A calibrated scale to measure heritage learning in digital environments. A network analysis approach

Area of Science:

• Digital Humanities
• Educational Measurement
• Cultural Heritage Studies

Background:

• Limited research exists on validated instruments for heritage learning assessment in digital contexts.
• Network analysis methodology is underutilized in heritage learning research.

Purpose of the Study:

• To address research gaps by applying network analysis to heritage learning assessment.
• To develop and validate a measurement instrument for digital heritage learning.
• To investigate the structure and invariance of heritage learning dimensions.

Main Methods:

• Utilized network analysis methodology with a Gaussian Graphical Model and regularization.
• Analyzed responses from 1323 participants across seven dimensions of the Heritage Learning Sequence.
• Ensured accuracy, validity, and reliability through network estimation and stability analysis.

Main Results:

• Achieved satisfactory network structure, predictability, replicability, and sensitivity.
• Demonstrated invariance of the network structure across different demographic groups (male/female) and random subsamples.
• Validated the application of network analysis for heritage learning assessment.

Conclusions:

• Network analysis provides a robust methodology for assessing heritage learning in digital contexts.
• The developed instrument shows promising accuracy, validity, and reliability.
• Findings support further research into digital heritage education assessment using network analysis.