Innovative Psychometric Modeling and Methods (hc)

Hong Jiao (u. a.)

ISBN 10: 1648022235 / ISBN 13: 9781648022234

Published by Information Age Publishing, 2020

About this Item

Innovative Psychometric Modeling and Methods (hc) | Hong Jiao (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2020 | Information Age Publishing | EAN 9781648022234 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Seller Inventory # 119387325

Bibliographic Details

• Title: Innovative Psychometric Modeling and Methods (hc)
• Publisher: Information Age Publishing
• Publication Date: 2020
• Language: English
• ISBN 10: 1648022235
• ISBN 13: 9781648022234
• Binding: Buch
• Condition: Neu
• Dimensions: 240W x 161H x 18D millimeters 240 millimeters width by 161 millimeters height by 18 millimeters depth
• Weight: 531 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

The general theme of this book is to present innovative psychometric modeling and methods. In particular, this book includes research and successful examples of modeling techniques for new data sources from digital assessments, such as eye-tracking data, hint uses, and process data from game-based assessments. In addition, innovative psychometric modeling approaches, such as graphical models, item tree models, network analysis, and cognitive diagnostic models, are included.

Chapters 1, 2, 4 and 6 are about psychometric models and methods for learning analytics. The first two chapters focus on advanced cognitive diagnostic models for tracking learning and the improvement of attribute classification accuracy. Chapter 4 demonstrates the use of network analysis for learning analytics. Chapter 6 introduces the conjunctive root causes model for the understanding of prerequisite skills in learning. Chapters 3, 5, 8, 9 are about innovative psychometric techniques to model process data. Specifically, Chapters 3 and 5 illustrate the usage of generalized linear mixed effect models and item tree models to analyze eye-tracking data. Chapter 8 discusses the modeling approach of hint uses and response accuracy in learning environment. Chapter 9 demonstrates the identification of observable outcomes in the game-based assessments. Chapters 7 and 10 introduce innovative latent variable modeling approaches, including the graphical and generalized linear model approach and the dynamic modeling approach.

In summary, the book includes theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to model and analyze multiple data sources from digital assessments. When computer-based assessments are emerging and evolving, it is important that researchers can expand and improve the methods for modeling and analyzing new data sources. This book provides a useful resource to researchers who are interested in the development of psychometric methods to solve issues in this digital assessment age.