14.3 Methodology
The project followed a participatory action approach since the researcher,
collaborators, extension officers, farmers, and funder are actively involved in all
phases of the project to ensure that the deliverables are achieved. According to
Backeberg and Sanewe (2010), the method of participatory action research is most
appropriate, since people, especially farmers, benefit while the research is ongoing.
The participatory action approach was also recommended by various researchers
who emphasised that the participatory action approach is a good alternative to the
traditional “transfer of technology” or “top–down approach” to agricultural research
and extension. It is against this background that the approach will be used to achieve
the research aims and deliverables, and that all phases have been successfully
completed. The research used quantitative and qualitative methods and purposive
sampling from an existing sample frame from the GDARD database of the homestead food garden project. The sample size of the research was agreed on with
GDARD officials, but the sample size should be statistically significant, which is
normally obtained at 10% of the total population. A detailed questionnaire was
developed as a quantitative data collection method and data was collected from 1150
households as follows: City of Tshwane Metropolitan (270), City of Johannesburg
Metropolitan (319), Ekurhuleni Metropolitan (141), and the West Rand District
(204). The questionnaire used both open and closed ended questions. Qualitative
data collection methods included focus group discussions and field observations.
The focus group discussions were conducted among 56 GDARD officials as follows:
City of Tshwane Metropolitan (24), City of Johannesburg Metropolitan and the West
Rand District combined (18), Ekurhuleni Metropolitan (7), and the Sedibeng District
(7). Data collected was analysed quantitatively using the Statistical Package for
Social Sciences (SPSS) windows version.
The following approach was used to determine correlations among variables:
Correlation is a bivariate analysis that measures the strengths of association
between two variables and the direction of the relationship. In terms of the strength
of relationship, the value of the correlation coefficient varies between +1 and À1.
When the value of the correlation coefficient lies around Æ1, it is said to be a perfect
degree of association between the two variables. As the correlation coefficient value
goes towards 0, the relationship between the two variables will be weaker. The
direction of the relationship is simply the + (indicating a positive relationship
between the variables) or—(indicating a negative relationship between the variables)
sign of the correlation. Usually, in statistics, four types of correlations are measured:
Pearson correlation, Kendall rank correlation, Spearman correlation, and the PointBiserial correlation. In this example, Pearson and Spearman correlations were used
and the following variables were found to be significant: garden availability, age,
gender, household members, and household income.
The following econometric model was used to determine the association of
variables (Greene 1993):
306
P. Maponya et al.
The project followed a participatory action approach since the researcher,
collaborators, extension officers, farmers, and funder are actively involved in all
phases of the project to ensure that the deliverables are achieved. According to
Backeberg and Sanewe (2010), the method of participatory action research is most
appropriate, since people, especially farmers, benefit while the research is ongoing.
The participatory action approach was also recommended by various researchers
who emphasised that the participatory action approach is a good alternative to the
traditional “transfer of technology” or “top–down approach” to agricultural research
and extension. It is against this background that the approach will be used to achieve
the research aims and deliverables, and that all phases have been successfully
completed. The research used quantitative and qualitative methods and purposive
sampling from an existing sample frame from the GDARD database of the homestead food garden project. The sample size of the research was agreed on with
GDARD officials, but the sample size should be statistically significant, which is
normally obtained at 10% of the total population. A detailed questionnaire was
developed as a quantitative data collection method and data was collected from 1150
households as follows: City of Tshwane Metropolitan (270), City of Johannesburg
Metropolitan (319), Ekurhuleni Metropolitan (141), and the West Rand District
(204). The questionnaire used both open and closed ended questions. Qualitative
data collection methods included focus group discussions and field observations.
The focus group discussions were conducted among 56 GDARD officials as follows:
City of Tshwane Metropolitan (24), City of Johannesburg Metropolitan and the West
Rand District combined (18), Ekurhuleni Metropolitan (7), and the Sedibeng District
(7). Data collected was analysed quantitatively using the Statistical Package for
Social Sciences (SPSS) windows version.
The following approach was used to determine correlations among variables:
Correlation is a bivariate analysis that measures the strengths of association
between two variables and the direction of the relationship. In terms of the strength
of relationship, the value of the correlation coefficient varies between +1 and À1.
When the value of the correlation coefficient lies around Æ1, it is said to be a perfect
degree of association between the two variables. As the correlation coefficient value
goes towards 0, the relationship between the two variables will be weaker. The
direction of the relationship is simply the + (indicating a positive relationship
between the variables) or—(indicating a negative relationship between the variables)
sign of the correlation. Usually, in statistics, four types of correlations are measured:
Pearson correlation, Kendall rank correlation, Spearman correlation, and the PointBiserial correlation. In this example, Pearson and Spearman correlations were used
and the following variables were found to be significant: garden availability, age,
gender, household members, and household income.
The following econometric model was used to determine the association of
variables (Greene 1993):
306
P. Maponya et al.