The document discusses how data science may reinvent learning and education. It begins with background on the author's experience in data teams and teaching. It then questions what an "Uber for education" may look like and discusses definitions of learning, education, and schools. The author argues interactive notebooks like Project Jupyter and flipped classrooms can improve learning at scale compared to traditional lectures or MOOCs. Content toolchains combining Jupyter, Thebe, Atlas and Docker are proposed for authoring and sharing computational narratives and code-as-media.
Personal Resilience in Project Management 2 - TV Edit 1a.pdf
Data Science Reinvents Learning?
1. 2015-08-24 • San Jose
Paco Nathan, @pacoid
Director, O’Reilly Learning
Data Science Reinvents Learning?
Beyond Gutenberg and Erasmus
meetup.com/SF-Bay-ACM/events/221693508/
2. 2
Some Background…
• O’Reilly Learning: you may only hear about us in
a few instances, if we do our job well; ACM is a great
forum for this discussion
• prior: built-out the community evangelism and training
program for Apache Spark at Databricks
• prior: led Data teams for several years, working on
large-scale ML apps in industry, including: one of the
largest Hadoop instances running in AWS (2008);
one of the first 100% AWS system architectures (2006)
• …
• ancient prior: Stanford CSD teaching fellowship (1984-86,
Alice Supton, Stuart Reges) peer-teaching CS course
which later became Residential Computing
6. 6
Intro
Ostensibly that leads to a question, how might
an “Uber for Education” look?
a) Similar to Cthulhu, we might regret actually seeing that
7. 7
Intro
Ostensibly that leads to a question, how might
an “Uber for Education” look?
a) Similar to Cthulhu, we might regret actually seeing that
8. 8
Intro
Ostensibly that leads to a question, how might
an “Uber for Education” look?
a) Similar to Cthulhu, we might regret actually seeing that
b) Would we really need that anywho?
9. 9
Intro
Ostensibly that leads to a question, how might
an “Uber for Education” look?
a) Similar to Cthulhu, we might regret actually seeing that
b) Would we really need that anywho?
c) Uber itself might not take that approach …
10. 10
Intro
Ostensibly that leads to a question, how might
an “Uber for Education” look?
a) Similar to Cthulhu, we might regret actually seeing that
b) Would we really need that anywho?
c) Uber itself might not take that approach …
Perhaps “Uber for Learning” might be somewhat
more apt?
In any case, what comes after Books,
Kindle, MOOCs?
13. 13
Some Definitions…
Even the best schools these days question
what they will become in 5-10 years
Not-so-best schools are perhaps questioning
much more than that
14. 14
Some Definitions…
Oh BTW, too many (funded) teams seem to
have this mediocre idea for “education”:
1. assessment: collect test scores ➜
2. define “quantified student” ➜
3. reuse online marketing funnel ad-tech ➜
4. invoke agile coding teams ➜
5. ship mobile/cloud-based SaaS platform ➜
6. ...
7. profit
15. Oh BTW, too many (funded) teams seem to
have this mediocre idea for “education”
1. assessment: collect test scores
2. define “quantified student”
3. reuse online marketing funnel ad-tech
4. invoke agile coding
5. ship a mobile/cloud-based SaaS platform
6. ...
7. profit
15
Some Definitions…
LMS
16. K-12 not so much, except perhaps in the
case of Safari for Schools
undergrad textbooks?
graduate textbooks, conferences?
professional focus of our audience
16
Some Definitions…
17. 17
• vocational:
making a career move
• aspirational:
improvement within a career path
• proficiency:
has a specific pain-point, needs to resolve it
• familiarity:
wants to join in a team dialog about a topic,
e.g., conversational programmer
Learner Personas for professional category
19. 19
What about MOOCs?
Massive Open Online Courses –
seven year trend, beginning with:
Connectivism and Connective Knowledge
George Siemens, Stephen Downes
University of PEI (2008)
http://cck11.mooc.ca/
21. 21
What about MOOCs?
Anthony Joseph
UC Berkeley
early Jun 2015
edx.org/course/uc-berkeleyx/uc-
berkeleyx-cs100-1x-
introduction-big-6181
Ameet Talwalkar
UCLA
late Jun 2015
edx.org/course/uc-berkeleyx/
uc-berkeleyx-cs190-1x-
scalable-machine-6066
22. 22
What about MOOCs?
Pros:
• cost-effective to reach a large audience
• popular with students
• ¿ addresses “train the trainers” bottleneck ?
Cons:
• expensive to produce and curate
• most students are sampling
• low completion rates
• somewhat chaotic
• lecture fatigue
• ¿ reinforces advantage of the elites ?
23. 23
What about MOOCs?
Online education: MOOCs taken by educated few
Ezekiel Emanuel, Nature 503, 342 (2013-11-21)
• 80% students already have an advanced degree
• 80% come from the richest 6% of the population
Michael Shanks @Stanford: retrenchment around traditional
disciplines will make disparities even more pronounced
An Early Report Card on Massive Open Online Courses
Geoffrey Fowler, WSJ (2013-10-08)
Amherst, Duke, etc., have rejected edX
see: Open edX Universities Symposium @GWU, 2015-11-11
24. 24
• search engines surface too many choices
among the available learning content
• we must get people wanting to interact with
the material – generally due to social context
• academe strives to decontextualize, which
is the opposite of learning in context
• how do we recognize that learning has
occurred?
• what is the learning promise?
What about MOOCs?
26. 26
Introduction to Robotics
Peter Corke @QUT
https://moocs.qut.edu.au/learn/introduction-to-
robotics-august-2015
• effective use of peer review for scaling
• worked well reaching into Africa, India
Peer Review
27. 27
EffectiveThinkingThrough Mathematics
Michael Starbird @UT/Austin
https://www.edx.org/course/effective-thinking-
through-mathematics-utaustinx-ut-9-01x
• getting students to articulate their
epiphany moments is more interesting
than other results – Donna Kidwell
Epiphany Moments
28. 28
Caltech Offers Online Course with
Live Lectures in Machine Learning
Yaser Abu-Mostafa (2012-03-30)
http://www.caltech.edu/news/caltech-offers-online-
course-live-lectures-machine-learning-4248
• significant improvement through the use
of “flipped” a.k.a. inverted classrooms
Inverted Classrooms
29. 29
Scalable Learning
David Black-Schaffer @Uppsala
Sverker Janson @KTH SICS
https://www.scalable-learning.com/
• active learning: Flipped Classroom and Just-in-timeTeaching
• exams built directly into specific diagrams within videos
• metrics for where in video+code that students get stuck
• instructor can customize subsequent classroom discussions
(active teaching phase) based on stuck/unstuck metrics
Inverted Classrooms
30. 30
How to Flip a Class
CLT @UT/Austin
http://ctl.utexas.edu/teaching/flipping-a-class/how
1. identify where the flipped classroom model makes
the most sense for your course
2. spend class time engaging students in application
activities with feedback
3. clarify connections between inside and outside
of class learning
4. adapt your materials for students to acquire course
content in preparation of class
5. extend learning beyond class through individual
and collaborative practice
Inverted Classrooms
31. 31
Learning programming at scale
Philip Guo
O’Reilly Radar (2015-08-13)
http://radar.oreilly.com/2015/08/learning-
programming-at-scale.html
• PythonTutor
• Codechella
Tutors could keep an eye on around
50 learners during a 30-minute session,
start 12 chat conversations, and
concurrently help 3 learners at once
Collaborative Learning
32. 32
Data-driven Education and the Quantified Student
Lorena Barba @GWU
PyData Seattle 2015
https://youtu.be/2YIZ2SY9mW4
• keynote talk: abstract, slides
• homepage
If you study just one link in this entire talk…
34. 34
If by some bizarre chance you haven’t used
it already, go to https://jupyter.org/
• 50+ different language kernels
• new funding 2015-07
• UC Berkeley, Cal Poly
• nbgrader autograder by Jess Hamrick
• jupyterhub multi-user server
• curating a list of examples
• repeatable science!
see also:
Teaching with Jupyter Notebooks
http://tinyurl.com/scipy2015-education
Project Jupyter
35. 35
Deploying JupyterHub for Education
Jessica Hamrick
Rackspace blog (2015-03-24)
https://developer.rackspace.com/blog/deploying-
jupyterhub-for-education/
Project Jupyter
36. 36
Literate Programming
Don Knuth
Univ of Chicago Press (1992)
literateprogramming.com/
Instead of imagining that our main task is
to instruct a computer what to do, let us
concentrate rather on explaining to human
beings what we want a computer to do
Evoking some earlier works…
37. 37
Most definitely check out CodeNeuro,
both online and the conf/hackathon…
Some great examples:
Jeremey Freeman, HHMI Janelia Farm
http://notebooks.codeneuro.org/
Matthew Conlen, NY Data Company
http://lightning-viz.org/
Olga Botvinnick, UCSD
http://yeolab.github.io/flotilla/docs/gallery/
Great Examples
40. 40
Embracing Jupyter Notebooks at O'Reilly
Andrew Odewahn
O’Reilly Media (2015-05-07)
https://beta.oreilly.com/ideas/jupyter-at-oreilly
O’Reilly Media is using our Atlas platform
to make Jupyter Notebooks a first class
authoring environment for our publishing
program
Jupyter, Thebe, Atlas, Docker, etc.
Content Toolchain
41. 41
Embracing Jupyter Notebooks at O'Reilly
Andrew Odewahn
O’Reilly Media (2015-05-07)
https://beta.oreilly.com/ideas/jupyter-at-oreilly
O’Reilly Media is using our Atlas platform
to make Jupyter Notebooks a first class
authoring environment for our publishing
program
Jupyter
Content Toolchain
42. 42
On Demand Analytic and Learning Environments with Jupyter
Kyle Kelley, Andrew Odewahn
lambdaops.com/jupyter-environments-odsc2015/
Exploring a couple themes, in particular:
• computational narratives
- exploratory data analysis
- software development/collaboration
- API exploration
- technical papers
- reports, exec dashboards
• code-as-media
- Thebe project, etc.
Content Toolchain
43. 43
Personal experiences during 2012-2015
as an author and instructor…
Just Enough Math
Paco Nathan
O’Reilly Media (2014)
http://justenoughmath.com
Content Toolchain
44. 44
Learnings based on working on this
project with Kyle and Andrew…
How to transit from roles of data scientist,
software developer, engineering director –
into roles of author, teacher – and vice versa
Content Toolchain
45. 45
Interactive notebooks:
Sharing the code
Helen Shen
Nature (2014-11-05)
nature.com/news/interactive-notebooks-
sharing-the-code-1.16261
Content Toolchain
46. 46
Content Toolchain
Atlas is our content platform backed by Git,
for project collaboration among authors,
editors, et al.
https://atlas.oreilly.com/
47. 47
Content Toolchain
Thebe (a moon of Jupiter) provides a layer
atop Jupyter that is needed for publishing,
white-labeled content, etc.
https://github.com/oreillymedia/thebe
49. 49
Content Toolchain
Contrast our current talent workflow and this
new world of Jupyter+Docker+Thebe+cloud …
How would it work with known successes such
as Head First?
production presentation
Thebe:
player
Jupyter:
notebook
Docker:
container
web page:
interaction
Git:
versioning
Atlas:
publications
various
formats
authoring
cloud
infra
53. 53
The Learning Architecture:
Defining Development and Enabling Continuous Learning
David Mallon, Dani Johnson
Bersin (2014-05-06)
http://www.bersin.com/Practice/Detail.aspx?
docid=17435&mode=search&p=Learning-@-Development
This report is designed to help leaders
and talent development and learning
professionals to take positive steps
toward understanding and implementing
learning architectures
Sidebar: Learning Architecture
54. Think of a favorite open source framework …
who (or where) are the experts in this graph?
Sidebar: Innovators vs. Experts
Diffusion of Innovation
Everett Rogers (1962)
http://sphweb.bumc.bu.edu/otlt/MPH-Modules/SB/SB721-
Models/SB721-Models4.html
54
55. 55
Building Blocks
In software engineering, we rarely hand a
developer the spec for some app and say
“Start from scratch, then come back when
you’re done.” Instead:
• focus on MVP
• leverage APIs, libraries, microservices, etc.
• iterate on small, incremental changes
• this allows for TDD, CI, etc.
• plus, customer experiments ➜ data science
Compare/contrast that with how publishers
approach authors, speakers, instructors?
56. 56
Building Blocks
Proposing a new format spec to replace
EPUB, MOBI, etc.:
• video segments + transcripts
• notebooks in Jupyter+Thebe+Docker
• metadata (persona, topics, cues, etc.)
• links to Git repos, Dat data
• annotations atop existing content
• webcast/livestream
• social interaction (TA/mentoring)
• evaluation modules
• discourse analytics
most reused across a spectrum
of synchronous to async
instrumented for experiments,
analytics, iteration
57. 57
total
newbie
good
overview
Do you have sufficient familiarity with the topic?
utterly
confused
familiar
territory
Can you build on familiarity with a related topic?
must get
unstuck
send pull
request
Do you have necessary proficiency in the topic?
learner
topic
experience
concise
topic
inter-
disciplinary
How many boundaries must you span to achieve structural literacy for this topic?
want to
for myself
have to
for my job
What is your primary motivation to learn this topic?
bleeding
edge
COBOL 2020
Where are you on the "diffusion of innovation" curve w.r.t. the topic?
on-
demand
major
event
How high is the transaction cost for the experience delivered to you?
"go read
the code"
full-team
participation
Does the learning experience immerse you within a diverse, supportive social context?
Dimensional Reduction
Did we mention intense needs
for data analytics at scale?
58. 58
Is it possible to measure “distance” between
a learner and a subject community?
From Amateurs to Connoisseurs:
Modeling the Evolution of User
Expertise through Online Reviews
Julian McAuley, Jure Leskovec
http://i.stanford.edu/~julian/pdfs/www13.pdf
Recommender Systems
59. 59
Back to “Uber for Learning” – approaching from a learner
(audience) perspective, generally within a social context
Given that:
• books aren’t used by learners as much anymore
• experts don’t have time to write books anymore
If we can:
• fit learners’ needs to topics w.r.t. subject communities,
based on their S-curve positions
• personalize lectures for learners’ pain-points
• reuse containerized building blocks
Imagine the extent to which our current data science
tooling and techniques can be leveraged?
Summary
60. 60
PS: If you are interested in opportunities
to write, speak, teach, mentor, code, etc.,
based on these approaches, let us know
Get Involved!