Presentation for Centre of Legal Education Conference 2014:
https://www4.ntu.ac.uk/apps/events/3/home.aspx/event/149178/default/centre_for_legal_education_conference_2014
9. Prominent trends shaping the
future of higher education
1. Openness
2. Digital learning
3. Granularized learning
4. Data & analytics
5. For-profit/startups (expanding ecosystem)
6. Personalization/adaptivity
7. Wearable/contextual computing
8. Unbundling of organizational roles
9. Blurring distinctive learning roles (lifelong)
10. Degrees and alternative recognition models
How Large Systems Change – Siemens (2013)
10. What
to
expect:
-‐
Outsourcing
of
services
(tech,
curriculum,
teaching,
tes4ng)
-‐
Increased
collabora4on/partnerships
with
sector-‐providers
-‐
New
entrants
(oNen
startups)
into
the
integrated
value
ecosystem
-‐ Successful
universi4es
are
“new
integrators”
How Large Systems Change – Siemens (2013)
12. An Avalanche is Coming – Barber, Donnelly & Rizvi (2013)
DEGREES
STUDENTS
FACULTY
EXPERIENCE
ASSESSMENT
TEACHING/LEARNING
CURRICULUM
GOVERNANCE
RESEARCH
19. Commodity Value vs Values
A university (Latin: "universitas", "a whole")
is an institution of higher education and
research which grants academic degrees
in a variety of subjects and provides both
undergraduate education and postgraduate
education. The word "university" is derived
from the Latin universitas magistrorum et
scholarium, which roughly means
"community of teachers and scholars.”
http://www.montagu.com/companies.aspx?lang=en
26. Student Experience
Students want academic staff to develop their teaching styles to be more engaging,
interactive and use technology and props to make the subject more accessible and
interesting.
Developing an active learning style is a teaching skill which needs to be taught and
developed over time.
Students were clear that they valued their experiences of working in small groups
during teaching time and through assessments because they understood how
these skills could be transferable in an employment
context. They did not, however, mention any other transferable skills which
they have acquired.
Questions on assessment and feedback have once again shown a
disconnect between what students are looking for, and what is provided by
institutions.
Students are still requesting more discussion based feedback with academics and
their peers, and want feedback to be more accessible and available online.
http://www.qaa.ac.uk/Publications/InformationAndGuidance/Documents/Student-Experience-Research-2012-Part-1.pdf
29. Data trails reveal
our sentiments,
our attitudes,
our social connections,
our intentions,
what we know,
how we learn,
and what we might do next.
The Data Intensive University – Siemens (2012)
30. Big Data & Analytics
“Analy4cs,
and
the
data
and
research
that
fuel
it,
offers
the
poten4al
to
iden4fy
broken
models
and
promising
prac4ces,
to
explain
them,
and
to
propagate
those
prac4ces.”
Grajek,
2011
Siemens, Long, 2011. EDUCUASE Review
31. Technique:
Baker
and
Yacef
(2009)
five
primary
areas
of
analysis:
-‐
Predic4on
-‐
Clustering
-‐
Rela4onship
mining
-‐
Dis4lla4on
of
data
for
human
judgment
-‐ Discovery
with
models
Applica:on:
Bienkowski,
Feng,
and
Means
(2012)
five
areas
of
applica4on:
-‐
Modeling
user
knowledge,
behavior,
and
experience
-‐
Crea4ng
profiles
of
users
-‐
Modeling
knowledge
domains
-‐
Trend
analysis
-‐
Personaliza4on
and
adapta4on
Baker, R. S. J.d., & Yacef, K. (2009). The state of educational data mining in 2009: A review and future visions. Journal of Educational Data
Mining, 1(1). http://www.educationaldatamining.org/JEDM/images/articles/vol1/issue1/JEDMVol1Issue1_BakerYacef.pdf
http://www.ed.gov/edblogs/technology/files/2012/03/edm-la-brief.pdf
39. Mo:va:on
Dynamics
Flow: The Psychology of Optimal Experience Csikszentmihalyi (1990)
http://pushingattheedges.wordpress.com/2014/01/25/moocs-content-curationlearning-what-motivates-me/
40. Apgar Tests in Class?
Virginia Apgar
http://www.gardnercampbell.net/blog1/?p=421
41.
42. “The ways you communicate with students, the way chairs
are arranged in the room, the fact of there being a room,
inside a building inside an institution inside staff cultures,
student cultures, professional cultures, broader social
cultures -- all these layers are bound together, laminated, and
much of our task as educators is to unpick the quotidian
assumptions that bind them and ask - does it really need to
be like that? can we do things differently and better?”
– Maharg (2014)
43. I
oNen
found
it
hard
work
understanding
the
textbooks.
I
felt
that
a
lot
of
the
4me
they
were
unclear,
badly
phrased
and
could
have
explained
complicated
topics
be`er.
They
also
frequently
seemed
to
over-‐complicate
topics
that
actually
weren't
that
complex.
Contract - The sections on remedies and
damages was very disjointed and speaking
with fellow students they agree that this is
the most unclear area of the Contract
course. Manuals. The manuals tended to be
'wordy' where it was not necessary. For
example sentences such as 'Now we will
use what you have just read in an activity'
are pointless and just elongate the reading
time.
I
think
one
would
take
in
more
from
the
textbooks
if
there
was
more
visual
s4mula4on,
perhaps
a
bit
of
colour.
http://youtu.be/4K11o19YNvk
http://read-able.com/
48. interaction and
assessment from
the replicable
content pole.
Digital
Publishers
&
Content
Universities?
What’s coming?
MOOCs
&
Pladorms
replicable content
from the interaction
and assessment
pole
Learning
Analy4cs
&
Adap4ve/Personalisa4on
Tools
Learning
Design
&
Pedagogy
Profiling
Tools
49. Learning and Performance Support Systems
A new $19 million 5-year initiative at the National Research Council lead by
Stephen Downes
http://halfanhour.blogspot.no/2013/12/learning-and-performance-support-systems.html
50. Learning as a Cloud Service – will create a distributed learning layer, which is a
mechanism for working with data no matter where it is stored, through desktop,
mobile and other devices.
Resource Repository Network – will create a resource graph of learning/training
resources data from multiple sources and multiple formats including live and
dynamic data such as workplace data, plant instrumentation, or market
information.
Personal Learning Record – will define how we represent, capture, and leverage
user activity, including ratings, test results, performance measures, and the like, in
a distributed learning and work environment.
Automated Competence Development and Recognition – whereas existing
recommender systems depend on manually defined metrics and taxonomies, this
system will detect new and emerging competences and automatically assess
employee performance.
Personal Learning Assistant – will develop an integrated learning appliance, a
mechanism for looking up or finding references or resources inside other programs
or environments.
http://halfanhour.blogspot.no/2013/12/learning-and-performance-support-systems.html
51. LWOWx
Project of Worth:
MOOCs, DOCCs, and Avatars, Oh My:
How Will We Educate Our Lawyers and Law School Students
Tomorrow?
http://www.lawwithoutwalls.org/lwow-x/