The Impact of Multilevel Computer Self-Efficacy on Effectiveness of Computer Training - End User Computing Challenges and Technologies: Emerging Tools and Applications - page 38

CSE (Agarwal et al., 2000; Hsu & Chiu, 2004),
we suggest that application CSE will also have an
inverse impact on computer anxiety. As such, the
following two hypotheses are presented.

individuals with higher CSE beliefs are expected
to expend more effort to understand and learn
the new skills and, as a result, will demonstrate
higher levels of learning performance than those
with lower CSE.
Martocchio and Hertenstein (2003) investi-
gated the impact of application CSE on declarative
knowledge (similar to near-transfer knowledge).
They found that Access 97 CSE had a significant
effect on declarative knowledge (i.e., specific
knowledge about basic features of Access 97).
Thus, based on the theoretical and empirical
studies described above, general and application
CSE beliefs are likely to have positive effects on
near-transfer and far-transfer learning of com-
puter skills.

H2a: General computer self-efficacy will have a
negative effect on computer anxiety.
H2b: Application computer self-efficacy will have
a negative effect on computer anxiety.

near-transfer and Far-transfer
learning

Learning transfer refers to the extent to which
new learning can be applied to other situations
(Haskell, 2001). Near-transfer learning refers
to learning which cannot be applied to novel
situations that are different from the training
environment. In contrast, far-transfer learning
refers to learning that can be applied to situations
that are different from the training situation. The
theoretical basis of near- and far-transfer learning
is grounded in rote and meaningful learning of
the assimilation theory of learning (ATL) (Aus-
ubel, 1968). ATL posits that rote learning occurs
when the learner memorizes the new information
without connecting it to existing knowledge al-
lowing the memorized knowledge to be recalled
in situations that are similar to the learning envi-
ronment. Conversely, meaningful learning occurs
when new knowledge is completely understood
and linked to existing knowledge structure.
Thus, meaningful learning can be manipulated,
extended, and applied to tasks and situations that
are different from the training setting in which
these skills were initially learned.
The type of learning (near- or far-transfer)
that one accomplishes depends, in part, on the
amount of effort he/she is willing to expend to
understand and integrate the new information
into existing knowledge (Novak, 2002). Since
self-efficacy represents a key determinant of
the amount of effort and persistence that people
exert to perform successfully (Bandura, 1986),

H3a: General computer self-efficacy will have a
positive effect on near-transfer learning.
H3b: Application computer self-efficacy will
have a positive effect on near-transfer
learning.
H4a: General computer self-efficacy will have a
positive effect on far-transfer learning.
H4b: Application computer self-efficacy will have
a positive effect on far-transfer learning.

method

procedure

Seventy-eight undergraduate juniors and seniors
(28 females, 50 males) enrolled in two elective
computer information systems courses at a
Midwestern university participated in this study.
All subjects indicated that IS was their major or
minor. Subjects were given extra credit for their
participation in the study. The mean age of subjects
was 23.06 years (SD = 2.77).
Davis (1993) recommends using less familiar
applications to allow users to form their beliefs
based on their interaction with the technology
rather than on their past experience with it. Thus,