001472292 000__ 06807cam\\22006497a\4500 001472292 001__ 1472292 001472292 003__ OCoLC 001472292 005__ 20230908003405.0 001472292 006__ m\\\\\o\\d\\\\\\\\ 001472292 007__ cr\un\nnnunnun 001472292 008__ 230805s2023\\\\sz\\\\\\o\\\\\001\0\eng\d 001472292 019__ $$a1392165905 001472292 020__ $$a9783031287763$$q(electronic bk.) 001472292 020__ $$a3031287762$$q(electronic bk.) 001472292 020__ $$z3031287754 001472292 020__ $$z9783031287756 001472292 0247_ $$a10.1007/978-3-031-28776-3$$2doi 001472292 035__ $$aSP(OCoLC)1392346887 001472292 040__ $$aEBLCP$$beng$$cEBLCP$$dYDX$$dGW5XE$$dEBLCP 001472292 049__ $$aISEA 001472292 050_4 $$aQ181 001472292 08204 $$a507.1$$223/eng/20230811 001472292 24500 $$aAdvances in applications of Rasch measurement in science education /$$cXiufeng Liu, William J. Boone, editors. 001472292 260__ $$aCham :$$bSpringer,$$c2023. 001472292 300__ $$a1 online resource (531 p.). 001472292 4901_ $$aContemporary Trends and Issues in Science Education ;$$vv.57 001472292 500__ $$a4.9 Comparisons Between Frequentist and Bayesian Methods 001472292 500__ $$aIncludes indexes. 001472292 5050_ $$aIntro -- Foreword -- Contents -- Chapter 1: Introduction to Advances in Applications of Rasch Measurement in Science Education -- 1.1 Item Response Theory Models vs. Rasch Models -- 1.2 Theory of Construct -- 1.3 Sample Size for Rasch Analysis -- 1.4 Uses of Fit Statistics -- 1.5 Local Independence and Dimensionality -- 1.6 Wright Map -- 1.7 Linking Rasch Measures -- 1.8 Using Rasch Measures for Subsequent Analyses -- References -- Chapter 2: Rasch Measurement in Discipline-Based Physics Education Research -- 2.1 Motivation and Introduction -- 2.2 Scope and Structure of Review 001472292 5058_ $$a2.3 Diverse Use of Rasch Measurement in Physics Education Research -- 2.3.1 Assessment Revalidation and Assessment Development -- 2.3.2 Diverse Constructs, Assessment Formats and Scoring Schemes -- 2.3.3 Diverse Models and Analytical Techniques -- 2.4 Confusions and Improper Practices of Rasch Measurement in Physics Education Research -- 2.4.1 Theory-Driven Nature of Rasch Measurement -- 2.4.2 Principles and Operations of Rasch Measurement -- 2.4.3 Confirmatory Bias in Practice -- 2.4.4 Inconsistent Benchmarks for Analysis -- 2.5 Discussion and Implication 001472292 5058_ $$aAppendix: A Summary of Reviewed Studies of Rasch Measurement in Discipline-Based Physics Education Research -- References -- Chapter 3: Using R Software for Rasch Model Calibrations -- 3.1 Introduction -- 3.2 What Is R? -- 3.2.1 Installation of the R Software and RStudio -- 3.2.2 Loading Data -- 3.3 Rasch Model Applications in R -- 3.3.1 R Programs/Packages for Rasch Modeling -- 3.3.2 Package Installation -- 3.3.3 Unidimensional Rasch Application for Dichotomous Data (Using the ``eRm ́́package) -- Fitting the Rasch Model -- Item Parameter Estimation -- Item Characteristic Curve (ICC) 001472292 5058_ $$aPerson Ability Parameter Estimation -- Model Evaluation -- 3.3.4 Unidimensional Rasch Application for Polytomous Data (Using ``TAM ́́for PCM) -- Fitting the Partial Credit Model -- Item Parameter Estimation -- Category Characteristic Curve -- Person Ability Parameter Estimation -- Model Evaluation -- 3.3.5 Multidimensional Rasch Application for Dichotomous Data (Using ``mirt)́́ -- Fitting the Two-Dimensional Rasch Model -- Item Parameter Estimation -- Item Characteristic Surface -- Person Ability Parameter Estimation -- Model Evaluation -- Epilogue -- R Code -- References 001472292 5058_ $$aChapter 4: Bayesian Partial Credit Model and Its Applications in Science Education -- 4.1 Introduction -- 4.1.1 Rasch Measurement in Science Education -- 4.1.2 Different Estimation Approaches to Rasch Analyses in Science Education -- 4.1.3 The Bayesian Approach -- 4.1.4 Programme for International Student Assessment -- 4.2 Objectives -- 4.3 Methods -- 4.4 Formulation of the PCM in Stan -- 4.5 Data Simulation for Parameter Recovery -- 4.6 Empirical Application Results and Model Checking -- 4.7 Convergence and Efficiency Diagnostics -- 4.8 Estimated Parameters 001472292 506__ $$aAccess limited to authorized users. 001472292 520__ $$aThis edited volume presents latest development in applications of Rasch measurement in science education. It includes a conceptual introduction chapter and a set of individual chapters. The introductory chapter reviews published studies applying Rasch measurement in the field of science education and identify important principles of Rasch measurement and best practices in applications of Rasch measurement in science education. The individual chapters, contributed by authors from Canada, China, Germany, Philippines and the USA, cover a variety of current topics on measurement concerning science conceptual understanding, scientific argumentation, scientific reasoning, three-dimensional learning, knowledge-in-use and cross-cutting concepts of the Next Generation Science Standards, medical education learning experiences, machine-scoring bias, formative assessment, and teacher knowledge of argument. There are additional chapters on advances in Rasch analysis techniques and technology including R, Bayesian estimation, comparison between joint maximum likelihood (JML) and marginal maximum likelihood (MML) estimations on model-data-fit, and enhancement to Rasch models by Cognitive Diagnostic Models and Latent Class Analysis. The volume provides readers who are new and experienced in applying Rasch measurement with advanced and exemplary applications in the forefront of various areas of science education research. 001472292 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed August 11, 2023). 001472292 650_0 $$aScience$$xStudy and teaching$$xStatistical methods. 001472292 650_0 $$aRasch models. 001472292 655_0 $$aElectronic books. 001472292 7001_ $$aLiu, Xiufeng,$$d1962- 001472292 7001_ $$aBoone, William J.$$q(William John) 001472292 77608 $$iPrint version:$$aLiu, Xiufeng$$tAdvances in Applications of Rasch Measurement in Science Education$$dCham : Springer International Publishing AG,c2023$$z9783031287756 001472292 830_0 $$aContemporary trends and issues in science education ;$$vv. 57. 001472292 852__ $$bebk 001472292 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-28776-3$$zOnline Access$$91397441.1 001472292 909CO $$ooai:library.usi.edu:1472292$$pGLOBAL_SET 001472292 980__ $$aBIB 001472292 980__ $$aEBOOK 001472292 982__ $$aEbook 001472292 983__ $$aOnline 001472292 994__ $$a92$$bISE