CHAPTER 6: QUANTITATIVE RESULTS
6.10 Summary of Hypothesise Testing Results
175 4. Behaviour→Results
Objectives→Results OB * Behaviour→Results
.368 .202 .404
.083 .069 .006
.637 1.585 -1.009
.002**
.113 .005**
Accepted Accepted Accepted
H4b: Training objectives moderate the relationship between learning and behaviour Accepted Note: TC= Training Content, OB= Training Objectives, β= Standardised Path Estimates (regression weights), S.E= Standard Error, C.R= Critical Value (t-value), P=Significance of value, *** = Significant at 0.001 levels (two tailed), ** = significant at 0.01 levels (two-tailed) As shown in Table 6.20, is the comparisons between the independent and dependent variables (simple effects), the effects of the moderator on the dependent variables and the interaction effects with independent variables on dependent variables. The results show no moderating significant effects for the three paths: the training content did not moderate the effects on the relationships between learning and behaviour (β= -0.99, t-value = 0.930, p = 0.706), and training objectives did not moderate the relationship between learning and behaviour (β= 0.005, t-value = 1.304, p = 0.812); and training objectives did not moderate the relationship between behaviour and results (β= 0.404, t-value = -1.009, p = 0.005). A significant moderating effect was found for the one path:
the training content moderate the effects on the relationships between behaviour and results (β=
0.344, t-value = 0.104, p = 0.004). The final hypothesised model is illustrated in Figure 8.1 in Chapter 8.
176 Table 6. 21 Summary of Hypotheses Testing Results
Hypotheses Statements Path Coefficient (β) Remarks
H1a: Training content → reaction __ Rejected
H1b: Training content →learning __ Rejected
H1c: Training content →behaviour 0.633*** Accepted
H1d: Training content →results 0.461** Accepted
H2a: Training objectives →reaction 0.131* Accepted
H2b: Training objectives →learning __ Rejected
H2c: Training objectives →behaviour __ Rejected
H2d: Training objectives →results __ Rejected
H3a: Training content → learning *behaviour __ Rejected
H3b: Training content →behaviour *results 0.344** Accepted
H4a: Training objectives →learning *behaviour __ Rejected
H4b: Training objectives →behaviour* results 0.404** Accepted
H5: Trainees ‘reaction →learning 0.145* Accepted
H6: Learning →behaviour 0.620*** Accepted
H7: Behaviour →results 0.565** Accepted
Notes: Significance levels: *p < 0.05; **p <0.01; ***p <0.001
6.11 Chapter Conclusion
This chapter provided the results from the final filtered scales and fifteen hypotheses testing of the survey questionnaire. Kaiser-Meyer-Olkin (KMO) and Bartlett ‘s tests were performed to determine if the confirmatory factor analysis can be conducted. Before the findings could be inferred, reliability and construct validity tests were computed to measure the reliability and construct validity of the instrument, all the measurement scales from the data were found to be satisfactory. The findings of the data analysis and testing the hypothesise of the final model found a positive, significant relationship between the four levels of training outcome (reaction, learning, behaviour and results). Furthermore, training content was found not to have a significant effect on the reactions of trainees, learning and the training results.
177 Similarly, training objectives were found not to have a significant effect on learning, behaviour and results; however, a significant effect was found on training objectives and the reaction of trainees to the training. Training content and training objectives were found to have no significant moderation effect on learning and behaviour. On the other hand, training content and training objectives were found to have a significant moderation effect on trainees behaviour and the training outcome/results. In-depth discussions on the results of the analysis will be covered in Chapter 8 of this study. The next chapter (Chapter 7), is the analysis of qualitative data that were collected through the semi-structured interviews.
178 CHAPTER 7: RESULTS OF QUALITATIVE DATA
7.1 Introduction
The purpose of this chapter is to present the results of the qualitative data collected from interviews with eight participants from different NPOs. The study purposively sampled fifteen participants, but only eight agreed to participate in the study—this translates to 53.3% response rate, with only seven consenting to be audio recorded. Only one participant did not consent to be audio recorded but agreed to participate in the interviews. The field notes were taken for the participant who did not consent to be audio recorded. In this chapter, the characteristics and responses of the participants during the interviews are presented. Since the core of this dissertation is to evaluate the effectiveness of the NDA training program, mainly focusing on one training intervention of NPO Governance. The NVIVO v.12 computer software was used to manage, organise and analyse the data. The main categories or themes for evaluating the effectiveness of the training were the reaction of trainees on the training, learning, job transfer and results of the organisation due to the training.
7.2. Demographic Data of Participants
The participants of the interviews were all serving on the governance structure in their respective organisations; these were Chairperson of the Board, Chief Executive Officers and Board Secretaries. The demographic details of the participants are summarised in Table 7.1.
179 Table 7. 1 Demographic Data of the Study Participants
There were some basic similarities and differences in the demographics of the participants, and the demographics included age, education, experience in the NPO, gender and occupation. The similarities and differences are indicated with the Figures below. The project map on NVIVO software was used for case classification to show associated items. The associations of demographics of Chief Executive Officers are shown in figure 7.1 below.
ID Age Education NPO Experience Gender Occupation
P1 Between 20 and 39 BD 6 to 9 years M Board Secretary
P2 Between 50 and 59 ND 6 to 9 years F Board Chairperson
P3 Between 50 and 59 G12 More than 10 years F Board Chairperson
P4 Between 50 and 59 ND More than 10 years F CEO
P5 Between 40 and 49 ND 2 to 5 years F Board Chairperson
P6 Between 40 and 49 BG12 More than 10 years F Board Secretary
P7 Between 50 and 59 ND 6 to 9 years F CEO
P8 Between 40 and 49 G12 10 years M Board Chairperson
BD-Bachelor’s Degree ND-National Diploma G12-Grade12 BG12 – Below Grade12
180 Figure 7.1 Demographic Similarities and Differences of Chief Executive Officers
The figure indicates that participant P4 and P7 had lots of similarities where they are both females, they occupy the position of Chief Executive Officer within their organisations, they both have Diploma as the highest level of formal education and both aged between 50 and 59 years old. The only difference found between these two participants were on their years of experience whereby participant “P7” has between 6 and 9 years of experience, whereas participant “P4” indicated that she has more than ten years of experience in the Non-profit
181 sector. Figure 7.2 depicts similarities and differences of Board Secretaries found during data analysis process.
Figure 7.2 Demographic Similarities and Differences of Board Secretaries
The figure indicates that participant P1 and P6 were both females, and this was the only similarity that was found between the two participants. The differences were found where “P6” indicated her level of education as Grade 12, aged between 40 and 49 years old with NPO experience of more than ten years. Participant “P1” indicated that she is between 20 and 39 years old and has a Bachelor’s degree qualification as her highest level of formal education and between 6 and 9 years of experience in the Non-profit sector. Figure 7.3 indicates the demographic similarities of participants who are Chairpersons of the Board.
182 Figure 7.3 Demographic Similarities and Differences of Chairpersons of the Board
Four participants were Chairpersons of the Board (P2, P3, P5, P8). With regards to gender, participants (P2, P3 and P5) were females and participant “P8” was male. Participants “P2” and
“P5” both had National Diploma, and participants “P3” and “P8” had Grade 12 as their highest level of formal education. Other similarities were between participant “P5” and “P8” who are between 40 and 49 years of age, and participants “p2” and “P3” who are between 50 and 59 years old. The demographic differences amongst these four participants were mainly on the years of experience of which participant “P2” indicated that she has between 6 and 9 years of experience in the Non-profit sector. Participant “P3” more than ten years of experience, “P5” between 2 and 5 years and “P8” indicated that he has ten years of experience. The next section discusses the findings of the research questions.
183 7.3. RESULTS OF THE RESEARCH THEMES
This section covers the results of the research themes on which the interview questions derived.
Four themes guided the interview questions, and these were:
Perceptions and attitudes of trainees on the training (Reaction);
Learning (skills and knowledge);
Trainees’ Behaviour (Learning transfer); and
Results (Change or Impact in the organisation)
Data were collected through face-to-face interviews with individuals from different NPOs who received the training from the NDA. The brief process on how the researcher arrived at the findings or results is depicted in figure 7.4 below
Figure 7.4 Data Analysis Process
Data were gathered through in-depth interviews through audio recording and field notes, then later transcribed in Microsoft Word. The data was first cleaned in Microsoft, and proper headings were assigned before imported to NVIVO software.
Data Gathering
Cleaning and Importing
Data
Reorganising Data
Data
Exploration Data Coding Generating Themes
184 Figure 7.5 Tree Nodes from NVIVO Software
The new project was created in NVIVO, and data were imported as text files. Queries and coding functions were then used for exploration and analysis of data, and graphs were used for visualization of the data. Data exploration is the process conducted before the data analysis to understand what is in the dataset as well as the characteristics of the data. The Nodes enabled the researcher to gather the related information together so that emerging patterns and issues could be easily identified. There are two common nodes, and these are Tree nodes and Free nodes