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

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 Environ...

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Autores principales: Cerezo, Rebeca, Esteban, María, Sánchez-Santillán, Miguel, Núñez, José C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5573842/
https://www.ncbi.nlm.nih.gov/pubmed/28883801
http://dx.doi.org/10.3389/fpsyg.2017.01403
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author Cerezo, Rebeca
Esteban, María
Sánchez-Santillán, Miguel
Núñez, José C.
author_facet Cerezo, Rebeca
Esteban, María
Sánchez-Santillán, Miguel
Núñez, José C.
author_sort Cerezo, Rebeca
collection PubMed
description 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. Materials and Methods: A sample of 140 undergraduate students participated in a blended learning experience implemented in a Moodle (Modular Object Oriented Developmental Learning Environment) 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 0.8 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. Conclusion: 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.
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spelling pubmed-55738422017-09-07 Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle Cerezo, Rebeca Esteban, María Sánchez-Santillán, Miguel Núñez, José C. Front Psychol Psychology 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. Materials and Methods: A sample of 140 undergraduate students participated in a blended learning experience implemented in a Moodle (Modular Object Oriented Developmental Learning Environment) 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 0.8 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. Conclusion: 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. Frontiers Media S.A. 2017-08-24 /pmc/articles/PMC5573842/ /pubmed/28883801 http://dx.doi.org/10.3389/fpsyg.2017.01403 Text en Copyright © 2017 Cerezo, Esteban, Sánchez-Santillán and Núñez. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Cerezo, Rebeca
Esteban, María
Sánchez-Santillán, Miguel
Núñez, José C.
Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle
title Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle
title_full Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle
title_fullStr Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle
title_full_unstemmed Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle
title_short Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle
title_sort procrastinating behavior in computer-based learning environments to predict performance: a case study in moodle
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5573842/
https://www.ncbi.nlm.nih.gov/pubmed/28883801
http://dx.doi.org/10.3389/fpsyg.2017.01403
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