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Outer
Observed variables α CR AVE
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PEOU1: I find digital technology easy to use in
teaching. 0.894
PEOU2: I do not encounter difficulties when using
digital technology for teaching. 0.785 0.799 0.882 0.714
PEOU3: I feel confident when using digital
technology in teaching. 0.853
Perceived Usefulness (PU)
PU1: Digital technology helps me teach more 0.836
effectively.
PU2: Using digital technology helps improve my 0.911
teaching quality. 0.870 0.912 0.721
PU3: Digital technology helps me deliver lesson 0.841
content more clearly.
PU4: Digital technology helps me save time in lesson 0.805
preparation.
Institutional Support (Support)
Support1: My institution provides adequate facilities 0.919
for digital technology use. 0.801 0.910 0.834
Support2: My institution organizes training courses 0.907
on the use of digital technology in teaching.
Perceived Accounting Teaching Quality (TQ)
TQ1: Digital technology helps me deliver lesson 0.718
content more effectively.
TQ2: I can interact better with students thanks to 0.695
digital technology.
TQ3: Students highly appreciate my teaching 0.718 0.776 0.848 0.527
methods that integrate digital technology.
TQ4: Digital technology helps me improve student 0.724
assessment and evaluation.
TQ5: I am satisfied with my teaching quality when 0.774
using digital technology.
Source: Data processing results from SmartPLS software
3.3. Structural model and hypothesis testing
The structural model did not indicate any serious multicollinearity issues, as all
variance inflation factor (VIF) values were below 3. As shown in Figure 1 below, the
coefficient of determination for the dependent variable, perceived accounting teaching
quality (TQ), was R² = 0.556, with an adjusted R² of 0.539. This indicates that the
independent variables in the model explain 55.6% of the variance in teaching quality. In
addition, the values of Q² = 0.245 and Q²_predict = 0.489 were both greater than zero,
suggesting that the model has acceptable predictive relevance. These results confirm that
the proposed model demonstrates satisfactory explanatory power and predictive capability
within the research context.
The bootstrapping analysis with 5,000 resamples indicated that all six hypotheses were
supported at a significance level of p < 0.05. Among the predictors, technology experience
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