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Table-7: Multicollinearity check

Intention
Factors
Tolerance VIF
Attitude .407 2.458
Motivation .514 1.945

Perception .465 2.150
Personality .452 2.213
Source: Primary Data
Table-7 is a summary regarding the of results (Wong, 2019). The significance
result of VIF calculations. All the values of relationships was tested at 1%
are below “5”, therefore there is no significance level such that t-statistics
question of multicollinearity. value should be above 2.57. The
t-statistics value of each path is above
2.57 except for path “Personality →
Structural Model Assessment Intention”, which means that personality
The structural model assessment does not affect the student’s intention
includes t-statistics calculation for to study through distance education
finding significance of relationships, mode. Therefore, hypotheses H01, H02,
effect size and predictive relevance H03 are accepted and hypothesis H04
of the model (Wong, 2019). Table-8 is rejected. It can be concluded that
shows the outcome of bootstrapping perception, attitude and motivation of
run, where t-statistics value is being students, determines their intention to
analyzed to conclude about significance enroll in distance learning courses.
Table-6: Path coefficient values of all the paths in Model

Original Sample Standard Standard
T Statistics
Path Sample Mean Deviation Error (|O/STERR|)
(O) (M) (STDEV) (STERR)
Attitude → Intention 0.168 0.170 0.047 0.047 3.609

Motivation → Intention 0.386 0.387 0.044 0.044 8.825

Perception → Intention 0.332 0.334 0.052 0.052 6.439

Personality → Intention 0.032 0.029 0.054 0.054 0.600
Source: Primary Data

Effect Size (F ) R2 included- R2 excluded
2
F2 =
The effect size of any construct may be 1- R2 included
calculated by Cohen’s formula (Wong,
2019) which reveals which variable Table-9 is a summary of effect size of
has larger impact on the dependent each construct, where “motivation” has
variable. the largest effect size and “personality”

Indian Journal of Educational Technology 35
Volume 3, Issue 2, July 2021