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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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2017-08-01
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| Series: | Frontiers in Psychology |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/article/10.3389/fpsyg.2017.01403/full |
| _version_ | 1818982931272564736 |
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| author | Rebeca Cerezo María Esteban Miguel Sánchez-Santillán José C. Núñez |
| author_facet | Rebeca Cerezo María Esteban Miguel Sánchez-Santillán José C. Núñez |
| author_sort | Rebeca Cerezo |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-20T17:55:03Z |
| format | Article |
| id | doaj.art-5fbffbe1aa43419f8ae1946ec1f866c4 |
| institution | Directory Open Access Journal |
| issn | 1664-1078 |
| language | English |
| last_indexed | 2024-12-20T17:55:03Z |
| publishDate | 2017-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychology |
| spelling | doaj.art-5fbffbe1aa43419f8ae1946ec1f866c42022-12-21T19:30:47ZengFrontiers Media S.A.Frontiers in Psychology1664-10782017-08-01810.3389/fpsyg.2017.01403273286Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in MoodleRebeca CerezoMaría EstebanMiguel Sánchez-SantillánJosé C. NúñezIntroduction: 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.http://journal.frontiersin.org/article/10.3389/fpsyg.2017.01403/fullprocrastinationCBLEslearning failureEducational Data Mining |
| spellingShingle | Rebeca Cerezo María Esteban Miguel Sánchez-Santillán José C. Núñez Procrastinating Behavior in Computer-Based Learning Environments to Predict Performance: A Case Study in Moodle Frontiers in Psychology procrastination CBLEs learning failure Educational Data Mining |
| 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 | procrastination CBLEs learning failure Educational Data Mining |
| url | http://journal.frontiersin.org/article/10.3389/fpsyg.2017.01403/full |
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