Chapter Seven

Simulations

An educational simulation is a model of an activity that users learn about through interaction.  They might involve techniques such as microworlds, virtual reality, and case-based scenarios.

Important characteristics

  • Based on an internal model
  • Main goal of users learning about the model
  • Replicates a phenomenon
  • Simplifies the phenomenon by omitting, changing, or adding details or features
  • Learners solve problems and determine what actions to take in different situations
  • Provide opportunities to explore, practice, test, and improve models safely and efficiently
  • May add elements not present in the real world (augmented reality)

Types

Simulations that are About Something

    • Physical:  a physical object or phenomenon is represented giving the user an opportunity to learn about it by continuously manipulating the simulation as it unfolds in either real or manipulated time (Examples:  SimCity, Future Lab:  Circuits for Physical Science; objective is to learn about the underlying computer model of a city, the earth, a farm, etc.)
    • Iterative:  teach about something like physical simulations except the learner runs the simulation over and over, selecting values for various parameters at the beginning of each run, observing, and interpreting results, i.e. static timeframe (Examples:  Catlab, Kangasaurus, Community Dynamics, Population Concepts, Future Lab:  Gravity for Physical Science; the user can complete many trials in less time with less effort)

Simulations that Show How to do Something

    • Procedural:  teach a sequence of actions to accomplish some goal, typically containing simulated physical objects so the learner imitates actual procedures of operating or manipulating them (Examples:  Buretta, BioLab Frog, Microsoft Flight Simulator, Africa Trail, Amazon Trail, MayaQuest; vary greatly in what is considered a correct sequence; user can explore questionable alternatives safely; when the user acts, the program reacts, providing feedback about the effects the actoin would have in the real situation)
      • Pre-laboratory simulations
      • Diagnosis simulation
      • Trip Simulation
    • Situational:  deal with behaviors and attitudes of people or organizations which are less predictable; most incorporate role playing so the user is a participant or object in the simulation (Examples:  Capitalism, The Interactive Courtroom; the least common type of simulation and more difficult/expensive to develop)

Advantages

Advantages of Simulations Compared to Reality

    • Enhance safety
    • Provide experiences not readily available in reality
    • Modify timeframes
    • Make rare events more common
    • Control complexity for instructional and financial benefit
    • More convenient

Advantages of Simulations Compared to Other Media and Methodologies

    • Motivation:  learners are more motivated by active participation in a situation than by passive learning; simulations capitalize on the motivation elements of challenge and realistic fantasy
    • Transfer of Learning:  the practice that results from using a simulation tends to result in increased performance in real situations
    • Efficiency:  more transfer of learning tends to occur per unit of learning time with simulation compared to other more conventional methods
    • Flexibility:  simulations can be used for several purposes, to present material, guide learners through it, provide practice, or assess learning.

Factors in Simulations

Fidelity

Fidelity refers to how closely a simulation resembles reality.  Complete fidelity is not the only factor affecting transfer – it it more complex.  For a novice learner, low-fidelity instruction does yield learning, but an increase in fidelity could result in better learning.  However, putting a novice in a high fidelity simulation could result in confusion, stress, and decreased learning.  The issue of cost is also relevant in deciding the fidelity for a simulation.  Fidelity should be determined factoring in the learner’s current instructional level; as a learner progresses, the appropriate level of fidelity may increase.

Delivery Mode

The choice of the mode of delivery should be made having considered instructional goals, learner characteristics, level of fidelity required, importance of performance, learner motivation, and economics.  However, in many cases the delivery mode has been selected from the start of the project since it can have such an impact on cost.

Instructional Strategy

    • Microworlds:  microworlds with an underlying model to be learned are simulations; programming microworlds, however, are not.
    • Scientific Discovery Learning:  usually iterative simulations to virtually perform scientific experiments
    • Virtual Reality:  may require special equipment; typically use tactile feedback for physical or procedural simulations
    • Laboratory Simulations:  often followed up with real laboratory experiences
    • Role Playing:  generally used in situational simulations; popular for training in business, salesmanship, counseling, parenting, and classroom teaching
    • Operator-in-the-Loop:  large-scale simulations; a physical device is runing while a live operator interacts with it in real time
    • Case-Based Scenarios:  similar to and sometimes incorporate role-playing; the learner is placed in a hypothetical situation and asked to carry out the job to find and implement solutions
    • Simulation Gaming:  often, but not always competitive; in order to be considered simulation, must have underlying model

The Underlying Model and Its Components

Simulations may be discrete (representing phenomena in which quantities vary by discrete amounts – queuing simulations, STELLA, PowerSim) or logical (represented by sets of if-then rules in a computer program).  the underlying model must include a number of components:

    • Objects:  physical entities, pictured or described
    • Precision:  how well we understand the process being simulated (more humans, less precision since they are less understood/predictable)
    • Type of Reality:  some phenomena do occur in reality, some occur but not exactly as shown in the simulation, and some are imagined
    • Sequence:  linear, cyclical, or more complex
    • Number of Solutions:  sometimes there is no such thing as one solution; sometimes not all solutions need to be included in a simulation
    • Timeframe:  period of time over which the phenomenon normally takes place (in my simulation, the  Mass takes place over one hour, for example)
    • Role of the Learner:  the learner might be in the simulation or external to it; they may be an actor (engaged in reactions to which other objects react) or a reactor (where objects are the actors to which the learner reacts)

Providing Objectives

For simulations, greater emphasis should be placed on introducing the purpose of a simulation so the learner know what they should expect to get out of it.

Directions

Also discussed in chapter 3, clear and complete directions are even more important for simulations.

The Opening

This part sets the stage for the simulation.  It does not have to describe everything the simulation can do, but rather provides the scenario for the learner to begin.

Instructional Supports

These supports include hints, corrective feedback, coaching, and assignments.

Motivators

Learners find simulations to be interesting and motivating because they are participating actively, a contrast to passive learning.  However, this motivation can be assumed; the designer should still design for motivation.  Learners tend to be more motivated when they have a sense of control and are properly challenged.

Sequence

Some procedural and most situational simulations have complex sequences with multiple paths and varying numbers of steps.  the sequence of the underlying model tends to be tied to the sequence found in reality so it tends to be outside the control of the designer.

Presentations

    • Mode:  text, pictures, voice, animations, video, combination
    • Types:  
      • Choices to be Made – textual or pictorial
      • Objects to be Manipulated – usually pictorial
      • Events to React to – can be any mode
      • Systems to Investigate – typically mixed modes
    • Presentation Realism: realism may increase or decrease fidelity, but this doesn’t necessarily determine effectiveness

Learner Actions

    • Mode of Actions:  simulations may use keyboard, mouse, steering hoke, joystick, microphone, etc.
    • Types of Actions:  choices to make – making a choice; objects to manipulate – manipulating an object; events to react to – reacting to an event; systems to investigate – collecting information
    • Realism of Actions:  fidelity may refer either to the mode of action (type, click, speech, movement) or the type of action (select, generate, control); low fidelity input such as typing or selections are predominant choices compared to speech

Learner Control of the Simulation

    • Initial Choices
    • Sequence
    • Obtaining Directions
    • Terminating the Simulation
    • Restarting within the Simulation
    • Restarting after Simulation
    • Saving Data
    • Printing
    • Changing the Level of Difficulty
    • Changing the Level of Fidelity

System Reactions and Feedback

    • Natural versus Artificial:  natural feedback would be like a user viewing a consequence (e.g. the plane crashes, you never reach your destination) whereas artificial feedback would come in the form of a visual/textual and/or audio message
    • Immediate versus Delayed:  feedback may be delayed until the consequence/catastrophe or evidence of success occurs
    • Selecting Natural versus Artificial and Immediate versus Delayed Feedback:  delay of feedback tends to have a detrimental effect on learning; natural feedback tends to be delayed so it is not always ideal

Completion of the Simulation

The completion may come in the form of the user succeeding or failing at the simulation.  Iterative simulations consolidate data from the run that has finished allowing the learner to run the simulation again; in this case, there needs to be a distinction between completion of the simulation and completion of the program.

Taxonomy for Fidelity Analysis

    • Fidelity considerations in Physical Simulations:  
      • Underlying model:  number of objects, cause-effect relationships, timeframe
      • Presentations:  detail/realism, visual versus textual, illusion of motion
      • User actions:  user control versus natural progression
      • System feedback:  mode, immediacy, whether there is any feedback at all, and exaggeration of feedback magnitude
    • Fidelity considerations in Iterative Simulations:  
      • Underlying model:  number of variables in the math model, accuracy of variables, time increment for recalculation
      • Presentations:  what variables are unknown, known but not manipulated, or known and manipulated; speeding or slowing timeframe
      • User actions:  setting initial variables, high level of user control between runs
      • System feedback:  mode of feedback (text or pictorial), whether there is any feedback at all
    • Fidelity considerations in Procedural Simulations:  
      • Underlying model:  number of possible solution paths, nature/complexity of solutions, number of objects, cause-effect relationship
      • Presentations:  mode of display (tet, graphic, real), realism and completeness of images or descriptors
      • User actions:  number of possible actions, mode of actions (e.g. typing a word versus moving a joystick)
      • System feedback:  modes of feedback (text, pictorial, real), immediacy, whether there is any feedback at all
    • Fidelity considerations in Situational Simulations:
      • Underling model:  number of persons in the simulation, probabilistic nature of human behavior, behavior a function of multiple events, level of precision of theory, accuracy of theory
      • Presentations:  mode of display (text, graphic, real), completeness of a scenario
      • User actions:  number of possible actions, flexibility of actions (e.g. multiple choice versus constructed response)
      • System feedback:  immediacy of and probabilistic feedback

Simulation Design and Development

    • Learn and analyze the phenomenon
    • Make design decisions concerning the simulation factors
    • Create and refine the underlying model
    • transfer the model into your authoring software
    • Develop the user interface in the authoring software
    • Develop instructional supports in the authoring software

I am much more relaxed in my project having read about simulations.  This is the perfect type of program for my client’s needs!  The flexibility will be helpful since I want my simulation to present content by leading the learner through the process, provide practice with the process, and assess their preparation for the role of senior altar server.

Fidelity was one issue that worried me prior to reading this chapter.  Looking at the current instructional level of my learners, though, leads me to feel more confident that the fidelity I will be able to achieve with my limited resources will likely be appropriate and effective.  Currently my learners have attended a face-to-face session, participated as a candle bearer, and is accustomed to K-12 instruction (some public, some private, some home schooled).

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s