A multiple analogy is a structured comparison in which several sources are likened to a target. In "Multiple analogies in science and philosophy," Shelley provides a thorough account of the cognitive representations and processes that participate in multiple analogy formation. Through analysis of real examples taken from the fields of evolutionary biology, archaeology, and Plato's "Republic," Shelley argues that multiple analogies are not simply concatenated single analogies but are instead the general form of analogical inference, of which single analogies are a special case. The result is a truly general cognitive model of analogical inference.Shelley also shows how a cognitive account of multiple analogies addresses important philosophical issues such as the confidence that one may have in an analogical explanation, and the role of analogy in science and philosophy.This book lucidly demonstrates that important questions regarding analogical inference cannot be answered adequately by consideration of single analogies alone.

A multiple analogy is a structured comparison in which several sources are likened to a target. In Multiple analogies in science and philosophy, Shelley provides a thorough account of the cognitive representations and processes that participate in multiple analogy formation. Through analysis of real examples taken from the fields of evolutionary biology, archaeology, and Plato's Republic, Shelley argues that multiple analogies are not simply concatenated single analogies but are instead the general form of analogical inference, of which single analogies are a special case. The result is a truly general cognitive model of analogical inference.Shelley also shows how a cognitive account of multiple analogies addresses important philosophical issues such as the confidence that one may have in an analogical explanation, and the role of analogy in science and philosophy. This book lucidly demonstrates that important questions regarding analogical inference cannot be answered adequately by consideration of single analogies alone.

In this highly-interdisciplinary volume, we systematically study the role of metaphors and analogies in (mis)shaping our understanding of the world. Metaphors and Analogies occupy a prominent place in scientific discourses, as they do in literature, humanities and at the very level of our thinking itself. But when misused they can lead us astray, blinding our understanding inexorably. How can metaphors aid us in our understanding of the world? What role do they play in our scientific discourses and in humanities? How do they help us understand and skillfully deal with our complex socio-political scenarios? Where is the dividing line between their use and abuse? Join us as we explore some of these questions in this volume.

In By Parallel Reasoning Paul Bartha proposes a normative theory of analogical arguments and raises questions and proposes answers regarding (i.) criteria for evaluating analogical arguments, (ii.) the philosophical justification for analogical reasoning, and (iii.) the place of scientific analogies in the context of theoretical confirmation.

Over the past century, educational psychologists and researchers have posited many theories to explain how individuals learn, i.e. how they acquire, organize and deploy knowledge and skills. The 20th century can be considered the century of psychology on learning and related fields of interest (such as motivation, cognition, metacognition etc.) and it is fascinating to see the various mainstreams of learning, remembered and forgotten over the 20th century and note that basic assumptions of early theories survived several paradigm shifts of psychology and epistemology. Beyond folk psychology and its naïve theories of learning, psychological learning theories can be grouped into some basic categories, such as behaviorist learning theories, connectionist learning theories, cognitive learning theories, constructivist learning theories, and social learning theories. Learning theories are not limited to psychology and related fields of interest but rather we can find the topic of learning in various disciplines, such as philosophy and epistemology, education, information science, biology, and – as a result of the emergence of computer technologies – especially also in the field of computer sciences and artificial intelligence. As a consequence, machine learning struck a chord in the 1980s and became an important field of the learning sciences in general. As the learning sciences became more specialized and complex, the various fields of interest were widely spread and separated from each other; as a consequence, even presently, there is no comprehensive overview of the sciences of learning or the central theoretical concepts and vocabulary on which researchers rely. The Encyclopedia of the Sciences of Learning provides an up-to-date, broad and authoritative coverage of the specific terms mostly used in the sciences of learning and its related fields, including relevant areas of instruction, pedagogy, cognitive sciences, and especially machine learning and knowledge engineering. This modern compendium will be an indispensable source of information for scientists, educators, engineers, and technical staff active in all fields of learning. More specifically, the Encyclopedia provides fast access to the most relevant theoretical terms provides up-to-date, broad and authoritative coverage of the most important theories within the various fields of the learning sciences and adjacent sciences and communication technologies; supplies clear and precise explanations of the theoretical terms, cross-references to related entries and up-to-date references to important research and publications. The Encyclopedia also contains biographical entries of individuals who have substantially contributed to the sciences of learning; the entries are written by a distinguished panel of researchers in the various fields of the learning sciences.

The central theme of this book is an under-studied link between the canon of Francis Bacon’s and Isaac Newton’s scientific and philosophical thought and Samuel Johnson’s critical approach that can be traced in a textual study of his literary works. The interpretive framework adopted here encourages familiarity with the history and philosophy of science, confirming that the history of ideas is an entirely human construct that constitutes an integral part of intellectual history. This further endorses the argument that intermediality can only be of benefit to future research into the richness of Johnson’s literary style. As perceived boundaries are crossed between conventionally distinct communication media, the profile of Johnson that emerges is of a writer of passionate intelligence who was able to combine a pragmatic approach to knowledge with flights of imagination as a true artist.

This book brings together powerful ideas and new developments from internationally recognised scholars and classroom practitioners to provide theoretical and practical knowledge to inform progress in science education. This is achieved through a series of related chapters reporting research on analogy and metaphor in science education. Throughout the book, contributors not only highlight successful applications of analogies and metaphors, but also foreshadow exciting developments for research and practice. Themes include metaphor and analogy: best practice, as reasoning; for learning; applications in teacher development; in science education research; philosophical and theoretical foundations. Accordingly, the book is likely to appeal to a wide audience of science educators –classroom practitioners, student teachers, teacher educators and researchers.

Models and theories are of central importance in science, and scientists spend substantial amounts of time building, testing, comparing and revising models and theories. It is therefore not surprising that the nature of scientific models and theories has been a widely debated topic within the philosophy of science for many years. The product of two decades of research, this book provides an accessible yet critical introduction to the debates about models and theories within analytical philosophy of science since the 1920s. Roman Frigg surveys and discusses key topics and questions, including: What are theories? What are models? And how do models and theories relate to each other? The linguistic view of theories (also known as the syntactic view of theories), covering different articulations of the view, its use of models, the theory-observation divide and the theory-ladenness of observation, and the meaning of theoretical terms. The model-theoretical view of theories (also known as the semantic view of theories), covering its analysis of the model-world relationship, the internal structure of a theory, and the ontology of models. Scientific representation, discussing analogy, idealisation and different accounts of representation. Modelling in scientific practice, examining how models relate to theories and what models are, classifying different kinds of models, and investigating how robustness analysis, perspectivism, and approaches committed to uncertainty-management deal with multi-model situations. Models and Theories is the first comprehensive book-length treatment of the topic, making it essential reading for advanced undergraduates, researchers, and professional philosophers working in philosophy of science and philosophy of technology. It will also be of interest to philosophically minded readers working in physics, computer sciences and STEM fields more broadly.