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

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Summary
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Academic procrastination negatively impacts student performance in online learning. This study used data mining to confirm this link in blended learning environments, highlighting time management

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Area of Science:

  • Educational Technology
  • Data Mining in Education
  • Student Performance Analysis

Background:

  • Traditional research links academic procrastination to negative academic achievement in classroom settings.
  • Limited research exists on procrastination's effects within Computer-Based Learning Environments (CBLEs).

Purpose of the Study:

  • To evaluate student behavior, specifically procrastination, in a blended learning program.
  • To analyze the relationship between procrastination and academic performance using Data Mining techniques.

Main Methods:

  • Utilized a sample of 140 undergraduate students in a Moodle-based blended learning program.
  • Selected interaction variables related to student achievement for analysis.
  • Applied association rules, a Data Mining technique, with accuracy >0.8 and presence in sub-samples as filtering criteria.

Main Results:

  • Confirmed a significant association between procrastination variables and student performance.
  • Highlighted the critical role of time management in online learning environments for academic success.

Conclusions:

  • The negative impact of procrastination on learning outcomes is evident in virtual learning settings.
  • Prevention and intervention strategies for procrastination in CBLEs require distinct approaches compared to traditional classrooms.