Background. Definitions of gamification tend to vary by person, both in industry and within academia. One particularly popular lay interpretation, introduced and popularized by Ian Bogost, and reiterated by Jan Klabbers, is that gamification is “bullshit” and “exploitationware.” They describe gamification as a marketing term or business practice invented to sell products rather than to represent a real and unique phenomenon relevant to a nascent game science. However, this view is an oversimplification, one which ignores a growing body of theory development and empirical research on gamification within a post-positivist epistemology. In fact, because gamification is so much more outcome-focused than general game design, current gamification research in many ways has a stronger footing in modern social science than much games research does. Aim. In this article, to address common misunderstandings like these, we describe the philosophical underpinnings of modern gamification research, define the relationship between games and gamification, define and situate gamification science as a subdiscipline of game science, and explicate a six-element framework of major concerns within gamification science: predictor constructs, criterion constructs, mediator constructs, moderator constructs, design processes, and research methods. This framework is also presented diagrammatically as a causal path model. Conclusion. Gamification science refers to the development of theories of gamification design and their empirical evaluation within a post-positivist epistemology. The goal of gamification scientist-practitioners should be to understand how to best meet organizational goals through the design of gamification interventions, drawing upon insights derived from both gamification science and games research more broadly.

The term encompasses a wide range of approaches of collecting and analyzing data in ways that were not possible before the era of modern personal computing. One approach to big data of great potential to psychologists is web scraping, which involves the automated collection of information from webpages. Although web scraping can create massive big datasets with tens of thousands of variables, it can also be used to create modestly sized, more manageable datasets with tens of variables but hundreds of thousands of cases, well within the skillset of most psychologists to analyze, in a matter of hours. In this article, we demystify web scraping methods as currently used to examine research questions of interest to psychologists. First, we introduce an approach called theory-driven web scraping in which the choice to use web-based big data must follow substantive theory. Second, we introduce, a term used to describe the assumptions a researcher must make about a prospective big data source in order to meaningfully scrape data from it. Critically, researchers must derive specific hypotheses to be tested based upon their data source theory, and if these hypotheses are not empirically supported, plans to use that data source should be changed or eliminated. Third, we provide a case study and sample code in Python demonstrating how web scraping can be conducted to collect big data along with links to a web tutorial designed for psychologists. Fourth, we describe a 4-step process to be followed in web scraping projects. Fifth and finally, we discuss legal, practical and ethical concerns faced when conducting web scraping projects. (PsycINFO Database Record

Game-thinking is beginning to appear in a wide variety of non-game contexts, including organizational support settings like human resource management (HRM). The purpose of this chapter is two-fold: 1) to explore the opportunities for game-thinking via gamification and serious games in HRM based on current and previous HRM literature and 2) to identify future research areas at the intersection of game-thinking and HRM. Prevailing HRM theories will be applied to the use of game-thinking in different sub-fields of HRM, including recruitment, selection, training, and performance management.

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