Predicting student success in MOOCs: a comprehensive analysis using machine learning models.

ABSTRACT:

Background

This study was motivated by the increasing popularity of Massive Open Online Courses (MOOCs) and the challenges they face, such as high dropout and failure rates. The existing knowledge primarily focused on predicting student dropout, but this study aimed to go beyond that by predicting both student dropout and course results. By using machine learning models and analyzing various data sources, the study sought to improve our understanding of factors influencing student success in MOOCs.

Objectives

The primary aim of this research was to develop accurate predictions of students' course outcomes in MOOCs, specifically whether they would pass or fail. Unlike previous studies, this study took into account demographic, assessment, and student interaction data to provi

SUBMITTER: Althibyani HA 

PROVIDER: S-EPMC11639146 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature