Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle

Cerezo, Rebeca and Esteban, María and Sánchez-Santillán, Miguel and Núñez, José C. (2017) Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle. Frontiers in Psychology, 8.

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Introduction: Research about student performance has traditionally considered academic procrastination as a behavior that has negative effects on academic achievement. Although there is much evidence for this in class-based environments, there is a lack of research on Computer Based Learning Environments (CBLEs). Therefore, the purpose of this study is to evaluate student behavior in a blended learning program and specifically procrastination behavior in relation to performance through Data Mining techniques. Method: A sample of 140 undergraduate students participated in a blended learning experience implemented in a Moodle Management System. Relevant interaction variables were selected for the study, taking into account student achievement and analyzing data by means of association rules, a mining technique. The association rules were arrived at and filtered through two selection criteria: 1, rules must have an accuracy over .8 and 2, they must be present in both sub-samples. Results: The findings of our study highlight the influence of time management in online learning environments, particularly on academic achievement, as there is an association between procrastination variables and student performance. Conclusions: Negative impact of procrastination in learning outcomes has been observed again but in virtual learning environments where practical implications, prevention of, and intervention in, are different from class-based learning. These aspects are discussed to help resolve student difficulties at various ages.

Item Type: Article
Uncontrolled Keywords: CBLEs, Class Association Rules, educational data mining, Learning failure, performance, procrastination
Depositing User: Elizabeth Dalton
Date Deposited: 16 Dec 2019 23:40
Last Modified: 16 Dec 2019 23:40

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