Designing a Digital Medical Management Training Simulator Using Distributed Cognition Theory

Rybing, Jonas; Prytz, Erik; Hornwall, Johan; Nilsson, Heléne; Jonson, Carl‐Oscar; Bång, Magnus

doi:10.1177/1046878116676511

Cited by 9 publications

(9 citation statements)

References 36 publications

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“…The DigEmergo simulation system used in this study was developed in a collaboration between the Centre of Teaching and Research in Disaster Medicine and Traumatology (KMC) and Linköping University based on the existing training system Emergo Train System (Rybing et al, 2015(Rybing et al, , 2016. The participants worked with DigEmergo on a 65" touchscreen with 1920x1080 resolution running on standard workstation Windows 7 PC.…”

Section: Equipmentmentioning

confidence: 99%

Short simulation exercises to improve emergency department nurses' self-efficacy for initial disaster management: Controlled before and after study

Jonson

Pettersson

Rybing

et al. 2017

Nurse Education Today

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Section: Equipmentmentioning

confidence: 99%

Short simulation exercises to improve emergency department nurses' self-efficacy for initial disaster management: Controlled before and after study

Jonson

Pettersson

Rybing

et al. 2017

Nurse Education Today

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“…The first emphasizes the learning of the individual, the second focuses on policy making and the collective learning and support of real decision making within groups of actors and stakeholders, and the third includes gaming simulation applications that help organizational (re)design for the innovation and improvement of a system. An example of the last subcategory is the design and evaluation of a digital medical management training simulator [48] because the debriefing of a training exercise can be used for reflection on cooperation strategies in the organizations of the participants. Another example of a simulator in this category is one for training crisis management.…”

Section: Training Simulator Evolutionmentioning

confidence: 99%

A Framework for Monitoring Evolution and its Drivers in Training Simulators

Hvannberg

2019

JoIS

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Software systems evolve with societal, business and technological changes. Because of these changes, socio-technical systems need to adapt to new situations that were unknown at the time of design. Good knowledge of software system evolution can help with that adaption. Although the evolution of software systems has been broadly debated, little research has been conducted on the specific genre of software systems and even less empirical research has been performed on the evolution of interactive software. We propose a three-factor framework which consists of identifying the changes during the evolution of training simulators, the drivers for those changes and how the changes effect innovation and robustness of the training simulators. In reviewing the literature on training simulators, we argue for this framework. The contribution of this paper is a framework that can be used to carry out empirical studies on the evolution of training simulators. Interaction ScienceSoftware systems evolve with societal, business and technological changes. Software technologies are said to evolve in a Darwinian manner by co-evolving with human culture [1]. Societal changes, including the migration of people and workers, poverty, health and education, can influence how software systems evolve. Business operations and their marketplace can be drivers of the evolution of software systems. Furthermore, innovations in technologies for building software systems influence their evolution. Because of these changes, today's sociotechnical systems need to adapt to new situations that were unknown at the time of design [2]; good knowledge of interactive software system evolution can help with that adaptation. Sociotechnical systems cover hardware, software, personal and community aspects [3] and when we refer to interactive software systems in this paper, we are not limiting the discussion to the software and its users. An example of a sociotechnical system is a training simulator for managing the response to large scale accidents such as those involving aircraft or trains. It concerns the hardware used, the software developed, the trainers and trainees using the system, and the community surrounding the professions and stakeholders. The development of such training simulators is costly. Training simulators can be long-lived up to several decades and thus undergo various changes in the course of use. Examples of these are changes because of improved work processes that are discovered during training exercises or real response, or demand for higher fidelity as trainees, for example firefighters training to extinguish fires.Researchers have debated whether there exist such things as revolutionary products, or inventions, or if all are evolutionary [4, p.86], created in small steps visible only to the designer but invisible to the consumer [5, p.2]. Vicente [6] distinguished between revolutionary design and evolutionary design problems. Whereas in the former, the constraints decided on in past versions can change, in the latter, the constraints...

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“…A different intersection is described by Jonas Rybing, Erik Prytz, Johan Hornwall, Heléne Nilsson, Carl-Oscar Jonson, and Magnus Bang (2016). Their article “Designing a Digital Medical Management Training Simulator Using Distributed Cognition Theory” link the application type IIa with categories IIb and IIc.…”

Section: Contents Of This Issue’s Simulation and Gaming Applicationsmentioning

confidence: 99%

Types of Gaming Simulation Applications

Kriz¹

2017

Simulation & Gaming

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In the last editorial articles my co-editors J. Tuomas Harviainen (2016) and Timothy C. Clapper (2016) described the rich history and currently growing interest in gaming simulation and discussed the diversity of the field. Jan Klabbers (2006) has pointed out that the diversity is partly related to the fact that contributors of articles on gaming simulation find themselves in a dual position. Researchers in gaming simulation may represent two distinct branches of science: the design sciences and the analytical sciences.In articles related to gaming simulation we therefore find different types of gaming simulation applications that can be grouped into the following categories:I. Traditional academic research is directed at extending domain-specific knowledge by using simulation games as experimental environments and behavioral labs. The analytical science perspective uses games and simulations as scenarios to empirically test, justify and develop theories in specific domains. The main focus is on creating universal and context independent knowledge (e.g. Klabbers, 2009). II. The science of design perspective puts an emphasis on the usability of simulation games. Here, games and simulations themselves are studied with the aim of supporting and evaluating their development and use in practical contexts (e.g. Greenblat & Duke, 1975). The main focus is on dealing with an interdisciplinary and practical approach to simulation game design (as science, art and craft) with local knowledge and unique problems or challenges. Design-inthe-small (Klabbers, 2006) produces gaming simulations (gaming artifacts) as interventions and interactive learning environments. Used with that goal in mind, they contribute to the design-in the-large process of socio-technical systems (e.g. for change management and organizational development). In practice, simulation games refer to a large number of different approaches. These include: computer simulation, behavior-oriented role plays with or without computer-assisted simulation, hands-on board games, but also more recent approaches such as digital and non-digital educational games, game-basedlearning, and web-based simulation games. Also significant are those areas currently discussed with reference to buzzwords such as serious games andSimulation & Gaming 48 (1) meaningful play. Nowadays these terms also describe the educational use of games with 3D video technology (sometimes games that were originally created for entertainment purposes). IIa. Many applications of gaming simulation fall into the category of education and training simulation games (e.g. Crookall et al., 1988). Here simulation games are for example used as experiential teaching and learning methods in order to foster knowledge acquisition, development of skills and competencies, understanding of complex relationships and especially facilitating simulation games to train performance of dangerous tasks in a safe learning environment. The focus of applications in this category is very often on the individual learning outcome ...

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Designing a Digital Medical Management Training Simulator Using Distributed Cognition Theory

Cited by 9 publications

References 36 publications

Short simulation exercises to improve emergency department nurses' self-efficacy for initial disaster management: Controlled before and after study

Short simulation exercises to improve emergency department nurses' self-efficacy for initial disaster management: Controlled before and after study

A Framework for Monitoring Evolution and its Drivers in Training Simulators

Types of Gaming Simulation Applications

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