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Constructs of simulation evaluation
Published in Florian Jentsch, Michael Curtis, Eduardo Salas, Simulation in Aviation Training, 2017
Andrew Hale Feinstein, Hugh M. Cannon
All of these terms refer to representational validation. Although their conclusions are useful in studying educational processes, they are nevertheless quite different from studies of educational validation. As we see in Figure 1. the desired output from an educational simulation is not an accurate replication of what would happen in the real world at all but rather a set of skills that will help students make real-world decisions. In this context, then, external validation means either the demonstration that a simulation teaches key business skills (validation as a method of teaching) or that key business skills are needed to perform well in a business simulation game (validation as an assessment instrument).
In praise of stupid
Published in Dale Leorke, Marcus Owens, Games and Play in the Creative, Smart and Ecological City, 2020
Jonathan Jae-an Crisman, Ken S. McAllister, Judd Ethan Ruggill
Interest in this kind of human-designed, machine-coordinated vision of player experience, learning and behaviour via computationally intelligent and adaptive systems is hardly new, however. Rolf F. Nohr’s compendious Unternehmensplanspiele 1955–1975: Die Herstellung unternehmerischer Rationalität im Spiel [Business Simulation Games 1955–1975: The Invention of Game-Based Entrepreneurial Rationality] (2019) extensively catalogues the earliest efforts to build ‘smart’ games – developed and deployed in the military–industrial complex – that functioned as corporate training tools and, at a broader level, as intellectual, cultural and ideological steering mechanisms. These efforts were extended into popular culture in the 1970s by toy and game manufacturers – Mattel, for instance, releasing its Intellivision (‘intelligent’ + ‘television’) game system in 1979, a system that the company described as a ‘master component’ that could, according to a 1980 television advertisement, ‘change your family’s life’ (Mattel, 1980). Over subsequent decades, game companies have increasingly committed portions of their research and development budgets to projects aimed specifically at automating those elements of the game development process still driven by human creativity: level design, plot development, character dialogue and sound. In 2001, for example, Epic Games collaborated with North Carolina State University Professor R. Michael Young and his Liquid Narrative Research Group to develop the Mimesis System: ‘an implementation of an intelligent controller for virtual worlds that generates and maintains a coherent, narrative-based storyline’ (p. 77). According to the Mimesis System’s creators, the underlying architecture ‘combines current research work in AI planning and natural language discourse generation with the real-time control of an existing commercial game system, Epic Games’ Unreal Tournament’ (p. 77).
The market evaluation
Published in Paul Clark, Buying the Big Jets, 2017
The model we shall use is based on the ‘SkyChess’ airline business simulation game. Before processing the data, we need to construct a mechanism that allows us to track variations of demand according to time of day. For the purposes of this illustration we shall divide the operating day into segments of 15 minutes. These segments must be small enough so that each can accommodate no more than one flight in the schedule.
What happens when decision support systems fail? — the importance of usability on performance in erroneous systems
Published in Behaviour & Information Technology, 2019
Philipp Brauner, Ralf Philipsen, André Calero Valdez, Martina Ziefle
The following section introduces a methodological approach to studying complex systems with user interaction: business simulation games. Business simulations and business simulation games are an established method not only for conveying knowledge to learners but also to understand how people interact with underlying business models (Zyda 2005; Deshpande and Huang 2011; Brauner and Ziefle 2016). In contrast to field studies in companies, they are sufficiently complex and allow systematic manipulation of user, interface and system factors to study their influence on relevant (game) metrics, such as production efficiency or the attained overall profit.