Understanding Cognitive Attributes and Hierarchies of Exponential and Logarithmic Functions: A Hierarchical CDM Framework

• In Event: AERA Poster Session Friday 9:45am
  In Poster Session: Student Learning in Mathematics Education

Abstract

Exponential and logarithmic (EL) functions are pivotal mathematical concepts that often challenge students due to limited understanding of the underlying cognitive processes. This study aims to enhance understanding of students’ learning of EL functions using a hierarchical cognitive diagnosis framework. Following the framework, a hierarchical cognitive diagnostic assessment (HCDA) for EL functions was developed, and its attributes and hierarchy were validated using HCDM models. Results indicate that the HCDA demonstrated sufficient validity in diagnosing students’ mastery of EL functions at both individual and group levels. The implications of using HCDM framework to provide diagnostic feedbacks about students’ learning mathematical concepts with hierarchical structures are discussed.

Authors

• Yufeng Guo, Beijing Normal University

• Xuan Shi, The High School Affiliated To Beijing Normal University

• Xue-Lan QIU, Australian Catholic University