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Using social network analysis to understand online Problem-Based Learning and predict performance.

Mohammed Saqr1, Uno Fors1, Jalal Nouri1

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Summary
This summary is machine-generated.

Social network analysis (SNA) effectively predicts student performance in online learning. By analyzing interaction data, SNA identifies high-achieving students and allows for early intervention for those at risk of underperforming.

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Area of Science:

  • Educational Technology
  • Social Network Analysis
  • Learning Analytics

Background:

  • Online collaborative learning offers opportunities to enhance educational processes.
  • Social network analysis (SNA) provides tools to understand complex interactions within learning environments.
  • Identifying factors influencing student success in online settings is crucial for effective pedagogy.

Purpose of the Study:

  • To investigate the value of social network analysis (SNA) in understanding online collaborative learning.
  • To explore the potential of SNA for predicting student achievement and identifying underachievers.
  • To examine the relationship between network structures, interaction patterns, and academic performance.

Main Methods:

  • Collected and processed online interaction data from four university courses.
  • Calculated SNA parameters related to knowledge sharing and construction at individual and group levels.
  • Employed quantitative network analysis, visualization, correlation tests, and regression models.

Main Results:

  • A consistent positive correlation was found between student performance, interaction metrics, and centrality measures.
  • Students with stronger connections to peers in cohesive groups demonstrated better academic outcomes.
  • SNA indicators accurately classified students by achievement level (93.3% accuracy).

Conclusions:

  • Social network analysis is a valuable tool for analyzing online collaborative learning dynamics.
  • SNA can reliably predict student underachievement, enabling timely interventions.
  • Leveraging interaction data through SNA offers a pathway to data-driven student support services.