For anyone who does research, this book offers an invaluable tool for learning the techniques of researching, reviewing and analyzing research literature. Applying basic tenets of sound data gathering to a comprehensive synthesis of past research on a topic, Cooper leads the reader step-by-step through the five stage process integrating research reviewing -- from conceptualization of the research problem to the concise summary of the research review. New to the second edition is coverage of computer literature searches, the theoretical underpinnings of meta-analysis, the application of these procedures, and new material on coding sheets.
During the last decade there were significant advances in the study of students' learning and problem solving in mathematics, and in the study of classroom instruction. Because these two research programs usually have been conducted individually, it is generally agreed now that there is an increasing need for an integrated research program. This book represents initial discussions and development of a unified paradigm for studying teaching in mathematics that builds upon both cognitive as well as instructional research.
The workshop summary provides guidance for researchers applying to the National Science Foundation (NSF) for funding. New NSF guidelines require applications to address the "broader impact" of the proposed research. Presentations at the workshop provided ideas on how to do this by engaging in undergraduate education, K-12 education or public outreach via museums or journalists. The workshop summary discusses issues to consider in choosing an appropriate collaborator for the education or outreach component of the project and how to build in methods for assessing the success of the project. It also provides lists of resources helpful in writing education proposals and discusses the similarities between research in education and scientific research.
Health care has been called one of the most complex sectors of the U.S. economy. Driven largely by robust innovation in treatments and interventions, this complexity has created an increased need for evidence about what works best for whom in order to inform decisions that lead to safe, efficient, effective, and affordable care. As health care becomes more digital, clinical datasets are becoming larger and more numerous. By realizing the potential of knowledge generation that is more closely integrated with the practice of care, it should be possible not only to produce more usable evidence to inform decisions, but also to increase the efficiency and decrease the costs of doing clinical research. Patient-Centered Clinical Research Network, or PCORnet, is a nation-wide patient-centered clinical research network intended to form a resource of clinical, administrative, and patient data that can be used to carry out observational and interventional research studies and enhance the use of clinical data to advance the learning health care system. The primary goal of the first phase of PCORnet will be to establish the data infrastructure necessary to do such research. In April and June 2014 the Institute of Medicine's Roundtable on Value and Science-Driven Health Care convened two workshops aimed at accelerating progress toward real-time knowledge generation through the seamless integration of clinical practice and research, one of the fundamental concepts of a continuously learning health system, centered on the development of the PCORnet. The first workshop brought together health care system leaders, both administrative and clinical, and researchers to consider issues and strategic priorities for building a successful and durable clinical research network and facilitate progress toward a continuously learning health care system more broadly, including issues related to science, technology, ethics, business, regulatory oversight, sustainability, and governance. The second workshop focused on implementation approaches. Health system CEOs convened to consider strategic priorities and explore approaches to implementation. These workshops will inform the decisions of field leaders moving forward, including PCORI, the PCORnet steering committee, and PCORnet grantees. Integrating Research and Practice is the summary of the presentations and discussions of the workshops.
This volume focuses on the important mathematical idea of functions that, with the technology of computers and calculators, can be dynamically represented in ways that have not been possible previously. The book's editors contend that as result of recent technological developments combined with the integrated knowledge available from research on teaching, instruction, students' thinking, and assessment, curriculum developers, researchers, and teacher educators are faced with an unprecedented opportunity for making dramatic changes. The book presents content considerations that occur when the mathematics of graphs and functions relate to curriculum. It also examines content in a carefully considered integration of research that conveys where the field stands and where it might go. Drawing heavily on their own work, the chapter authors reconceptualize research in their specific areas so that this knowledge is integrated with the others' strands. This model for synthesizing research can serve as a paradigm for how research in mathematics education can -- and probably should -- proceed.
Research based universities occupy prime position have multiple roles to play beyond teaching, learning and supporting the academic achievements of students. Offering an international perspective, this book demonstrates how these emerging trends are being viewed across different countries with a broad range of diverse socio-cultural backgrounds.
This volume focuses on the important mathematical idea of functions that, with the technology of computers and calculators, can be dynamically represented in ways that have not been possible previously. The book's editors contend that as result of recent technological developments combined with the integrated knowledge available from research on teaching, instruction, students' thinking, and assessment, curriculum developers, researchers, and teacher educators are faced with an unprecedented opportunity for making dramatic changes. The book presents content considerations that occur when the mathematics of graphs and functions relate to curriculum. It also examines content in a carefully considered integration of research that conveys where the field stands and where it might go. Drawing heavily on their own work, the chapter authors reconceptualize research in their specific areas so that this knowledge is integrated with the others' strands. This model for synthesizing research can serve as a paradigm for how research in mathematics education can -- and probably should -- proceed.
In this book, the authors highlight recent findings that hold the potential to improve software products or development processes; in addition, they help readers understand new concepts and technologies, and to see what it takes to migrate from old to new platforms. Some of the authors have spent most of their careers in industry, working at the frontiers of practice-based innovation, and are at the same time prominent researchers who have made significant academic contributions. Others work together with industry to test, in industrial settings, the methods they’ve developed in the lab. The choice of subject and authors represent the key elements of this book. Its respective chapters cover a wide range of topics, from cloud computing to agile development, applications of data science methods, re-engineering of aging applications into modern ones, and business and requirements engineering. Taken together, they offer a valuable asset for practitioners and researchers alike.
This book shows why and how the concepts, control and happenstance, are crucial to methodology and statistics, respectively. Control, as a means to reduce ambiguity, fulfills its function because of inductive rules. Statistical null hypothesis renders it possible to use test of statistical significance to rule out happenstance as explanation of research result. This book shows why and how the concepts, control and happenstance, are crucial to methodology and statistics, respectively. Control, as a means to reduce ambiguity, fulfills its function because of inductive rules. Statistical null hypothesis renders it possible to use tests of statistical significance to rule out happenstance as an explanation for research results. Basic concepts of descriptive statistics are introduced in the context of data collection, tabulation, derivation, and standardization. Issues related to psychometric measurement, correlation and regression are thereby explained as well. Random sampling distribution renders possible inferential statistics (viz., confidence interval, parameter estimation, hypothesis testing and goodness-of-fit). The book shows how standardizing random sampling distribution gives rise to parametric tests. In short, this book shows that research impartiality is possible despite the belief in (as well as instances of) “beauty is in the eye of the beholder.”
Integrating Analyses in Mixed Methods Research goes beyond mixed methods research design and data collection, providing a pragmatic discussion of the challenges of effectively integrating data to facilitate a more comprehensive and rigorous level of analysis. Showcasing a range of strategies for integrating different sources and forms of data as well as different approaches in analysis, it helps you plan, conduct, and disseminate complex analyses with confidence. Key techniques include: Building an integrative framework Analysing sequential, complementary and comparative data Identifying patterns and contrasts in linked data Categorizing, counting, and blending mixed data Managing dissonance and divergence Transforming analysis into warranted assertions With clear steps that can be tailored to any project, this book is perfect for students and researchers undertaking their own mixed methods research.
