Exploring the interaction of cognition and emotion in small group collaborative discourse by Heuristic Mining...

Area of Science:

• Educational Psychology
• Cognitive Science
• Information Technology Education

Background:

• Blended collaborative learning combines online and offline educational methods.
• Understanding the interplay between cognitive and emotional factors is crucial for effective learning.
• Previous research has not fully explored these interactions in blended learning environments.

Purpose of the Study:

• To investigate the relationship between cognitive and emotional interactions in blended collaborative learning.
• To identify behavioral patterns associated with high and low task performance in blended learning groups.
• To provide insights for designing effective blended learning courses.

Main Methods:

• Utilized a heuristic mining algorithm and inductive miner algorithm to analyze participant behavior.
• Observed 30 undergraduate students in a 16-week information technology teaching course.
• Categorized participants into high-scoring and low-scoring groups based on task performance.

Main Results:

• High-scoring groups demonstrated more frequent reflection and self-regulation phases and cycles.
• The frequency of emotion events unrelated to cognition was higher in high-scoring groups.
• Behavioral analysis revealed distinct interaction patterns between successful and less successful learning groups.

Conclusions:

• Reflection and self-regulation are key components of successful blended collaborative learning.
• Cognitive-unrelated emotional events may play a significant role in high performance.
• Findings offer practical suggestions for optimizing blended course design and implementation.