Learning in vivo

Effective user interface for simulated learning

For at least three decades the design principles of user interface has a presence in computer science literature. During the last decade computer systems became increasingly more interactive and code for interface increased accordingly. Interactive user interface developments and graphic user interfaces (GUI) in particular do provide simpler ways for humans to communicate with PCs. Although GUI requires complex programming, several software tools emerged that assist with the implementation of GUI, such as NeXT Interface Builder; WindowsMAKER; TelePICTIVE; and TelePICTIRE (Sidhu, 2010: 36).

Sidhu (2010: 36-38) suggests the following design guidelines for better user interface:

• Simple, clear and standardised screen layout with liberal use of blank space. Functional aspects such as title, help text and buttons should be consistent throughout; with distinctive design that emphasise critical information. Textual information should be easily legible, by using appropriate fonts, typestyles and typesets. The resolution of graphics should eb good quality.
• Make use of easily navigatable multi-windows and menus to enable users to bring relevant windows to the front.
• Make use of menus that indicate the selected option and visited items. Provide keyboard shortcuts (accelerators) and indicators of drastic action if executed, e.g. exiting or quiting without having saved. Use hierarchical (sub) menus with clear indicators.
• Provide selection lists (pop-ups) when hovering with mouse.
• Make use of realistics icons to give visual clues to users.
• Make use of feedback indicators, e.g. progress or time/percentage remaining; and/or graphic indicators, such as bars.
• Provide online help that is context sensitive.
• Error messages should be constructive and offer remedy suggestions.
• Use colour to enhance usefulness, e.g. similar functional background colours; contrast to focus users; and bright colours for caution.
• Mouse input (and other input devices) should be consistent with contemporary software.

Sidhu, M.S. 2010. Technology-assisted problem solving for engineering education: interactive multimedia applications. Hershey: Engineering Science Reference.

Replacing natural experiments by computer simulations

Simulations as viable alternative to doing experiments on natural systems, offer anchor points to integrate scientific discovery learning or inquiry learning with instructional support in educational settings (for example distance) where for a number of reasons actual experiments may not be feasible, because (Van Joolingen & De Jong, 2003: 1):

• the natural system may not be accessible due to expense of the measuring equipment required or non-availability
• of safety hazards, such as radioactive samples, toxical chemical substances or populations of certain bacteria
• performing the experiments may be unethical, for example in the case of experiments with livestock
• time scale of experiments on natural phenomena may not fit with the educational timeframe— some experiments take days, months or even years to complete or may happen so fast that it is hard to visualize the processes the learning is about
• experiments may consume rare resources

“Simulations are computer programs containing an executable model of a natural or other system, capable of computing the behavior of the modeled system by means of dedicated algorithms and presenting the results of these computations to the user” (Van Joolingen & De Jong, 2003:2).

However, caution Van Joolingen and De Jong (2003: 3-4) the creation of computer simulations embedded in instruction is out of reach of most lecturers; and off-the-shelf simulations often do not match the specific teaching requirements. Creating simulations require specific skills for the various steps in the process:

1. Creating the model that would drive the simulation—Capability to do this requires expertise of either a programming language or a special simulation language; expertise in the domain simulated and knowledge of the target language; and in the case of a general purpose programming language one must also create the algorithm to simulate the model.
2. Creating the learner interface to the simulation—Including visual representation, using graphics representing domain elements, graphs, numbers, etc. Capability to create interfaces requires expertise of the available tools as well as to create the domain specific graphics within the interface.
3. Creating the instructional design of the environment from the perspective of the learner— Instructional design expertise, such as which activities to be performed; the goals of such activities; what information/explanations would be needed at specific moments (discipline knowledge); knowing/awareness of frequently occurring misconceptions; and which instructional interventions should form part of the simulation?
4. Integrate the parts of the simulation environment to a complete system in order to create a coherent integrated simulation— This means that all parts need to co-operate and that the interactions between simulation model, learner interface and all instructional interventions should be smooth and stable. This step requires programming skills in order to create an efficient and transparent environment.

The remainder of the referenced article discusses SimQuest—a simulation authoring system developed as free and open software by University of Twente for the designing and creating of simulation-based learning environments for discovery learning—downloadable for free.

Van Joolingen, W.R., & De Jong, T. (2003). SimQuest, authoring educational simulations. In: T. Murray, S. Blessing, S. Ainsworth. Authoring Tools for Advanced Technology Learning Environments: Toward cost-effective adaptive, interactive, and intelligent educational software. pp. 1-31. Dordrecht: Kluwer. Accessed from Internet 18 May 2012 from: http://halshs.archives-ouvertes.fr/docs/00/19/06/76/PDF/SimQuest-VanJoolingenDeJong.pdf

Virtual Reality—visualisation and interactivity enable simulation

The delivery of educational experiences by means of computer started in the 1950s. The use of computer aided learning (CAL) gained popularity with the growth in use of personal computers (PCs). In the 1980s a paradigm shift from text to CAL commenced. Rapid developments of user-friendly technology enable integration of multimedia, interactivity with virtual realities and simulations. The term virtual reality (VR), says Sidhu (2010: 2), describes “a range of computer-based systems in which a user can explore hardware or software generated ‘micro world’ (artificial environments) that allow close resemblance to reality.” The modelling of objects and interactive behaviours within virtual environments is feasible. As is “integrating position-tracking human-computer interaction devices, and performing numerically intensive computations for real-time navigation.”

Sidhu, M.S. 2010. Technology-assisted problem solving for engineering education: interactive multimedia applications. Hershey: Engineering Science Reference.

Doing law as means to learning about law

In the developed, technocratic world people—especially younger generations—became accustomed to virtual realities on PC screens. Interactive PC games offer excitement, insight and fulfilment. Clinical simulations could offer similar stimulus, engagement observation how law works. Brayne, Duncan and Grimes (1998: 173) state aptly “doing law as means to learning about law is different from learning the law by reading it”. Reconstruction of legal incidents through the vehicle of simulations; and the presentation of social problems as law ‘cases’; are but two examples. A legal problem on paper does not contain the uncertainties, emotions and interactions that form part of the real-world realities of, for example, the attorney’s office, the police station or the courtroom.

Brayne, Duncan and Grimes (1998: 174) observes that “simulation is commonly regarded as a valuable part of clinical teaching, but one which is the poor relation of the real-client clinic”, because simulation lacks the “startling and awakening encounters … of coping with people” present in legal practice “who have a need of legal expertise”. On the other hand, simulations can provide opportunities not readily available and can invoke the emotions and flow of adrenalin associated with daily client work.

In undergraduate legal education, simulations would inculcate appropriate behaviours in addition to the realisation that there is more to lawyering than mastery of legal knowledge. Simulations further offer students safe opportunities to experiment and to learn from mistakes.

Brayne, Duncan and Grimes (1998: 183) emphasise that simulation can never be an alternative to real client work, but within a spectrum of teaching methods simulations could contribute to effective law learning.

Brayne, H; Duncan, N & Grimes, R. 1998. Clinical legal education: active learning in your law school. London: Blackstone.

Simulations are interactive abstractions of real-life

Akilli (2007: 4) defines a simulation “as an interactive abstraction or simplification of some real life … or any attempt to imitate a real or imaginary environment or system”.

Although a substantial body of literature accumulated about simulations, Akilli (2007: 5) observes that it is still vague if games and/or simulations influence the learning of students in a positive way. Some literature does, however, describe the effects on:

• Discovery learning strategies
• Problem solving skills
• Computer usage skills
• Intellectual, visual and motor skills of students
• The engagement and interactivity of students
• Motivation to take responsibility for own learning

Evidence suggests, according to Akilli (2007: 6) “the use of games as instructional tools” in 3000 B.C. in China. Despite re-entry of use in the educational context in 1950s; games and simulations only became part of formal instructional design in the 1970s. However, it is reported that instructional designers encounter two problems:

• Absence of available comprehensive design paradigms — addressed through the publication referenced
• Lack of well-designed research findings — existing are mainly perceived reactions of students

Akilli, GK. 2007. Games and simulations: a new approach in education? In D Gibson; C Aldrich & M Prensky. 2007. Games and simulations in online learning: research and development frameworks (pp 1 – 20). Hershey: Information Science Publishing.

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.

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

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

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

 

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)

Definitions and essential attributes of games and simulations

Louise Sauvé; Lise Renaud and David Kaufman (2010) found little agreement among theoreticians and researchers about the meanings for the concepts of game and simulation. They tried to remedy this methodological shortcoming by carrying out systematic literature reviewing in order to establish definitions and articulate the essential attributes of games and simulations. Literature reviewed suggest that learning through games result in acquisition of new knowledge; “the development of intellectual skills (e.g., abstraction, anticipation, strategic thinking, problem resolution, lateral thinking, spatial representation, hand-eye coordination), and [the] development of behaviour and attitudes” (p. 5).

An essential attribute is a characteristic or specific property without which the concept in question can no longer be recognised as such. The six critical attributes of educational games are:

• player(s) — a game cannot work without at least one player making decisions while assuming a role
• fictitious (contrived) situation of conflict, competition or cooperation
• rules as set of conditions describing the relations between players and the environment — rules describe procedures; provide control and specify closure
• predetermined goal(s)
• artificial character — “If the constraints of reality [are] applied, the activity would become a simulation game rather than a game” (p. 5)
• educational character — from an implicit learning-centred purpose to need learn explicitly identified

Sauvé, Renaud and Kaufman (2010) group simulations into two broad categories, namely (a) simulations in the sciences and engineering used to experiment and test hypotheses; and (b) training simulations that offer environments simplifying reality and allow learning without the risks of specific “live” situations. The five attributes of educational simulations are:

• a model of reality defined as a system — the reality described represents one or several aspects of a complex real system; a model is a simplified mental image
• dynamic —the essential elements of reality are copied allowing the participant to control this reality; to study it at own pace and convenience
• simplification introduces a degree of abstraction needed to understand the functions and tasks of a system
• having validity, is faithful and accurate — “Fidelity” is a two-dimensional degree of similarity of the operational situation which is simulated, measured in terms of (a) physical characteristics—for example visual, spatial, kinesthetic; and (b) functional characteristics—for example the informational, stimulus and response options (the simpler the model, the bigger the risk of falsifying what it intend simulating)
• having educational value — varied realistic examples imitate the real-world

The seven attributes of educational simulation-games or of “serious games” (as alternative term) are:

• a model of a real or fictitious system
• simplified
• dynamic
• players of varying numbers
• in competition or cooperation
• rules
• an educational character

Sauvé, Renaud and Kaufman (2010: 17) summarise the essential attributes as follow, pointing out that a game is not a simulation; a simulation is distinguished from a game by a model; and a simulation-game is a ‘serious game’:

GAME	SIMULATION	SIMULATION-GAME
Artificial character	Reality defined as a system	Reality defined as a system
	Model Simplified Dynamic Faithful, accurate and valid	Model Simplified Dynamic
Player(s) Conflict (competition) Rules Predetermined goal (to win)		Player(s) Conflict (competition) Rules Predetermined goal (to win)

Sauvé, L; Renaud, L & Kaufman, D. 2010. Games, Simulations, and Simulation Games for Learning, pp 1-26. In D Kaufman & L Sauvé (Eds) 2010. Educational game play and simulation environments case studies and lessons learned. Hershey, PA: IGI Global.