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This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data-processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and to computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimental, and methodological studies will also appear from time to time. Few areas of inquiry have generated as much interest and enthusiasm in recent times as has the discipline known as "evolutionary psychology", but its pretentions and its accomlishments have not always been properly understood. This collection brings together important work in psychology, anthropology, and the philosophy of science that contributes toward that goal, especially by emphasizing the role of natural selection and sexual selection as crucial factors in the evolution of cognitive mechanisms for information processing. The methodological studies that are presented here are bound to enhance appreciation for the scope and limits of this fascinating domain. The editor has produced a fascinating volume that should appeal to a broad and diverse audience.

This handbook provides both an overview of state-of-the-art scholarship in philosophy of science, as well as a guide to new directions in the discipline. Section I contains broad overviews of the main lines of research and the state of established knowledge in six principal areas of the discipline, including computational, physical, biological, psychological and social sciences, as well as general philosophy of science. Section II covers what are considered to be the traditional topics in the philosophy of science, such as causation, probability, models, ethics and values, and explanation. Section III identifies new areas of investigation that show promise of becoming important areas of research, including the philosophy of astronomy and astrophysics, data, complexity theory, neuroscience, simulations, post-Kuhnian philosophy, post-empiricist epistemology, and emergence. Most chapters are accessible to scientifically educated non-philosophers as well as to professional philosophers, and the contributors - all leading researchers in their field -- bring diverse perspectives from the North American, European, and Australasian research communities. This volume is an essential resource for scholars and students.

This book constitutes the refereed proceedings of the Second International Workshop on Data Integration in the Life Sciences, DILS 2005, held in San Diego, CA, USA in July 2005. The 20 revised full papers presented together with 8 revised posters and demonstration papers, 2 keynote articles and 5 invited position statements were carefully reviewed and selected from 50 initial submissions. The papers are organized in topical sections on user applications, ontologies, data integration, and others and address all current issues in data integration from the life science point of view.

In recent years the organisation and practice of collaboration in the life sciences has undergone radical transformations, owing to the advent of big science enterprises, newly developed data gathering and storage technologies, increasing levels of interdisciplinarity, and changing societal expectations for science. Collaboration in the New Life Sciences examines the causes and consequences of changing patterns of scientific collaboration in the life sciences. This book presents an understanding of how and why collaboration in the life sciences is changing and the effects of these changes on scientific knowledge, the work lives and experiences of scientists, social policy and society. Through a series of thematically arranged chapters, it considers the social, technical, and organizational facets of collaboration, addressing not only the rise of new forms of collaboration in the life sciences, but also examining recent developments in two broad research areas: ecology and environment, and the molecular life sciences. With an international team of experts presenting case studies and analyses drawn from the US, UK, Asia and Europe, Collaboration in the New Life Sciences will appeal not only to scholars and students of science and technology studies, but also to those interested in science and social policy, and the sociology of work and organisations.

Computational thinking is a lifelong skill important for succeeding in careers and life. Students especially need to acquire this skill while in school as it can assist with solving a number of complex problems that arise later in life. Therefore, the importance of teaching computational thinking and coding in early education is paramount for fostering problem-solving and creativity. Teaching Computational Thinking and Coding to Young Children discusses the importance of teaching computational thinking and coding in early education. The book focuses on interdisciplinary connections between computational thinking and other areas of study, assessment methods for computational thinking, and different contexts in which computational thinking plays out. Covering topics such as programming, computational thinking assessment, computational expression, and coding, this book is essential for elementary and middle school teachers, early childhood educators, administrators, instructional designers, curricula developers, educational software developers, researchers, educators, academicians, and students in computer science, education, computational thinking, and early childhood education.

Broad perspective on collectivity in the life sciences, from microorganisms to human consensus, and the theoretical and empirical opportunities and challenges. Many researchers and scholars in the life sciences have become increasingly critical of the traditional methodological focus on the individual. This volume counters such methodological individualism by exploring recent and influential work in the life sciences that utilizes notions of collectivity, sociality, rich interactions, and emergent phenomena as essential explanatory tools to handle numerous persistent scientific questions in the life sciences. The contributors consider case studies of collectivity that range from microorganisms to human consensus, discussing theoretical and empirical challenges and the innovative methods and solutions scientists have devised. The contributors offer historical, philosophical, and biological perspectives on collectivity, and describe collective phenomena seen in insects, the immune system, communication, and human collectivity, with examples ranging from cooperative transport in the longhorn crazy ant to the evolution of autobiographical memory. They examine ways of explaining collectivity, including case studies and modeling approaches, and explore collectivity's explanatory power. They present a comprehensive look at a specific case of collectivity: the Holobiont notion (the idea of a multi-species collective, a host and diverse microorganisms) and the hologenome theory (which posits that the holobiont and its hologenome are a unit of adaption). The volume concludes with reflections on the work of the late physicist Eshel Ben-Jacob, pioneer in the study of collective phenomena in living systems. Contributors Oren Bader, John Beatty, Dinah R. Davison, Daniel Dor, Ofer Feinerman, Raghavendra Gadagkar, Scott F. Gilbert, Snait B. Gissis, Deborah M. Gordon, James Griesemer, Zachariah I. Grochau-Wright, Erik R. Hanschen, Eva Jablonka, Mohit Kumar Jolly, Anat Kolumbus, Ehud Lamm, Herbert Levine, Arnon Levy, Xue-Fei Li, Elisabeth A. Lloyd, Yael Lubin, Eva Maria Luef, Ehud Meron, Richard E. Michod, Samir Okasha, Simone Pika, Joan Roughgarden, Eugene Rosenberg, Ayelet Shavit, Yael Silver, Alfred I. Tauber, Ilana Zilber-Rosenberg

Design-Based Concept Learning in Science and Technology Education brings together contributions from researchers that have investigated what conditions need to be fulfilled to make design-based education work.