دانلود کتاب روش های تحقیق در تنظیمات کاربردی

In this third edition of Research Methods in Applied Settings: An Integrated Approach to Design and Analysis we continue to promote our philosophy of an integrated approach to quantitative research methods and to the selection and interpretation of data analyses. Our book provides guidance for graduate students in the applied behavioral sciences about planning and conducting a research project, including collecting and analyzing data and writing a research report. The target disciplines include education, allied health, psychology, and other applied behavioral science areas. The table of contents shows the 26 chapters divided into five sections: (I) Introductory Chapters; (II) Quantitative Research Approaches, Questions, and Designs; (III) Sampling, Measurement, and Data Collection; (IV) Data Analysis and Interpretation; and (V) Evaluating and Writing Research Reports. Although we have organized the chapters in a logical order, we also wanted the sections and chapters to “stand alone” as much as possible. This required some repetition, or at least brief redefinition of terms at various points in the text. Thus, the reader should have some flexibility to skip chapters or read them in a different order. For example, the first section in Chapter 26, Anatomy of an Article, might be part of an early lecture to introduce students to what might be expected when reading a journal article. We continue to believe that all phases of the research process are interdependent. Many authors treat the different parts of their research methods books as essentially unrelated. Nowhere is this more obvious than viewing the curriculum of a typical graduate program where a course in research methods is separate from a course in measurement, and statistics is taught as though it had no relation to research design. We continue to make a strong case that in any quantitative research study, the research design guides the data analysis and that the two should not be viewed as totally different content areas, to be taught in two different courses. We have had so many experiences where students have a good grasp of statistics but have no idea why a par – ticular analysis is used for a particular design. However, this is not a statistics book so there are few formulas or computations. We have tried to make this book student friendly as well as sophisticated, partly by being consistent and clear in terminology and partly by organizing the material so that the various chapters are consistent and fit together logically. We have found in our approach to teaching research methods that students become confused due to inconsistent terminology. Perhaps the most common example is the confusion created by the terms selection and assignment. Traditionally, research texts have interchanged the two terms so that students cannot tell the difference between selection into the study, an external validity issue, and assignment to groups, an internal validity issue. Another example is the term validity. Is this a term to be used only when assessing a measurement tool, or does it apply to the evaluation of the design of a study, or to the whole study? We are reminded of Bruce Thompson’s frequently repeated, inten – tionally facetious remark at his many national workshops: “We use these different terms to confuse the graduate students.” For these reasons we have tried to present a semantically consistent and coherent big picture of what we call research approaches (experimental, quasi-experimental, etc.) and how they lead to three basic kinds of research questions (difference, associational, and descriptive), which, in turn, lead to three kinds or groups of statistics with the same names. We realize that these and other attempts to develop and utilize a consistent framework are both nontraditional and somewhat of an over – simplification. However, we think the framework and consistency pay off in terms of student understanding and ability to actually design research and use statistics to help answer research questions.