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001448793 001__ 1448793
001448793 003__ OCoLC
001448793 005__ 20230310004257.0
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001448793 019__ $$a1341260651
001448793 020__ $$a9789811699863$$q(electronic bk.)
001448793 020__ $$a9811699860$$q(electronic bk.)
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001448793 0247_ $$a10.1007/978-981-16-9986-3$$2doi
001448793 035__ $$aSP(OCoLC)1341345516
001448793 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX$$dEBLCP$$dN$T$$dSFB$$dOCLCQ
001448793 049__ $$aISEA
001448793 050_4 $$aQA76.9.D343
001448793 08204 $$a006.3/12$$223/eng/20220818
001448793 1001_ $$aShojima, Kojiro,$$eauthor.
001448793 24510 $$aTest data engineering :$$blatent rank analysis, biclustering, and Bayesian network /$$cKojiro Shojima.
001448793 264_1 $$aSingapore :$$bSpringer,$$c[2022]
001448793 264_4 $$c©2022
001448793 300__ $$a1 online resource (xxii, 579 pages) :$$billustrations (chiefly color).
001448793 336__ $$atext$$btxt$$2rdacontent
001448793 337__ $$acomputer$$bc$$2rdamedia
001448793 338__ $$aonline resource$$bcr$$2rdacarrier
001448793 4901_ $$aBehaviormetrics - quantitative approaches to human behavior ;$$vvolume 13
001448793 504__ $$aIncludes bibliographical references.
001448793 5050_ $$aConcept of Test Data Engineering -- Test Data and Item Analysis -- Classical Test Theory -- Item Response Theory -- Latent Class Analysis -- Biclustering -- Bayesian Network Model.
001448793 506__ $$aAccess limited to authorized users.
001448793 520__ $$aThis is the first technical book that considers tests as public tools and examines how to engineer and process test data, extract the structure within the data to be visualized, and thereby make test results useful for students, teachers, and the society. The author does not differentiate test data analysis from data engineering and information visualization. This monograph introduces the following methods of engineering or processing test data, including the latest machine learning techniques: classical test theory (CTT), item response theory (IRT), latent class analysis (LCA), latent rank analysis (LRA), biclustering (co-clustering), and Bayesian network model (BNM). CTT and IRT are methods for analyzing test data and evaluating students abilities on a continuous scale. LCA and LRA assess examinees by classifying them into nominal and ordinal clusters, respectively, where the adequate number of clusters is estimated from the data. Biclustering classifies examinees into groups (latent clusters) while classifying items into fields (factors). Particularly, the infinite relational model discussed in this book is a biclustering method feasible under the condition that neither the number of groups nor the number of fields is known beforehand. Additionally, the local dependence LRA, local dependence biclustering, and bicluster network model are methods that search and visualize inter-item (or inter-field) network structure using the mechanism of BNM. As this book offers a new perspective on test data analysis methods, it is certain to widen readers perspective on test data analysis. .
001448793 588__ $$aDescription based on print version record.
001448793 650_0 $$aData mining.
001448793 650_0 $$aInformation visualization.
001448793 650_0 $$aEducational tests and measurements$$xData processing.
001448793 650_0 $$aBayesian statistical decision theory.
001448793 650_0 $$aCluster analysis.
001448793 650_6 $$aExploration de données (Informatique)$$0(CaQQLa)201-0300292
001448793 650_6 $$aVisualisation de l'information.$$0(CaQQLa)201-0371241
001448793 650_6 $$aTests et mesures en éducation$$0(CaQQLa)201-0007299$$xInformatique.$$0(CaQQLa)201-0380011
001448793 650_6 $$aThéorie de la décision bayésienne.$$0(CaQQLa)000272233
001448793 650_6 $$aClassification automatique (Statistique)$$0(CaQQLa)201-0026933
001448793 655_0 $$aElectronic books.
001448793 655_7 $$aLlibres electrònics.$$2thub
001448793 77608 $$iPrint version:$$aSHOJIMA, KOJIRO.$$tTEST DATA ENGINEERING.$$d[Place of publication not identified] : SPRINGER VERLAG, SINGAPOR, 2022$$z9811699852$$w(OCoLC)1291171345
001448793 830_0 $$aBehaviormetrics ;$$vv. 13.
001448793 852__ $$bebk
001448793 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-16-9986-3$$zOnline Access$$91397441.1
001448793 909CO $$ooai:library.usi.edu:1448793$$pGLOBAL_SET
001448793 980__ $$aBIB
001448793 980__ $$aEBOOK
001448793 982__ $$aEbook
001448793 983__ $$aOnline
001448793 994__ $$a92$$bISE