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Predicting Student Dropout in Moodle by vv5456462 is a document available to read on EtoBox.

What is Predicting Student Dropout in Moodle about?

The document presents a predictive model for early identification of student dropout using data mining techniques such as classification, clustering, and association methods. It aims to analyze student profiles and behaviors to enhance educational management and reduce dropout rates, achieving a prediction accuracy of 93.9%. The model integrates various data sources to characterize at-risk students and identify underlying patterns influencing academic performance and retention.

Author
vv5456462
Language
EN

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