This document discusses the future of training and learning moving towards more modular, data-driven and adaptive models. Key points include:
- Consumer media is increasingly seamless, data-driven, gamified, social, micro-integrated and personalized in a cloud-based format. Learning models should follow this trend.
- Modular content paired with robust assessments can drive personalized learning paths optimized by data on factors like accuracy, confidence, time and cohorts.
- An adaptive learning approach informed by learning science theories can lead to better learner outcomes like higher mastery levels across more learners compared to conventional learning models.
- Data and analytics provide benefits for all stakeholders in learning including improved efficiency, engagement and organizational
3. But consumer media looks like this now…
Copy Text Copy Text
SEAMLESS
DATA-DRIVEN
GAMIFIED
SOCIAL
MICRO
INTEGRATED
HUMAN-CENTRIC
PERSONALIZED
JUST-IN-TIME
CLOUD-BASED
8. What is the big difference between learning and
entertainment?
Entertainment
Learning
Like Dislike Star
Rating
Time Tagging
Factors
Demographic
Factors
16. Data used to optimize each learner’s experience
Entertainment
Learning
Like Dislike Star
Rating
Time Tagging
Factors
Demographic
Factors
Accuracy Confidence Time Cohort
Trends
21. Beyond the individual: unlock organizational
performance
21
Measurement Mastery Efficiency Engagement Agility
When insight into
learning is needed
When compliance and true
proficiency are required
When real participation is
necessary
When learners are diverse in
incoming skill and require
individual paths
When learning needs to translate
into action or behavior change
22. Traditional and Computer-Assisted Training
Instructor and Computer-based (CBT)
LMS becomes the Administrative Platform
The E-Learning Era
Materials On-Line, Information vs. Instruction
Blended and Informal Learning
Mixing forms of media with informal learning
Learning on demand with Integrated Programs
Collaborative, Talent-Driven Learning
Formalize Informal Learning
Collaboration and talent management by Design
2009 +
2005 +
2000 +
1990’s
The Evolution of Corporate Learning
Source: BERSIN
23. The Evolution of Corporate Learning
Traditional and Computer-Assisted Training
Instructor and Computer-based (CBT)
LMS becomes the Administrative Platform
The E-Learning Era
Materials On-Line, Information vs. Instruction
Blended and Informal Learning
Mixing forms of media with informal learning
Learning on demand with Integrated Programs
Collaborative, Talent-Driven Learning
Formalize Informal Learning
Collaboration and talent management by Design
Mastery-Based Adaptive Learning
Personalized, Competency-Based
Data-Driven, Digital, Seated in Science
2016 +
2009 +
2005 +
2000 +
1990’s
24. Powerful data layer with advanced analytics
Agile
Authoring
Tailored
Instruction
Data Layer
Your
Content
Our
Platform
Personalized
Learning
25. Benefits for every stakeholder
• Eliminates course
versioning
• Real-time feedback
for agile authoring
LEARNER
• Measureable
reportable outcomes -
advanced analytics
• Improved efficiency
and retention
• Direct savings in
cost to train
• A personalized
experience
• Self-paced and
easy-to-use
• 100% mastery
AUTHOR MANAGER/TRAINER
27. ROI: Possible metrics to evaluate learning
ROI METRIC
Measurement
Mastery
Efficiency
Engagement
Agility
DESCRIPTION EXAMPLE
Data layer allows stakeholders to
identify trends (learning, content,
and cohort analytics down to the
objective)
100% mastery of all learning
objectives (increase in proficiency
rates, organizational readiness)
Reduces training time (opex
savings, increased productivity in
redistributed full-time hours)
Right content at right time makes
learning inspire (increased
retention, improved quantitative
and qualitative survey data)
Real-time analytics means real-time
action for all stakeholders (leads to
increased revenue, margin, market
penetration)
75% of learners who exceed their
sales quota are aware of their
accuracy 80% of the time, in
addition to achieving 100% mastery.
1000 learners are certified
(achieved 100% mastery of
50 Learning Objectives, up
from 75% mastery).
45% increase in efficiency due to
transition from one-size-fits all to
personalized learning.
90% of learners would
recommend the course to others.
100% of learners completed the
course, up from 50%.
Learner data has been used to
make course revisions and
decreased the versioning time
required by 30%.
27
28. Learners
Case Study | Data improves learning efficiency
Original
Program
70 Min
Adaptive
Program
Average
37 Min
IT Services Industry
Fixed 70 Min Webinar w/test
Conversion to Adaptive Platform
All Gained 100% Mastery
Time / Opex Savings of 48%
28
29. MHE adaptive leverages investment in science
and technology
29
$175M+ Investment per
Year in Digital Platforms
2012
DPG
Formed
2017
Growth via
Investment
450
Engineers,
etc
200
Engineer
s, etc
$
1,600+
Adaptive products
4,000
Authors trained to use MHE Adaptive
5,000,000
Learners using MHE Adaptive
10,000,000,000
Data Layer Interactions
MHE Adaptive
Growth via
Acquisition
Growth via User Knowledge
30. We exist to unlock the full potential of every learner
30