Modelling online community constructs through interaction data: A learning analytics based Approach

Area of Science:

• Educational Technology
• Learning Analytics
• Online Learning Communities

Background:

• The Community of Inquiry (CoI) framework is crucial for understanding online learning experiences.
• Analyzing student interactions within Learning Management Systems (LMS) provides valuable insights into CoI constructs.
• Previous research has explored CoI presences, but a detailed analysis of interaction patterns within LMS data is needed.

Purpose of the Study:

• To investigate the relationship between various student interaction types in an LMS and the three presences of the CoI framework.
• To propose a method for understanding CoI constructs using LMS log data and learning analytics.
• To identify which specific interactions are most indicative of cognitive, social, and teaching presences.

Main Methods:

• Utilized Moodle LMS log data to capture student online interactions.
• Applied learning analytics techniques to analyze interaction traces.
• Employed the Euclidean Distance Model and Correspondence Analysis to evaluate interaction levels and presences.

Main Results:

• Cognitive presence was found to be central to the CoI constructs.
• Student-content interaction emerged as the most prominent interaction related to cognitive presence.
• Social presence scores correlated with student-student and student-teacher interaction scores.
• Teaching presence scores aligned with student-system interaction scores.

Conclusions:

• Student-content interaction is a significant indicator of cognitive presence in online learning environments.
• Distinct interaction patterns are associated with social and teaching presences within the CoI framework.
• LMS log data analysis offers a robust method for understanding and quantifying CoI constructs.