The purpose of the volume is to explore the theory, development and use of visual displays and graphic organizers to improve instruction, learning and research. We anticipate five sections that address (1) frameworks for understanding different types of displays, (2) research-tested guidelines for constructing displays, (3) empirically-based instructional applications, (4) using displays to promote research and theory development, and (5) using displays to report test and research data to improve consumer understanding. Authors represent a variety of perspectives and areas of expertise, including instructional psychology, information technology, and research methodologies. The volume is divided into four sections. Section 1 provides a conceptual overview of previous research, as well as the contents of the current volume. Section 2 includes theoretical perspectives on the design and instructional uses of visual displays from major theorists in the field. These chapters discuss ways that visual displays enhance general cognition and information processing. Section 3 provides eight chapters that address the use of visual displays to enhance student learning. These chapters provide examples of how to organize content and use visual displays in a variety of ways in the real and virtual classroom. Section 4 includes three chapters that discuss ways that visual displays may enhance the research process, but especially improved data display.

Visual displays play a crucial role in knowledge generation and communication. The purpose of the volume is to provide researchers with a framework that helps them use visual displays to organize and interpret data; and to communicate their findings in a comprehensible way within different research (e.g., quantitative, mixed methods) and testing traditions that improves the presentation and understanding of findings. Further, this book includes contributions from leading scholars in testing and quantitative, qualitative, and mixed methods research, and results reporting. The volume’s focal question is: What are the best principles and practices for the use of visual displays in the research and testing process, which broadly includes the analysis, organization, interpretation, and communication of data? The volume is organized into four sections. Section I provides a rationale for this volume; namely, that including visual displays in research and testing can enhance comprehension and processing efficiency. Section II includes addresses theoretical frameworks and universal design principles for visual displays. Section III examines the use of visual displays in quantitative, qualitative, and mixed methods research. Section IV focuses on using visual displays to report testing and assessment data.

Describes a purposeful classroom structure that relies on four phases. Included with the description of each phase are practical strategies that help teachers use this approach, plus tips on how to differentiate instruction, make effective use of class time, and plan backwards from learning objectives.

This book examines the human factors issues associated with the development, testing, and implementation of helmet-mounted display technology in the 21st Century Land Warrior System. Because the framework of analysis is soldier performance with the system in the full range of environments and missions, the book discusses both the military context and the characteristics of the infantry soldiers who will use the system. The major issues covered include the positive and negative effects of such a display on the local and global situation awareness of the individual soldier, an analysis of the visual and psychomotor factors associated with each design feature, design considerations for auditory displays, and physical sources of stress and the implications of the display for affecting the soldier's workload. The book proposes an innovative approach to research and testing based on a three-stage strategy that begins in the laboratory, moves to controlled field studies, and culminates in operational testing.

Digital and online learning is more prevalent than ever, making multimedia learning a primary objective for many instructors. The Cambridge Handbook of Multimedia Learning examines cutting-edge research to guide creative teaching methods in online classrooms and training. Recognized as the field's major reference work, this research-based handbook helps define and shape this area of study. This third edition provides the latest progress report from the world's leading multimedia researchers, with forty-six chapters on how to help people learn from words and pictures, particularly in computer-based environments. The chapters demonstrate what works best and establishes optimized practices. It systematically examines well-researched principles of effective multimedia instruction and pinpoints exactly why certain practices succeed by isolating the boundary conditions. The volume is founded upon research findings in learning theory, giving it an informed perspective in explaining precisely how effective teaching practices achieve their goals or fail to engage.

The rising reliance on testing in American education and for licensure and certification has been accompanied by an escalation in cheating on tests at all levels. Edited by two of the foremost experts on the subject, the Handbook of Quantitative Methods for Detecting Cheating on Tests offers a comprehensive compendium of increasingly sophisticated data forensics used to investigate whether or not cheating has occurred. Written for practitioners, testing professionals, and scholars in testing, measurement, and assessment, this volume builds on the claim that statistical evidence often requires less of an inferential leap to conclude that cheating has taken place than do other, more common sources of evidence. This handbook is organized into sections that roughly correspond to the kinds of threats to fair testing represented by different forms of cheating. In Section I, the editors outline the fundamentals and significance of cheating, and they introduce the common datasets to which chapter authors' cheating detection methods were applied. Contributors describe, in Section II, methods for identifying cheating in terms of improbable similarity in test responses, preknowledge and compromised test content, and test tampering. Chapters in Section III concentrate on policy and practical implications of using quantitative detection methods. Synthesis across methodological chapters as well as an overall summary, conclusions, and next steps for the field are the key aspects of the final section.