Technology in Training
By Gayle Shaw-Hones
Traditionally, professional expertise was
believed to be the key to expert
performance. To be considered an
expert, people were required to demonstrate
mastery of specific knowledge and skills, and
their performance was measured in terms of
experience and reputation. However, research
has shown that the real key to expert
performance is deliberative practice (DP).
What is DP? In a 2008 article, published in
Academic Emergency Medicine, K. Anders
Ericsson defined DP as training that focused on
improving particular tasks through the use of
problem solving and evaluation, immediate
feedback, and opportunities for repeated
performance. Ericsson believes the same
training methods used to develop expert
performance in areas like music and sports can
be used to develop expert performance in other
This idea is not new to the sales training
industry. For years, professional performance was built on the concept of role play. Reps were
flown in for a one or two-day workshop during
which they received new information and then
practiced delivering that information in a
variety of scenarios. They then flew back to
their territories to practice what they had
learned. But that was a long time ago and the
training world has changed significantly since
then. For example, while the best place for a rep
to be is in the field (as opposed to in a
workshop), practicing on actual customers is
not a great idea.
Then came the technological revolution.
Training could now be delivered in a digital
format that offers reps the ability to learn on the
job and in the field. But as learning
technologies evolved, so did the modern
learner. According to research by Deloitte, the
modern learner is often overwhelmed,
distracted and impatient. In fact, many learners
only have 1 percent of a typical work week to
focus on training and development – including
practice. This new reality is the impetus behind
the current approach of learning in the
moment of need. The key tenets of this
approach require training to be:
• Personalized: Learner-centric, based on
demonstrated learner needs.
• On-demand: Available in the moment of
• Behavior-focused: Drive required behaviors
through real-world practice.
• Fast and simple: Effective, efficient,
• Data-driven: Provide metric-based coaching
about learner performance.
So how best to meet these demands?
Simulation training uses a “synthetic” practice
environment to teach competencies to learners
and improve their performance. Simulation training enables learners to acquire new knowledge and to
practice applying new skills all within realistic contexts. It
can accelerate the development of professional expertise
while providing a complex model of reality that allows
learners to practice the skills they need in a relatively risk-free
We, as learning leaders, are constantly exploring how to
leverage the power of simulation while striving to accelerate
learning, improve outcomes and measure the impact of that
training. Simulation allows learners to learn and practice
skills in a risk-free environment.
Another example is using story-driven learning, which
has been shown to improve understanding and retention. It
places the learner into a real-world story as the main
character. This story unfolds based on the decisions that
learners make. Research shows that by making decisions
and experiencing consequences, both optimal and
suboptimal, learners will improve their ability and
confidence to apply their knowledge in real life situations –
which is the goal of training. A well-designed simulation
should be short in duration, typically 10 minutes or less,
and have data capture capabilities providing actionable
insights to organizations that assess improvement and that
It is also important to consider using a branching logic
model that allows for adaptive, experiential learning. This
not only benefits learners but also provides the ability to
create all types of activities based on different learning
models, for example spaced learning, flipped classroom or
blended learning. Perhaps most importantly, the learning
experience must be engaging and interesting for learners,
which is most easily accomplished with a story-based,
branched logic model.
A learning experience should not stop with completion,
it should entail a design to collect metrics that will help
learning leaders measure business impact and identify gaps
to help enable personalized learning plans. Strategic metrics
enable leaders to quantify the value of training and the
long-term improvements that can be correlated with
effective learning experiences.
Metrics that help leaders better understand not only the
choices made by the learners throughout the simulation,
but also the drivers of those decisions (and behaviors) are
the most effective.
It’s time to bring agility, personalization and
measurement to training design as a best practice. We need
designers and trainers that not only bring content expertise
but also deliver a learning experience that allows for
deliberate practice to improve suboptimal behaviors while
reinforcing optimal behaviors.
Gayle Shaw-Hones, RN, Ph.D., is director of learning and development for Kynectiv. Email Gayle at firstname.lastname@example.org.