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training design principles 253
that is often encountered with a hard-to-easy or variable sequencing (Gick & Holyoak,
1987). It also allows trainees to experience success early in training, thereby enhancing
perceptions of self-efficacy that are critical to positive training outcomes (Ford, Smith,
Weissbein, Gully, & Salas, 1998). However, at some point more challenging problems
needtobephasedintothetrainingprogram,asvariabilityanddifficultyarekeyconditions
for transfer (Schmidt & Bjork, 1992). Studies of problem solving have shown that, in
some cases, transfer problems are solved more easily when individuals practice on a
harder problem in training (Reed, Ernst, & Banerji, 1974; Klaczynski & Laipple, 1993).
In the same way in which athletes benefit from training under more difficult conditions
than those under which they will eventually compete, employees too may benefit from
training to a standard that is somewhat more demanding than that usually required in the
workplace. Typically this requires effort on the part of the trainee, and hence motivation
has to be high.
There are obvious limits to the benefits of increasing the difficulty of training. If
training is too difficult, the capacity of employees will be exceeded and motivation to
engage in further training will be reduced. An optimum sequencing of the course content
appears to involve the initial mastery of several relatively easy problems, followed by
increasingly harder problems that eventually meet or exceed the level of difficulty that
will be encountered in the workplace. Computer-based training involving self-paced
interactive exercises may be useful in ensuring that the level of difficulty of the training
problem is appropriate for the current competence of individual trainees. Given that
individual differences in rates of learning and learning capacity are usually quite large,
it is not easy to ensure that the difficulty level is appropriate for all participants when
training is undertaken in groups.
ENCOURAGE APPROPRIATE INFORMATION-PROCESSING
Current research on learning and memory demonstrates the importance of ensuring
that trainees practice appropriate information-processing strategies during training. This
idea is apparent in the work of Downs and Perry (1984) who suggested that different
learning strategies (memorizing, understanding, doing) may be required depending on
the type of material to be mastered (facts, concepts, or procedural tasks). A more specific
hypothesisisthattransferwillbeachievedtothedegreethatprocessesinvolvedintraining
and transfer overlap (Morris, Bransford, & Franks, 1977). Effective training, therefore,
should create the same information-processing demands as the transfer environment,
i.e., the transfer appropriate processing principle. Support for this hypothesis has been
obtained by Needham and Begg (1991). They found that training based on rote memory
facilitated the recall of factual information, whereas training based on problem solving
facilitated solving an analogous problem. Similarly, Lockhart, Lamon, and Gick (1988)
found that a clue word was used to solve a problem when the clue word was presented
initially in puzzle form, but not when the clue word was memorized. More recently,
using a driving simulator for the research, Ivancic and Hesketh (2000) found that drivers
avoided accidents when training also required them to learn to actively develop strategies
for preventing similar errors, but not when training involved watching a video of a driver
demonstrating the correct strategies.
The similarity of training and transfer information-processing strategies appears to
be critical because these processes establish the context in which training occurs. How
the information is presented in training (as a fact to be learned or as a problem to