Literaturnachweis - Detailanzeige
| Autor/inn/en | Zhan, Peida; Wang, Wen-Chung; Li, Xiaomin; Bian, Yufang |
|---|---|
| Titel | The Probabilistic-Inputs, Noisy Conjunctive Model for Cognitive Diagnosis |
| Quelle | (2016), (6 Seiten)
PDF als Volltext |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Monographie |
| Schlagwörter | Probability; Models; Language Proficiency; Psychometrics; Mastery Learning; Cognitive Measurement; Item Response Theory; English (Second Language) |
| Abstract | To measure individual difference in latent attributes more precisely, this study proposed a new cognitive diagnosis model (CDM), which is referred as the probabilistic-inputs, noisy conjunctive (PINC) model, by treating the deterministic binary latent attributes as probabilistic, and directly estimating the probability in the model. Simulation studies were conducted to evaluate parameter recovery of the new model, and the results revealed that the parameters can be recovered well with WinBUGS. An empirical example of the Examination for the Certificate of Proficiency in English was provided to demonstrate applications of the new model. (As Provided). |
| Anmerkungen | AERA Online Paper Repository. Available from: American Educational Research Association. 1430 K Street NW Suite 1200, Washington, DC 20005. Tel: 202-238-3200; Fax: 202-238-3250; e-mail: subscriptions@aera.net; Web site: http://www.aera.net |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2020/1/01 |
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