An Empirical Study on the Factors Influencing Users’ Continuance Intention of Using Online Learning Platforms for Secondary School Students by Big Data Analytics
Table 6
Summary of the internal model analysis.
Hypothesis
Standardized path coefficient
Unstandardized path coefficient
Standard error
-value
-value
Result
Hypothesis1a: SQ ---> PU
0.186
0.194
0.090
2.154
Supported
Hypothesis 1b: SQ ---> PEU
0.645
0.622
0.072
8.583
Supported
Hypothesis 2: RQ ---> PU
0.304
0.289
0.081
3.581
Supported
Hypothesis 3: TP ---> PU
0.325
0.285
0.064
4.443
Supported
Hypothesis 4a: PEU ---> PU
0.136
0.147
0.076
1.932
0.053
Not supported
Hypothesis 4b: PEU ---> SA
0.202
0.197
0.049
4.054
Supported
Hypothesis 5: PU ---> SA
0.347
0.313
0.046
6.735
Supported
Hypothesis 6: SE ---> SA
0.586
0.434
0.041
10.697
Supported
Hypothesis 7: SE ---> CI
0.709
0.701
0.061
11.575
Supported
Hypothesis 8: SA ---> CI
0.109
0.146
0.070
2.073
Supported
Hypothesis 9: AI ---> CI
0.197
0.258
0.059
4.403
Supported
Note 1: RQ = resource quality; SQ = system quality; PU = perceived Usefulness; CI = continuance intention; TP = teaching presence; SA = satisfaction; PEU = perceived ease of use; AI = academic identity; SE = self-efficacy. Note 2: ; (two-tailed); =381.
