Development of a Computerized Adaptive Assessment and Learning System for Mathematical Ability Based on Cognitive...

Area of Science:

• Educational Technology
• Cognitive Science
• Artificial Intelligence in Education

Background:

• Digital transformation in education drives the need for personalized and adaptive learning.
• Existing systems often lack integrated cognitive diagnostic capabilities for tailored instruction.
• The study addresses the growing demand for effective digital learning solutions.

Purpose of the Study:

• To develop a cognitive diagnostic assessment framework aligned with China's mathematics curriculum.
• To investigate the operational mechanisms of a cognitive diagnosis-based computerized adaptive learning system (CAL-CDS).
• To facilitate personalized student learning through cognitive diagnosis in mathematics.

Main Methods:

• Construction of a foundational cognitive diagnostic assessment framework.
• Integration of cognitive modeling, Q-matrix generation, and diagnostic test development.
• Dissection of the system's operational logic: adaptive testing, diagnostic, and recommendation systems, supported by empirical case studies.

Main Results:

• A systematic solution for developing mathematics-specific cognitive diagnosis-driven adaptive learning systems.
• Demonstration of how to construct a cognitive diagnostic assessment framework tailored to specific educational contexts.
• Validation of the system's potential to facilitate personalized student learning via cognitive diagnosis.

Conclusions:

• The CAL-CDS offers a comprehensive approach to personalized learning by integrating cognitive diagnosis.
• The developed framework and operational mechanisms provide a blueprint for similar adaptive learning systems.
• This research contributes to advancing educational technology through intelligent diagnostic and adaptive learning strategies.