RESEARCH METHOD COHEN ok

TRUE EXPERIMENTAL DESIGNS 281
Factorial designs also have to take account
of the interaction of the independent variables.
For example, one factor (independent
variable) may be ‘sex’ and the other ‘age’
(Box 13.3). The researcher may be investigating
their effects on motivation for learning mathematics
(see http://www.routledge.com/textbooks/
9780415368780 – Chapter 13, file 13.10. ppt).
Here one can see that the difference in
motivation for mathematics is not constant
between males and females, but that it varies
according to the age of the participants. There is
an interaction effect between age and sex, such
that the effect of sex depends on age. A factorial
design is useful for examining interaction effects.
At their simplest, factorial designs may have
two levels of an independent variable, e.g. its
presence or absence, but, as has been seen here,
it can become more complex. That complexity is
bought at the price of increasing exponentially the
number of groups required.
(four levels of the independent variable ‘reading
ability’). Four experimental groups are set up
to receive the intervention, thus: experimental
group one (poor readers); experimental group two
(average readers), experimental group three (good
readers and experimental group four (outstanding
readers). The control group (group five) would
receive no intervention. The researcher could
chart the differential effects of the intervention
on the groups, and thus have a more sensitive
indication of its effects than if there was only
one experimental group containing a wide range
of reading abilities; the researcher would know
which group was most and least affected by
the intervention. Parametric designs are useful
if an independent variable is considered to have
different levels or a range of values which may have
abearingontheoutcome(confirmatoryresearch)
or if the researcher wishes to discover whether
different levels of an independent variable have
an effect on the outcome (exploratory research).
Chapter 13
The parametric design
Here participants are randomly assigned to groups
whose parameters are fixed in terms of the levels
of the independent variable that each receives.
For example, let us imagine that an experiment
is conducted to improve the reading abilities
of poor, average, good, and outstanding readers
Repeated measures designs
Here participants in the experimental groups are
tested under two or more experimental conditions.
So, for example, a member of the experimental
group may receive more than one ‘intervention’,
which may or may not include a control
condition. This is a variant of the matched pairs
Box 13.3
Interaction effects in an experiment
Motivation for mathematics
100
80
60
40
20
0
15 16 17 18
Age
Males
Females