This research proposed four concise longitudinal nonparametric diagnostic methods:longitudinal non-parametric classification(LNPC),longitudinal weighted nonparametric classification(LWNPC),longitudinal generalized nonparametric classification(LGNPC),and longitudinal weighted generalized nonparametric classification(LWGNPC),by leverag-ing the connection of students'knowledge state and the ideal response pattern between adjacent time points.The performance of the four new methods was evaluated by two simulation studies and an empirical study.The results of simulation studies showed that:(1)the established link could improve the accuracy of longitudinal classification;(2)compared to the HO-HMM model,the new methods could achieve similar precision while being less affected by the sample size;(3)the new methods outperformed the Long-HDD method in terms of accuracy,and the LNPC and LWNPC still performed well even with low-quality items.The results of the empirical study showed that the four new methods were highly con-sistent with the HO-HMM model and Long-HDD classification.We recommend using the LWNPC method to analyze the real data.
维普
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