicting the Performance of Students in Higher Education in Offline Mode Using Machine Learning Techniques
For scholarly organizations, students' academic performance (AP) computes student
achievements in different academic subjects. Therefore, a systematic literature review based …
achievements in different academic subjects. Therefore, a systematic literature review based …
A Survey of Machine Learning for Assessing and Estimating Student Performance
A Kaur, M Bhatia - Proceedings of International Conference on Recent …, 2023 - Springer
Educational data mining (EDM) contributes cutting-edge methodologies, strategies, and
applications to the advancement of the education system, hence playing a crucial part in its …
applications to the advancement of the education system, hence playing a crucial part in its …