Aircraft Maintenance Technology - 39

learners with a personalized experience
that adapts to meet their individual
learning needs and close their specific
knowledge gaps. They also work on a
competency-based framework, only
allowing students to progress to higherorder learning when they've mastered
fundamental concepts. The most
advanced adaptive systems - those
that are powered by AI and machine
learning - can closely mimic oneon-one instruction of the classroom.
Adapting content, feedback, learning
recommendations and motivational
messages in real time - just like an
in-person instructor would do in a
classroom.
*	 Interactive: One of the biggest benefits of adaptive learning is that it offers
learners an environment to practice
what they've learned from reading and/
or watching a lecture/demonstration
with a variety of interactive practice
question types. Practice is one of the
ways that these systems are able to build
both mastery of information and confidence in that knowledge - so learners
are equipped with the skills they need
and can accurately apply them when
it counts (e.g. FAA certification exams
and maintenance careers).
*	 Self-Directed: Another benefit of
adaptive learning systems for aviation
maintenance programs is that it can be
highly self-directed. This means that
learners can spend time focusing on the
content they need to review most and
quickly move past what they already
know - making adaptive learning an
ideal tool for a learner population with a
wide spectrum of knowledge and skills
as is the case in aviation maintenance.
Using AI, these systems can even recommend personalized pathways to
mastery to each student based on their
performance and behavior within the
learning experience.
*	 Measurable: The most advanced of
these systems leverage machine learning to provide deep insights into student
knowledge, depth and degree of mastery,
confidence and predicted performance
in a way that no other remote learning

tool is able to do. This helps instructors
better understand specific areas where
an individual student might be struggling and why, so they can reach out to
offer support, as needed. Additionally,
for institutions and instructors that are
required, for example, to measure hours
spent learning for FAA accreditation,
adaptive learning can be very helpful. These systems can track learning
times, along with mastery down to
the learning objective-level, so schools
have a wealth of data to pass along to
accreditors.
As students and schools grow more comfortable with the "new normal" brought
about by COVID-19, there will be a call
for more engaging online learning tools
that can address the challenges of remote
learning and that are proven to help aviation maintenance students build, master
and apply their critical skills. In this new
world, schools and institutions working to

deliver high quality training that keeps their
aviation maintenance students on track so
that they're prepared to capitalize on the
opportunities of the market in the near, mid
and long term, adaptive learning can be a
powerful tool.
In 2014, Patrick Weir saw
an opportunity to combine
artificial intelligence,
cognitive science and data
analytics into an adaptive
learning platform as a
solution for a rapidly changing education
and training market. He founded Fulcrum
Labs and began pushing the company to
develop a world-class, Adaptive Learning
3.0 platform with a customer-centric
mindset. Under Weir's guidance, Fulcrum
has helped partners from both enterprise
and higher education achieve, and often
exceed, their most critical goals and
earned numerous industry awards.

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39
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Aircraft Maintenance Technology

Table of Contents for the Digital Edition of Aircraft Maintenance Technology
