Training Industry Magazine - July/August 2019 - 55

WHAT'S NEXT IN TECH
STELLA LEE, PH.D.

LEARNING ANALYTICS IS MORE
THAN DATA COLLECTION

The benefits of learning analytics are
manifold. Learners can get real-time
information on their progress and learning
gaps; instructional designers and facilitators
can be better informed regarding how
learning activities are received by individuals
and groups of learners in order to adjust
learning programs accordingly. Additionally,
managers are able to glean insights on how
learning potentially supports and translates
to on-the-job performance.
The underlying assumption of learning
analytics is that we will use the data
collected to gain insights on the learning
activities and learner behaviors, interpret
the data, and provide interventions and
predictions. Typically, much of the data
comes from the learning management
system (LMS), but also through informal
learning channels, face-to-face session
attendance records and evaluations,
access to other content repositories, and
even mobile phone usage.

LEARNING
PROFESSIONALS
NEED TO START WITH
THE END IN MIND.
However, when it comes to implementing
learning analytics, we are faced with many
data problems. The following factors
outline a few of the problems surrounding
learning analytics and potential solutions:
POOR DATA
The main problem with the use of data
in learning: We need to have them.

Many learning and development (L&D)
departments still rely on paper-based
records, some don't get past the collection
of smile sheets for training evaluations
and some are not in the habit of collecting
any learning data. Often, data are out of
date, stored across different databases and
formats, and are in general quite messy. It
is hard enough just getting the data; we
need to take the first step in collecting
data in a format that is structured, cohesive
and standardized. There are tools and data
science professionals to help you with
data cleansing using statistical software.
DIFFERENT TYPES OF DATA
We need to get past the Shareable Content
Object Reference Model (SCORM) in
terms of the types of data to collect. SCORM
measures learning activity completion, but
completion doesn't prove that learning has
taken place. To identify if the desired learning
outcomes are being achieved, learning
professionals need to start with the end
in mind when designing learning activities
and programs. One solution is to design
formative self-knowledge checks throughout
an online course to spot whether learners
have grasped the concepts or if additional
supports are needed in real time.
I HAVE DATA AND I NEED INSIGHTS
There is a fundamental flaw in approaching
learning analytics this way. We should
be asking: What learning problem and,
ultimately, performance problem am I
trying to solve that data can help provide
insights to? For example, you are trying to
solve the problem of customers' complaints

about the poor service provided by your
call center staff. You might hypothesize
that, by providing a customer service
training simulation experience for the staff,
the number of complaints from customers
will go down by a certain percent. Does the
data reflect that? If not, you must figure out
the root cause of what is not working.
DATA IS NOT KNOWLEDGE
Knowledge involves a practical understanding
of subjects, an acquisition of skills, and
a demonstration of competencies. Data
collected from various learning sources that
haven't undergone thorough processing
are meaningless. While it is important to
collect diverse sets of data, it is from the
analysis of the data that we can infer how
learners learn and the conditions needed
for successful learning. Once you've gained
these insights, the question becomes:
How do you convert insights into actions?
All in all, learning analytics represent a
real opportunity for learning professionals
to provide evidence-based learning
interventions, enhance learning experiences
and foster better performance support.
Understanding and applying data
strategically will go a long way in the
successful implementation of learning
analytics at your workplace.
Dr. Stella Lee has over 20 years of experience in
consulting, planning, designing, implementing,
and measuring learning initiatives. Today,
her focus is on large-scale learning projects
including LMS evaluation and implementation,
learning analytics, and artificial intelligent
applications in learning. Email Stella.

T R A I N I N G I N DUSTR Y MAGAZ INE -LEARNING ANALYTICS 20 19 I WWW. T RAININGINDU S T RY . C OM/ MAGAZ I NE

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https://library.educause.edu/topics/teaching-and-learning/learning-analytics https://www.kirkpatrickpartners.com/Portals/0/Storage/The%20new%20world%20level%201%20reaction%20sheets.pdf https://www.trainingindustry.com/glossary/scorm/ https://www.trainingindustry.com/glossary/learning-management-system-lms/ https://www.trainingindustry.com/glossary/scorm/ https://www.trainingindustry.com/glossary/learning-management-system-lms/ https://www.trainingindustry.com/magazine

Training Industry Magazine - July/August 2019

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