{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T10:18:54Z","timestamp":1775125134737,"version":"3.50.1"},"reference-count":47,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Humanities and Social Sciences Fund of the Ministry of Education","award":["22YJA190005"],"award-info":[{"award-number":["22YJA190005"]}]},{"name":"Zhejiang Philosophy and Social Science Laboratory for the Mental Health and Crisis Intervention of Children and Adolescents, China","award":["23MHCICAZD04"],"award-info":[{"award-number":["23MHCICAZD04"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Behavioral Sciences"],"abstract":"<jats:p>Small-scale (e.g., classroom) assessment represents the most common and needed scenario for cognitive diagnostic testing. In such settings, polytomously scored items (e.g., constructed-response tasks) are widely used, as they provide more fine-grained measurement of students\u2019 skills and cognitive processes. However, a significant gap remains between the current methods and pressing practical needs. On one hand, parametric cognitive diagnosis models capable of handling polytomous response data require large samples for stable estimation, making them unsuitable for small-scale classroom use. On the other hand, existing nonparametric classification methods, while robust in small samples, are largely confined to dichotomous (0\/1) response data. There is a lack of dedicated nonparametric methods for polytomous responses, creating a disconnect between practical testing and diagnostic tools. To address this real-world necessity, this study proposes the seq-GNPED method. It extends the generalized nonparametric classification framework to polytomous data by introducing weighted ideal category response and a collapsed class iterative algorithm. Simulations and empirical applications confirm that seq-GNPED achieves robust and accurate diagnosis under small sample conditions where parametric models falter, effectively leveraging the informational richness of polytomous items. This work bridges a critical gap by providing a practical, nonparametric tool tailored for fine-grained, classroom-ready cognitive diagnosis.<\/jats:p>","DOI":"10.3390\/bs16040528","type":"journal-article","created":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T09:26:12Z","timestamp":1775121972000},"page":"528","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Sequential Generalized Nonparametric Classification Method for Small-Scale Cognitive Diagnostic Assessment"],"prefix":"10.3390","volume":"16","author":[{"given":"Junjie","family":"Li","sequence":"first","affiliation":[{"name":"School of Psychology, Jiangxi Normal University, Nanchang 330022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huijing","family":"Zheng","sequence":"additional","affiliation":[{"name":"Teacher Development Center of Yongjia County, Wenzhou 325199, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-6155-4790","authenticated-orcid":false,"given":"Chunhua","family":"Kang","sequence":"additional","affiliation":[{"name":"School of Psychology, Zhejiang Normal University, Jinhua 321004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Psychology, Jiangxi Normal University, Nanchang 330022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongbo","family":"Tu","sequence":"additional","affiliation":[{"name":"School of Psychology, Jiangxi Normal University, Nanchang 330022, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1177\/014662168701100404","article-title":"Open-ended versus multiple-choice response formats\u2014It does make a difference for diagnostic purposes","volume":"11","author":"Birenbaum","year":"1987","journal-title":"Applied Psychological Measurement"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1177\/014662169201600406","article-title":"Effects of response format on diagnostic assessment of scholastic achievement","volume":"16","author":"Birenbaum","year":"1992","journal-title":"Applied Psychological Measurement"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1007\/s11336-015-9482-9","article-title":"A new online calibration method for multidimensional computerized adaptive testing","volume":"81","author":"Chen","year":"2015","journal-title":"Psychometrika"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1007\/s11336-012-9255-7","article-title":"Online calibration methods for the DINA model with independent attributes in CD-CAT","volume":"77","author":"Chen","year":"2012","journal-title":"Psychometrika"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Chen, X., Feng, S., Yang, M., Xu, R., Chen, M., Zhao, K., and Cui, C. 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