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COMPUTER SIMULATIONS 245
authority and authenticity of the material, which
should both be authoritative and declare its
sources
content of the material – its up-to-dateness,
relevance and coverage
credibility and legitimacy of the material (e.g. is
it from a respected source or institution)
correctness, accuracy, completeness and fairness
of the material
objectivity and rigour of the material being
presented and/or discussed.
In evaluating educational research materials on
the web, researchers and teachers can ask
themselves several questions (Hartley et al.1997):
Is the author identified
Does the author establish her/his expertise in
the area, and institutional affiliation
Is the organization reputable
Is the material referenced; does the author
indicate how the material was gathered
What is the role that this web site is designed to
play (e.g. to provide information, to persuade)
Is the material up-to-date
Is the material free from biases, personal
opinions and offence
How do we know that the author is
authoritative on this web site
It is important for the researcher to keep full
bibliographic data of the web site material used,
including the date in which it was retrieved and
the web site address.
Computer simulations
Computer simulations and virtual technology have
significant contributions to make to educational
research. Simulations have two main components:
a system in which the researcher is interested and
that lends itself to being modelled or simulated,
and a model of that system (Wilcox 1997). The
system comprises any set of interrelated features,
while the model, that is, the analogue of the
system, is often mathematical.
Wilcox (1997) has indicated two forms of
simulation. In deterministic simulations all the
mathematical and logical relationships between
the components of a system are known and fixed.
In stochastic simulations, typically the main types
used in educational research, at least one variable
is random. A simulation is a model of the real
world in which the relevant factors in the research
can be included and manipulated. A model may
operationalize a theory and convert it into a
computer programme (see Gilbert and Troitzsch
2005: 3), making explicit its assumptions.
Gilbert and Troitzsch (2005: 6) suggest that
the prime purposes of computer simulations are
for discovery, proof and experiment. Beyond
simply prediction, computer simulations enable
an understanding and explanation to be gained of
how processes operate and unfold over time, and
the results of these. This explodes the value of
prediction as a test of a theory; rather it argues
that the test of a theory should be its explanatory
and hermeneutic power, rather than its predictive
value. Indeed computer simulations may be useful
in developing rather than testing theories.
Computer simulations, by enabling the researcher
to control and manipulate the variables
and components, are useful in addressing ‘what
if’ questions, e.g. ‘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’
The relevant elements are put into the simulation
and are then manipulated – set to different
parameters – to see what happens and what results.
Computers can handle very rapidly data that
would take humans several years to process.
Simulations based on mathematical modelling
(e.g. multiple iterations of the same formula)
provide researchers with a way of imitating
behaviours and systems, and extrapolating what
might happen if the system runs over time
or if the same mathematical calculations are
repeated over and over again, where data are
fed back – formatively – into the next round
of calculation of the same formula. Hopkins
et al. (1996: 159-62) report such a case in
proving the Central Limit Theorem (discussed
in Chapter 4), where the process of calculation of
means was repeated 10,000 times. Such modelling
Chapter 10