Prediction of Students’ Academic Performance in the Programming Fundamentals Course Using Long Short-Term Memory Neural Networks

Prediction of Students’ Academic Performance in the Programming Fundamentals Course Using Long Short-Term Memory Neural Networks

In recent years, there has been evidence of a growing interest on the part of universities to know in advance the academic performance of their students and allow them to establish timely strategies to avoid desertion and failure. One of the biggest challenges to predicting student performance is pr...

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Bibliographic Details
Main Authors: Luis Vives, Ivan Cabezas, Juan Carlos Vives, Nilton German Reyes, Janet Aquino, Jose Bautista Condor, S. Francisco Segura Altamirano
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Educational data mining
generative adversarial networks
long-short term memory
synthetic minority over-sampling technique
Online Access:https://ieeexplore.ieee.org/document/10381724/

Internet

https://ieeexplore.ieee.org/document/10381724/

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