International Comparative Study of Statistics Learning Trajectories Based on PISA Data on Cognitive Diagnostic Models

Area of Science:

• Educational Measurement
• Cognitive Psychology
• Data Science

Background:

• The cognitive diagnosis model (CDM) is an emerging evaluation theory.
• Understanding fine-grained knowledge mastery and learning trajectories is crucial for linking teaching and learning.
• Student learning progress in specific domains requires detailed analysis.

Purpose of the Study:

• To analyze student learning trajectories in statistical knowledge using the cognitive diagnosis model.
• To identify common learning patterns across diverse national contexts.
• To provide insights for improving statistical education.

Main Methods:

• Utilized data from the Program for International Student Assessment (PISA) 2012, involving 30,092 students from 14 countries.
• Applied the cognitive diagnosis model (CDM) to analyze response data across nine statistical items.
• Focused on four key attributes to determine student learning trajectories.

Main Results:

• Identified distinct learning trajectories in statistical knowledge for students across 14 countries.
• Found that Bulgaria, Costa Rica, Peru, Mexico, and Serbia share identical learning trajectories.
• Established a common learning trajectory sequence for most countries: (1) uncertainty, (2) data handling, (3) statistical chart, and (4) average.

Conclusions:

• The cognitive diagnosis model effectively describes student learning trajectories in statistical knowledge.
• Learning trajectories in statistics exhibit common patterns across different national educational systems.
• The identified sequence provides a framework for understanding and supporting student progression in statistical literacy.