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Oct 22, 2024 · Due to high attrition rates, the problem of student dropouts became of immense importance for course designers, and course makers. In this paper ...
We investigated how early dropout can be predicted, and why dropouts occur. To answer the first question, we created models for eight different time frames, ...
Jul 23, 2024 · The model can correctly classify 89% of the students (as enrolled and dropped) and accurately identify 98.1% dropouts.
Feb 8, 2024 · This paper presents a novel method for predicting at-risk learners based on their performance-based behavior in e-learning environments.
Missing: Predicting online
Predicting Student Dropout in Online Learning Platforms Using Deep ...
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In this paper, a predictive model is built to analyze the problems subject to higher dropout rates of students.
The dropout models are produced with logistic regression as an algorithm because it provides interpretable models and because it is very suitable to work with ...
This study seeks to improve student dropout predictions, with three main contributions. First, it benchmarks a recently proposed logit leaf model (LLM) ...
Mar 12, 2024 · This systematic literature review presents a comprehensive analysis of the literature to uncover the reasons behind dropout rates in virtual learning ...
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Besides, an increase in rates of dropout will unavoidably lead to reduce graduation rates, which may have a negative effect on social online learning ...
Oct 22, 2024 · While online education keeps expanding, web-based institutions face high dropout rate, pushing costs up and making a negative social impact.