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Yunxiao Chen; Xiaoou Li; Jingchen Liu; Gongjun Xu; Zhiliang Ying – Grantee Submission, 2017
Large-scale assessments are supported by a large item pool. An important task in test development is to assign items into scales that measure different characteristics of individuals, and a popular approach is cluster analysis of items. Classical methods in cluster analysis, such as the hierarchical clustering, K-means method, and latent-class…
Descriptors: Item Analysis, Classification, Graphs, Test Items
Longford, Nicholas T. – 1994
This study is a critical evaluation of the roles for coding and scoring of missing responses to multiple-choice items in educational tests. The focus is on tests in which the test-takers have little or no motivation; in such tests omitting and not reaching (as classified by the currently adopted operational rules) is quite frequent. Data from the…
Descriptors: Algorithms, Classification, Coding, Models
Lau, C. Allen; Wang, Tianyou – 2000
This paper proposes a new Information-Time index as the basis for item selection in computerized classification testing (CCT) and investigates how this new item selection algorithm can help improve test efficiency for item pools with mixed item types. It also investigates how practical constraints such as item exposure rate control, test…
Descriptors: Algorithms, Classification, Computer Assisted Testing, Elementary Secondary Education