An Integrated Analysis of Cognitive Diagnostic Theory and Knowledge Space Theory for Adaptive Assessment

Cognitive Diagnostic Models (CDM) and Knowledge Space Theory (KST) are foundational theories for adaptive assessment. This study contrasts CDM, particularly the DINA model with KST. CDM, based on probability theory, uses Q-matrices to relate items to attributes, focusing on students' cognitive abilities. The DINA model suggests that student responses are determined by attribute mastery. In contrast, KST, anchored in set theory, relates knowledge points through knowledge structures, targeting students' knowledge constructs. The basic local independence models in KST suggests that mastery in one area influences performance in others. While CDM emphasizes cognitive diagnosis, KST centers on knowledge structure modeling. The study suggests potential integration of both theories for enhanced adaptive assessment in education.