More than 30 years of research into artificial intelligence looked at pre-determined, logic-based approaches to static maps of domain knowledge. In the last five years, much research and development has been done to make data-driven recommendations and personalized content a reality in the near-term. The technology, math, and science that makes this possible is astounding, but how well it works is completely dependent on the design of the content, the quality of the data, and ultimately the accuracy of a learner's experience with the content, compared to what the content is designed for.
While all the technologies aren't ready for enterprise learning yet, some technologies are here now. The design practices needed to make use of adaptive learning represent the best practices organizations should be applying in their information and content management practices, including using the Experience API to collect analytics on how content is used in context, compared to the design goals of that content; and continuously improving content experiences to bridge the gaps.
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
The Big Picture of Adaptive Learning
1. The Big Picture of
Adaptive Learning
Aaron E. Silvers & Megan Bowe,
ATD TechKnowledge 2015
Las Vegas, NVUSE THE TWITTERS!!!!!
@aaronesilvers @meganbowe
#atdTK
2. “ - Bruce Lee
“Be like water making its way
through cracks. Do not be
assertive, but adjust to the
object, and you shall find a way
round or through it. If nothing
within you stays rigid, outward
things will disclose
themselves.”
#AdaptivityZen
3. Adaptive
Learning
What is
Adaptive Learning assessessomeone’s currentknowledge state andrecommends a sequence ofactivity that changes thatknowledge state toward adefined learning outcome.
7. Online, Self-Paced Learning
• Pre-testing preselects content
based on a pre-tests or learner’s
history to “test out” of content.
This porridge is too hot (arbitrary).
• Linear eLearning delivers the same
content to every user.
This porridge is too cold (not all that
adaptive).
• Micro-adaptive adjusts the
sequence of content based on a
learner’s reactions in real-time.
This porridge is just right.
Photo by SlyOwl - http://flic.kr/p/j9fFYy
8. Next, Goldilocks has to
choose among the Micro-
Adaptive systems…
Photo by SlyOwl - http://flic.kr/p/j9fFYy
9. Micro-Adaptive Systems
• Preference-based systems adapt to
the style or medium preferred by
each learner
This chair is too big (it’s imaginary).
• Rule-based systems are pre-
programmed with closed loops of
“if… then…” logic.
This chair is too small (“rules”).
• Algorithmically sequenced systems
calculate the sequence of content
dynamically.
This chair is just right.
Photo by Viracocha - http://bit.ly/1A6fcdM
10. Next, Goldilocks has to
choose among different
types of Micro-adaptive,
algorithmically
sequenced systems…
Photo by SlyOwl - http://flic.kr/p/j9fFYy
11. Algorithmically-Sequenced Systems
• Test-driven systems are based on
automated test sequencing.
This bed is too hard (so testy).
• Memorization systems prioritizes
repetitions based on data about the
individual, the learning activity and the
interaction between the two.
This bed is too soft (narrow
applications).
• Proficiency-driven systems look broadly
at what someone is trying to learn,
pulling from a wide range of content.
This chair is just right.
Photo by BlueStarMedia - http://bit.ly/1y0IEVZ
12. Adaptive
Learning
There’s a lot of promise for
adaptive learning in the
enterprise, but the way
forward has some bumps.
Challenges
13. You probably don’t haveenough content.
Photo by Tim Ebbs - http://flic.kr/p/aiBFtv
14. Photo by woodleywonderworks - http://flic.kr/p/4Lx3mh
Defining competencies
while the nature of work
changes is hard.
15. Photo by Brian Corredor - http://flic.kr/p/dLW2aT
The LMS
is a fortress for content.
17. You can develop
practices to get your
organization ready for
Adaptive Learning.
Photo by Jared Chan - http://flic.kr/p/pC2vbz
18. IA
Nav
LLR&A Au T Re
Inv Feed Look G
Sta Weed Find M
Use Need D
Granularity
Modularity
Content
Strategy
@mkngbttr
Discreteness
19. Granularity (size)How small can thecontent be and stillbe useful?
How to
prepare a
cocktail?
How to
mix the
ingredients
20. Modularity (context)
How much confusion
can be stripped
away so the content
stands on its own?
Can you
learn to
make this
flame
without
learning
about the
cocktail?
Are we learning
about bartending?
Are we learning
about flaming drinks?
22. IA
Nav
LLR&A Au T Re
Inv Feed Look G
Sta Weed Find M
Use Need D
Want to learn more about
Content Strategy?
Click here:
http://makingbetter.us/2014/11/
getting-started-with-content-
strategy/
23. Photo by Legit Alex - http://flic.kr/p/8JTccx
Content strategy supported by granularity,
modularity & discreteness makes sense of content
today and for the future, inside or out of the LMS.
24. Photo by Tobias Larner - http://flic.kr/p/eauixu
“Be water, my friend.”