Using Self-Organizing Neural Network Map Combined with Ward's Clustering Algorithm for Visualization of Students'...

Area of Science:

• Cognitive Science
• Educational Psychology
• Data Visualization

Background:

• Understanding students' cognitive structures is crucial for effective pedagogy.
• Previous methods for analyzing conceptual understanding can be limited in scope and visualization.
• The concept of 'aliveness' offers a unique lens into fundamental cognitive frameworks.

Purpose of the Study:

• To develop and present a novel approach for clustering and visualizing students' cognitive structural models.
• To analyze how students construct the concept of 'aliveness'.
• To identify dominant cognitive structures underlying the 'aliveness' concept.

Main Methods:

• Employed a combination of Self-Organizing Maps (SOM) and Ward's clustering for cluster analysis.
• Utilized a conceptual understanding test with open-ended questions administered to 100 student subjects.
• Trained the SOM with data derived from the conceptual understanding test.

Main Results:

• Students predominantly associate 'aliveness' with 'human', highlighting an anthropocentric perspective.
• The term 'motion' was most frequently linked to the concept of 'aliveness'.
• Analysis revealed the construction of 'aliveness' through anthropocentric and animistic cognitive structures.

Conclusions:

• The proposed method effectively clusters and visualizes cognitive structures.
• Students' conceptualization of 'aliveness' is largely rooted in human-centric and life-attributed frameworks.
• This approach provides valuable insights into student conceptualization and aids in educational strategy development.