CHAPTER 5 DISCUSSION AND CONCLUSION
5.1 Summary of Statistical Analyses
The two types of analyses mentioned in the earlier chapter are descriptive and inferential analyses. A bar chart and a pie chart are used in the descriptive analysis test to display the percentages of respondent demographic information such as gender, age, ethnicity, religion, university, and level of education, which is found in question 1 till 6 of the questionnaires. Multiple Regression Analysis has been used in inferential analysis to examine the strength, direction, and significance of the relationship between the independent and dependent variables.
5.1.1 Descriptive Analysis
Table 5.1 shows the demographic profile of the respondents in this study. Male respondents outnumber female respondents, with a reported rate of 50.6 per cent versus 49.4 per cent, respectively. Majority respondents are aged between 21 to 23 years old, accounting for 79.4 per cent of our data. About 0.2% of our respondents are Malay, Chinese stands for 98.4%, and Indian stands for 1.4%, while
respondents' religious majority are Buddhist with a reported figure of 79.6%. Most respondents (24.4 per cent) attended UTAR as their study university. The most common level of education among respondents was a bachelor's degree, which accounted for 75.2 per cent of our data, followed by Foundation, which was 13.0 per cent of the data.
Table 5.1
Summary of Descriptive Analysis
Variables Frequency Percentage (%)
Gender
Male 253 50.6
Female 247 49.4
Age19 to 20 years old 74 14.8
21 to 23 years old 397 79.4
24 to 26 years old 29 5.8
27 years old and above 0 0
Ethnicity
Malay 1 0.2
Chinese 492 98.4
Indian 7 1.4
Religion
Islam 2 0.4
Buddha 398 79.6
Hinduism 5 1.0
Christian 95 19.0
University
MMU 34 6.8
TARUMT 40 8.0
UTAR 122 24.4
UCSI 40 8.0
INTI 41 8.2
Taylor’s 82 16.4
Sunway 78 15.6
HELP 63 12.6
Level of Education
Foundation 65 13.0
Diploma 53 10.6
Bachelor’s Degree 376 75.2
Master’s Degree 5 1.0
Doctoral Degree 1 0.2
Note.Developed for the research.
5.1.2 Central Tendency
Behavioural intention has the most significant average score (mean) of 4.2296, with a standard deviation of 0.47503, as shown in Table 5.2. Perceived usefulness of hybrid learning system (4.2076) has the second-highest mean, with a standard deviation of 0.57582, followed by Internet Access (4.1168), with a standard deviation of 0.53566. Perceived ease of use has the fourth-highest mean of 4.1104 with a standard deviation of 0.50438, while campus support has the lowest mean of 3.9952 with a standard deviation of 0.54458. Meanwhile, teacher support (4.0565) and self-efficacy (4.0120) have the fifth highest and sixth-highest mean, with a standard deviation of 0.49083 and 0.54211, respectively.
Table 5.2
Summary of Central Tendency Measurement
Variable N Mean Standard Deviation
Perceived Usefulness of Hybrid
Learning System 500 4.2076 0.57582
Perceived Ease of Use 500 4.1104 0.50438
Internet Access 500 4.1168 0.53566
Self-efficacy 500 4.0120 0.54211
Teacher Support 500 4.0565 0.49083
Campus Support 500 3.9952 0.54458
Behavioural Intention 500 4.2296 0.47503
Note.Developed for the research.
5.1.3 Reliability Test
For the reliability test, 500 sets of questionnaires were used in the current study.
Based on the findings as shown in Table 5.3, all independent and dependent variables have showed a great strength of reliability, with Cronbach’s Alpha values ranging from 0.7 to 0.8 except for the independent variable of teacher support, with Cronbach's Alpha value of 0.638. PU had the highest Cronbach's Alpha value (0.805) out of the six independent variables, come after with CS (0.804), IA (0.749), SE (0.724), PE (0.702), and TS (0.638). In the reliability test, the dependent variable, higher education students’ behavioural intention towards hybrid learning, showing a Cronbach's Alpha value of 0.743.
Table 5.3
Summary Result of Reliability Test
No Variable Cronbach’s Alpha Reliability
1 Perceived Usefulness of Hybrid Learning
System (PU) 0.805 Good
2 Perceived Ease of Use (PE) 0.702 Acceptable
3 Internet Access (IA) 0.749 Acceptable
4 Self-efficacy (SE) 0.724 Acceptable
5 Teacher Support (TS) 0.638 Questionable
6 Campus Support (CS) 0.804 Good
7 Behavioural Intention (BI) 0.743 Acceptable
Note.Developed for the research.
5.1.4 Normality Test
Table 5.4 outlined the summary actual findings for the normality test. The findings for the skewness ranged from –1.182 to –0.245 while for the kurtosis, it ranged from –0.057 to 3.009. As a result, the data is normally distributed, with the kurtosis and skewness values falling between ±2 and ±1, respectively. Moreover, the mean values of all construct ranges from 3.7660 to 4.3260. According to the results, most respondents selected 'neutral,' 'agree,' or ‘strongly agree' for every element. Further, the standard deviation of the factors is less than 1, which range from 0.58165 to 0.88363.
Table 5.4
Summary Result of Normality Test (Actual Test)
Note.Developed for the research.
5.1.5 Inferential Analysis
5.1.5.1 Multiple Linear Regression Analysis
R square has a value of 0.441 or 44.1 per cent. This means that the six independent variables handle 44.1 per cent of the variation in the dependent variable of higher education students’ behavioural intention towards hybrid learning. According to Table 5.5, other potential variables explained 55.9 per cent (100 per cent – 44.1 per cent) of the dependent variable of higher education students’ behavioural intention towards hybrid learning. The adjusted R square is
0.435, with the significant contribution of the six independent variables to the dependent variable accounting for 43.5 per cent.
The alpha value of 0.05 is more than the p-value (0.000). With a value of 64.932, the F-statistic is noteworthy. This manifests that the model used in this research is adequate. With a positive beta of 1.276, the independent variable that was perceived usefulness of hybrid learning system has the highest significant positive beta. Compared to other independent variables, it has a more significant impact on higher education students’ behavioural intention towards hybrid learning.
To sum up, the PU, PE, IA, and TS significantly affects higher education students’ behavioural intention towards hybrid learning in Malaysian private universities, but SE and CS has insignificant impact. Because PU, PE, IA, and TS contributes more to higher education students’ behavioural intention towards hybrid learning than SE and CS, one’s institute should focus on PU, PE, IA, and TS rather than SE and CS to enhance higher education students’ behavioural intention towards hybrid learning.
Table 5.5
Summary Result of Multiple Linear Regression
Note.Developed for the research.