Powering Personalized Learning and Adaptive Teaching Matthew Kaylie Sr. Director, Strategy and Business Development [email protected] 646.942.0212
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Powering Personalized Learningand Adaptive Teaching
Matthew Kaylie
Sr. Director, Strategy and Business Development
646.942.0212
Check All The Boxes
2
• Learning science
• Learning drives the bus
-Dr. Andrew McCollough
3
Student Experience
Student Engagement & Agency
Faculty Line of Sight
5
Faculty Real-time & Actionable Insights
For Illustration Purposes
Target Knowledge
Finance 201
College Algebra
Finance 101
Here’s What Sets Realizeit Apart
FACULTY TESTED; STUDENT APPROVED
MASTERY
VERSATILITY
SCALE
COMMUNITY OF PRACTICE
8
If this is important to you….
CONTROL – CONTENT, DATA
(REALLY) MEASURE LEARNING
IMPLEMENTATION SUPPORT & COLLABORATION
IMPACT STUDENT OUTCOMES AT ALL LEVELS
9
Let’s talk….
Thanks to UCF
10
http://realizeitlearning.com/customers/
80.00%
85.00%
90.00%
95.00%
100.00%
105.00%
Knowledge state Knowledge covered
0
1
2
3
4
5
6
7
8
9
Mo
d 1
4 S
um
ma
ry
Mo
d 1
4 In
tro
du
cti
on
an
d V
ide
o L
ectu
re
Ra
nd
om
Ea
rly
De
tecti
on
an
d T
raff
ic S
ha
pin
g,
etc
.
Mo
d 1
2 S
um
ma
ry
Mo
d 1
0 S
um
ma
ry
Re
du
cin
g S
eri
aliza
tio
n D
ela
y a
nd
Qo
S
Mo
d 1
1 S
um
ma
ry
Mo
d 9
Su
mm
ary
To
ols
fo
r Te
sti
ng a
Ne
two
rk D
esig
n
Mo
d 3
In
tro
du
cti
on
an
d V
ide
o L
ectu
re
Mo
d 1
Su
mm
ary
Gu
ide
lin
es f
or
Assig
nin
g N
am
es
Pa
cke
t S
ize
s
Re
qu
ire
me
nts
an
d T
rad
eo
ffs
Ne
two
rk S
ecu
rity
De
sig
n
Qo
S R
eq
uir
em
en
ts
Mo
d 2
In
tro
du
cti
on
an
d V
ide
o L
ectu
re
Ca
mp
us T
op
olo
gy
De
sig
n
Te
ch
nic
al G
oa
ls
Ne
two
rk T
op
olo
gy
De
sig
n T
he
me
s
WLA
Ns a
nd
VLA
Ns
Se
lecti
ng E
nte
rpri
se
Te
ch
no
logie
s
Bri
dge
s (
Sw
itch
es)
Ru
nn
ing S
TP
De
lay
Re
mo
te A
cce
ss T
ech
no
logie
s
Se
cu
rin
g t
he
Ne
two
rk
Imp
lem
en
tati
on
Pla
n a
nd
Ap
pe
nd
ice
s
WA
N T
ech
no
logie
s
Ne
two
rk P
erf
orm
an
ce
To
po
logy
De
fin
ed
En
d o
f M
od
ule
Qu
iz
IPv6
Ad
dre
sse
s
Mo
d 4
In
tro
du
cti
on
an
d V
ide
o L
ectu
re
Co
mp
on
en
ts o
f a
Te
st
Pla
n
Wir
ing a
nd
Me
dia
Tra
ffic
Flo
w
Ma
na
ge
ab
ilit
y, U
sa
bilit
y, a
nd
Ad
ap
tab
ilit
y
Mo
d 1
3 In
tro
du
cti
on
an
d V
ide
o L
ectu
re
Mo
d 1
In
tro
du
cti
on
an
d V
ide
o L
ectu
re
Su
bn
ets
Ro
uti
ng P
roto
co
ls
Are
as o
f S
ecu
rity
Mo
d 1
1 In
tro
du
cti
on
an
d V
ide
o L
ectu
re
IP A
dd
resse
s
Mo
d 7
In
tro
du
cti
on
an
d V
ide
o L
ectu
re
Mo
d 4
Su
mm
ary
Mo
d 1
2 In
tro
du
cti
on
an
d V
ide
o L
ectu
re
Average time (mins)
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
En
d o
f M
od
ule
Qu
iz
Ava
ila
bilit
y
IP A
dd
resse
s
Ava
ila
bilit
y
Ma
kin
g R
ou
tin
g D
ecis
ion
s
WA
N T
ech
no
logie
s
Re
mo
te A
cce
ss T
ech
no
logie
s
Ne
two
rk P
erf
orm
an
ce
Tra
ffic
Ch
ara
cte
risti
cs
Wir
ele
ss N
etw
ork
Se
cu
rity
Do
ma
in N
am
e S
yste
m (
DN
S)
Ro
uti
ng P
roto
co
ls
Bu
sin
ess C
on
str
ain
ts
Wir
ing a
nd
Me
dia
IPv6
Ad
dre
sse
s
Ne
two
rk M
an
age
me
nt
Co
mp
on
en
ts
Ca
mp
us T
op
olo
gy
De
sig
n
LA
N T
ech
no
logie
s
WLA
Ns a
nd
VLA
Ns
Ne
two
rk D
esig
n
IP T
ype
of
Se
rvic
e F
ield
an
d L
AN
Tra
ffic
Ad
dre
ssin
g a
nd
Na
min
g
Co
mp
on
en
ts o
f a
Te
st
Pla
n
Are
as o
f S
ecu
rity
Bri
dge
s (
Sw
itch
es)
Ru
nn
ing S
TP
Ne
two
rk T
op
olo
gy
De
sig
n T
he
me
s
Str
uctu
red
De
sig
n
Bu
sin
ess G
oa
ls
Su
bn
ets
Ca
mp
us N
etw
ork
Me
dia
Tra
ffic
Flo
w
Ca
mp
us N
etw
ork
De
sig
n
Gu
ide
lin
es f
or
Ad
dre
ssin
g a
nd
Na
min
g
To
po
logy
De
fin
ed
Re
aso
ns t
o T
est
Ma
na
ge
ab
ilit
y, U
sa
bilit
y, a
nd
Ad
ap
tab
ilit
y
Imp
lem
en
tati
on
Pla
n a
nd
Ap
pe
nd
ice
s
Cis
co
Sw
itch
ing T
ech
niq
ue
s a
nd
Qu
eu
ing S
erv
ice
s
Re
aso
ns t
o O
pti
miz
e a
nd
IG
MP
Se
lecti
ng E
nte
rpri
se
Te
ch
no
logie
s
Te
ch
nic
al G
oa
ls
Sw
itch
ing a
nd
Ro
uti
ng C
ho
ice
s
Use
r C
om
mu
nit
ies a
nd
Da
ta S
tore
s
Ne
two
rk M
an
age
me
nt
Se
cu
rin
g t
he
Ne
two
rk
De
lay
Co
nte
nts
of
a N
etw
ork
De
sig
n D
ocu
me
nt
Average score
Wrap-Up
14
Questions
FEEDBACK – NEXT STEPS
Starts with the Student Engagement
15
• Provide a personalized learning experience• Deliver learning at an appropriate time
• Deliver appropriate learning material
• Learn about the learner
• Manage and adapt to change: abilities, metrics, behavior etc.
• Identify weaknesses and try to remedy
• Help a learner to realize their potential
• Remain subject and content independent
Personalized Learning – Empowered Students
• Continually Informed – Strength, Weakness, Progress and Mastery
• Individualized pathways and pace – Chart and follow personal journey to completion and achievement
• Confidence building – Experience incremental success, improve engagement
• Engaged collaborators – Learner agency
16
What students are saying…
17
The platform is very engaging, it keeps your attention span because the sections within each week are only 20 min long and the follow up questions are excellent!!!! I usually get B's and C's in my classes because it is very hard to learn and with Realizeit I can finally get an A in my class!!! Realizeit is very important in keeping you on track and keeping you motivated when you take online classes!
- UMUC Student
I loved how it took the time to figure out what I knew before it gave me a bunch of work to do. It made me feel like my time was valuable. It taught the material really well and helped reinforce things I wasn’t so great at.
- UCF Student
Student View Screenshot
Real-time and Actionable Data
19
Can’t Happen Without You- Empowered Teachers
• Faculty focused practice – Technology and data enabled
• Real-time view into every student’s strengths, weaknesses, progress and mastery
• Informed guide – Data driven interactions and interventions
• Efficiency and Value – Less time grading, more time connecting with students, more time for practice through applied learning
20
What faculty are saying…
21
I have been very impressed with both the potential for Realizeit to drastically change how I can deliver my course to my students and with the professionalism of the Realizeit team members… This is the first time I have felt that I now have the tools to deliver a truly adaptive learning and testing experience…
- Dr. Julie F. Hinkle RN, PhDFaculty and Coordinator, College of Nursing
University of Central Florida
The faculty are now more engaged and actually teaching and managing, monitoring, and mentoring the student’s educational path through their learning. students are performing at a much higher level on their assessments. The very first year we ran it, we saw a 10 to 12% increase across the board in test scores, which is very significant the faculty that are in charge of these programs or that are delivering these programs are also starting to really enjoy the teaching process. They’re becoming more engaged with the students and having fun, and learning more ideas about how to work with them.
Faculty View Screenshot
What partners are saying…
24
Realize It has been a good partner for myself and for Western University from the standpoint that we wanted to make this available for the world. You take anatomy for instance. It’s very limited resources for people. Usually they’re limited to just local two-dimensional diagrams of human anatomy. With the Realize It platform we’re able to integrate all of this high resolution, 3D anatomy, and human anatomy models that we have, along with a platform, and synthesize it together and make it distributable.
- Western University of Health Sciences
Secret Sauce- Artist image – pacaso image
• (stress that the “secret sauce” is first in the DESIGN because designing a course to be personalized and adaptable is NOT the same as designing an online course. Secondly, the next key ingredient is in Realizeit’s powerful engine which adapts every element of experience to the student. Thirdly, the realtime learning analytics help the instructor to plan their time each week to be more effective. Remember it is NEVER right the first time out of the box – continuous calibrations and refinements are always required to achieve the very best results and course quality. Others “talk the talk”, we “walk the walk”
26
Machine Learning Adaptive
Rules Based
Adaptive
Decision Tree
Based Adaptive
• Basis of core IP - Adaptive Engine
• Content and Assessment selection
• Mastery/Prior knowledge determination
• Continuous calibration and prediction of
knowledge pathways
• Content profiles
• Curriculum hierarchy/maps
• Diagnostic Assessments
• Competency progression rules
• Competency progression
hierarchies for program level
personalization
• Multiple models working cohesively to provide a holistic solution for personalization of learning.
• Rules and Decision tree based adaptive approaches layered on machine learning adaptive
Reference:
Adaptive Learning Systems; Surviving the Storm by Lou Pugliese
Educause Review, October 2016
So what model of adaptive is ?
For Illustration Purposes
Calculus III
Calculus I
Calculus II
Target Knowledge Map
Support Every Step of the Way
… TRUE PARTNERSHIP MINDSET
• The diverse Realizeit expertise
• The unlimited support
• Community of practice
• Faculty centered incentives
• Commitment to Florida (I am based in FL. FL partners, etc)
• Annual Sumitt
• Conference Presence (in the know)
Client Success Management
Learning Design
Services
Course Authoring
Training Services
Technical Solutions
Incident Management
Content Solutions
Realizeit Professional ServicesCentered on Client Success
Engagement Management
Customer Advocacy
Partnership
Ingestion ~ Learning Maps
Lessons ~ Assessments
Change Management
Faculty Orientation
Course Authoring
ID Training
Integrations ~ Extensions
Architecture ~ Design
Support ~ Resolution
Software Patches
Content Edits
Instructional Design
Learning Experience
Access to SME Network
Sourcing ~ Curation
Starter Content
Community of Practice
Institutions Seek Solutions In Service To …
32
STUDENT SUCCESS
Engagement, Retention, Persistence, Completion
STUDENT ACHIEVEMENT
Mastery, Progression, Exam Scores, Grades
TEACHING & LEARNING EFFECTIVENESS
Flipped Classroom Model
LEARNING ANALYTICS & REPORTING
Institutional Research/Effectiveness
PROGRAM QUALITY
Curriculum, Content and Assessment Performance
Institutional Partners are Highly Diverse- Versatile Platform, Products & Services -
…1 million COURSE-TAKERS; 300+ COURSES…WHETHER SEAT-TIME OR COMPENTENCY-BASED MODEL
Growing set of Partner Institutions
….a few KEY WORDS to help simplify and crystalize each of the THREE FOCAL POINTS
• Re: Students … in a word … CONFIDENCE … another is ENGAGEMENT
(students report that this approach to learning really helps them build up their confidence)
• Other….
• Not keen on the title tag “The adaptive learning ecosystem” … obviously we have not landed on our new tag but prefer something else … here are some ideas we’re kicking around but not yet sanctioned …. “Going Beyond Adaptive” … “Powering Educational Transformation” … “More Than Adaptive” … “The Ultimate Learning Platform” … “Adaptive Learning – The Real Thing” … “Powering Personalized Learning and Adaptive Teaching” … “Adaptive: Student Tested, Faculty Approved” … “Powering Personalized Learning and Adaptive Teaching”
• Logos … need to drop UTX, IvyTech, Indiana, Significant Technology … need to be careful because at Ole Miss we’re currently working with a faculty member and not the “institution”
• Rather than “Centered on Client Success” you can say “Centered on YOUR Success”
• Re: Instructors … it is about … TRANSPARENCY … DIRECT LINE-OF-SIGHT … PIERCING INSIGHTS … INSTANT & ACTIONABLE INTEL … OPTIMIZING THEIR TIME to spend more time on high-value teaching activities and less time on rote administrative tasks like grading. I always like to say that Realizeit makes the instructor “The Hero” because whenever they engage a student they are instantly able to provide the exact right help because they are armed with data/intel about that students exact strengths and weakenesses at that moment and exactly where they are struggling (or excelling).
• (did you get any good quotes from Tamara?)
• Re: Support and Collaboration … TRUE PARTNERSHIP MINDSET … UNIQUE EXPERTISE (SHERPA’s) … FORMER OPERATORS experienced with implementation … EASY TO WORK WITH … PROBLEM SOLVERS … HIGHLY EXPERIENCED designing and redesigning adaptive learning experiences in a wide variety of circumstances making our team highly effective
• (stress that the “secret sauce” is first in the DESIGN because designing a course to be personalized and adaptable is NOT the same as designing an online course. Secondly, the next key ingredient is in Realizeit’s powerful engine which adapts every element of experience to the student. Thirdly, the realtime learning analytics help the instructor to plan their time each week to be more effective. Remember it is NEVER right the first time out of the box – continuous calibrations and refinements are always required to achieve the very best results and course quality. Others “talk the talk”, we “walk the walk”
Wrap-Up
37
Questions
FEEDBACK – NEXT STEPS
Goals
38
• Provide a personalized learning experience• Deliver learning at an appropriate time
• Deliver appropriate learning material
• Learn about the learner
• Manage and adapt to change: abilities, metrics, behavior etc.
• Identify weaknesses and try to remedy
• Help a learner to realize their potential
• Simulate or emulate a good teacher
• Remain subject and content independent
Realizeit Adaptive Engine Architecture
Underpinning Principles and Models
Adaptive Engine
Profiling
Content
Target
Knowledge
(Curriculum)
Determine
Knowledge
Ability
Values
Work where you are most ready
Your current mastery
Learning
Paths
How you learn most effectively
Find out what you already know
Related Documents
