Learning in vivo

Post-simulation reflection

Margaret Gredler (1992: 141 – 159) emphasises the role of post-simulation activities and the planning thereof. She asserts that simulations are experiential in nature in that participants “step into the assigned roles, accept the responsibilities and constraints and work through the problems and difficulties that arise in the execution of the roles”. To overcome the reality of can’t see the woods for the trees (because of active involvement in the simulation); bring the learning forth; and to maximise the learning; reflection about the simulation is essential.

Gredler (1992) discusses two experiential learning models, namely Kurt Lewin’s (a Gestalt theorist) group-dynamics model and Jean Piaget’s (a Swiss psychologist) cognitive development model.

Jaques (1985, referenced in Gredler) describes the adaptation of Lewin’s ideas in a five-part experiential learning cycle, which upon completion feeds into another cycle.

Piaget postulates that cognitive structures happens through two processes; namely by means of assimilation of new information into the existing to enrich; and by accommodating which can occur in two different ways. The one way of accommodation is modification in order to integrate new information; the other way is through reconstruction to a higher level of thinking.

Post-simulation reflection need to form part of and conclude the simulation. In a distance learning context, this could be achieved through online discussion.

Gredler, M. 1992. Designing and evaluating games and simulations, a process approach. London: Kogan Page.

Jaques, D. 1985. Debriefing, debriefing, 55 – 66. In M van Ments and K Hearndon (eds). Effective use of games and simulations. Loughborough: SAGSET, Loughborough Institute of Technology.

Composing a simulation

Professor Margaret E. Gredler, at the Department of Educational Psychology of the University of South Carolina since 1973, obtained her PhD in Instructional Design Research. She published substantially in the field, among others the 1992 & 1994 editions of Designing and evaluating games and simulations.

In another post I captured the four questions Jones (1995 & 1997) recommends for designing a simulation. A synthesis of chapters 4 to 10 (Gredler 1992: 53 – 140) produced the following composition elements:

• Establish a framework/blueprint — instructional designers cannot simply present a curriculum issue, assign roles, and different perspectives; the simulation must be designed systematically in order that participants can interpret data rationally and devise strategies to resolve the issue at hand.
• The opening scene sets the stage for the simulation — it should be brief; and describe the issue in concrete but neutral terms.
• Nature/climate of the crisis or problem — the term ‘crisis’ originate from Greek krinen, which means to separate; to judge — the simulation is essentially a potential turning or branching point which participants are required to address.
• Designate the roles of participants in the simulation.
• Post simulation debriefing and reflection

Gredler, M. 1992. Designing and evaluating games and simulations, a process approach. London: Kogan Page.

Tactical-decisions and social-system simulations

Higher education graduates often acquired little more than textbook problem abilities. Although theory taught is sometimes followed by some clinic, workshop, laboratory, practicum, field experience, clinical/workplace experience, or internship; students often lack the opportunity to develop their own cognitive and systematic problem-solving ability. Furthermore, the different situations individual students are exposed to often vary substantially in complexity and difficulty, resulting in the development of varied abilities. Gredler (1992) suggests that tactical-decision simulations can alleviate this shortcoming in problem-solving ability. Such simulations entail a situation that require of participants to make independent decisions in a dynamic environment. Tactical-decision simulations involve data-interpretation and management decision-making. Gredler (1992) presents three kinds:

• Diagnostic simulations help develop the ability to solve complex evolving problems, which is a requirement of several career-paths and walks of life. Two sub-types are common, namely professional-client/patient situations and solve-the-mystery challenges.
• Crisis-management simulations in the form of a scenario that requires appropriate intervention. Different participants fulfil different roles in seeking a solution to avert or minimise an impending threat or danger, which escalates and become more acute as time passes.
• Data-management simulations entail the manipulation of quantifiable variables, such as financial. In contemporarily society the ability to manage data and make trade-offs in order to thrive (and survive) is a given. Two simulation formats exists, namely closed-structure for individual roles to manage data and open-structure for team-collaboration. Simulation-design issues typically include the relevant mathematical model and identification of the key decisions required from participants.

Gredler (1992) further suggests social-process-simulations which require of participants to focus on interactions among people. The beliefs, assumptions, and goals of individual participants and significant others may hinder or assist. Social-process-simulations also include three kinds:

• Social-system simulations include the integrate fabric of inter-relations of groups further complicated by different cultures, religions and personalities. Decision-making that involves the interaction among people is of particular importance.
• Language-skills and communication is crucial to social-processes. Simulations are powerful ways of mastering language, including written and verbal communication.
• Empathy and insight simulations enact typical fast pace and competing demand realities of life, which are not conducive to demonstrating sensitivity and empathy. The aim of these simulations is for participants to acquire insight in the feelings of other and to demonstrate empathy.

Gredler, M. 1992. Designing and evaluating games and simulations, a process approach. London: Kogan Page.

Development through assessment centre simulations

The three common uses of assessment centres (slide 25) include (a) selection; (b) diagnosis; and (c) development. While reading about simulations I recalled my own experiences with assessment centres. A quick search confirmed my expectations.

Five major characteristics of simulations

In the 1960s interactive group exercises represented a staple in education and training curricula, remarks Gredler (1992). However some 30 years later comprehensive design guidelines were lacking.

The term simulation has five major descriptive characteristics, states Gredler (1992: 16), which are:

1. Simulations are problems-based units of learning that are set in motion by a particular task, issue, policy, crisis, or problem. The problems to be addressed by the participant may be either implicit or explicit, depending on the nature of the simulation.
2. The subject matter, setting and issues inherit in the simulation are not textbook problems or questions in which answers are cut-and-dried and determined quickly.
3. Participants carry out functions associated with their roles and the settings in which they find themselves.
4. The outcomes of the simulation are not determined by chance or luck. Instead, participants experience consequences that follow from their own actions
5. Participants experience reality of function to the extent that they fulfil their conscientiously and in a professional manner, executing all the rights, privileges and responsibilities associated with a role.

Gredler, M. 1992. Designing and evaluating games and simulations, a process approach. London: Kogan Page.

When selecting a simulation

By reading a ready-made simulation’s notes and inspecting the documents unfortunately does not reveal the likely unfolding and flow of the interactions among participant, observes Jones (1995) with regard to choosing a simulation for a particular purpose. Often clues, suggestions and options are concealed within the design of the simulation.

Selection by the inexperienced is often based in incorrect assumptions, such as:

• Voluminous documents and materials imply complexity, which may indeed be a faulty assumption.
• In contrast, few documents are assumed to be inadequate and that participants may not know what to do.

Even lecturers/facilitators experienced in making use of simulations often have difficulty foreseeing how well a specific simulation may function.

Jones (1995) suggests that when choosing a simulation one should take on a role after reading the notes and envisage how a participant would perceive it.

Jones (1995: 80 – 94) offers an inventory of conditions upon which to base choice:

• Budget and value for money
• Number of participants
• Required timeframe
• Abilities of the target participants
• Materials required
• Space restrictions versus requirements
• The extent to which the objectives of the simulation match the intended learning outcomes
• Conveying facts and/or information
• The model inherent to the simulation
• The openness (or closed) nature for enabling decision-making
• The communication skills inherent to the simulation
• Language usage requirements
• The behavioural objectives
• The relationship/team-building value
• Prediction practice it offers

Jones, K. 1995. Simulations, a handbook for teachers and trainers. 3^rd edition. London: Kogan Page.

Ethical simulations

Jones (1995: 68-69) cautions about deception, however small, and the long-term effects thereof. He indicates two kinds of ethics at play in simulations, namely:

• Outside ethics as it pertain to the real world
• Ethics inside the simulation—values, beliefs and feelings—as experienced, portrayed and/or enacted by participants

Both kinds of ethics could be explicit or implicit. Both kinds may be inherent in the simulation materials; introduced by participants; or introduced by the facilitator—who has the responsibility to prevent harm taking place, as well as defuse and/or address the potential negative impact through the debriefing at the end of the simulation.

Jones (1997: 110-111) identify, in contrast to the above, three categories of ethics:

1. The facilitator's ethics
2. The ethics of the scenario — Jones caution about potential lip service with regard to simulations aimed at encouraging awareness. He asserts that people resent manipulation.
3. The ethics participants enact within the simulation

Jones, K. 1995. Simulations, a handbook for teachers and trainers. 3^rd edition. London: Kogan Page.

Jones, K. 1997. Games & somulations made easy. London: Kogan Page.

Quality assurance of simulations

The assessment of the quality of simulations, Jones (1995) observes, entails the conceptual judging of three notions:

• Consistency — is the simulation consistent within itself?
• Balance — is it balanced or does it allow for passive observation?
• Plausibility — is the scenario/situation (such-and-such) plausible?

The three concepts tend to fuse in that what may be implausible also tend to be inconsistent and as result lack balance.

Plausibility does not equate to “does the simulation imitate real life?” — Simulations are not meant to be imitations or simplifications of real-life. However, simulations allow for analogies, metaphors and upside-down realities/reversed positions. Plausibility does not restrict roles to being human.

Jones (1995: 62) caution designers about inconsistency as result of ‘author-muddling’. Often designers ‘improve’ simulations after try-out for publication purposes; assuming the final version is better. However, alterations may cause imbalances, which may impact on plausibility.

Jones, K. 1995. Simulations, a handbook for teachers and trainers. 3^rd edition. London: Kogan Page.

The design of simulations

Literature on simulation design reveals numerous step-by-step designs, report Jones (1995: 60), often in the form of a sequential flow diagram, for example:

Jones (1995) finds such a sequential process restricting, because creating a simulation is not about a series of tasks. Instead designing simulations involve imagination, values, and consistency he says. Jones (1995: 61 & 1997: 121) recommends four basic questions for design:

1. What is the problem? — issue, situation (or what is the event about? — general picture)
2. Who are the participants? — roles, identities, powers
3. What do they have to do? — job, decision-making, function
4. What do they do it with? — documents, materials, instructions, existing knowledge

Jones cautions that these four questions should not be seen as steps; but rather a conscious underlying methodology. The questions should not be answered explicitly either—Jones (1995: 61) points out that all well designed simulations contain implicit answers to the four questions.

Jones, K. 1995. Simulations, a handbook for teachers and trainers. 3^rd edition. London: Kogan Page.

Jones, K. 1997. Games & simulations made easy. London: Kogan Page.

Modes of interactive events; real-life and ambivalence

Jones (1995: 16-17) postulates that academics mostly regard ‘real life’ to mean realities outside simulations. However, he differentiates four kinds of ‘real life’, namely:

1. Reference points pertain to customary, legal, and ordinary that gives simulations a common code of conduct — Jones gives the example of meetings usually voting on an amendment, before voting on the motion itself.
2. Consequences of real life imply the long-term repercussions, ethics, environmental impact, etc.
3. Mimicry belongs on stage or in movies, but is not appropriate in a simulation — participants should during debriefing be capable to substantiate their behaviour exhibited during.
4. Intrusions are prevalent of real life and take many forms; intrusions may be constructive and/or disruptive — it is not advisable that facilitators intrude in a simulation, because inevitably the facilitator ends up being blamed by participants

In addition to real life, Jones (1995) differentiates simulations, role plays, games and exercises as various modes of interactive methodologies. He also adds ambivalence:

Ambivalent/ce originate from Latin ‘ambi’ meaning ‘both’ & ‘valentia’ meaning ‘strength’ or ‘valere’ meaning ‘be strong’ — it is the simultaneous/coexisting conflicting/opposing/contradictory feelings/ attitudes/view points, such as attraction and repulsion. Jones (1995: 19) uses the term ambivalence for an interactive event that is incompatible and entail conflicting methodologies, which may cause considerable harm—both personally and interpersonally—and are best avoided.

Jones, K. 1995. Simulations, a handbook for teachers and trainers. 3^rd edition. London: Kogan Page.

Simulations in context

Simulations have the power to challenge and alter the beliefs, as well as to promote flexibility with regard to decision making and management styles, argue Wolfe and Keys (1997). They emphasise the value of sensitivity to cultural diversity and appreciation for different values and perspectives, particularly in foreign global situations. “Unlike games, where everyone has a role of player with a duty to try to win, simulations require ‘professional behaviour, including professional ethics”, assert Jones (1995: 7). Simulations in group-settings offer experiential and active learning opportunities that are reasonably realistic and psychologically safe learning situations in that in these contexts psychological assumptions can be challenged; perspectives broadened; and critical reflection simulated (Wolfe & Keys, 1997).

A simulation should not attempt to reproduce reality, says Jones (1995: 9-10). The more an attempt is made to reproduce the real world with all the intricate complexities, he cautions, the more unworkable the simulations becomes. He puts forward four essential characteristics, namely:

• Simulation participants each have functional roles to fulfil, including the authority
• Given adequate information about the setting, problem or issue is essential — participants should not be required to invent the key facts (however improvisations and using imagination is encouraged); if participants are required, it is not a well designed simulation
• The lecturer does not play an active part in the carrying out the required action — a simulation is “a NON-TAUGHT event” [emphasis added], during which mistakes are “inevitable and desirable” — best characterised by “what actually goes on in the minds of the participants” (p. 12)
• Simulations are concluded with debriefing and reflection in order to appraise what happened and consolidate the learning

Jones (1995: 14) emphasises a clear differentiation of terminology and caution that wrong word-choices could cause simulations to go terribly wrong, because (wrong) words lead to (wrong) expectations which in turn lead to (inappropriate) behaviour:

Appropriate	Inappropriate
Simulation, activity, event Participant Facilitator (or organiser) Behaviour, function, profession Role (functional) Real-world responsible behaviour Real-world ethics Professional conduct	Game drama, role play, exercise Player, actor, puzzler, trainee, student [Lecturer, tutor], teacher, trainer, instructor Player, acting, staging, puzzling Role (acting a part) Winning (losing) the game Point scoring, having fun Performing the exercise (game, etc)

Jones, K. 1995. Simulations, a handbook for teachers and trainers. 3^rd edition. London: Kogan Page.

Wolfe, J & Keys, JB (eds). 1997. Business simulations, games and experiential learning in international business education. New York: International Business Press.

Simulating 20 years of heavy road traffic

A mobile laboratory enabling an engineer to test new road building material and proposed new construction techniques, writes Sarah Wild in the Business Day. Imagine the civil engineering and build environment learning that can be derived from such kinds of simulation. Obviously the cost is much too high for any one university to invest, but collaboration and partnerships with owners could give students most valuable experience. Download SA’s fast-track truck simulator

Simulation literature analysis about implementation and design

Dominant themes arose from recurring issues in literature about the implementation of educational simulations (Magee, 2006: 31-33), namely:

Element	Occurrence in literature reviewed
Providing feedback	2%
Repetitive practice	12%
Curriculum integration	5%
Range of difficulty	2%
Multiple learning strategies	2%
Capturing variation	2%
Individualized learning	5%
Defined outcomes	7%
Simulator validity	21%
Realistic simulation context	12%
Low cost of failure	27%

Providing feedback: Appropriate feedback to the user involves the simulation providing some form of assessment as to the performance of the user. It is considered important for the learner to be able to understand where they succeeded and failed and adjust their behaviour accordingly.

Repetitive practice: The simulation must allow for the learning activity to be performed over and over again. This was seen as the key to mastering the fundamental skills within the simulator so that the learner could perform those same skills in a real life context. It was recognized that each learner would need to repeat the simulated skills at very different levels of repetition. By allowing him or her to do so, the simulation would provide a very learner-centric experience that could be customized to each learner.

Curriculum integration: This is related to the ability of a simulation to take several different curriculum subject areas and demonstrate how they are all integrated together. This type of simulation was designed to break the traditional constraints of linear curriculum by showing how it integrates into a dynamic model. It is considered important because too many students did not understand the knowledge they were building in a holistic or systematic perspective.

Range of difficulty: The simulation must have an ability to facilitate learners of different levels of competence. It is important that learners must not be bored if the simulation proves too easy or frustrated when they cannot perform the tasks in the simulation. A simulation that can slowly scaffold in additional tasks is seen as the ideal design as it allows learners to build up complex behaviours over time and at their own pace.

Multiple Learning Strategies: Some learning objectives required very open simulation models that would allow learners to experiment with many different options. The ability to achieve similar results through a variety of strategies would allow several different approaches to learning to be integrated into a single simulation.

Capturing Variation: For some simulations it is important that the natural variation that occurs within the real world is captured. This is certainly the case in biological systems. A simulation was not considered to have enough authenticity unless it had a degree of randomness and uncertainty that the learner would also experience in the real world. Without this element the learner would only build mastery of a single procedure within the simulation and neglect to build up skills for dealing with unexpected elements.

Individualized learning: This is the ability of a simulation to allow entry of different variables in order to customize each experience to the individual learner. This could involve changing the quantitative parameters that go into the simulation models or modifying the rules that define the win state of the simulation or game. This could be easily changed to address the learning needs and skill level of individual learners.

Defined outcomes: No matter how valid the underlying model is, it was important that the simulation make the learning outcomes of the experience very explicit. Learners needed to have a complete understanding of the purpose of the simulation experience as well as the parameters they would need to achieve to finish it.

Simulator validity: This is a very important aspect of a successful educational simulation. As every virtual environment is constructed it is critical that it be based on valid models that closely represent reality. In most adult learning contexts, the skills that are built up within the simulation must translate to a real world context. In many cases, the cost of failing in the real world can have consequences to both health and safety.

Realistic simulation context: The realism of the simulation context is related to the placement of the simulation into a real life context. It is considered important that even though the learning is occurring in a simulation that both the learner and the simulation be physically located in the place where the skills will be performed in real life.

Low cost of failure: One of the most important elements identified within a simulation was the ability to fail during the learner’s attempts to successfully navigate them. The concept relies on the belief that it is better to fail in a simulated environment, as it is a low-cost environment. This was considered important for dealing with learners who needed to not only fail but also be able to see the consequences of that failure within the simulation. The goal of having this kind of element is to provide the learner with an understanding of a system so that they can successful deal with a situation in the real world that may affect health or safety.

Magee, M. 2006. State of Field Review: Simulation in Education (Final Report, 12 May 2006). Calgary AB: Alberta Online Learning Consortium. Electronically retrieved 19 October 2011 from: http://www.ccl-cca.ca/pdfs/StateOfField/SFRSimulationinEducationJul06REV.pdf

Game industry and academic world share common language

Among specialists, the two largest groups are the game industry and the academic world. A universal language to allow flawless communication is unlikely, observes Magee (2006), because of the many different perspectives and terms used. This confusion delays the adoption of simulation-based educational material.

The post-modern perspectives on knowledge do not the fit the existing framework well on how learning occurs in simulations. For example, the belief in an objective reality prevalent in the domain of computing science stands in stark contrast to the post-modern perspectives of ambiguous and chaotic virtual environments. Similarly, views about instructional design differ.

Magee, M. 2006. State of Field Review: Simulation in Education (Final Report, 12 May 2006). Calgary AB: Alberta Online Learning Consortium. Electronically retrieved 19 October 2011 from: http://www.ccl-cca.ca/pdfs/StateOfField/SFRSimulationinEducationJul06REV.pdf

Use simulations to enable authentic learning

Simulation technology became good enough to let students believe that they have encountered an accurate representation of reality, observes Magee (2006). This allows for acting virtually in ways acting in the real world would have required.

Research about trends in implementation of educational simulations indicates differential philosophical perspectives on the nature of knowledge, learning and instructional design in, for example, specialties of military, medical, business and educational gaming (Magee, 2006). Different models for creating simulations and games for learning experiences exist.

According to Shirts (1975: 76, in Magee 2006: 9) “A pure simulation represents a set of rules that define a specific model that reflects reality”. Based on Feldman (1995, in Magee 2006: 9) Magee asserts that a “simulation is a model of events, items or processes that do or could exist” and present some examples:

• Verbal models present statements about the world
• Visual models can present graphic representations of abstract concepts
• Operating models represent the dynamic nature of systems, allowing observers to view not only a single point in time in the model but also how it changes under different parameters
• Research models represent the focus a researcher is investigating
• Educational models represent the issue or concept an educator is teaching to students

Magee (2006: 9) elaborates that a simulation “is not meant to be a complete representation of an event but rather an abstraction that focuses on a specific aspect of that event”. Simulations “provide a venue where new ideas can be explored and complex interrelationships examined”; and “can provide a variety of outcomes” when experimenting with different variables.

Magee (2006: 9-10) further differentiates:

• Non-game simulation challenges — only designed to simulate real life conditions without any artificial constraints
• Simulation challenge games — participants are experiencing a contest, either against themselves, others or resources.
• Non-challenge simulation games — focused mainly on the rules that are imposed by the game elements and reacting to the environment created by the simulation

Magee, M. 2006. State of Field Review: Simulation in Education (Final Report, 12 May 2006). Calgary AB: Alberta Online Learning Consortium. Electronically retrieved 19 October 2011 from: http://www.ccl-cca.ca/pdfs/StateOfField/SFRSimulationinEducationJul06REV.pdf

Get education into simulations rather than the opposite

The same probably applies to simulations, namely: “Rather than striving to get games into education, educators should be investigating ways to get education into games.” (Royle, 2008).

Although gamers often claim that playing is educational; gamers concede (laughingly) that much of this learning has little relevance to ordinary life. Teacherised commercial games that embed, add or link educational/curriculum content are questioned. A new genre is emerging characterised by gamelike learning instead of purely entertaining based on the pedagogy of problem-based learning. The real learning does not happen in game; instead players must solve problems to progress through the game; they can only solve a given problem by accumulating the necessary tools and experience in lower levels of the game.

Storytelling is a further potent learning tool, because they enable listeners to make connections between what is said and their own experience—this helps create meaning and can trigger people into action.

Royle, K. 2008. Game-Based Learning: A Different Perspective. Innovate, 4(4), April/May 2008. Retrieved electronically 23 October 2011 from: http://innovateonline.info/pdf/vol4_issue4/Game-Based_Learning-__A_Different_Perspective.pdf

Students experience phenomena through multi-user virtual environments

Students often read about without experiencing, because the creation of experiential learning opportunities is no easy task. Baba Kofi Weusijana, Vanessa Svihla, Drue, and John Bransford (2009) are particularly interested in the potential of multi-user virtual environments (MUVEs) to help students experience the benefits of the aha effect by connecting the knowledge by description to knowledge by experience.

Weusijana, BK; Svihla, V; Gawel, D & Bransford, J. 2009. MUVEs and Experiential Learning: Some Examples. Innovate—a former official journal of online education of the Nova Southeastern University's Fischler School of Education and Human Services (FSEHS), Volume 5, Issue 5 (penultimate), June/July 2009. Retrieved electronically 23 October 2011 from: http://innovateonline.info/pdf/vol5_issue5/MUVEs_and_Experiential_Learning-__Some_Examples.pdf

Simulations for Education; Virtual Worlds and Games

In seeking literature about simulations I find many mentioning games in the same breath, as well as simulation-games. Clark Aldrich (2009) observes that many practitioners have been struck by the paradox of sensing an overlap between virtual worlds, games, and simulations; yet knowing that they are not synonymous. He offers a succinct depiction:

The three often look similar, yet the differences are profound says Aldrich (2009):

• Games are fun, engaging activities usually used purely for entertainment, but they may also allow people to gain exposure to a particular set of tools, motions, or ideas.
• Simulations use rigorously structured scenarios carefully designed to develop specific competencies that can be directly transferred into the real world.
• Virtual worlds are multiplayer (and often massively multiplayer), three-dimensional, persistent social environments with easy-to-access building capabilities. They share with games and simulations the three-dimensional environment, but they do not have the focus on a particular goal, such as advancing to the next level or successfully navigating the scenario.

Aldrich, C. 2009. Virtual Worlds, Simulations, and Games for Education: A Unifying View. Innovate—a former official journal of online education of the Nova Southeastern University's Fischler School of Education and Human Services (FSEHS), Volume 5, Issue 5 (penultimate), June/July 2009. Retrieved electronically 23 October 2011 from: http://innovateonline.info/pdf/vol5_issue5/Virtual_Worlds,_Simulations,_and_Games_for_Education-__A_Unifying_View.pdf

 

Virtual simulations to replicate tabletop exercises

Offering “online students the same realistic training experience traditionally provided by an in-person tabletop exercise” say Anne M. Hewitt, Susan Spencer, Danielle Mirliss, and Riad Twal (2009). They caution, however, that technology access and student support must be addressed prior to the successful implementation of virtual world simulations.

A tabletop exercise is a simulated scenario designed to test the response capability, for example an emergency evacuation or health-threatening pandemic. Tabletop exercises are used extensively “to practice response to and recovery from a wide range of incidents” where participants need coordinate in real time to formulate comprehensive response strategies of multiple agencies.

Hewitt, Spencer, Mirliss, and Twal (2009) established a number of goals for their virtual version of the tabletop, namely:

• offer a real world activity for students,
• permit synchronous collaboration among students on campus and from various geographical locations,
• apply basic course concepts in a problem-based learning format, and
• introduce complex systems in a systematic way.

With the goals in mind, they explored available alternatives for virtual simulations and found many readily available emergency preparedness training platforms. However, several either did not allow for customisation or required technical capabilities exceeding institutional capacity. Hewitt, Spencer, Mirliss, and Twal (2009) determined that Play2Train was the most promising option to conduct training in Second Life. John Lester, academic program manager at Linden Labs, states that "Second Life gives both students and faculty a new medium for exploring things like distance learning, experiential learning, simulation, and scientific visualization in a fundamentally collaborative environment"

Hewitt, AM; Spencer, S; Mirliss, D & Twal, R. 2009. Preparing Graduate Students for Virtual World Simulations: Exploring the Potential of an Emerging Technology. Innovate—a former official journal of online education of the Nova Southeastern University's Fischler School of Education and Human Services (FSEHS), Volume 5 (final), Issue 6, August/September 2009. Retrieved electronically 23 Oct 2011 from: http://innovateonline.info/pdf/vol5_issue6/Preparing_Graduate_Students_for_Virtual_World_Simulations-__Exploring_the_Potential_of_an_Emerging_Technology.pdf

Interactive Simulations and User Interface

A meaningful active and/or discovery learning environment is encouraged by interactive simulations; but is time consuming to develop; in particular tailoring the user interface (UI) says Jeetinder Singh and Jayanthi Sivaswamy (2010). The UI can be thought of as a virtual environment comprising graphical objects that act as active object playing a different role, such as navigation menu, input controls, and simulation body. Interactive simulations do not normally let the end user choose what controls and menus will be displayed.

Interactive simulations are single purpose, standalone, short and focused instructional aides falling in the instructionism-constructionism range—examples include applets, flash-based demos, and animations (Singh & Sivaswamy, 2010). The use of interactive simulations could significantly enhance online distance education.

A simulation teaching aide comprises three components:

1. The content
2. The simulation software
3. The students interface or view layer, which is a very critical aspect because it serves as link between the user and simulation programme

In contrast to traditional designs, where the three are closely connected, Singh and Sivaswamy (2010) propose separation of the last component, which enables the integration of the interface layer with various simulations. They designed, developed and evaluated a Graphical interface construction Kit (GicK), which enables creating UI and combining it with simulation program for creating interactive simulations

Singh, J & Sivaswamy, J. 2010. Creating User Interface for Interactive Simulations. In the proceedings of the 2010 IEEE International Conference on Digital Game and Intelligent Toy Enhanced Learning, held 12 to 16 April 2010, at the National Science and Technology Museum; Kaohsiung, Taiwan.

The Institute of Electrical and Electronics Engineers (IEEE, read I-Triple-E)