Name: Advances in Applications of Rasch Measurement in Science Education (en Inglés)
Price: 503.93 PEN
Availability: InStock
Author: Liu, Xiufeng ; Boone, William J.
ISBN: 9783031287756

portada Advances in Applications of Rasch Measurement in Science Education (en Inglés)

Advances in Applications of Rasch Measurement in Science Education (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Liu, Xiufeng ; Boone, William J.

Idioma

Inglés

N° páginas

529

Encuadernación

Tapa Dura

Dimensiones

23.4 x 15.6 x 3.0 cm

Peso

0.93 kg.

ISBN13

9783031287756

Categorías

Psicología de la educación
Educación: exámenes y evaluación
Enseñanza de una materia específica
Ciencia: cuestiones generales

Advances in Applications of Rasch Measurement in Science Education (en Inglés)

Liu, Xiufeng ; Boone, William J. (Autor) · Springer · Tapa Dura

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Reseña del libro "Advances in Applications of Rasch Measurement in Science Education (en Inglés)"

This 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 techniquesand 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.