From unsuccessful to successful learning: profiling behavior patterns and student clusters in Massive Open Online Courses

The imbalance in student-teacher ratio and the diversity of student population pose challenges to MOOC's quality of instructor support. An understanding of student profiles, such as who they are and how they behave, is critical to improving personalized support of MOOC learning environments. Wh...

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Veröffentlicht in:Education and information technologies 2024-04, Vol.29 (5), p.5509-5540
Hauptverfasser: Shi, Hui, Zhou, Yihang, Dennen, Vanessa P., Hur, Jaesung
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creator Shi, Hui
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Hur, Jaesung
description The imbalance in student-teacher ratio and the diversity of student population pose challenges to MOOC's quality of instructor support. An understanding of student profiles, such as who they are and how they behave, is critical to improving personalized support of MOOC learning environments. While past studies have explored different types of student profiles, few have been done to investigate which student profiles lead to successful performance and what behavior patterns are exhibited by successful and unsuccessful performance groups. To address this research gap, we employed both bottom-up and top-down strategies, to gain useful insights into student learning in the context of MOOCs. From learning behavior records of 26,862 students in six MOOCs, we identified and validated three behavior attributes: effort regulation, self-assessment, and learner participation. Our results revealed that effort regulation emerged as the foremost important factor that positively contributes to students’ academic performance in MOOCs. Particularly, online persistence was the strongest positive predictor impacting student success. Based on the behavior attributes ascertained, we demonstrated five student sub-profiles with different behavior patterns: Persistence Achievers and Social Collaborators in the successful group; Dabblers, Disengagers, and Slackers in the unsuccessful group. Our analysis revealed that successful performers engaged with the course in quite different ways. We also investigated how effort regulation differed significantly between successful and unsuccessful performers. Unexpectedly, we also noticed that Persistence Achievers, despite their success, exhibited a high degree of procrastination. This work offers novel insights into instructional interventions for supporting MOOC learning.
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subjects Behavior Patterns
Computer Appl. in Social and Behavioral Sciences
Computer Science
Computers and Education
Distance learning
Education
Educational Technology
Information Systems Applications (incl.Internet)
MOOCs
Online instruction
Persistence
Profiles
Psychological Patterns
Student behavior
Student Diversity
Teacher Student Ratio
User Interfaces and Human Computer Interaction
title From unsuccessful to successful learning: profiling behavior patterns and student clusters in Massive Open Online Courses
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