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1091 results in Qualitative research methods

Page 29 of 55

  • 5 - Using the Internet for Research

  • from Part One - Performing Good Research
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book:
    Advanced Research Methods for the Social and Behavioral Sciences
    Published online:
    22 February 2019
    Print publication:
    14 March 2019, pp 68-82

  • Summary

    The Internet was created in the mid-20th century as a communication tool for American scientists. Since then, it has grown into a tool that much of the world’s population uses on a daily basis for a wide variety of reasons ranging from social interaction, commerce, and to obtain information. Given its ubiquity, the amount of scholarship on the use of the Internet for conducting research has grown along with it. To date, thousands of books and journal articles include research conducted on the Internet using myriad research methodologies and theoretical perspectives. This chapter reviews the literature on Internet research, exploring questions such as: What is Internet research? What topics do social scientists study on the Internet? What are the different approaches for conducting research on the Internet? Ethical considerations for Internet research, suggestions for best practices in using the Internet for research, and recommendations for future research conclude this chapter.

  • 18 - A Gentle Introduction to Bayesian Statistics

  • from Part Five - New Statistical Trends in the Social and Behavioral Sciences
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book:
    Advanced Research Methods for the Social and Behavioral Sciences
    Published online:
    22 February 2019
    Print publication:
    14 March 2019, pp 289-308

  • Summary

    Bayesian methods are becoming more popular in the social sciences because they offer solutions to problems that arise with classical methods, e.g., convergence issues and the inability to interpret the results probabilistically. However, Bayesian statistics remain controversial because they require specifying prior distributions that reflect the researcher’s state of knowledge before observing the data. Critics of Bayesian statistics note that prior distributions allow researchers to sway the results in the desired direction. This chapter shows how to conduct a Bayesian mediation analysis using real data from a study of delays in PhD completion in the Netherlands. The authors illustrate the challenges in specifying prior distributions and how to examine the influence of a prior distribution in a sensitivity analysis. The chapter also contains detailed examples of how to report the results of a Bayesian mediation analysis and future directions for the field of applied statistics for social sciences.

  • 3 - Performing Research in the Laboratory

  • from Part One - Performing Good Research
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book:
    Advanced Research Methods for the Social and Behavioral Sciences
    Published online:
    22 February 2019
    Print publication:
    14 March 2019, pp 38-52

  • Summary

    The current chapter attempts to cover the most important aspects of conducting research in the laboratory while allowing the reader to refer to other chapters in this volume to better understand the most prevalent and important limitations of the lab. We begin by describing what a lab is and by giving examples, from our own research and others, of the many different ways that a normal space can be used for laboratory research. We then explore the many advantages and disadvantages that often result from lab research, followed by the different types of research that are often conducted in the lab. Next, we move on the some of the many issues that one must consider when conducting lab research. We focus this section on issues related to both participants and potential research assistants, including recruitment, training, and minimizing biases. Following this, we present the different types and uses of deception while encouraging the reader to carefully examine each research question and study design before making any research decision. Finally, we discuss the generalizability of lab research to the real world and provide some considerations for increasing the likelihood that your research will generalize.

  • 16 - Interdisciplinary Research

  • from Part Four - Emerging Issues in Social and Behavioral Science Research
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book:
    Advanced Research Methods for the Social and Behavioral Sciences
    Published online:
    22 February 2019
    Print publication:
    14 March 2019, pp 258-273

  • Summary

    Interdisciplinary research (IDR) focuses on particular problems or questions that are too comprehensive to be answered satisfactorily by any one discipline. Overall, across disciplines, the practice of IDR is rapidly accelerating because the combination of researchers from different disciplines allows complicated problems to be solved. There is an urgent need for IDR and specific interdisciplinary training to address pressing social, political, economic challenges society faces. Additionally, the necessity to prepare students for an increasingly interdisciplinary, collaborative, and global future also calls for interdisciplinary exposure in post-secondary education. In this article, we aim to provide an explanation of IDR, and to offer a guiding framework towards interdisciplinary research with measurable and positive impact.

  • 10 - Physiological Measures

  • from Part Three - The Social and Behavioral Scientist’s Toolkit
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book:
    Advanced Research Methods for the Social and Behavioral Sciences
    Published online:
    22 February 2019
    Print publication:
    14 March 2019, pp 147-167

  • Summary

    Many studies in behavioral science involve physiological measures because they allow the researcher a window into some underlying neural and biological processes. The use of such measures requires a multiple-levels-of-analysis approach to understanding behavior, where the physiological processes are just one level of analysis that should be considered in conjunction with others, such as the social situation or the structure of society. We provide an overview of three basic principles of psychophysiology that are important to consider when planning and interpreting research with these measures. We then give a brief introduction to most commonly used measures, including those that tap into in the autonomic nervous system (e.g., electrodermal activity, heart rate), hormones (e.g., cortisol, testosterone), muscle activity (e.g., facial electromyography), and the brain (e.g., event-related potentials, functional brain imaging). The chapter concludes with tips for reducing participant anxiety during experiments, which can otherwise interfere with physiological recordings.

  • 20 - Social Network Analysis

  • from Part Five - New Statistical Trends in the Social and Behavioral Sciences
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book:
    Advanced Research Methods for the Social and Behavioral Sciences
    Published online:
    22 February 2019
    Print publication:
    14 March 2019, pp 328-345

  • Summary

    This chapter provides an introduction to Social Network Analysis (SNA) for social scientists that are new to the method. As a theoretical perspective and a research method, SNA distinguishes itself from other research methods by focusing on social relationships and the idea that social actors (e.g., individuals, groups, organizations, and countries) are influenced by the patterns of social relations surrounding them. SNA enables researchers to investigate these patterns and understand their antecedents and consequences. In this chapter, we articulate the logic of key network concepts and provide a visual roadmap that helps researchers in navigating through measures and methods and at different levels of analysis. Extensive references to further readings, empirical applications, and methodological contributions are given.

  • 11 - Eyetracking Research

  • from Part Three - The Social and Behavioral Scientist’s Toolkit
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book:
    Advanced Research Methods for the Social and Behavioral Sciences
    Published online:
    22 February 2019
    Print publication:
    14 March 2019, pp 168-190

  • Summary

    Despite our conscious experience, the image quality (and information density) of the human visual system varies dramatically across the visual field. Only a small, central fovea (covering less than 0.01% of the visual field) provides enough acuity to support common tasks like reading. The oculomotor system overcomes this limitation by rapidly rotating the eyes to foveate objects of interest with saccades and stabilizes those objects with a range of other eye movements. Critically, humans usually foveate objects that they attend to, even if those objects do not require high acuity, so an observer’s point of gaze offers an externally observable marker of attention. Chapter 11 describes the oculomotor system, a taxonomy of eye-movement types, the different types of eyetracking instrumentation available to monitor gaze in the laboratory and in natural environments, data quality issues in eyetracking, and introduces several sample applications in the social sciences.

  • 14 - Replications and the Social and Behavioral Sciences

  • from Part Four - Emerging Issues in Social and Behavioral Science Research
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book:
    Advanced Research Methods for the Social and Behavioral Sciences
    Published online:
    22 February 2019
    Print publication:
    14 March 2019, pp 229-243

  • Summary

    Replication is an essential part of the scientific process, but replicable research has been more of an assumption than a practice. Over the last few years a number of high profile replicability projects have raised questioned about the replicability of research in a variety of disciplines and brought the practice of replication to the forefront of scientific discourse. But how do researchers decide what kind of replication to do and what are the steps needed to conduct a replication? This chapter briefly summarizes different types of replications and the different ways they contribute to scientific knowledge. Step-by-step guidance for researchers looking to conduct replications is described, as well as a discussion of how to interpret results and new options for publishing replications.

  • 4 - Field Research

  • from Part One - Performing Good Research
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book:
    Advanced Research Methods for the Social and Behavioral Sciences
    Published online:
    22 February 2019
    Print publication:
    14 March 2019, pp 53-67

  • Summary

    Fundamentally, social and behavioral scientists want to understand and explain human behavior. Research with human subjects conducted in laboratory settings removes people from their natural environment and thus potentially changes how they would otherwise behave. Field research, which involves observing and participating in people’s lives and keeping a detailed written record of those experiences and observations, is a powerful method for documenting and explaining people’s behaviors in situ. This chapter discusses the practice of field research for social and behavioral scientists. The chapter is largely intended as a primer on field research and covers topics such as: getting started on a field research project; locating the researcher in fieldwork; gaining access to a fieldsite; conducting field experiments; writing fieldnotes and notes-on-notes; ethics in field research; developing an analysis; and exiting the field. The chapter ends by considering several issues and debates around contemporary fieldwork and posing ideas for future research.

  • 9 - Suspicion Probes and Debriefing in the Social and Behavioral Sciences

  • from Part Two - Understanding Issues Present Throughout the Research Process
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book:
    Advanced Research Methods for the Social and Behavioral Sciences
    Published online:
    22 February 2019
    Print publication:
    14 March 2019, pp 129-144

  • Summary

    When participants are deceived in experimental research, researchers in the social and behavioral sciences must make several ethical and methodological considerations, including how to debrief participants and how to probe for participant suspicion. Because participants must be debriefed whenever an experiment involves deception, we discuss the debriefing process, including how to reduce potential harm to participants while maintaining experimental control. We also discuss several methods researchers may use to probe for participant suspicion and knowledge as well as empirical research examining the effectiveness of suspicion probes. Finally, we make recommendations to researchers in the social and behavioral sciences on how to best debrief participants and probe for participant suspicion and knowledge.

  • 12 - Questionnaire Design

  • from Part Three - The Social and Behavioral Scientist’s Toolkit
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book:
    Advanced Research Methods for the Social and Behavioral Sciences
    Published online:
    22 February 2019
    Print publication:
    14 March 2019, pp 191-208

  • Summary

    Questionnaires are one of the most common data collection tools because of their versality and ease of use. However, designing a valid and reliable questionnaire can be difficult without a thoughtful approach to design and distribution. This chapter details considerations researchers should take into account prior to questionnaire development, how to approach writing questionnaire items, and challenges they may encounter when administering their questionnaire. The chapter provides examples for rethinking questionnaire design and offer recommendations for how to avoid falling into questionnaire pitfalls.   

  • 8 - Experimenter Effects

  • from Part Two - Understanding Issues Present Throughout the Research Process
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book:
    Advanced Research Methods for the Social and Behavioral Sciences
    Published online:
    22 February 2019
    Print publication:
    14 March 2019, pp 115-128

  • Summary

    Experimenter effects, or the impact that an experimenter can independently have on a study’s outcome, is an important consideration in social and behavioral research. These effects can occur in two ways. Noninteractional experimenter effects involve study biases that do not directly impact participants’ actual behaviors. Examples include biases in the decisions an experimenter makes, such as choice of study stimuli, types of observations made, and data analysis strategies. Interactional experimenter biases arise through the interactions between the experimenter and the participant. Examples include the experimenter’s biosocial and psychosocial attributes which may affect a participant’s behavior independent of the study variables. Experimenter expectations can also bias a study’s outcome in favor of its hypotheses. The potential for experimenter effects emphasizes the importance of good study design, including the use of properly trained experimenters blind to the study’s hypotheses and transparency in one’s study decisions.

  • 13 - Reaction Time Measures in the Social and Behavioral Sciences: Speed Matters

  • from Part Three - The Social and Behavioral Scientist’s Toolkit
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book:
    Advanced Research Methods for the Social and Behavioral Sciences
    Published online:
    22 February 2019
    Print publication:
    14 March 2019, pp 209-226

  • Summary

    The term reaction time (RT) describes the interval between the initial appearance of a stimulus and an organism’s response to that stimulus. How is reaction time measured? And why is it of great interest to social and behavioral scientists? To address these key questions, this chapter unfolds in four major sections: (1) An overview of the evolution of reaction time research, including key historical developments; (2) a discussion of the state of reaction time knowledge today, including key variables that moderate RTs such as task type, sensory modality, stimulus intensity and complexity, and arousal; (3) a review of common reaction time measures employed by contemporary social and behavioral scientists, such as the Stroop test, Eriksen flanker task, and Implicit Association Test; and (4) a description of specific technological tools that can be used to administer RT measures in both offline and online settings.

Page 29 of 55