Toward An Early Risk Alert In A Distance Learning Context

The high failure rate is a common issue among online institutions. Early Warning Systems (EWSs) are widely adopted as a solution to deal with this issue. However, these systems do not go beyond the early identification of failing learners. In this paper, we propose a new alert algorithm of an educat...

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Bibliographic Details
Published in2022 International Conference on Advanced Learning Technologies (ICALT) pp. 206 - 208
Main Authors Soussia, Amal Ben, Roussanaly, Azim, Boyer, Anne
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2022
Subjects
Alarm systems
alerts generation
Computer aided instruction
Early warning system
failure risk
k-12 learners
Prediction algorithms
prediction earliness
Predictive models
Stability analysis
Target tracking
temporal stability
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Summary:The high failure rate is a common issue among online institutions. Early Warning Systems (EWSs) are widely adopted as a solution to deal with this issue. However, these systems do not go beyond the early identification of failing learners. In this paper, we propose a new alert algorithm of an educational EWS for generating risk alerts at the earliest. This algorithm is based on a weekly prediction model that aims to generate early alerts. The regular tracking of prediction results enabled to propose measures for the right prediction earliness and the model's temporal stability. These measures prepare the last step of the algorithm which is the alerts generation according to a predefined rule. The objective of this rule is to target at-risk learners to improve their learning. For this aim, we used data of k-12 learners enrolled in an online physics-chemistry module.
ISSN:2161-377X
DOI:10.1109/ICALT55010.2022.00067