9. Challenges for KZN Department of Education
9.3. Results
In what follows, various results from the analysis of the data is presented. As pointed out
earlier, the education system in the country was split along racial lines. It is the researcher's contention that, while the legislated segregation of schools, together with the unequal distribution of resources, is no longer applicable, the imbalances of the system are still evident. To illustrate this, one begins by dividing the respondents into three categories: Ex-NED school, Ex-HOD schools and Ex-DET schools. These schools are then analised in relation to the questions being researched. In the sample, there were no schools from the previously Ex-HOR Department of Education, hence there are only 3 categories. In the Ethekwini region of KwaZulu-Natal there is a very small minority of Coloured people. In this sample, many of the Coloured educators from the former Ex- HOR schools are now teaching in one of the other former ex- department schools.
Frequency Percent
Ex-DET 485 39.7
Ex-HOD 533 43.6
Ex-NED 204 16.7
Total 1222 100.0
Table 32: Classification of educators by historical ex-departments
As expected, the majority of respondents are now employed at Ex-HOD schools. This is easily explained by the fact that Durban, which forms the major part of Ethekwini, was originally the primary residential location for people oflndian origin.
9.3.1. Attitude towards Technology
To determine the respondents' attitudes towards technology, they were required to respond to 20 Likert-type statements. The data was collated and analyzed in SPSS according to the following categories: historical school department (Ex-DET, Ex-HOD, Ex-NED), Race, and Socio-economic category of school based on the Department of Education's "deciles" rankings (Low, Medium & High). In attempting to justify the assertion that the low socio-economic schools are predominantly the African schools (Ex- DET), primarily staffed by African educators who are, for the most part, not yet proficient in leT, the researcher first defines unambiguously what is meant by a low socio-economic school. The Department of Education's definition which defines schools according to economic deciles is used. Without loss of any generality, one aggregates the lower four deciles (1 - 4) and define these as low socio-economic schools, while deciles 5 to 7 are defined as medium socio-economic schools, and deciles 8 to 10 are considered to be high socio-economic schools.
70 60 50
Percent 40 30 20
Attitudes Towards Technology by Ex-Departments
1
~ ~~=-I:!SI~IIII:.
Negative Neutral Positive Strongly Positive Categories
o Ex-DET
• Ex-Hod o Ex-Ned
Figure 22: Overall Attitudes Towards Technology based on Ex-Departments.
70 60 50 40
Percent
30 20 10 0
Negative
Attitudes Towards Technology by Race
Neutral Positive Categories
Strongly Positive
Figure 23: Overall Attitudes Towards Technology based on Race.
o African
• Coloured o Indian
o White
Percent
Attitudes Towards Technology based on Socio-economic Scales
Negative Neutral Positive
Categories
Strongly Positive
o
Low• Meduim
o
HighFigure 24: Overall Attitudes Towards Technology based on Socio-Economic scales.
9.3.2. Discussion
It is interesting to note what may be considered as a counter-intuitive result: the attitude towards technology is far more positive in the both educationally and economically historically disadvantaged schools (Ex-DET) than in the historically advantaged Ex-NED schools (Figure 22). However, the researcher believes that this trend reflects the national political trends in which Black people in general, and African people in particular, are much more positive about the future of the country than other race groups. This is reinforced by the fact that, when considered according to Race, only 45% of White people (Figure 23) are strongly positive, while 55% of the educators in Ex-NED schools (Figure 22) are strongly positive. The difference is apparent because a significant number of Indian educators and approximately 10% of African educators are teaching in these
schools. It is noteworthy that very few of the respondents are neutral or negative about technology, which provides a sound basis upon which the KZN DOE can build.
9.3.3. Overall Proficiency in Technology
To determine the educators' readiness to adapt to, and to adopt technological interventions within their schools a variable called "technology competence" was computed (as is explained under methods in chapter 4). This is represented in figures 25, 26 and 27. Again, the technological proficiency of educators is illustrated as a function of several variables.
Technology Proficiency by Race
No Proficiency Less Proficiency M:>derate High Proficiency Proficiency
Categories
Figure 25: Overall Technology Proficiency based on Race
o African
• Coloured
o Indian
o White
60 50 40
Percent 30
20 10
o
Technology Proficiency by Ex -Dpartments
NoProfic iency Less Proficiency M eduim High Proficiency Proficiency
Categories
Figure 26: Overall Technology Proficiency based on Ex-Departments
60 50 40
Percent 30
20
10
o
Technology Proficiency by Socio-Economic Scales
No Proficiency Less Proficiency Moderate High Proficiency Proficiency
Categories
Figure 27: Overall Technology Proficiency based on Socio-Economic Scales
o Ex-DET
• Ex-HOD o Ex-NED
o Low
• Medium
o High
9.3.4. Discussion
Figures 25, 26 and 27 illustrate clearly that the overall proficiency in technology is unsatisfactory, with the majority of respondents across all categories showing little, or no, proficiency in technology. This trend is only reversed for the White Race group and the Ex-NED schools. The situation is by far worse for the African Race group and the Ex-DET schools, than for any other category. This trend is exacerbated by the fact that most of these schools fall within the low and medium economic sector.
9.3.5. Core Proficiency in Technology
The core proficiency measures the absolute minimum skills required by the respondents to begin implementation of leT, and is calculated using only 4 from the 17 items investigated for the overall proficiency in technology. These are: computer knowledge, word processing, email and Internet. The results are illustrated in figures 28, 29 and 30.
Core Proficiency
I ~NO
• YesI
African Coloured Indian White Race
Figure 28: Core Proficiency by Race
90 80 70 60 50 Percent 40 30 20 10
Core Proficiency
O~"'ii
Ex-DET Ex-NED Ex-Departments
Ex-HOD
Figure 29: Core Proficiency by Ex-Departments of Education
Percent
90 80
7060
50 40 3020
10
o
Core Proficiency
Low Medium
Socio-Economic Scales
Figure 30: Core Proficiency by Socio-Economic Scales
High
~ ~
IoNol
~
9.3.6. Discussion
The researcher has found that, in the schools that most need technological intervention, the core computational skills are sorely lacking. This brings into question the attempts by the KZN DOE to implement ICTs in these schools, without other non-technological interventions such as educator training programmes and educator relocation exercises.
The trend, as illustrated by historical education departments, is reflected when one considers core proficiency by race group. This is not surprising since, as shown later, the educator population is still largely distributed as it was historically, with the exception of the Indian race group whose educators may now be found almost equally in the Ex-NED, as well as the Ex-HOD schools. As a result of the fact that the learner population is still primarily distributed along historical grounds (again with the exception of the Indian learners), the lack of significant ICT intervention in the Ex-DET schools further exacerbates the economic divide in the country.
9.3.7. Socio-economic Distribution
Based upon the definitions of "socio-economic scales", provided previously in this chapter, one obtains the relationships contained in figures 31 and 32 which illustrate the racial distribution of educators according to the socio-economic scales, and the distribution of schools according to the same scales.
1
Percent
Educators by Race and Socio-Economic Scales
Low rv1eduim High Socio-Economic Scales
Figure 31: Distribution of educators by Race and Socio-Economic scales
LJ African
• Coloured
LJ Indian
o
WhiteEducators by Ex-Departments & Race
100 90 80 70 60 Percent 50 40 30 20 10 0
African Coloured Indian White Race
Figure 32: Distribution of Educators by Ex-Departments & Race
Schools by Ex-Departments & Socio- Economic Scales
100 80
Percent
60 40 20 0
Low Meduim High Socio-Economic Scales
Figure 33: Distribution of schools into socio-economic classes
El DET .HOD ONED
EJ Ex-DET
• Ex-HOD D Ex-NED
9.3.8. Discussion
As can be seen from figures 31 and 32, Indian and White educators are almost exclusively employed in schools classified in the high socio-economic scales, which are mostly the Ex-HOD and Ex-NED schools, while the majority of African educators are employed within the low and medium socio-economic schools. Figure 33 shows that previously Indian and White schools are all classified as privileged. It is important to recognize that this classification does not, in any way, reflect on the learner population in these schools. The Department's classification attempts merely to categorize the schools by variables such as access to electricity, water, paved roads and telephones, amongst others.