Information and Knowledge Management using ArcGIS ModelBuilder

Hesbon Nyagowa, Dennis Ocholla and Stephen Mutula
six schools were purposively included in the sample to provide insight into variation in the eSchools
settings. Stratified probabilistic sampling of eSchool users was done to reduce the costs of data
collection and yield results that could be inferred to the population (Guerrero, 2010). To reduce
sampling error in the study an acceptably large sample was sought, and the variability of the sample
characteristics was increased by using stratification within schools and between schools (Hussmann,
Mehran & Varma, 1990). Stratification between schools was based on the population of eSchool
users. Within each school, stratification was done at class level based on number of students in each
class and the gender ratio in the case of co-education school.
The respondents were spread across four levels of education (Forms I, II, III and IV). Each dimension
of eSchool Success model was assessed using many question items. Blaikie (2009) observes that
when many conditions have to be satisfied, the sample size should be made larger. With the average
degree of freedom of 8 for each dimension, a power of alpha = 0.8, and the level of confidence of 0.05
set for the current study, the desired sample size came to 754 (MacCallum, Browne & Sugawara,
1996). To accommodate the use of a split-half in undertaking exploratory factor analysis, the ideal
sample size was doubled to 1508. Data collected was triangulated from observations, interviews and
a questionnaire (Gupta, 2007). Observation was made on installed infrastructure and use of the
eSchool. Interviews were conducted for school principals to get in-depth information on benefits of the
eSchool and challenges encountered. The questionnaire facilitated collation of perception of eSchool
users on different attributes of all the six dimensions of ESchool Success model. A total of 776
completed questionnaires were returned. This constituted 51.4% response rate which is considerably
high and is attributed to the hand delivery of the questionnaire (Maxfield and Babbie, 2008).
4. Validation of instruments
The study instruments stood the test of reliability and validity. Data was found to be stable in the splithalf
exploratory factor analysis and had high reliability, with all dimensions recording an alpha value of
0.7 and above apart from the ‘training for use effectiveness’ dimension which recorded alpha value of
0.46. A scatter plot (figure 1) of the alpha from exploratory and confirmatory factor analysis show
close correlation which confirms stability in the data sets. To validate the conceptualized seven
dimensions of eSchool Success model, a scree plot of the possible factors was made and it revealed
an elbow between five and nine component positions. The exact position of the elbow could be
pinned to seven components as demonstrated in Figure 2.
Figure 1: Scatter plots of test and confirmatory alpha
Construct validity was established through factor analysis. Seven factors with many measurement
items loading to them, in the same way as was theoretically conceptualised, were confirmed. These
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