Information Technology Reference
In-Depth Information
individuals perform their work tasks, requiring
employees to learn new computing skills and
learn how to apply their new knowledge to their
jobs (Tai, 2006). As a result, most organizations
are faced with an incessant challenge to provide
effective computer training to enable employees
to learn the necessary skills and knowledge
needed for effective use of computer systems.
Thus, computer training remains a critical issue
in information systems (IS) research and practice
that deserves further examination and better
understanding.
Much research attention has been given to
computer training over the past few years (e.g.,
Davis & Bostrom, 1993; Harrison & Rainer, 1992;
Johnson & Marakas, 2000; Lu, Yu, & Liu, 2003;
Simon & Werner, 1996; Yi & Davis, 2001, 2001;
Tai, 2006). Most of this research activity has
focused on identifying factors that contribute to
(or hamper) trainees' ability to learn and master
the skills presented in training (e.g., Agarwal,
Sambamurthy, & Stair, 2000; Bostrom, Olfman,
& Sein, 1990; Simon et al., 1996; Yi & Davis,
2003). This line of research has shown that
computer self-efficacy (CSE), one's confidence
in his/her computing skills, represents a signifi-
cant determinant of learning performance and
other outcomes associated with computer train-
ing (Agarwal et al., 2000; Compeau & Higgins,
1995; Gist, Schwoerer, & Rosen, 1989; Johnson
& Marakas, 2000; Yi & Davis, 2003).
However, a review of past studies concern-
ing CSE and computer training reveals two
significant voids. First, most prior studies have
evaluated computer learning performance in
general terms, without distinguishing between
near-transfer and far-transfer learning (Haskell,
2001). Since the type of learning that a trainee ac-
complishes in training affects the extent to which
he/she can apply and extend the newly learned
skills (Cormier & Hagman, 1987) and transfer
of learning knowledge represents a key objec-
tive of training (Holladay & Quiñones, 2003), it
is important to understand factors that influence
each type of learning in order to enhance train-
ing transfer. Moreover, in addition to learning,
effective training should lead to improvements in
trainees' reactions (Kirkpatrick, 1959). Hence, it
is important to assess reactions as an outcome in
computer training (Tai, 2006).
Second, although CSE is a multilevel construct
that operates at a general and application level
(Agarwal et al., 2000; Johnson & Marakas, 2000;
Marakas, Yi, & Johnson, 1998; Yi & Davis, 2003),
most previous studies have focused on CSE as a
general and system-independent construct. To
date, very little research has examined the gen-
erality of CSE beliefs or the impact of application
CSE on computer training outcomes.
Although general and application CSE repre-
sent similar concepts, there are genuine differ-
ences between the two constructs. While CSE
at the general level is considered a trait-oriented
efficacy (applicable to a variety computing tasks
and achievements), CSE at the application level
is considered a state-oriented efficacy (applicable
to specific tasks and situations within the same
computing domain) (Hsu & Chiu, 2004). Fur-
thermore, the evaluation of CSE at the general
and application level is more closely aligned with
the generality dimension of self-efficacy which
suggests that self-efficacy operates at general and
task-specific levels (Bandura, 1986; Gist, 1987).
Finally, this distinction allows the assessments of
application CSE to exclude evaluations of cross-
domain and distant skills necessary to perform
a given computing task. For instance, using a
spreadsheet application to prepare a financial
forecast requires knowledge of forecasting and
financial concepts and (Marakas et al., 1998).
The current study attempts to fill the afore-
mentioned limitations. Thus, it attempts to pro-
vide better insights into the relationships among
CSE beliefs (general and application-specific)
and key computer training outcomes. Thus, the
study proposes and empirically tests a research
model that comprises the following variables:
general CSE, application CSE, perceived ease
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