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Research methods in human-computer interaction
Research Methods in Human-Computer Interaction is a comprehensive guide to performing research and is essential reading for both quantitative and qualitative methods.Since the first edition was published in 2009, the book has been adopted for use at leading universities around the world, including Harvard University, Carnegie-Mellon University.
eBook
Interpretive social science : an anti-naturalist approach
In this book Mark Bevir and Jason Blakely set out to make the most comprehensive case yet for an 'interpretive' or hermeneutic approach to the social sciences. Interpretive approaches are a major growth area in the social sciences today. This is because they offer a full-blown alternative to the behavioralism, institutionalism, rational choice, and other quasi-scientific approaches that dominate the study of human behavior. In addition to presenting a systematic case for interpretivism and a critique of scientism, Bevir and Blakely also propose their own uniquely 'anti-naturalist 'notion of an interpretive approach. This anti-naturalist framework encompasses the insights of philosophers ranging from Michel Foucault and Hans-Georg Gadamer to Charles Taylor and Ludwig Wittgenstein, while also resolving dilemmas that have plagued rival philosophical defenses of interpretivism. In addition, working social scientists are given detailed discussions of a distinctly interpretive approach to methods and empirical research. The book draws on the latest social science to cover everything from concept formation and empirical inquiry to ethics, democratic theory, and public policy. An anti-naturalist approach to interpretive social science offers nothing short of a sweeping paradigm shift in the study of human beings and society. This book will be of interest to all who seek a humanistic alternative to the scientism that overwhelms the study of human beings today.
Book
Compensating Wage Differentials in Labor Markets: Empirical Challenges and Applications
The model of compensating wage differentials is among the cornerstone models of equilibrium wage determination in labor economics. However, empirical estimates of compensating differentials have faced persistent credibility challenges. This article summarizes the Rosen model of compensating differentials and chronicles the advances, setbacks, and lessons learned from empirical studies. The progression from cross-sectional to panel models alleviated biases caused by unobserved human capital but yielded new insights into the importance of other biases, including those caused by labor market frictions and endogenous job mobility. I discuss recent approaches that use matched employer-employee data and quasi-random variation in job amenities to address some of these challenges. I then present two examples of applications of compensating differentials: the evaluation public health and safety policies that rely on the value of statistical life, and the measurement and interpretation of earnings inequality.
Journal Article
Handbook of research methods and applications in spatially integrated social science
\"The chapters in this book provide coverage of the theoretical underpinnings and methodologies that typify research using a Spatially Integrated Social Science (SISS) approach. This insightful Handbook is intended chiefly as a primer for students and budding researchers who wish to investigate social, economic and behavioural phenomena by giving explicit consideration to the roles of space and place. The majority of chapters provide an emphasis on demonstrating applications of methods, tools and techniques that are used in SISS research, including long-established and relatively new approaches.\" --Cover.
Book
A set of principles for conducting critical research in information systems
While criteria or principles for conducting positivist and interpretive research have been widely discussed in the IS research literature, criteria or principles for critical research are lacking. Therefore, the purpose of this paper is to propose a set of principles for the conduct of critical research in information systems. We examine the nature of the critical research perspective, clarify its significance, and review its major discourses, recognizing that its mission and methods cannot be captured by a fixed set of criteria once and for all, particularly as multiple approaches are still in the process of defining their identity. However, we suggest it is possible to formulate a set of principles capturing some of the commonalities of those approaches that have so far become most visible in the IS research literature. The usefulness of the principles is illustrated by analyzing three critical field studies in information systems. We hope that this paper will further reflection and debate on the important subject of grounding critical research methodology.
Journal Article
Measuring remote working skills: Scale development and validation study
Remote work, one of the most significant working arrangements of today, requires certain employee skills. Although there are some hints, there is not much information in the literature on this subject. This study aims to identify the skills required for productive remote working activities and to develop a scale for measuring these skills. For this purpose, a thorough review of the literature, consultation with experts, and analysis of data obtained from four samples with remote working experience were all conducted. Within this context, item generation and content validation, initial factor structure analysis, and factor structure confirmation and construct validity examination were performed. Consequently, the Remote Working Skills Scale was developed, which has 36 items and five dimensions (cybersecurity, problem-solving, time management, verbal communication, and written communication).
Journal Article
Sequential Analysis and Observational Methods for the Behavioral Sciences
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.
eBook
Big Data, Little Data, No Data
\"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.
eBook
Long-Run Effects of Dynamically Assigned Treatments: A New Methodology and an Evaluation of Training Effects on Earnings
We propose and implement a new method to estimate treatment effects in settings where individuals need to be in a certain state (e.g., unemployment) to be eligible for a treatment, treatments may commence at different points in time, and the outcome of interest is realized after the individual left the initial state. An example concerns the effect of training on earnings in subsequent employment. Any evaluation needs to take into account that some of those who are not trained at a certain time in unemployment will leave unemployment before training while others will be trained later. We are interested in effects of the treatment at a certain elapsed duration compared to “no treatment at any subsequent duration.” We prove identification under unconfoundedness and propose inverse probability weighting estimators. A key feature is that weights given to outcome observations of nontreated depend on the remaining time in the initial state. We study effects of a training program for unemployed workers in Sweden. Estimates are positive and sizeable, exceeding those obtained with common static methods. This calls for a reappraisal of training as a tool to bring unemployed back to work.
Journal Article