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Many animals, including humans, acquire valuable skills and knowledge by copying others. Scientists refer to this as social learning. It is one of the most exciting and rapidly developing areas of behavioral research and sits at the interface of many academic disciplines, including biology, experimental psychology, economics, and cognitive neuroscience.Social Learningprovides a comprehensive, practical guide to the research methods of this important emerging field. William Hoppitt and Kevin Laland define the mechanisms thought to underlie social learning and demonstrate how to distinguish them experimentally in the laboratory. They present techniques for detecting and quantifying social learning in nature, including statistical modeling of the spatial distribution of behavior traits. They also describe the latest theory and empirical findings on social learning strategies, and introduce readers to mathematical methods and models used in the study of cultural evolution. This book is an indispensable tool for researchers and an essential primer for students. Provides a comprehensive, practical guide to social learning researchCombines theoretical and empirical approachesDescribes techniques for the laboratory and the fieldCovers social learning mechanisms and strategies, statistical modeling techniques for field data, mathematical modeling of cultural evolution, and more

Biocultural and archaeological research on food, past and present, often relies on very specific, precise, methods for data collection and analysis. These are presented here in a broad-based review. Individual chapters provide opportunities to think through the adoption of methods by reviewing the history of their use along with a discussion of research conducted using those methods. A case study from the author's own work is included in each chapter to illustrate why the methods were adopted in that particular case along with abundant additional resources to further develop and explore those methods.

A practical introduction to epidemiology, biostatistics, and research methodology for the whole health care community This comprehensive text, which has been extensively revised with new material and additional topics, utilizes a practical slant to introduce health professionals and students to epidemiology, biostatistics, and research methodology. It draws examples from a wide range of topics, covering all of the main contemporary health research methods, including survival analysis, Cox regression, and systematic reviews and meta-analysis—the explanation of which go beyond introductory concepts. This second edition of Quantitative Methods for Health Research: A Practical Interactive Guide to Epidemiology and Statistics also helps develop critical skills that will prepare students to move on to more advanced and specialized methods. A clear distinction is made between knowledge and concepts that all students should ensure they understand, and those that can be pursued further by those who wish to do so. Self-assessment exercises throughout the text help students explore and reflect on their understanding. A program of practical exercises in SPSS (using a prepared data set) helps to consolidate the theory and develop skills and confidence in data handling, analysis, and interpretation. Highlights of the book include: * Combining epidemiology and bio-statistics to demonstrate the relevance and strength of statistical methods * Emphasis on the interpretation of statistics using examples from a variety of public health and health care situations to stress relevance and application * Use of concepts related to examples of published research to show the application of methods and balance between ideals and the realities of research in practice * Integration of practical data analysis exercises to develop skills and confidence * Supplementation by a student companion website which provides guidance on data handling in SPSS and study data sets as referred to in the text Quantitative Methods for Health Research, Second Edition is a practical learning resource for students, practitioners and researchers in public health, health care and related disciplines, providing both a course book and a useful introductory reference. 

The first practical guide to research methods in memory studies. This book provides expert appraisals of a range of techniques and approaches in memory studies, and focuses on methods and methodology as a way to help bring unity and coherence to this new field of study.

Qualitative Data is meant for the novice researcher who needs guidance on what specifically to do when faced with a sea of information. It takes readers through the qualitative research process, beginning with an examination of the basic philosophy of qualitative research, and ending with planning and carrying out a qualitative research study. It provides an explicit, step-by-step procedure that will take the researcher from the raw text of interview data through data analysis and theory construction to the creation of a publishable work. The volume provides actual examples based on the authors' own work, including two published pieces in the appendix, so that readers can follow examples for each step of the process, from the project's inception to its finished product. The volume also includes an appendix explaining how to implement these data analysis procedures using NVIVO, a qualitative data analysis program.

\"Big Data\" is on the covers ofScience, Nature, theEconomist, andWiredmagazines, on the front pages of theWall Street Journaland theNew York Times.But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. In many cases, there are no data -- because relevant data don't exist, cannot be found, or are not available. Moreover, data sharing is difficult, incentives to do so are minimal, and data practices vary widely across disciplines.Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure -- an ecology of people, practices, technologies, institutions, material objects, and relationships. After laying out the premises of her investigation -- six \"provocations\" meant to inspire discussion about the uses of data in scholarship -- Borgman offers case studies of data practices in the sciences, the social sciences, and the humanities, and then considers the implications of her findings for scholarly practice and research policy. To manage and exploit data over the long term, Borgman argues, requires massive investment in knowledge infrastructures; at stake is the future of scholarship.

Mastering the Semi-Structured Interview and Beyondoffers an in-depth and captivating step-by-step guide to the use of semi-structured interviews in qualitative research. By tracing the life of an actual research project-an exploration of a school district's effort over 40 years to address racial equality-as a consistent example threaded across the volume, Anne Galletta shows in concrete terms how readers can approach the planning and execution of their own new research endeavor, and illuminates unexpected real-life challenges they may confront and how to address them.The volume offers a close look at the inductive nature of qualitative research, the use of researcher reflexivity, and the systematic and iterative steps involved in data collection, analysis, and interpretation. It offers guidance on how to develop an interview protocol, including the arrangement of questions and ways to evoke analytically rich data.Particularly useful for those who may be familiar with qualitative research but have not yet conducted a qualitative study,Mastering the Semi-Structured Interview and Beyondwill serve both undergraduate and graduate students as well as more advanced scholars seeking to incorporate this key methodological approach into their repertoire.Anne Gallettais Associate Professor at the College of Education and Human Services at Cleveland State University.William E. Cross, Jr.is the author of Shades of Black: Diversity in African-American Identity.In theQualitative Studies in Psychologyseries

Recognised as the most influential publication in the field, ARM facilitates deep understanding of the Rasch model and its practical applications. The authors review the crucial properties of the model and demonstrate its use with examples across the human sciences. Readers will be able to understand and critically evaluate Rasch measurement research, perform their own Rasch analyses and interpret their results. The glossary and illustrations support that understanding, and the accessible approach means that it is ideal for readers without a mathematical background. Intended as a text for graduate courses in measurement, item response theory, (advanced) research methods or quantitative analysis taught in psychology, education, human development, business and other social and health sciences. Professionals in these areas will also appreciate the book’s accessible introduction. Highlights of the new edition include: More learning tools to strengthen readers’ understanding including chapter introductions, boldfaced key terms, chapter summaries, activities and suggested readings. Greater emphasis on the use of R packages; readers can download the R code from the Routledge website. Explores the distinction between numerical values, quantity and units, to understand the measurement and the role of the Rasch logit scale (Chapter 4). A new four-option data set from the IASQ (Instrumental Attitude toward Self-assessment Questionnaire) for the Rating Scale Model (RSM) analysis exemplar (Chapter 6). Clarifies the relationship between Rasch measurement, path analysis and SEM, with a host of new examples of Rasch measurement applied across health sciences, education and psychology (Chapter 10).

Representation in Scientific Practice, published by the MIT Press in 1990, helped coalesce a long-standing interest in scientific visualization among historians, philosophers, and sociologists of science and remains a touchstone for current investigations in science and technology studies. This volume revisits the topic, taking into account both the changing conceptual landscape of STS and the emergence of new imaging technologies in scientific practice. It offers cutting-edge research on a broad array of fields that study information as well as short reflections on the evolution of the field by leading scholars, including some of the contributors to the 1990 volume. The essays consider the ways in which viewing experiences are crafted in the digital era; the embodied nature of work with digital technologies; the constitutive role of materials and technologies -- from chalkboards to brain scans -- in the production of new scientific knowledge; the metaphors and images mobilized by communities of practice; and the status and significance of scientific imagery in professional and popular culture.ContributorsMorana Alac, Michael Barany, Anne Beaulieu, Annamaria Carusi, Catelijne Coopmans, Lorraine Daston, Sarah de Rijcke, Joseph Dumit, Emma Frow, Yann Giraud, Aud Sissel Hoel, Martin Kemp, Bruno Latour, John Law, Michael Lynch, Donald MacKenzie, Cyrus Mody, Natasha Myers, Rachel Prentice, Arie Rip, Martin Ruivenkamp, Lucy Suchman, Janet Vertesi, Steve Woolgar

Behavioral scientists – including those in psychology, infant and child development, education, animal behavior, marketing and usability studies – use many methods to measure behavior. Systematic observation is used to study relatively natural, spontaneous behavior as it unfolds sequentially in time. This book emphasizes digital means to record and code such behavior; while observational methods do not require them, they work better with them. Key topics include devising coding schemes, training observers and assessing reliability, as well as recording, representing and analyzing observational data. In clear and straightforward language, this book provides a thorough grounding in observational methods along with considerable practical advice. It describes standard conventions for sequential data and details how to perform sequential analysis with a computer program developed by the authors. The book is rich with examples of coding schemes and different approaches to sequential analysis, including both statistical and graphical means.