The Website

This is the personal website of Haijiang Qin, used to store some of his personal information, research data and results, as well as some technical ideas and articles. Qin is a researcher passionate about educational and psychological methods. His current work primarily focuses on Item Response Theory, Cognitive Diagnosis Theory, Exploratory Factor Analysis, and related areas. Qin is also highly interested in machine learning and artificial intelligence, aiming to advance methodological research through these emerging computational technologies.

ORCID: Haijiang Qin (0009-0000-6721-5653) – ORCID

E-mail: Haijiang133@outlook.com

Published Papers:

Qin, H., & Guo, L. (2025). Priority Attribute Algorithm for Q-matrix Validation: A Didactic. Behavior Research Methods.

郭磊, 秦海江. (2024). 基于信号检测论的认知诊断评估：构建与应用. 心理学报, 56(3), 339-351. https://journal.psych.ac.cn/xlxb/CN/Y2024/V56/I3/339.

Qin, H., & Guo, L. (2024). Using machine learning to improve Q-matrix validation. Behavior Research Methods, 56(3), 1916-1935. https://doi.org/10.3758/s13428-023-02126-0.

秦海江, 霍学晨, & 郭磊. (2024). 高中平面向量的认知诊断研究. 数学教育学报, 33(02), 1-7. 高中平面向量的认知诊断研究 – 中国知网

秦海江, 郭磊. (2023). 基于随机森林的认知诊断Q矩阵修正. 心理技术与应用, 11(11): 685-704. http://www.xljsyyy.com/CN/Y2023/V11/I11/685.

Software:

Qin H., & Guo L (2024). Qval: The Q-Matrix Validation Methods Framework. R package version 1.0.0, https://CRAN.R-project.org/package=Qval.

Qin H., & Guo L (2024). EFAfactors: Determining the Number of Factors in Exploratory Factor Analysis. R package version 1.1.0, https://CRAN.R-project.org/package=EFAfactors.

The software above all provide detailed manuals, which can be found under SOFTWARE.