Educational data mining: a review of the state of the art
Educational data mining (EDM) is an emerging interdisciplinary research area that deals
with the development of methods to explore data originating in an educational context. EDM …
with the development of methods to explore data originating in an educational context. EDM …
Educational data mining to predict students' academic performance: A survey study
Educational data mining is an emerging interdisciplinary research area involving both
education and informatics. It has become an imperative research area due to many …
education and informatics. It has become an imperative research area due to many …
Participation-based student final performance prediction model through interpretable Genetic Programming: Integrating learning analytics, educational data mining …
Building a student performance prediction model that is both practical and understandable
for users is a challenging task fraught with confounding factors to collect and measure. Most …
for users is a challenging task fraught with confounding factors to collect and measure. Most …
[PDF][PDF] Modeling and predicting students' academic performance using data mining techniques
The main objective of this study is to apply data mining techniques to predict and analyze
students' academic performance based on their academic record and forum participation …
students' academic performance based on their academic record and forum participation …
Developing early warning systems to predict students' online learning performance
An early warning system can help to identify at-risk students, or predict student learning
performance by analyzing learning portfolios recorded in a learning management system …
performance by analyzing learning portfolios recorded in a learning management system …
[PDF][PDF] Data mining algorithms to classify students
In this paper we compare different data mining methods and techniques for classifying
students based on their Moodle usage data and the final marks obtained in their respective …
students based on their Moodle usage data and the final marks obtained in their respective …
Web usage mining for predicting final marks of students that use Moodle courses
This paper shows how web usage mining can be applied in e‐learning systems in order to
predict the marks that university students will obtain in the final exam of a course. We have …
predict the marks that university students will obtain in the final exam of a course. We have …
An early feedback prediction system for learners at-risk within a first-year higher education course
D Baneres, ME Rodríguez-Gonzalez… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Identifying at-risk students as soon as possible is a challenge in educational institutions.
Decreasing the time lag between identification and real at-risk state may significantly reduce …
Decreasing the time lag between identification and real at-risk state may significantly reduce …
An early warning system to detect at-risk students in online higher education
Artificial intelligence has impacted education in recent years. Datafication of education has
allowed developing automated methods to detect patterns in extensive collections of …
allowed developing automated methods to detect patterns in extensive collections of …
Increased digital resource consumption in higher educational institutions and the artificial intelligence role in informing decisions related to student performance
As education is an essential enabler in achieving Sustainable Development Goals (SDGs), it
should “ensure inclusive, equitable quality education, and promote lifelong learning …
should “ensure inclusive, equitable quality education, and promote lifelong learning …