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Updated: Jun 14, 2025

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
Published on: August 28, 2021
Cognitive analysis and path construction of Chinese students' mathematics cognitive process based on CDA
Xiaopeng Wu1,2, Nanxin Li3, Rongxiu Wu4
1Faculty of Education, Northeast Normal University, Changchun, China. wuxp722@nenu.edu.cn.
Mainland Chinese students show strong math skills in cognitive diagnostic assessment (CDA) within the TIMSS framework, excelling in calculation and measurement. This study highlights diverse learning paths and the value of CDA for understanding student cognition.
Area of Science:
- Educational Assessment
- Cognitive Psychology
- International Comparative Studies
Background:
- Cognitive diagnostic assessment (CDA) offers personalized learning insights.
- The Trends in International Mathematics and Science Study (TIMSS) lacks participation from Mainland China.
- Understanding Chinese students' performance in TIMSS is crucial.
Purpose of the Study:
- To assess Mainland Chinese students' performance within the TIMSS framework.
- To compare their cognitive abilities with high-performing nations.
- To analyze learning paths and progressions using CDA.
Main Methods:
- Developed a Q-matrix based on TIMSS-2015 items and eight cognitive attributes.
- Administered a diagnostic assessment to 4,733 Grade 8 students.
- Utilized a mixed model from the G-DINA package in R for analysis.
Main Results:
- Grade 8 students in Mainland China demonstrated an advantage in mathematical cognitive processes.
- Specific strengths were observed in Calculation and Measurement (CM), Operation and Solution (OS), and Representation Modeling (RM).
- Analysis revealed diverse knowledge states and learning progressions among students.
Conclusions:
- CDA provides valuable insights into students' cognitive strengths and weaknesses.
- The study advances methods for TIMSS cognitive diagnostic assessment and learning progression construction.
- Findings underscore the potential of CDA for in-depth data mining in educational assessment.
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