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Early Dropout Prediction in MOOCs by aida chefrour is a document available to read on EtoBox.
What is Early Dropout Prediction in MOOCs about?
The document discusses the development of an early dropout prediction system for at-risk scholars in Massive Open Online Courses (MOOCs) using deep learning algorithms. It highlights the high dropout rates in MOOCs and proposes a dropout prediction model that analyzes learning patterns to assist instructors in providing timely interventions. The research utilizes datasets from MITx and HarvardX to enhance prediction accuracy and improve student retention in online courses.
- Author
- aida chefrour
- Language
- EN