RESEARCH METHOD COHEN ok

TYPES OF QUESTIONNAIRE ITEMS 329
I can take advantage of new opportunities [ ]
Icanworkeffectivelywithallkindsofpeople [ ]
Generating new ideas is one of my strengths [ ]
I can usually tell what is likely to work in
practice [ ]
Iamabletoseetasksthroughtotheveryend [ ]
Iampreparedtobeunpopularforthegoodofthe
school [ ]
This enables priorities to be identified, comparing
highs and lows, and for equality of choices to
be indicated, and, importantly, for this to be
done in the respondents’ own terms. It requires
respondents to make comparative judgements and
choices across a range of items. For example, we
may wish to distribute 10 points for aspects of an
individual’s personality:
Talkative [ ]
Cooperative [ ]
Hard-working [ ]
Lazy [ ]
Motivated [ ]
Attentive [ ]
This means that the respondent has to consider
the relative weight of each of the given aspects
before coming to a decision about how to award
the marks. To accomplish this means that the allround
nature of the person, in the terms provided,
has to be considered, to see, on balance, which
aspect is stronger when compared to another. 1
The difficulty with this approach is to
decide how many marks can be distributed (a
round number, for example 10, makes subsequent
calculation easily comprehensible) and how many
statements/items to include, e.g. whether to have
the same number of statements as there are marks,
or more or fewer statements than the total of marks.
Having too few statements/items does not do
justice to the complexity of the issue, and having
too many statements/items may mean that it is
difficult for respondents to decide how to distribute
their marks. Having too few marks available may
be unhelpful, but, by contrast, having too many
marks and too many statements/items can lead to
simple computational errors by respondents. Our
advice is to keep the number of marks to ten and
the number of statements to around six to eight.
Constant sum data are ordinal, and this means
that non-parametric analysis can be performed on
the data (see Part Five).
Ratio data questions
We discuss ratio data in Part Five and we
refer the reader to the discussion and definition
there (see http://www.routledge.com/textbooks/
9780415368780 – Chapter 15, file 15.9. ppt). For
our purposes here we suggest that ratio data
questions deal with continuous variables where
there is a true zero, for example:
How much money do you have in the bank ––
How many times have you been late for school ––
How many marks did you score in the mathematics
test ––
How old are you (in years) ––
Here no fixed answer or category is provided,
and the respondent puts in the numerical answer
that fits his/her exact figure, i.e. the accuracy is
higher, much higher than in categories of data. This
enables averages (means), standard deviations,
range, and high-level statistics to be calculated,
e.g. regression, factor analysis, structural equation
modelling (see Part Five).
An alternative form of ratio scaling is where the
respondent has to award marks out of, say, ten, for a
particular item. This is a device that has been used
in business and commerce for measuring service
quality and customer satisfaction, and is being used
in education by Kgaile and Morrison (2006); see
for example Box 15.3.
This kind of scaling is often used in telephone
interviews, as it is easy for respondents to
understand. The argument could be advanced that
this is a sophisticated form of rating scale, but the
terminology used in the instruction clearly suggests
that it asks for ratio scale data.
Open-ended questions
The open-ended question is a very attractive
device for smaller scale research or for those
Chapter 15