AUTHOR=Guo Lei , Yang Jing , Song Naiqing 

TITLE=Spectral Clustering Algorithm for Cognitive Diagnostic Assessment

JOURNAL=Frontiers in Psychology

VOLUME=11

YEAR=2020

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2020.00944

DOI=10.3389/fpsyg.2020.00944

ISSN=1664-1078

ABSTRACT=<p>In cognitive diagnostic assessment (CDA), clustering analysis is an efficient approach to classify examinees into attribute-homogeneous groups. Many researchers have proposed different methods, such as the nonparametric method with Hamming distance, K-means method, and hierarchical agglomerative cluster analysis, to achieve the classification goal. In this paper, according to their responses, we introduce a spectral clustering algorithm (SCA) to cluster examinees. Simulation studies are used to compare the classification accuracy of the SCA, K-means algorithm, G-DINA model and its related reduced cognitive diagnostic models. A real data analysis is also conducted to evaluate the feasibility of the SCA. Some research directions are discussed in the final section.</p>