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tions were below the cutoff value of 0.8 suggested
by Bryman and Cramer (1994) to suspect the
presence of multicollinearity.
Regression analysis was used to test the
research hypotheses. Accordingly, a separate
regression test was performed for each dependent
variable and the results of regression analyses are
presented in Table 2. The regression results show
that general CSE has significant effects on: (1)
perceived ease of use (
β
= 0.421,
p = 0.003
); (2)
computer anxiety (
β
= - 0.360
, p = 0.004
); and
(3) far-transfer learning (
β
= 0.259
, p = 0.033
).
Thus, hypotheses 1a, 2a, and 4a were supported
by the data. However, general CSE demonstrated
a nonsignificant negative effect on near-transfer
learning (
β
= - 0.229
, p = 0.076
). Therefore, hy-
pothesis 3a was not supported.
With respect to application CSE, the results in
Table 2 show that application CSE has significant
effects on: (1) computer anxiety (
β
= - 0.317
, p =
0.012
); (2) near-transfer learning (
β
= 0.683,
p =
0.000
); and (3) far-transfer learning (
β
= 0.447,
p
= 0.000
). Thus, hypotheses 2b, 3b, and 4b were
supported by the data. Contrary to expectations,
the effect of application CSE on perceived ease
of use was small and nonsignificant (
β
= 0.127,
p = 0.345
). As such, hypothesis 1b was not sup-
ported. Moreover, Table 2 shows that general and
application CSE explained about 25% of the vari-
ance in perceived ease of use; 37% for computer
anxiety; 32% for near-transfer learning; and 41%
for far-transfer learning.
disCussion
The purpose of this study was to examine the
impact of CSE on computer training effectiveness.
A research model positing relationships among
general and application CSE on perceived ease of
use, computer anxiety, near-transfer learning, and
far-transfer learning was developed and tested.
Experimental results provided adequate support
for the research model and supported six of the
eight hypothesized relationships. As expected,
general CSE demonstrated a significant positive
effect on perceived ease of use. Accordingly,
perceptions of ease of use of a given system are
expected to be higher for individuals with higher
CSE judgments than those with lower CSE. This
finding is consistent with previous studies (e.g.,
Hong, Thong, Wong, & Tam, 2002; Hu et al., 2003;
Igbaria & Iivari, 1995; Venkatesh & Davis, 1996)
and further corroborates the relationship between
general CSE and perceived ease of use.
In contrast to recent findings which showed
a significant relationship between application
CSE and perceived ease of use (Agarwal et al.,
2000;
Yi & Hwang, 2003), application CSE failed
Table 2. Results of regression testing
Training Outcome R2 Level of CSE β t Sig. Hypothesis Result
Perceived ease of use 0.256 General 0.421 3.123 0.003 1a S
Software-specific 0.127 0.950 0.345 1b NS
Computer Anxiety 0.374 General -0.360 -2.942 0.004 2a S
Software-specific -0.317 -2.588 0.012 2b S
Near-transfer learning 0.322 General -0.229 -1.801 0.076 3a NS
Software-specific 0.683 5.356 0.000 3b S
Far-transfer learning 0.412 General 0.259 2.182 0.033 4a S
Software-specific 0.447 3.769 0.000 4b S
S: Supported, NS: Not Supported
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