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The paper aims to address the issue of low retention rates in MOOCs by introducing an innovative prediction model that provides the best (optimal) learning path for at-risk learners. For this purpose, learners at risk of dropping out are identified, and their courses are adapted to meet their needs and skills.
Oct 25, 2023
The paper aims toaddress the issue of low retention rates in MOOCs by introducing an innovative prediction modelthat provides the best (optimal) learning path ...
Return to Article Details Towards an Adaptive Learning Model using Optimal Learning Paths to Prevent MOOC Dropout Download Download PDF. Thumbnails Document ...
This document discusses an adaptive learning model to prevent dropout in MOOCs by providing optimal learning paths for students.
The two profiles obtained using the K-means with the course · Towards an Adaptive Learning Model using Optimal Learning Paths to Prevent MOOC Dropout. Article.
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Feb 8, 2022 · The idea is to build a system that takes into account the heterogeneity of learners profifiles and offers each learner a path adapted to their ...
Jun 10, 2024 · Moulay El Hassan Charaf : Towards an Adaptive Learning Model using Optimal Learning Paths to Prevent MOOC Dropout. Int. J. Eng. Pedagog. 13 ...
To this end, we suggest using the PSO method ”Particle Swarm Optimization” in order to construct the optimal choices of learning paths in the system.
An Innovative Approach to Prevent Learners' Dropout from MOOCs using Optimal Personalized Learning Paths: An Online Learning Case Study.
2018. TLDR. This study focuses on the problem of dropouts in MOOCs and how to reduce the phenomenon by adapting learning according to criteria that enhance MOOC ...
Missing: Optimal Prevent