The chapters in Thinking With Data are based on presentations given at the 33rd Carnegie Symposium on Cognition. The Symposium was motivated by the confluence of three emerging trends: (1) the increasing need for people to think effectively with data at work, at school, and in everyday life, (2) the expanding technologies available to support people as they think with data, and (3) the growing scientific interest in understanding how people think with data.

What is thinking with data? It is the set of cognitive processes used to identify, integrate, and communicate the information present in complex numerical, categorical, and graphical data. This book offers a multidisciplinary presentation of recent research on the topic. Contributors represent a variety of disciplines: cognitive and developmental psychology; math, science, and statistics education; and decision science. The methods applied in various chapters similarly reflect a scientific diversity, including qualitative and quantitative analysis, experimentation and classroom observation, computational modeling, and neuroimaging. Throughout the book, research results are presented in a way that connects with both learning theory and instructional application.

The book is organized in three sections:

• Part I focuses on the concepts of uncertainty and variation and on how people understand these ideas in a variety of contexts.
• Part II focuses on how people work with data to understand its structure and draw conclusions from data either in terms of formal statistical analyses or informal assessments of evidence.
• Part III focuses on how people learn from data and how they use data to make decisions indaily and professional life.

The ability to navigate across town, comprehend an animated display of the functioning of the human heart, view complex multivariate data on a company's website, or to read an architectural blueprint and form a three-dimensional mental picture of a house are all tasks involving visuospatial thinking. The field of visuospatial thinking is a relatively diverse interdisciplinary research enterprise. An understanding of visuospatial thinking, and in particular, how people represent and process visual and spatial information, is relevant not only to cognitive psychology but also education, geography, architecture, medicine, design computer science/artificial intelligence, semiotics and animal cognition. The goal of this book, first published in 2005, is to present a broad overview of research on visuospatial thinking that can be used by researchers as well as students interested in this topic in both basic research and applied/naturalistic contexts.

Working memory is currently a "hot" topic in cognitive psychology and neuroscience. Because of their radically different scopes and emphases, however, comparing different models and theories and understanding how they relate to one another has been a difficult task. This work offers a much-needed forum for systematically comparing and contrasting existing models of working memory. It does so by asking each contributor to address the same comprehensive set of important theoretical questions on working memory. The answers to these questions elucidate the emerging general consensus on the nature of working memory among different theorists and clarify incompatible theoretical claims that must be resolved in future research. As such, this volume serves not only as a milestone that documents the state of the art in the field, but also as a theoretical guidebook that will promote new lines of research and more precise and comprehensive models of working memory.

The ability to navigate across town, comprehend an animated display of the functioning of the human heart, view complex multivariate data on a company's website, or to read an architectural blueprint and form a three-dimensional mental picture of a house are all tasks involving visuospatial thinking. The field of visuospatial thinking is a relatively diverse interdisciplinary research enterprise. An understanding of visuospatial thinking, and in particular, how people represent and process visual and spatial information, is relevant not only to cognitive psychology but also education, geography, architecture, medicine, design computer science/artificial intelligence, semiotics and animal cognition. The goal of this book, first published in 2005, is to present a broad overview of research on visuospatial thinking that can be used by researchers as well as students interested in this topic in both basic research and applied/naturalistic contexts.

The chapters in Thinking With Data are based on presentations given at the 33rd Carnegie Symposium on Cognition. The Symposium was motivated by the confluence of three emerging trends: (1) the increasing need for people to think effectively with data at work, at school, and in everyday life, (2) the expanding technologies available to support people as they think with data, and (3) the growing scientific interest in understanding how people think with data.

What is thinking with data? It is the set of cognitive processes used to identify, integrate, and communicate the information present in complex numerical, categorical, and graphical data. This book offers a multidisciplinary presentation of recent research on the topic. Contributors represent a variety of disciplines: cognitive and developmental psychology; math, science, and statistics education; and decision science. The methods applied in various chapters similarly reflect a scientific diversity, including qualitative and quantitativeanalysis, experimentation and classroom observation, computational modeling, and neuroimaging. Throughout the book, research results are presented in a way that connects with both learning theory and instructional application.

The book is organized in three sections:

• Part I focuses on the concepts of uncertainty and variation and on how people understand these ideas in a variety of contexts.
• Part II focuses on how people work with data to understand its structure and draw conclusions from data either in terms of formal statistical analyses or informal assessments of evidence.
• Part III focuses on how people learn from data and how they use data to make decisions in dailyand professional life.