Visual Data in Science Education builds upon previous work done by the editors to bring some definition to the meaning of visual data as it relates to education, and highlighted the breadth of types and uses of visual data across the major academic disciplines. In this book, the editors have brought this focus specifically to science education through the contributions of colleagues in the field who actively research about and engage in teaching with visual data. The book begins by examining how the brain functions with respect to processing visual data, then explores models of conceptual frameworks, which then leads into how related ideas are actuated in education settings ranging from elementary science classrooms to college environments. As a whole, this book fosters a more coherent image of the multifaceted process of science teaching and learning that is informed by current understandings of science knowledge construction, the scientific enterprise, and the millennium student as they relate to visual data.

This book addresses key issues concerning visualization in the teaching and learning of science at any level in educational systems. It is the first book specifically on visualization in science education. The book draws on the insights from cognitive psychology, science, and education, by experts from five countries. It unites these with the practice of science education, particularly the ever-increasing use of computer-managed modelling packages.

External representations (pictures, diagrams, graphs, concrete models) have always been valuable tools for the science teacher. This book brings together the insights of practicing scientists, science education researchers, computer specialists, and cognitive scientists, to produce a coherent overview. It links presentations about cognitive theory, its implications for science curriculum design, and for learning and teaching in classrooms and laboratories.

The visual inputs we receive can be collectively called visual data. Precisely how one defines visual data is a key question to ask. That is one of the questions we asked each author who wrote a chapter for this book. If one comes to a decision with respect to what visual data are, then the next question becomes, "What are visual data like?" Then, "What do they mean?" As with any data, we can collect it and compile it, but if we don't have some way to bring meaning it, it has little value to us. The answers may not be as straightforward as one might assume at the outset. The extent to which visual data permeates what we do as educators is such that it may be difficult to identify every discipline in which it emerges. In this book, we have tried to provide a forum for authors from a cross section of common disciplines: visual arts, English, literacy, mathematics, science, social science, and even higher education administration.

This book examines visual data use with students (PK-16) as well as in pre-service in- service science teacher preparation. Each chapter includes discussion about the current state of the art with respect to science classroom application and utilization of the particular visual data targeted by the author(s), discussion and explanation about the targeted visual data as applied by the author in his/her classroom, use of visual data as a diagnostic tool, its use as an assessment tool, and discussion of implications for science teaching and/or science teacher preparation. Although the body of research and practice in this field is growing, there remains a gap in the literature about clearly explicating the use of visual data in the science classroom. A growing body of literature discusses what visual data are (although this topic is still viewed as being at the beginning of its development in educators’ thinking), and there are some scattered examples of studies exploring the use of visual data in science classrooms, although those studies have not necessarily clearly identified their foci as visual data, per se. As interest and attention has become more focused on visual data, a logical progression of questioning has been how visual data are actually applied in the science classroom, whether it be early elementary, college, or somewhere in between. Visual data applications of interest to the science education community include how it is identified, how it can be used with students and how students can generate it themselves, how it can be employed as a diagnostic tool in concept development, and how it can be utilized as an assessment tool. This book explores that, as well as a variety of pragmatic ways to help science educators more effectively utilize visual data and representations in their instruction.

"This book comprises a wide range of scholarly essays introducing readers to key topics and issues in science education. Science education has become a well established field in its own right, with a vast literature, and many active areas of scholarship. Science Education: An International Course Companion offers an entry point for students seeking a sound but introductory understanding of the key perspectives and areas of thinking in science education. Each account is self-contained and offers a scholarly and research-informed introduction to a particular topic, theme, or perspective, with both citations to key literature and recommendations for more advanced reading. Science Education: An International Course Companion allows readers (such as those preparing for school science teaching, or seeking more advanced specialist qualifications) to obtain a broad familiarity with key issues across the field as well as guiding wider reading about particular topics of interest. The book therefore acts as a reader to support learning across courses in science education internationally. The broad coverage of topics is such that that the book will support students following a diverse range of courses and qualifications. The comprehensive nature of the book will allow course leaders and departments to nominate the book as the key reader to support students – their core ‘course companion’ in science education."

Data Visualization Made Simple is a practical guide to the fundamentals, strategies, and real-world cases for data visualization, an essential skill required in today’s information-rich world. With foundations rooted in statistics, psychology, and computer science, data visualization offers practitioners in almost every field a coherent way to share findings from original research, big data, learning analytics, and more. In nine appealing chapters, the book: examines the role of data graphics in decision-making, sharing information, sparking discussions, and inspiring future research; scrutinizes data graphics, deliberates on the messages they convey, and looks at options for design visualization; and includes cases and interviews to provide a contemporary view of how data graphics are used by professionals across industries Both novices and seasoned designers in education, business, and other areas can use this book’s effective, linear process to develop data visualization literacy and promote exploratory, inquiry-based approaches to visualization problems.

Effective communication within learning environments is a pivotal aspect to students’ success. By enhancing abstract concepts with visual media, students can achieve a higher level of retention and better understand the presented information. Knowledge Visualization and Visual Literacy in Science Education is an authoritative reference source for the latest scholarly research on the implementation of visual images, aids, and graphics in classroom settings and focuses on how these methods stimulate critical thinking in students. Highlighting concepts relating to cognition, communication, and computing, this book is ideally designed for researchers, instructors, academicians, and students.

Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field.

This book argues for the essential use of drawing as a tool for science teaching and learning. The authors are working in schools, universities, and continual science learning (CSL) settings around the world. They have written of their experiences using a variety of prompts to encourage people to take pen to paper and draw their thinking – sometimes direct observation and in other instances, their memories. The result is a collection of research and essays that offer theory, techniques, outcomes, and models for the reader. Young children have provided evidence of the perceptions that they have accumulated from families and the media before they reach classrooms. Secondary students describe their ideas of chemistry and physics. Teacher educators use drawings to consider the progress of their undergraduates’ understanding of science teaching and even their moral/ethical responses to teaching about climate change. Museum visitors have drawn their understanding of the physics of how exhibit sounds are transmitted. A physician explains how the history of drawing has been a critical tool to medical education and doctor-patient communications. Each chapter contains samples, insights, and where applicable, analysis techniques. The chapters in this book should be helpful to researchers and teachers alike, across the teaching and learning continuum. The sections are divided by the kinds of activities for which drawing has historically been used in science education: An instance of observation (Audubon, Linnaeus); A process (how plants grow over time, what happens when chemicals combine); Conceptions of what science is and who does it; Images of identity development in science teaching and learning.