Organizations are always
seeking more effective methods to train staff. Although certainly
a cost, the right training is also an asset. Staff who have a
clear understanding of the expectations an organization places
on their performance and who have honed their job related skills,
are more likely to help an organization achieve desired outcomes.
In a study involving a Fortune 500 manufacturing
firm, Kenneth Brown investigated individual differences and learner
choices on learner controlled computer based training. While
computer based training is more cost and time effective than
traditional instructor led training, its very strength may also
be a major weakness. Computer based training gives employees
more control over learning features such as the amount of practice
and time on task. In other words, the student can decide the
level of his or her involvement in the training activity.
One major finding in this study, not surprisingly,
was that knowledge gained was a function of two important variables:
- Time completing practice opportunities;
and,
- The time on task.
The problem is that despite the appeal
of computer based training, employees may not make wise learning
choices, i.e., they may not complete activities and practice
exercises that will give them command of the material. The challenge
is for managers and trainers to find ways for employees to persist
in participating in the training activities and staying on task.
As companies move more fully from instructor based learning to
computer based learning, it will only truly be cost and time
effective to the extent that organizations deal with individual
differences and learner choices. With respect to this issue,
Brown suggests that prior research has shown that follow-up meetings
to increase accountability for learning may be useful.
Another key question of this study was
to identify which employees learn from computer based training
that allows a high degree of student control (i.e., individual
differences that would predict who might gain from computer based
learning). With respect to this issue, the results were not clear.
This is an area that future research will certainly continue
to address.