PARTICIPANTS AND EXTENSION OFFICERS 7.3.1 Introduction
Project data should be up-to-date and recorded correctly through setting up a knowledge centre (Bruce & Langdon, 2007:76) so that everybody might have easy access to key project information whenever they need it. The production knowledge of an individual was assessed by looking at factors that were considered when the project was selected and when planning the project commodities. The following scales were used: 1 = No knowledge, 2 = Some knowledge, 3 = Average knowledge, 4 = Above average knowledge and 5 = Excellent knowledge for project planning, with seven factors being investigated (i) “before production”
and (ii) “at interview” and using a scale of 1 = Not important, 2 = Less important, 3 = Important, 4 = More important and 5 = Very important for project selection.
7.3.2 Status of production knowledge of the commodity in the area before production The knowledge of project participants on the status of production of the commodities in the area was assessed and 34% of project participants and 32% of extension officers reported only an average knowledge about the commodity in the area before the start of production, while only a few project participants (2%) and extension officers (9%) reported that they had excellent knowledge before the production started. An alarming aspect is that 50% of project participants had only some and even no knowledge at all.
Out of the total number of extension officers, a total of 37% indicated only some knowledge and even no knowledge. The total percentage of both respondent categories revealed that:
33% average knowledge;
24% had no knowledge;
21% had some knowledge;
17% above average knowledge, and
4% excellent knowledge.
The exact Sig. (2-Sided) Pearson Chi-Square test (Table 7.10 below) indicated a significant difference ( = 14.60; p = 0.005) between the views of participants and extension officers regarding their knowledge about the production status of the commodity in the area before commencement of production. Significantly more project participants (31%) had no knowledge at all, against only 13% of extension officer respondents.
157
Table 7.10: The status of production knowledge of the commodity before the project planning starts according to respondent categories
Respondent categories
Total Production knowledge
categories when planning the project
Project Participants
Extension officers
1. No knowledge (n) 39 10 49
(%) 30.7% 13.2% 24.1%
2. Some knowledge (n) 25 18 43
(%) 19.7% 23.7% 21.2%
3. Average knowledge (n) 43 24 67
(%) 33.9% 31.6% 33.0%
4. Above average knowledge
(n) 18 17 35
(%) 14.2% 22.4% 17.2%
5. Excellent knowledge
(n) 2 7 9
(%) 1.6% 9.2% 4.4%
Total (N) 127 76 203
(%) 100.0% 100.0% 100.0%
= 14.606; p = 0.005
7.3.3 Status of production knowledge of the commodity in the area at the time of interview
A total of 23% of project participants and 14% of extension officers reported that they had average knowledge about the commodity in the area at the time of interview, while only 12%
of project participants and 26% of extension officers reported that they had excellent knowledge. An interesting aspect is that 16% of project participants and 15% of extension officers indicated still having no knowledge, which is an alarming aspect, as shown in Table 7.11 below. A Pearson Chi-Square exact Sig. (2-sided) indicated no statistical difference at 5% significant level between the report of participants and extension officers about the production knowledge at interview. Most important, however, is the increase of above- average knowledge by both respondent categories, from 17% before production to 44% at interview. Excellent knowledge production also increased from 4% to 17%.
158
Table 7.11: The status of production knowledge of commodity at the time of interview according to both respondent categories
Respondent categories
Total Production knowledge categories
at the time of interview
Project participants
Extension officers
1. No knowledge (n) 20 11 31
(%) 16.3% 15.3% 15.9%
2. Some knowledge (n) 6 1 7
(%) 4.9% 1.4% 3.6%
3. Average knowledge (n) 28 10 38
(%) 22.8% 13.9% 19.5%
4. Above average knowledge (n) 54 31 85
(%) 43.9% 43.1% 43.6%
5. Excellent knowledge (n) 15 19 34
(%) 12.2% 26.4% 17.4%
Total (N) (%)
123 100.0%
72 100.0%
195 100.0%
8.659; p = 0.068
7.3.4 Summary of status of production knowledge of the commodity before project start and at the time of the interview
Table 7.12 below shows the improvement in terms of knowledge gained at interview of both respondent categories. There is a significant improvement of 26% (from 17.2% to 43.6%) of respondents who gained above-average knowledge at interview, and a 13% increase (from 4.4% to 17.4%) of all respondent categories gaining excellent knowledge. Project participants indicated a 30% increase of above-average knowledge and extension officer respondents indicated an increase of 21%. This finding supports the need for training of project participants before and during the life cycle of the project.
159
Table 7.12: Comparison of production knowledge before project start and at time of interview Production
knowledge categories
Knowledge before production Knowledge at interview Percentage increase(+)/
decrease (-) of both respondent
categories Project
particip ants (%)
Extension officers
(%)
Both respon dents (%)
Project partici pants (%)
Extension officers
(%)
Both respon dents (%) 1. No
knowledge 30.7 13.2 24.1 16.3 15.3 15.9 -8.2
2. Some
knowledge 19.7 23.7 21.2 4.9 1.4 3.6 -17.6
3. Average
knowledge 33.9 31.6 33.0 22.8 13.9 19.5 -13.5
4. Above average knowledge
14.2 22.4 17.2 43.9 43.1 43.6 +26.4
5. Excellent
knowledge 1.6 9.2 4.4 12.2 26.4 17.4 +13
Total 100 100 100 100 100 100
7.3.5 Knowledge of special design requirements before production
A special design requirement refers to specific designs suitable for the produce of the project.
It is very imperative for producers to know the special design requirements of their projects before production; this will reduce delays as a result of re-designing the projects during establishment which might also disturb production. The perception of knowledge of special design requirements “before” production was assessed. According to Table 7.13 below, 40%
of project participants and 34% of extension officers did not have knowledge about special design requirements before production. Only 2% of the project participants and 11% of extension officer respondents reported that they had excellent knowledge. Significantly lesser project participants (15%) than extension officers (27%) indicated average knowledge, while 12% of project participants and 19% of extension officers had above-average knowledge.
160
Table 7.13: The level of knowledge of special design requirements before production starts according to the respondent categories
Knowledge of special design requirement categories when planning the project
Respondent categories
Total Project
participants
Extension officers
1. No knowledge (n) 50 25 75
(%) 39.7% 33.8% 37.5%
2. Some knowledge (n) 40 7 47
(%) 31.7% 9.5% 23.5%
3. Average knowledge (n) 19 20 39
(%) 15.1% 27.0% 19.5%
4. Above average knowledge (n) 15 14 29
(%) 11.9% 18.9% 14.5%
5. Excellent knowledge (n) 2 8 10
(%) 1.6% 10.8% 5.0%
Total (N) 126 74 200
(%) 100.0% 100.0% 100.0%
What is pleasing is that extension officers (27%) indicated an average knowledge and an above-average knowledge (19%), which means that information was communicated to them as advisors that would have enabled them to communicate it to the 40% of participants who did not have knowledge, as well as the 32% of those who had only some knowledge.
According to the total percentage of both respondent categories, 38% did not have knowledge and 24% only had average knowledge. The Pearson Chi-Square test ( ) concludes that there is a statistically significant association at 5%
significant level between project participants and extension officers respondents about their knowledge of special design requirements. Most alarming is that 71% of project participants indicated only some knowledge and even no knowledge. This is a clear indication that the knowledge of special design requirements has an effect on the success or failure of a project.