118
4.4.2.5 Data collection
The process of data collection began in February 2006 and was completed in the first
week of July of the same year. To reiterate, data were collected by means of two
methods. One was a pre-coded questionnaire, and the other was the VConf-FGI.
The questionnaire was used for quantitative data collection which included among
others, personal demographic information, career profile/prior experience; skills, tasks,
roles and responsibilities; job challenges and strategies for dealing with them,
perceptions and role expectations. Questionnaires were posted overland to the
participants towards the end of March 2006 and responses were received during April
and July 2006. The response rate was 77 per cent.
4.4.2.6 Data analysis
In this study, the SAS/STAT statistical package, version 9.1, was used to analyse the data
captured from the questionnaire responses. Twenty three questionnaires were returned
and their responses captured. Data analysis and presentation procedures for the
quantitative data were employed. Each questionnaire item was regarded as representing a
biographical characteristic or perception of the respondent on some managerial issue, and
thus a separate variable. Analyses undertaken on the responses to these variables included
the following:
• one- way frequencies: exploratory frequency tables on each and every
questionnaire item.
• combined frequency tables: combined frequency tables for each section (D-L)
ranked according to sum totals, calculated for each item within an aspect;
the sum totals were calculated as the sums of frequencies in the two most
favoured adjacent categories in each section
• summary tables of sub-item means: standard deviations minimum and maximum
values for each of the issues covered within sections D-L of the various
managerial issues
119
• relationships: cross-tabulations of the sub-sets of items within sections D-L of the
questionnaire with biographical variables of age, years experience as HoD and
years attached to their particular institution.
The purpose of each strategy is discussed below.
The analysis was conducted using one-way frequency tables for each question on the
questionnaire. As an initial exploratory analysis step, univariate one-way frequency
tables, categorised according to the specific options of each question, such as, ‘strongly
agree’ to ‘strongly disagree’ ; or ‘single’, married’, ‘divorced’, were initially calculated
for each variable. This step was undertaken to validate data and correct or remove any
spurious responses. For example, if a response of ‘7’ should be encountered for any of
the 5 point rating scale questionnaire items in sections D-L, the particular response for
the participant can be further investigated, traced back to the participants’ questionnaire
and checked. A value of ‘7’ falls outside the range of valid responses - which vary
between ‘1’ and ‘5’ for the five point rating scale questionnaire items.
The one-way frequency tables on the biographical variables, questions 1-33, were
furthermore calculated as a means of describing the sample population of women in
managerial positions. This was done in two stages, first on the entire sample population,
then frequencies were split into SA and UK participants separately.
Combined frequency tables for sub-sets of items for each of the sections, D-L, of the
questionnaire were utilised. In each of the sections, D to L, participants’ ratings on
several sub-issues were required. Each of these sub-issues represented a separate
variable. The responses to the sub-issues in each section were integrated into a combined
frequency table for each section/managerial aspect. By studying the response distribution
within the various tables, a general impression of participants’ perceptions on the various
managerial issues can be formed.
Summary tables of mean, standard deviations, means and maximum values for each of
the sub-issues covered within each of the managerial issues were calculated as well as for
120
each of the sub-issues covered within each of the managerial issues of sections D-L. By
studying the mean response values within a section, sub-issues that deviate from the
others within the section/aspect can easily be identified as a mean value substantially
larger/smaller than the other mean values. These identified mean values indicate that
participants perceived/rated the particular items/sub-issues differently to the others.
Combined-items frequency tables for each of sections D-L of the questionnaire were
ranked. Participants had to decide which sub-items/sub-issues within each managerial
issue they regarded as more important than others. In an attempt to rank the importance
of the various aspects, the frequencies of the most favoured adjacent categories within a
section, usually the positively rated categories, such as, ‘important’ and ‘very important’/
or ‘agree’ and ‘strongly agree’ categories were summed for each sub-item within a
section/managerial issue. It was argued that by combining adjacent ‘positively’ rated
‘agree’, ‘strongly agree’ or ‘negatively’ rated disagree/strongly disagree’ categories,
sub-items within a section could be ranked according to levels, of ‘like’ if positively rated
or ‘dislike’ if majority of the items were negatively rated. The sum for each sub-item
within a managerial aspect was ranked in descending order and presented as a separate
table; such as,
•
relationships: cross-tabulations of sub-items within sections D-L of the
questionnaire with biographical variables of age, years experience as HoD and
years attached to their particular institution
•
frequency tables of cross-tabulations present how the biographical variables of
age, years experience as HOD and years experience at current institutions
affect/interact with the positively perceived part of each section’s rating scale; the
cross-tabulations were done in an attempt to determine whether these selected
biographical variables influence participants’ perceptions of the various
managerial aspects
•
chi-square tests were calculated from the table of frequencies to determine if there
was any significance.
121
4.4.2.7. Reliability and validity
According to McMillan and Schumacher (1993:227), reliability refers to the
consistency of measurement, which is, the extent to which the results are similar over
different forms of the same instrument or occasions of data collecting. A highly reliable
instrument (Cates 1985: 124) can be depended upon to produce the same, or nearly same,
score when administered twice to the same subject or when administered to two subjects
of equivalent talent and experience. To ensure consistency of measurement in the current
investigation, the researcher administered the instruments to subjects of similar
educational and professional backgrounds.
Validity is the degree to which scientific explanations of phenomena match the realities
of the world (McMillan & Schumacher 1993:601). A measurement instrument
(Cates1985:123) is valid if it measures or represents what it claims to measure or
represent. In the case of this investigation, the survey instrument was used to assess the
lived experiences of the participants as women HoDs in universities. Thus the items on
the questionnaire were all related to this phenomenon of interest. Questionnaires were
posted overland to all participants.
In quantitative research, reliability refers to the consistency of the instrument and test
administration in the study (McMillan & Schumacher1993:385). To enhance reliability
the survey instrument was administered during the same time period to all participants.
Do'stlaringiz bilan baham: |