3. Sampling weight: The sampling weight is the number for restoring the original importance of each unit within the population segment. In each stage of sampling there is a different weight
3.4 Quantitative Results and Key Findings
3.4.4 Research Question Four: What factors determine effective NET deployment, utilisation, and integration in schools?
Table 9.2
Chi-square analysis of perceived effectiveness of professional development activities.
Stakeholder
Weighted Count Percentage
Chi-square p valuea Effective Not Effective Effective
Not Effective How effective is the ATs’ professional support?
LET 362.39 9.95 97.33 2.67 0.4217
NET 61.63 4.01 93.89 6.11
How effective are school-based workshops organised by the ATs?
LET 336.39 12.56 96.40 3.60 0.4213
NET 48.12 2.75 94.59 5.41
How effective are the NET Section’s professional development seminars or workshops?
LET 342.15 9.73 97.23 2.77 0.0021
NET 58.92 7.61 88.56 11.44
aIf Chi-square is missing, then the p value is yielded from the Fisher’s exact test. P values <0.05 are shown in bold.
3.4.4 Research Question Four: What factors determine effective NET
Figure 10. Stakeholder opinions on the effectiveness of NET use, support, and integration.
Table 10
Chi-square analyses of NET deployment, utilisation, and integration in schools Stakeholder
Weighted Count Percentage
Chi-square p valuea
Disagree Agree Disagree Agree
The NET is used effectively at your school.
LET 44.25 354.91 11.09 88.91 0.02 0.9888
NET 7.79 58.75 11.70 88.30
SH 5.86 47.15 11.06 88.94
The NET is supported effectively by your school.
LET 27.38 367.74 6.93 93.07 1.000
NET 5.51 61.02 8.28 91.72
SH 1.84 52.16 3.41 96.59
The NET is integrated into the school effectively.
LET 44.43 353.40 11.17 88.83 0.24 0.8877
NET 7.53 59.00 11.32 88.68
SH 4.73 47.91 8.98 91.02
Note. If 20% of cells have expected count less than 5, then the Fisher’s exact test is used and no Chi-square is reported.
aIf Chi-square is missing, then the p value is yielded from the Fisher’s exact test. P values <0.05 are shown in bold.
SF11. Stakeholders’ views regarding the support that they believe School Heads provide NETs with vary slightly, but are generally positive. There are slight differences in perceptions of School Heads’ support both vertically (between Schools Heads and teachers) and horizontally (between LETs and NETs).
There were discrepancies in the responses to the questions about the perceived support of the School Head. Although 100% of the School Heads felt that they acknowledged the NETs contributions, only 81% of the NETs felt this way. Figure 11 and Table 11 illustrate findings related to stakeholder perceptions of the School Heads’ involvement in the PNET Scheme.
Figure 11. Stakeholder opinions on the School Head’s involvement in the PNET Scheme.
Table 11
Chi-square analysis of stakeholders’ perspectives on the School Head’s role Stakeholder
Weighted Count Percentage
Chi-square p valuea
Disagree Agree Disagree Agree
The School Head has identified the role of the NET clearly.
LET 20.89 369.25 5.35 94.65 1.00
NET 9.36 57.17 14.07 85.93
SH 2.06 51.94 3.82 96.18
The School Head has realistic expectations for the NET.
LET 27.23 363.65 6.97 93.03 3.04 0.2188
NET 8.52 58.01 12.81 87.19
SH 3.14 50.86 5.82 94.18
The School Head has utilised the NET fully as an educator.
LET 42.18 341.22 11.00 89.00 2.56 0.2777
NET 10.09 56.44 15.17 84.83
SH 9.55 44.46 17.68 82.32
The School Head has supported the NET in his/her role.
LET 17.37 373.07 4.45 95.55 <.0001
NET 4.61 61.03 7.03 92.97
SH 1.09 52.91 2.03 97.97
The School Head has acknowledged the NET’s contributions.
LET 24.40 362.79 6.30 93.70 0.0086 0.1660
NET 12.13 53.44 18.50 81.50
SH 0 54.01 0 100
Note. If 20% of cells have expected count less than 5, then the Fisher’s exact test is used and no Chi-square is reported.
aIf Chi-square is missing, then the p value is yielded from the Fisher’s exact test. P values <0.05 are shown in bold.
To verify these discrepancies and to obtain additional details, non-parametric tests were performed with the original scale (1[strongly disagree]-4[strongly agree]). Although the pre-collapsed ordinal data could be treated as continuous, the data structure cannot meet the parametric assumptions of ANOVA (e.g. normality and homogeneity of variance), and therefore non-parametric tests were more appropriate. The Wilcoxon/Kruskal-Wallistest is a rank-sum test, in which the relative position of each observation is arranged. The so-called mean difference is actually the difference of the sum of the ranks.
Non-parametric test of “The school head has identified the role of the NET clearly” By Stakeholder
Wilcoxon/Kruskal-Wallis test yields an overall significant difference (p = 0.0012). The Wilcoxon non-parametric multiple comparison procedure shows that there is a significant
difference between NET and LET, and between SH and LET in their responses to the statement
“The school head has identified the role of the NET clearly” (shown in Table 11.1).
Table 11.1
Non-parametric multiple comparison
Level - Level Adjusted Mean
Difference
Std Err Dif Z p
NET LET 47.01 14.39 3.27 0.0011
School Head LET 32.15 14.71 2.19 0.0289
School Head NET -4.73 5.79 -0.82 0.4135
Note. P values <0.05 are shown in bold.
Non-parametric test of “The school head has realistic expectations for the NET”
By Stakeholder
As shown in Table 11.2, Wilcoxon/Kruskal-Wallis test yields an overall significant difference (p = 0.0038). The Wilcoxon non-parametric multiple comparison procedure shows that there is a significant difference between NET and LET in their responses to the statement “The school head has realistic expectations for the NET.” Specifically, both the NETs and School Heads have higher ratings than local teachers for this question.
Table 11.2
Non-parametric multiple comparison
Level - Level Adjusted Mean
Difference
Std Err Dif Z p
NET LET 45.10 14.44 3.12 0.0018
School Head LET 24.53 14.92 1.64 0.1000
School Head NET -5.79 5.745 -1.01 0.3139
Note. P values <0.05 are shown in bold.
Non-parametric test of “The school head has utilised the NET fully as an educator”
By Stakeholder
Wilcoxon/Kruskal-Wallis test yields an overall significant difference (p = 0.0013). The Wilcoxon non-parametric multiple comparison procedure shows that there is a significant difference between NET and LET, and between SH and LET in their perception of “The school head has utilised the NET fully as an educator” (shown in Table 11.3). To be more specific, NETs have higher scores than local teachers for this question.
Table 11.3
Non-parametric multiple comparison
Level - Level Adjusted Mean
Difference
Std Err Dif Z p
NET LET 48.80 14.77 3.31 0.0009
School Head NET -16.96 5.86 -2.89 0.0038
School Head LET -18.04 15.24 -1.18 0.2364
Note. P values <0.05 are shown in bold.
Non-parametric test of “The school head has supported the NET in her/his role”
By Stakeholder
Wilcoxon/Kruskal-Wallis test yields an overall significant difference (p = 0.0008). The Wilcoxon non-parametric multiple comparison procedure shows that there is a significant difference between NET and LET, and between SH and LET in their perception of “The school head has supported the NET in her/his role” (shown in Table 11.4). Between the LETs and the NETs, NETs had a stronger perception that the School Head supported the NET. Similarly, between School Heads and LETs, School Heads had a stronger perception that they supported the NETs.
Table 11.4
Non-parametric multiple comparison
Level - Level Adjusted Mean
Difference
Std Err Dif Z p
NET LET 50.25 14.63 3.43 0.0006
School Head LET 31.26 15.17 2.06 0.0393
School Head NET -5.45 5.65 -0.97 0.3340
Note. P values <0.05 are shown in bold.
Non-parametric test of “The school head has acknowledged the NET’s contributions”
By Stakeholder
Wilcoxon/Kruskal-Wallis test yields an overall significant difference (p = 0.0204). The Wilcoxon non-parametric multiple comparison procedure shows that there is a significant difference between NET and LET in their perception of “The school head has acknowledged the NET’s contributions” (shown in Table 11.5). Between the School Heads and the LETs, School Heads had a stronger perception that they acknowledged the NET’s contribution.
Table 11.5
Non-parametric multiple comparison
Level - Level Score Mean
Difference
Std Err Dif Z p
School Head LET 39.68 14.77 2.69 0.0072
NET LET 20.82 14.43 1.44 0.1490
School Head NET 3.62 5.73 0.63 0.5274
Note. P values <0.05 are shown in bold.
As indicated by the preceding analyses, sometimes NETs and LETs significantly disagree with each other, and sometimes SH and teachers have different perceptions. These results imply differences in perceptions both vertically (between School Heads and teachers) and horizontally (between NETs and LETs).
3.4.5 Research Question Five: What factors foster and inhibit NET-LET