Deep Learning Model to Predict Students Retention Using BLSTM and CRF

Deep Learning Model to Predict Students Retention Using BLSTM and CRF

There is an increasing awareness that predictive analytics helps universities to evaluate students’ performances. Big data analytics, such as student demographic datasets, can provide insight that helps to support academic success and completion rates. For example, learning analytics is a...

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Bibliographic Details
Main Authors: Diaa Uliyan, Abdulaziz Salamah Aljaloud, Adel Alkhalil, Hanan Salem Al Amer, Magdy Abd Elrhman Abdallah Mohamed, Azizah Fhad Mohammed Alogali
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Student retention
data analytics
bidirectional long short term
condition random field
deep learning
Online Access:https://ieeexplore.ieee.org/document/9555608/

Internet

https://ieeexplore.ieee.org/document/9555608/

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