Contents
e-Learning Methodologies
Introduction
Types of Simulations
Simulations
Advantages of Simulations
Factors affecting Quality of Simulations
Simulation Design and Development
Introduction
An educational simulation is a model of some phenomenon
or activity that users learn about through interaction
with the simulation.
According to the above definition, movies and animations are not
simulations because although they often contain some imitation
or representation of reality, they typically are not based on an
internal model.
Similarly many games cannot be considered simulations because
although they use an internal model they use it solely as a
motivating device
The purpose of simulations is to help learners built their
own mental models of the phenomena or procedures and
provide them opportunities to explore, practice, test,
and improve those models safely and efficiently
Types of Simulations
About something simulations:
Physical: A physical object or phenomenon is represented on
the screen, giving the user an opportunity to learn about it
Iterative: They are also called process or black box simulations.
They are similar to the physical simulations but instead of
continuously manipulating the simulation, the learner runs the
simulation over and over, selecting values for various
parameters and observing the phenomena that occur without
intervention
How to do something simulations:
Procedural: Teach a sequence of actions to accomplish some
goal
Situational: Deal with behaviors and attitudes of people or
organizations in different situations, rather than with skilled
performance
Types of Simulations =>
Physical Simulations
In physical simulations each program has an underlying
computer model of a system (a city, the earth, a farm,
an electronic circuit, a microprocessor, etc.)
Examples:
SimCity Classic: Simulation of urban planning
Analog Circuit Simulator: http://www.falstad.com/circuit/
Pep 7 Computer: Computer organization
Future Lab: Circuits for Physical Science, shows children how
to build and understand electrical circuits on a computer
before they work with actual electrical parts. The program
offers students the opportunity to study various types of
circuits and gives them instructions so they can explore the
effects of manipulating portions of these circuits.
Types of Simulations =>
Procedural Simulations
Procedural simulations typically contain simulated
physical objects. However, the simulation of the physical
objects is necessary to meet procedural requirements,
that is to allow engagement in the procedure.
Types:
Laboratory simulation:
⌧BioLab Frog: Allows learners dissect frogs and perform other
experiments
⌧A.D.A.M Interactive anatomy: Anatomy simulation.
Diagnosis simulation: The learner is presented with a problem to
solve, such as a patient with particular symptoms, and must
follow a set of procedures to determine the solution, i.e., the
illness
Flight Simulators and Car driving simulators
Types of Simulations =>
Iterative Simulations
In iterative simulations time is not included as a
variable. That is, whether the real phenomenon occurs
very quickly or very slowly, the learner manipulates
parameters, runs the simulation and sees the
immediate results.
Examples:
Catlab: An introductory genetics simulation on the mating of
cats selected by color, pattern and tail presence. Covers the
basics of single gene traits: dominant/ recessive/ incomplete/
autosomal/ sex-linked.
CAD tools: AutoCAD, PCAD, OrCAD etc.
PS Spice: Electronic circuit design
Matlab Simulink: Computer models for a variety of devices and
mathematical concepts
Types of Simulations =>
Situational Simulations
Situational simulations, is a special type of procedural
simulations. Learners are encouraged to explore
alternatives and see their effects. However, in
situational simulations special emphasis is given in
modeling people, organizations and their interactions.
Examples:
Capitalism: Allows participants to create companies, manufacture
and products and compete market.
Interactive Courtroom: Includes simulations of interviewing,
examining and cross examining, being the judge, making motions,
negotiating, and other courtroom skills
Advantages of Simulations
Advantages compared to reality:
Enhance safety
Provide experiences not readily available in reality
Modify time frames
Make rare events more common
Control the complexity of the learning situation
Save money
Advantages compared to other e-learning
methodologies:
Motivation
Transfer of learning
Efficiency
Flexibility
Factors in Simulations
Fidelity
Instructional Strategy
The underlying model and its Components
Providing objectives
Directions
Instructional Supports
Motivators
Sequence
Presentations
Learner Actions
System Reaction and Feedback
Factors in Simulations =>
A theory from learning from Simulation
Knowledge Attributes:
Type
Organization
Complexity
Precision
Learner Attributes: age, gender, prerequisite knowledge
or skills, prior knowledge or ability in the subject area,
general cognitive abilities, metacognitive abilities,
learning styles and preferences
Simulation Attributes: realization of the simulation
factors
Factors in Simulations =>
Fidelity
Fidelity refers to how closely a simulation imitates
reality:
Historically, people believed that increasing fidelity in an
instructional setting le to better transfer of learning
However, research has demonstrated that the relation between
fidelity and transfer is more complex and depends, also, on the
instructional level of the learner (initial learning)
Increasing fidelity may lower initial learning
Increasing initial learning increases transfer
Dilemma: Increasing fidelity, increases transfer but may
inhibit initial learning, which in turn inhibits transfer
Solution: use a level of fidelity based on learner’s
current instructional level. Increase fidelity as learners
progresses in learning
Factors in Simulations =>
Instructional Strategy
Some of the more common instructional strategies for
simulations are:
Microworlds, where the learner is given a collection of objects
that can be assembled, manipulated, turned on and off,
measured, etc. Examples: Simulink, Future Lab: Gravity for
Physical Sciences
Scientific Discovery Learning. These are typically iterative
simulations, in which learners perform scientific experiments to
ascertain the laws of governing a phenomenon. Example: Catlab
Virtual Reality. VR environments replicate a real-life
environment, visually, functionally, (the actions you can perform),
aurally, and sometimes kinesthitically. They are used generally
for physical or procedural simulations. Example: A.D.A.M
Factors in Simulations =>
The Underlying model and its Components
Computer models that underly simulations are primarily
of three types:
Continuous simulation models have an infinite number of states.
They are based calculus and used to represent phenomena of the
physical sciences
Discrete simulation models are based on probability, statistics
and queuing theory and are used in cases such as air and
automobile traffic modeling. They are not very common in
education.
Logical simulation models are represented by sets of if-then
rules in computer programs. They are used to model operations
in machines, decisions in businesses and social interactions. In
education logical models are commonly combined with continuous
models. The continuous model represent the physical system
itself while the logical model represents the ways in which
learners interact with the physical system
Factors in Simulations =>
Instructional Strategy (II)
Common instructional strategies (cnt’d):
Laboratory Simulations, allow, in some cases, learners to follow
any paths they want (including completely nonsensical ones), but
most have constraints, which guide the learner to the correct
pathway. They are used generally for physical or procedural
simulations. Example: BioLab Frog
Role Playing, is a popular approach for training in business,
counseling, classroom teaching, etc. They are used generally for
situational simulations. Examples: Capitalism. The Interactive
Courtroom
Operator-in-the-Loop, refers to the fact that a physical device
(such as an aircraft simulator) is running while a live operator
(the learner) interacts with it in real time. Example: Flight and
Car Driving Simulators
Factors in Simulations =>
The Underlying model and its Components (II)
Computer models include a number of components that
determine both the nature of the simulation and the
nature of the learner’s interactions with it:
Objects are any physical entities, pictured or described within
the simulation
Precision refers to how well we understand the process being
simulated.
Type of Reality refers to whether the phenomenon depicted is
one that occurs in the real world:
⌧ Phenomena that do occur as simulated
⌧ Phenomena that do occur but not exactly as simulated
⌧ Phenomena that simulated are imaginary
Number of Solutions. Reality varies a great deal with respect to
the number of solutions available.
Factors in Simulations =>
The Underlying model and its Components (III)
Components (cnt’d):
Time Frame is the period of time which a phenomenon normally
takes place
Role of the Learner refers to whether the person using the
simulation is considered one of the objects in the model or is
external to it:
⌧ Being part does not mean being a person
⌧ In physical and iterative simulations people manipulates and
observes objects from outside while in situational and procedural
people are part of the simulation
⌧ Learner can be considered actor or reactor or both
Simulation Design and Development
The following steps are suggested for simulation
development:
Learn and analyze the phenomenon
Make design decision 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 support in the authoring
software
Fidelity Analysis in Simulations
Fidelity in Physical Simulations
Primary decision: What objects to include and how realistic
this objects would be
Fidelity in Iterative Simulations
Primary decision: The physical model of the phenomenon
Fidelity in Procedural Simulations
Primary decision: Fidelity of presentations, actions and
feedback
Fidelity in Situational Simulations
Primary decision: Number of actions learners could take so as
to model as much as possible the human behavior