VIRTUAL WORLDS IN
EDUCATIONAL RESEARCH
© LOUIS COHEN, LAWRENCE
MANION & KEITH MORRISON
STRUCTURE OF THE CHAPTER
• Simulations and virtual worlds
• Theoretical bases of simulations and virtual
worlds
• Applications of virtual worlds
• A worked example of virtual world research
• Opportunities and limitations
• Issues and problems in virtual world research
• Using a virtual world and simulations in
educational research
• Ethical issues in virtual world research
• Online tools for data collection from virtual worlds
SIMULATIONS
Main components:
• A system of interrelated features in which the
researcher is interested and that lends itself
to be modelled or simulated.
• A model of that system that is often a
mathematical analogue.
• Deterministic simulations all the
mathematical relationships between the
components of a system are known.
• Stochastic simulations: at least one variable
is random.
COMPUTER SIMULATIONS ARE
CHARACTERIZED BY . . .
• Modelling and imitating the behaviour of
systems and their major attributes;
• Enabling researchers to see ‘what happens if’
the system is allowed to run its course or if
variables are manipulated;
• A mathematical formula that models key
features of the reality;
• Mathematical relationships that are assumed
to be repeating in controlled, bounded and
clearly defined situations, sometimes giving
rise to unanticipated outcomes.
COMPUTER SIMULATIONS ARE
CHARACTERIZED BY . . .
• Feedback and multiple iteration procedures
for understanding the emergence of
phenomena and behaviours;
• Complex phenomena and behaviours derived
from the repeated interplay of initial
conditions/variables;
• Deterministic laws (the repeated calculation
of a formula) sometimes leading to
unpredictable outcomes.
‘WHAT IF’ QUESTIONS
• What happens if I change this parameter or
that parameter?
• What if the person behaves in such-and-such
a way?
• What happens if I change such-and-such a
feature of the environment?
ATTRACTIONS OF SIMULATIONS
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Prediction
Understanding
Explanation
Exploration (in a safe environment)
Virtual worlds are created by the participants
and the world emerges from the interaction of
the participants.
• Individuals can project their own views and
values on topics through their avatar and
receive the feedback of others in the system.
ATTRACTIONS OF SIMULATIONS
• Economy (they are cheaper to run than the reallife situations);
• Visibility (they can make a phenomenon more
accessible and clear to the researcher);
• Control (the researcher has more control over
the simulation than in the real life situation);
• Safety (researchers can work on situations that
may be too dangerous, sensitive, ethically
questionable or difficult in real life natural
situations);
• Practice (they can be used for training).
RESERVATIONS ABOUT
SIMULATIONS
• Artificiality (they mimic life, rather than
being the real thing);
• Cost (computer simulations can be
expensive);
• Training of participants (simulations often
require considerable training);
• Quantitative problems (they may require
programming expertise).
Features and affordances of simulations/virtual worlds
Simulations
Virtual worlds
Modeling / imitating
Realizing / Acting
‘What if’ modeling of known
Few known variables
variables
An underlying mathematical
Minimal underlying constructs
construct
Modelled and interpreted
Catching and manipulating the
reality
fine grain of reality
Bounded, defined parameters Unbounded and undefined
parameters
Iteration and feedback to
Human agency as the driver of
reveal emergent phenomena
emergence
Repeated interplay of set initial Any set initial conditions rapidly
conditions
abandoned
Unpredictable outcomes
Unpredictable outcomes common
sometimes
Limited simultaneous users
Multiple simultaneous users
Transience
Persistence
THEORETICAL BASES OF
SIMULATIONS AND VIRTUAL WORLDS
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Chaos theory
Complexity theory
Immersive experiences and co-presence
Agent-based modelling
Social facts
Artificial life
Social networking
Communicative action (Habermas)
APPLICATIONS OF VIRTUAL WORLDS
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‘Real life’ scenarios
Collect large amount of data
Store data
Study of human interaction, especially in
dynamic, fluid, uncertain or contested
contexts
Explore complex behaviour variables
Monitor developments over time
Explore sensitive issues
Explore values and viewpoints
OPPORTUNITIES
• The experimenter has complete manipulative
control over every aspect of the situation (e.g. in
flight simulators, surgical simulators, training in
dangerous environments and decision-making
training).
• Participants are given a realistic situation in which
to act in whatever way they think appropriate.
• Inclusion of the time dimension allows the subject
to take an active role in interacting with the
environment, and enables the experimenter to
observe a social system in action, with feedback
loops and multidirectional causal connections.
OPPORTUNITIES
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Experiential and active learning;
Encourages motivation and engagement;
Visualization, managing complex environments;
Access to impossible/difficult environments;
Flexibility (can be programmed to offer wide
range of situations/stimuli);
• Monitoring (sessions can be recorded,
examined, evaluated and assessed);
• Connect geographically distant participants;
• Synchronous and asynchronous.
CHALLENGES
• Creating common research protocols
• Use of different IT systems
• Assumptions (and cultures) of participants
differ
• Necessary expertise and training in their use
(for researchers and participants)
• Sufficient bandwidth
• Ability to work with different firewalls
CONSIDERATIONS FOR
EDUCATIONAL RESEARCH
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Type of project
Focus of the activity
Carefully formulate the research question
Venue: a private/closed or open environment
Participants
Methodology
Ethical issues
Data analysis
Dissemination
ETHICAL ISSUES
• Vulnerability
• Individual risk
• Informed consent, especially when dealing
with:
– Online identities
– The nature of communication (public or
private)
– Security
– Confidentiality and privacy
– Inworld standards and rules