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XLP Owner’s Manual
Professor Ben Koo, Alex Cureton-Griiths, Gautam Mitra,
Sam Sanders, Awid Vaziry
Sep 5, 2018
Contents
1 What is XLP? 1
XLPinaNutshell ..................................... 1
Inputs........................................ 1
Activities ...................................... 2
Outputs....................................... 2
Eects........................................ 2
AShortHistoryofXLP .................................. 3
2 Why XLP? Why Now? 5
ComputingPower .................................... 5
BigData.......................................... 5
OpenSource ....................................... 5
MobileDevices ...................................... 6
ContainersandClouds.................................. 6
Globalization ....................................... 6
Summary ......................................... 6
3 How XLP Works 9
Missions.......................................... 9
Participants........................................ 9
MissionDesigner .................................. 10
MissionExecutor .................................. 10
Sponsor....................................... 10
Resources......................................... 10
Outputs.......................................... 11
Containers of Knowledge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Team ........................................ 12
RefinedXLPManual ................................ 12
4 XLP for Mission Designers 13
Kick-OMeeting ..................................... 13
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DigitalPublishingContainer............................... 13
Constitution........................................ 14
5 XLP for Mission Executors 15
Delegations, Groups, and Teams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
OrientationProgram ................................... 15
DigitalIdentity ................................... 15
ConstitutionReading................................ 16
Lab/Knowledge Exploration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
TheMission........................................ 16
MissionBreakdown.................................... 18
Decomposition and Recomposition . . . . . . . . . . . . . . . . . . . . . . . . 18
LogicModel..................................... 19
MissionStatement ................................. 22
PlanningandManagement................................ 23
Scheduling and Task Allocation . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Story-boarding ................................... 24
BriefingsandDebriefings ............................. 25
ActivityCoordination................................... 26
Surveys ....................................... 26
Research ...................................... 26
ProductDevelopment .................................. 26
DigitalPublishing..................................... 27
Wiki ......................................... 27
Blog......................................... 28
Presentation .................................... 29
Poster........................................ 30
UsefulResources.................................. 30
EvaluationandAssessment ............................... 31
6 Remix: The XLP Online Platform 33
RemixTools........................................ 33
WhatisaMicroservice?............................... 34
RemixMicroserviceOverview .............................. 35
DataInput...................................... 35
DataManagement ................................. 36
DataPublishing................................... 39
Groupware ..................................... 40
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Architecture..................................... 40
Education on the Blockchain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
HistoricalContext.................................. 42
The Future: Education 3.0: Education on the Chain . . . . . . . . . . . . . . . 45
Summary...................................... 53
TechnicalAnalysis ................................. 54
7 XLP Philosophy 57
Micro,Meso,Macro.................................... 57
MacroscopicinNature ............................... 57
Mesoscopic in Sorting Order . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
MicroscopicinContexts .............................. 57
TheoryU ......................................... 58
EarlySuccess.................................... 59
FailEarly,FailSafe ................................. 59
Convergence .................................... 59
Demonstration ................................... 59
Lessig’sFourForces.................................... 60
Law: The Rules a Community Recognizes . . . . . . . . . . . . . . . . . . . . . 60
Social Norms: How a Community Expects You to Behave . . . . . . . . . . . . 60
Market: How Much Do You Pay? . . . . . . . . . . . . . . . . . . . . . . . . . . 60
Architecture: The Way the World Is . . . . . . . . . . . . . . . . . . . . . . . . 61
Example:Smoking ................................. 61
How do the Four Forces Interact? . . . . . . . . . . . . . . . . . . . . . . . . . 62
How do the Four Forces Relate to XLP? . . . . . . . . . . . . . . . . . . . . . . 63
The Four Forces, XLP, and The Real World . . . . . . . . . . . . . . . . . . . . . 63
8 Technical Analysis 65
Containerization ..................................... 65
DockerContainers ................................. 65
What do We Run in Docker? . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
Namespaces .................................... 66
Verification and Security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
SecureConcurrentEditing................................ 67
Decentralization ..................................... 68
Tokenization ....................................... 68
Distributed Ledger Technology (Blockchain) . . . . . . . . . . . . . . . . . . . 68
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FourForces ........................................ 69
LegalMechanisms ................................. 69
MarketMechanisms ................................ 69
SocialNorms .................................... 69
9 Glossary 71
10 Appendices 75
Constitution........................................ 75
Preface: A New Kind of Constitution . . . . . . . . . . . . . . . . . . . . . . . . 75
TheConstitutionofTheXLP ............................ 80
Howto:UseMediaWiki.................................. 92
LogIn ........................................ 92
CreateaNewPage ................................. 92
EditaPage ..................................... 93
Format Text and Insert Images . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
How to: Use WordPress and Elementor . . . . . . . . . . . . . . . . . . . . . . . . . 96
LogIn ........................................ 96
CreateaNewReportPage ............................. 97
CreateaNewLandingPage ............................ 100
EditaPage ..................................... 102
BackUpYourWork................................. 102
For Participants Coming to China . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
How to: Install WordPress and MediaWiki . . . . . . . . . . . . . . . . . . . . . . . . 104
Youwillneed .................................... 104
OptionalFirstStep ................................. 104
MediaWiki...................................... 104
Wordpress ..................................... 105
Piwik ........................................ 105
Accessing on your local machine . . . . . . . . . . . . . . . . . . . . . . . . . 105
How to: Crowd Learn with remote participants . . . . . . . . . . . . . . . . . . . . . 106
WhyCrowdLearning? ............................... 106
Advice........................................ 106
11 Bibliography 109
Constitution........................................ 109
Links ........................................ 116
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1 What is XLP?
XLP stands for Extreme Learning Process, a methodology that lets communities of learners
design and conduct collaborative learning activities. Taking a look more closely at the name:
•Extreme: XLP explores frontiers, identifies boundaries, and helps participants push
those boundaries.
•Learning: XLP enables individual learning, group learning, and large-scale crowd learn-
ing.
•Process: XLP has a clear process, through which participants prepare, deploy, and exe-
cute missions.
We aim to become a crowd-learning system that facilitates collective learning in this increas-
ingly complex world. Learners are empowered to work together within and between teams,
and incorporate both digital and physical elements.
Due to advancing technology, educational institutions can now operate in ways unthinkable
only a few years ago. This is because today it is possible to collect and process organizational
behavior data in ways that were impossible before. Therefore XLP is not merely about improv-
ing individual learning, but also measuring and improving organizational learning.
XLP in a Nutshell
XLP is a process with inputs,outputs,activities, and eects:
Inputs
• Sponsors and groups of participants, who become mission designers and mission execu-
tors. These participants come together for a specific learning objective and duration.
• Resources such as hackerspaces, campuses, mentoring, etc.
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Activities
• Mission based learning, which is designed and executed by groups of participants.
Each mission uses gamified techniques to impart valuable knowledge and skills with
real-world applications.
• Digital publishing of all activities and results, in the form of containers of knowledge, via
our Remix suite of tools.
Outputs
• Containers of knowledge, carrying a full record of participant activity, and able to be read,
shared and deployed with ease
• Knowledge and skills transfer
• Credentials and qualifications, stored on the Blockchain. Access can be granted to se-
lected employers and institutions to prove participants expertise.
• Crowd Learning, i.e. large scale collaboration on learning missions.
Eects
For participants:
• Real world decisions: XLP challenges participants to make financial, legal, cultural and
technical decisions, so they can achieve goals set by the participant groups themselves.
• Real world experience: XLP is pragmatic. The XLP method induces realistic human dy-
namics, utilizes modern technologies, encourages participants to create social norms,
and establishes executable regulations based on the design principles of the fast-evolving
Internet.
• Tapping potential: XLP drives participants to realize their untapped potentials and emerg-
ing powers of collaboration through having them stretch the educational envelope by
shiing the focus from teaching (top-down) to learning (bottom-up).
For educators and institutions:
• No-one le behind: XLP encourages an evolutionary process, which creates a digitally
enabled learning context that delivers rich social-interactions and leaves no-one behind.
• Curating, not teaching: By placing participants in control of learning, XLP redefines edu-
cators’ roles as curators of learning resources and as evaluators of participants’ learning-
potentials.
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• Deeper, richer data: XLP provides network-enabled learning data management technol-
ogy that enables stakeholders to record, analyze and identify learning trajectories to de-
fine new directions for progress.
A Short History of XLP
Since June 2012, XLP-based orientation programs and semester-long courses have been con-
ducted at:
• Tsinghua University, Beijing
• National Taiwan University of Science and Technology
• Singapore University of Technology and Design
• Taylor’s University, Malaysia
• Eurasia University, Xi’an
• Tianjin Vocational College of Mechanics and Electricity
Courses have also been conducted at many leading high schools in China. Due to XLP’s exper-
imental success, China’s Ministry of Education has invited the founder of XLP to serve on the
Design Committee of National Curriculum Standards on Technology Education, with the goal
of rolling out XLP as a learning architecture and a learning activity design methodology for over
300 million registered students in the Chinese education system.
XLP is scalable and applicable to a broad range of students. A teacher from Tianjin Vocational
College of Mechanics and Electricity stated his observation:
”In the past, I could only judge students’ quality by their test scores. However, aer seeing
that students with low test scores can sometimes be the most productive contributors in XLP-
enabled learning process, I realized XLP presents many opportunities for students to demon-
strate their natural talents.”
Mr. Wang Hong Yu, the General Manager of China’s Open Course Resource Center, stated how
XLP might aect his business:
”With shock and awe, I personally witnessed the transformative eect of a few XLP events on
students. I realized that a radical transformation in education has already taken place here in
China. The traditional textbook-oriented industry could no longer last. We have to re-position
ourselves in the future ecology of education.”
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2 Why XLP? Why Now?
XLP did not spring fully formed from a vacuum. There is a specific context surrounding the
framework and its development:
Computing Power
Roughly every 2 years, the number of transistors on a computer chip doubles1. The resulting
increases in computational processing power strongly synergizes with skyrocketing levels of
data storage and falling costs. This influences every aspect of our lives, and the opportunities
to learn in new and dierent ways are expanding exponentially.
Big Data
Every second, gigabytes of data are being collected, and no one – or even any organization –
will ever be able to access or process it all. However, learning communities can come together
to deal with subsets of this data and solve real-world problems.
This big data makes what and how humans learn more important. As data collection and pro-
cessing increasingly lets machines connect and aid human decisions (hence creating value), hu-
man ingenuity, creativity and intuition are becoming increasingly important. More and more,
the only things that people should do are the things that only people can do – and this, of course,
places a premium on humans’ ability to learn.
Open Source
Open source gives anyone the right to use, change, or share a given technology, thus dramat-
ically reducing the cost of using, copying, modifying, and redistributing soware (and indeed,
1Mollick, Ethan. (2006). Establishing Moore’s Law. Annals of the History of Computing, IEEE. 28. 62 - 75.
10.1109/MAHC.2006.45.
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hardware). This means anyone can be a creator and build upon the achievements of those who
came before.
Mobile Devices
Developments in mobile communications and the ubiquity of digital electronic devices mean
that more people can connect to the internet – and each other – anytime, anywhere. This means
newer, richer opportunities to learn from and with others, no matter where they are.
Containers and Clouds
Big data needs big computing power – too much for any one institution. With cloud providers
like AliCloud or Amazon Web Services, anyone can run virtual machines to perform big comput-
ing tasks, and with the power of container platforms (Docker, Kubernetes) they can scale and
replicate with ease.
Globalization
The problems of today’s world require diverse communities to oer new insights. These prob-
lems are too big for just one individual or institution, but aordable Internet access is enabling
people all over the world to collaborate in micro-learning communities to solve these problems.
Learning and working together globally across boundaries of space and time – across all bound-
aries – is mankind’s greatest hope for making progress, and XLP enables this crowd-learning
and collaborative eort to improve the state of the world.
XLP pushes for the emergence of the world as we believe it should be – egalitarian and equitable,
a world in which everyone has a fair chance to have their voice heard, and a fair opportunity to
contribute to the progress of the world and humanity.
Summary
The above factors both enable and require new modes of learning which are increasingly col-
laborative, personalized, self-directed, active, engaging, and global. XLP has enabled commu-
nities of learners to form, disband, and learn collectively more easily and inexpensively than
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ever before. The ubiquitous interconnectedness of data, people, things, and processes, the op-
portunities for collaborative crowd-learning – and new modes of crowd-learning – will increase
exponentially. These trends will enable learning to be measured in new ways, and will rede-
fine what the outcomes of learning should be. XLP capitalizes on these trends and enables
new learning environments and opportunities, while being enabled and indeed necessitated
by them. What humans learn, and the way they learn, must and will be transformed.
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3 How XLP Works
Missions
XLP’s core activity is the mission. Participants either prepare the mission or execute it.
These missions engage individuals and the group as a whole. Each group designs and operates
its own small (or ”micro”) learning community that serves the individual and collective aims of
the creators and participants.
Each mission is governed by a logic model to deliver maximum learning value through hands-
on activities. In this chapter we will give a high-level overview of the activities and participants
in an XLP mission and the resources made available to achieve the mission goals. In the fol-
lowing chapters we will present detailed step-by-step breakdowns to help you prepare and run
missions yourself.
Participants
XLP engages with learning communities of all shapes and sizes. They may be:
• Large or small
• Physically together, near each other, or spread around the world
• Of similar (or vastly dierent) ethnic, cultural, educational, professional, and religious
backgrounds
• Similar (or dierent) skill sets, skill levels, interests, and life experiences
• Relatively homogeneous, or highly diverse
• Stay together for many years, or come together to design and conduct a single learning
activity
These micro learning communities come together to learn something specific, oen for a spe-
cific duration. Multiple communities can interact, and may later merge to form larger learn-
ing communities, just as amoebas divide and recombine in dierent ways. As a community
becomes larger, it becomes more and more like the real world, and participating individuals,
institutions, systems and societies can iterate upon increasingly optimal solutions.
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Each community may have three kinds of members: Mission Designers (MD’s), Mission Execu-
tors (ME’s) and Sponsors. The Designers and Executors learn individually and collectively, and
this community is a microcosm of a larger context – for example, a university, a society, or a
nation. XLP challenges every learning team to be a focused, goal-oriented microscopic society
in a digital publishing/learning workflow environment.
Mission Designer
Mission Designers (MD’s) design and test learning missions in accordance with the goals of spon-
sors, tailored for participants based on the available resources and requirements.
MD’s are generally divided into four or five groups that reflect Lawrence Lessig’s Four Forces
that are discussed in a later chapter:
• A law court and perhaps a patent oice to regulate the legal interactions between ME’s
• A media department to reflect the social norms of the ME’s through social media, other
digital media, and traditional media
• Market regulators to regulate the operation of the market
• Technology support to enable ME’s to execute missions using the technology architecture
required to do so
Mission Executor
Mission Executors (ME’s) participate in the missions designed by Mission Designers, and later
become Mission Designers themselves. While on the mission, they learn to execute at a higher
level of complexity or speed, and learn how to guide others to perform the mission.
Sponsor
School/department that provides resources for XLP program.
Resources
A learning environment encompasses resources in both the virtual and physical worlds. These
can be further divided into two categories: Resources to prepare before the learning process
and resources (which have been used and tested in the past) to implement during the learning
process:
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Figure 3.1: Resources used in XLP
Outputs
Containers of Knowledge
Containers are the foundation of XLP. A container can be thought of as a box that contains so-
ware, the data needed to configure that soware, and data created by users (i.e. digital assets).
These containers can be installed and used anywhere, and data can be imported and exported
easily.
• XLP creates replicable, learning missions in containers, which can then be installed and
used anywhere in the world
• Our online platform, Remix, provides the infrastructure to perform this digitally
• Participants create digital assets in their containers using digital publishing, as a record
and proof of the work they have performed in the mission.
By taking part in the mission and digital publishing workflow, participants create a body of
knowledge covering their area of study. This is in the form of a container which includes so-
ware (typically MediaWiki and other tools like WordPress), configuration, and content produced
by the participants. These containers may contain many forms of digital asset:
Proposal or Report Form
Discusses the conclusion of a certain research study, or the conclusion of certain industry anal-
ysis (”research study,” ”business proposal,” or ”industry analysis report.”)
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Budget
Including both a planning schedule (i.e., a resource and human resource budget and timetable)
in addition to a financial budget.
Short Movie
Usually a compilation of interesting video footage of the activity, annotated with written text
and non-proprietary music.
Prototype Product
A book, pamphlet, brochure, or even physical product.
Example Containers
• Bauhinia Program
Team
One of the most important aspects and products of any XLP event is the friendship developed
between participants. Ideally they can create a social network so they can always tap into these
human resources for future cooperation.
Refined XLP Manual
Because everyone uses a similar mechanism to learn from each other, we can collect data on
this to improve XLP as a general learning process – so that everything we do in XLP can be used
as case studies or data to improve practices in future. The most direct contributions will be
sections, refinements or revisions to the XLP operating manual that you are reading now.
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4 XLP for Mission Designers
The job of a Mission Designer is to design the mission for Mission Executors, then deploy it and
guide them through it. Typically a Mission Designer has been an active Mission Executor in the
past.
Mission Designers put together:
•Constitution: Defines the goals of the mission, and rights and responsibilities of Mission
Designers, Mission Executors, Sponsors
•Logic Model: Defines the context, goal, inputs, activities, outputs, eects, and external
factors of the mission
•Mission Specification: Specifies the mission clearly
This process generally takes a month or so, since extensive planning is required.
It is highly recommended to ”eat your own dogfood” while preparing the mission - namely us-
ing the XLP methodology itself (logic model, constitution, etc) to govern the mission design
process, with the end goal of having students produce their own logic models, etc, as outputs
of said mission. For that reason, MD’s should become familiar with how executors execute XLP
missions since designing an XLP mission is itself an XLP mission.
Kick-O Meeting
Sponsors, Mission Designers, and support stu should come together to ensure mutual under-
standing of the XLP mission preparation process. Upon setting up the Digital Publishing Con-
tainer, the team can use tools like Phabricator to assign tasks and deadlines.
Digital Publishing Container
Each learning community uses digital publishing tools (like MediaWiki) to publish their activi-
ties and results. These tools are contained in a Docker container which lets users access them
online. MD’s should coordinate with technical support sta to ensure these containers are de-
ployed and fully tested, with a regular backup system in place.
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Constitution
The constitution is a living document that lays out:
• Which entities can engage in an XLP mission
• The purpose of the mission
• Responsibilities of participants
• Rights of participants
• How to change or amend the constitution (typically via git or other version control sys-
tems)
Mission Designers write their own constitution which ”overlays” the XLP Meta Constitution.
Check an example constitution for reference.
This constitution is supplemented by a smart contract. Whereas the constitution provides the
framework, the smart contract handles the specifics. The constitution is the overarching set of
rules, obligations, privileges and rights for the membership of accounts, while the smart con-
tract is one defined and created by the parties involved in a particular digital publishing work-
flow or creation. That is, every account is to be governed by both this overarching constitution,
and a smart contract which defines the specifics of one’s work in the XLP.
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5 XLP for Mission Executors
Each Mission Executor goes through an extensive orientation program before engaging in the
mission that the Mission Designers created.
Delegations, Groups, and Teams
Depending on the amount of people taking part in activities, they can be broken down as fol-
lows:
• A delegation may consist of several groups who attend a venue together, but work on
dierent courses with frameworks dierent to XLP.
• A group is all the participants working on an XLP course together. They may (or may not)
be part of a larger delegation.
• Each group is split into teams, each working on a specific project that they will be graded
on.
Orientation Program
Usually involves digital identity, agreement reading/signing and quick overview of how to use
digital publishing tools. Participants also gain experience dealing with many other people on
the fly, encountering the courtroom, participating in market transactions, participating in me-
dia – i.e. learning how the four forces interact with XLP activities.
Digital Identity
Every entity in an XLP mission has a verifiable which they use to:
• Log in to the digital publishing tools stored in their container (like MediaWiki, WordPress,
or NextCloud)
• Attach ownership to the content they generate
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• Track their learning progress via built-in analytics tools
• Digitally sign the constitution and smart contracts
• Securely link their identity to their qualifications and credentials
These participating entities include individuals and organizations, as well as physical resources
and technical services. Digital identities (like email addresses or OpenID) enable the tracking of
every entity’s contribution to the crowd-learning process, and allow participants to sign Smart
Contracts.
Constitution Reading
Before each XLP mission, each prospective participant reads through the constitution to learn
the mission framework. This details the rights and responsibilities of each participant in the
activity, in addition to services provided by the sponsor. Participants digitally sign a Smart Con-
tract (stored on the Blockchain) stating that they understand the details of the constitution and
their responsibilities, and an agreement stating that they agree to abide by the overarching
constitutional framework during the activity.
Lab/Knowledge Exploration
”Taster” classes allow participants to visit many laboratories and researchers in a big campus
(e.g. Tsinghua University’s laboratory exploration program that makes available more than 100
laboratories and gets participants on campus to see each other’s research results.) This gives a
broader context of available technology and research results.
Some examples include:
• The Intelligent Manufacturing Incubator at Zhongguancun
• The Digital Capability Center at iCenter, Tsinghua University
• Other local high tech companies
• Tianhe Super Computing Center
• Tianjin High Tech Zone
The Mission
Mission Executors will form teams and create a digital publication, for example an Industry Anal-
ysis Report (IAR), based on field trips, in-person interviews, and lectures conducted by speakers
and tutors. Ideally, Mission Executors should collect and compile relevant industry indication
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data, pictures, and videos taken on field trips or daily observations during the program, and
integrate them into their publication.
All teams will collaborate on a hosted wiki to write and collate their reports, and then present
the finished products on a visually appealing blog and as a class presentation.
•Example: Experience China, Industry Frontiers, 2018: wiki, blog
Missions usually fall into one of three tracks, each of which use dierent tools to create dierent
outputs:
•Industrial frontier: Participants globally search and compile relevant information, and
creatively tell a compelling story using trustworthy data sources and presentation tech-
niques.
•Computational thinking: Participants apply optimization technologies and understand
the principles of optimal limits, and can thus apply optimization to all their learning ac-
tivities.
•Domain Specific: Participants learn domain-specific vocabulary and rules, so that they
can leverage existing bodies of knowledge in an organized manner.
Typically, a mission follows five steps:
Figure 5.1: Mission steps
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Mission Breakdown
Decomposition and Recomposition
Each XLP Mission follows our V Curve:
Figure 5.2: V Curve, showing mission decomposition and recomposition
Starting from the le of the diagram, participants break down (decompose) the mission until
they get to the most basic (atomic) level, and then rebuild (recompose) the constituent parts
into potential viable outputs. Breaking it down step-by-step:
1. Mission specification.
2. Decomposition of mission specification.
3. Decompose and repeat steps 1-3 until you reach the atomic level. Keep going down, ma-
chine checking if you have met the specification. Must be at the atomic level.
4. Go back up once you have defined the most basic decomposition.
5. Propose a solution of some sort. You can use machines to generate new solutions. Fre-
quently test to see if it matches your specification.
6. Pick the best option and digitally publish it.
A useful analogy is a Lego set:
• The mission specification would be the picture of the finished model on the box
• The mission would be to build the model
• The most atomic level is the individual Lego bricks
Participants would look at the picture on the box, decompose it into component parts until they
reach the brick level, then work out the best way to recompose it (or potentially build something
even better) from there.
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Logic Model
A logic model (also known as a logical framework, theory of change, or program matrix) is a
tool used by funders, managers, and evaluators of programs to evaluate the eectiveness of a
program. They can also be used during planning and implementation. Logic models are usually
a graphical depiction of the logical relationships between the resources, activities, outputs and
outcomes of a program. While there are many ways in which logic models can be presented, the
underlying purpose of constructing a logic model is to assess the ”if-then” (causal) relationships
between the elements of the program.
As part of their digital publication, teams create a one-page logic model, taking into account
activity context, inputs, activities, eects, external factors, and outcomes.
Each of the boxes below will have precise linguistic properties that can be examined by human
or machine (via Natural Language Processing), to know if the information in the box fits the
specified requirements. In this way, participants can be assessed and certified automatically,
using Blockchain-witnessed process data collected using the Remix platform.
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Figure 5.3: XLP Logic Model
1. Context
• What’s your current situation or context?
• Includes spatial and temporal description (where will you do the activity, and when?)
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2. Goal
• What do you want to do?
• Imperative statement, for example ”conquer Rome,” or ”land a man on the Moon”
3. Measurable Eects
• How will you determine success?
• Set of conditional statements. Output will be measured against these to confirm it has
achieved desired goal
4. Output
• What will you deliver?
• Concrete objects like micro-movies, logic model documents, industry analysis reports,
financial statements, etc
5. Activities
• What do you need to do to succeed?
• Set of partially ordered activities, outlining what happens during the project and how to
accomplish the project goal
6. Input
• Resources required to execute the mission, including budget, human skills, head counts,
etc
7. External Factors
• What factors that could prevent the team from achieving their goal?
The logic model is one of the first activities each team conducts, which helps to build a common
understanding of the mission as well as the influencing parameters. During the next steps, con-
tinuously referring back to the logic model helps them check that they are consciously aware
of their own actions.
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Using the logic model ensures that every task or project starts with explicitly-analyzed test
cases, originating from Test Driven Design. Each step of the model feeds into the next step, gen-
erally with a one-to-one relationship. Similar to writing a computer program, the logic model
has two stages of checking/analysis:
• Static Analysis: A way to read the model itself, and see if the content in all boxes is consis-
tent and relevant.
• Dynamic Analysis: A way to use the ”measurable eects” to confirm output matches ex-
pected outcomes, and if task performance fits the goal.
Many examples of logic models can be seen from the teams that took part in Experience China
2018.
Mission Statement
A mission statement acts as a carrier of culture, ethos and ideology1. Many mission statements
are pithy and up-beat, and deal with abstractions possessing ’a strategic level of generality and
ambiguity’2
A team’s mission statement should capture the essence of their goals and reflect their specific
niche. The best mission statements are clear, concise, and useful (informs. focuses. guides.)3
Examples
•Public Broadcasting System (PBS): To create content that educates, informs and
inspires.
•charity: water: Bringing clean, safe drinking water to people in developing countries.
•National Parks Conservation Association: To protect and enhance America’s National
Park System for present and future generations.
•TED: Spreading Ideas.
•Defenders of Wildlife: The protection of all native animals and plants in their natural
communities.
1[Discourse and the projection of corporate culture: The mission statement https://deepblue.lib.umich.edu/
bitstream/handle/2027.42/67339/10.1177_0957926595006002005.pdf?sequence=2]; JM Swales, PS Rogers -
Discourse & Society, 1995 - journals.sagepub.com
2Fairhurst, G.T., Echoes of the Vision: When the Rest of the Organization Talks Total Quality, Management Commu-
nication Quarterly 6: 331-71
3https://topnonprofits.com/examples/nonprofit-mission-statements/
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Planning and Management
Mission Executors use physical resources like whiteboards, post-its and note paper, and digital
resources like Phabricator to storyboard their mission, assign tasks, and set a schedule.
Figure 5.4: Phabricator
Scheduling and Task Allocation
Ideally use a whiteboard board, with post-it notes:
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Figure 5.5: Kan Ban with post-its to organize tasks
1. Each team member writes down a list of tasks they think need to be done
2. Team comes together to share their post-its, and come to consensus
3. Connect post-its with whiteboard markers to mark related ideas
4. Post-its are put on kanban, arranged by schedule (today/tomorrow/this week/later/done)
5. Each activity is assigned to a team member and recorded on Phabricator
Story-boarding
Teams designing a product or producing a video may find it useful to produce a storyboard, to
visually organize their story or use case.4
4https://multimedia.journalism.berkeley.edu/tutorials/starttofinish-storyboarding/
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Figure 5.6: Example storyboard5
Briefings and Debriefings
At the beginning of each day, the team coordinator should meet with the team and ensure ev-
eryone is up-to-date and clear on their tasks. Some example questions include:
1. What thoughts have you had on the project since the end of the last working day?
2. What tasks will you be working on today?
3. What obstacles do you think may pop up? (and as a team, work out how to overcome
them)
4. What other commitments do you have today?
At the end of the day, we suggest a debrief to ensure the team achieved everything they planned.
Some example questions are:
1. What did you get done today?
2. What did you plan to do, but didn’t do? Why not?
3. What surprises (good or bad) came up? (and as a team, work out how to overcome those
bad surprises if they happen again)
5[https://www.flickr.com/photos/feppa/4512490304” Benegrip - storyboard”] by feppa, licensed under CC BY 2.0
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4. What’s your plan for tomorrow?
5. Any other business?
Activity Coordination
Based on the planning done in the previous steps, each team collects data via interviews with
industry experts, site visits, online and oline research, and surveys. All research must be cited
and collected on the wiki.
Surveys
• Writing good survey questions
Research
Some helpful links include:
• Google Scholar
• ArXiv
Product Development
Note: Not all XLP courses require a product development step, for example when writing Industry
Reports, this step would likely not be required.
Mission Executors use tools like Jenkins, Modelica, Jupyter Notebook, and other prototyping
and integration tools to develop their product, which may be soware, hardware, or a business
idea.
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Figure 5.7: Jupyter Notebook
Digital Publishing
Many of the mission objectives you will be graded on revolve around digital publishing. Each
group participating in the course will have their own digital container that holds the soware
and data you will use and/or create during the course.
When you sign up for the course, you should be given a URL for your container and a unique
login and password. If you haven’t, please speak to your coordinator. The soware you will use
is WordPress and MediaWiki
Wiki
Mission Executors use the wiki to group edit your report and other documents.
A wiki is a website on which users collaboratively modify content and structure directly from
the web browser. In a typical wiki, text is written using a simplified markup language.
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Figure 5.8: Example wiki, running on MediaWiki
Wikipedia is by far the most popular wiki-based website, and is one of the most widely viewed
sites of any kind in the world, having been ranked in the top ten since 2007. There are tens
of thousands of other wikis in use, both public and private, including wikis functioning as
knowledge management resources, notetaking tools, community websites, and intranets. The
English-language Wikipedia has the largest collection of articles; as of September 2016, it had
over five million articles.
We use Mediawiki, the same soware that runs Wikipedia, to allow participants to collabora-
tively create reports and other documents.
A guide to using MediaWiki is in the appendix.
Blog
Aer your report is ready, you will use the blog to create pages and present it in a visually ap-
pealing manner.
A blog (short for ”weblog”) is a discussion or informational website consisting of posts (diary-
style updates, displayed newest-first) and pages (more permanent information).6
6Adapted from Wikipedia, July 30, 2018
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Figure 5.9: Example blog, running on WordPress
Our blogging soware is WordPress: a free and open-source content management system. It is
most associated with blogging, but supports other types of web content including more tradi-
tional mailing lists and forums, media galleries, and online stores. Used by more than 60 million
websites, including 30.6% of the top 10 million websites as of April 2018, WordPress is the most
popular website management system in the world.7. Our WordPress installation includes sev-
eral plugins to make editing easier, most notably Elementor.
A guide to using WordPress and Elementor is in the appendix.
Presentation
Each team will create a presentation to present the work they’ve done, and present to the class.
Typically, a presentation should last 5-7 minutes, plus questions and answers aerwards. Don’t
worry about getting everyone on stage to present - instead limit it to 2-3 speakers.
Since Microso PowerPoint is the industry standard (and you may not be presenting from your
own computer), we recommend creating your presentation in pptx format. Don’t use Google
Docs or other online oice suites, since connnectivity (due to VPN or lack of network) may be
an issue.
Aer each team has presented, everyone will regroup and the group will nominate a team to
create one final presentation to summarise the industry reports of all the teams.
7Adapted from Wikipedia, July 30, 2018
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Poster
Quite oen, all of the teams will come together as a group and create one or more posters that
present the work they’ve done. While other groups may use markers or a collage to create their
poster, we recommend sticking with the theme of digital publishing and creating it with so-
ware like Adobe Illustrator.
Example poster from Experience China 2018: Industry Frontiers:
Figure 5.10: Example poster
Useful Resources
We encourage participants to use Creative Commons (CC) licensed materials in their work. Cre-
ative Commons licenses let others copy, distribute, edit, remix, and build upon various works,
all within the boundaries of copyright law.8
The following websites let you search for content licensed under Creative Commons. Don’t for-
get to cite your sources and respect the license when you use these materials!
• Creative Commons Search - images, music, video
• Noun Project - symbolic icons (for example, world, people, internet, etc)
• 14 Websites To Find Free Creative Commons Music
• The Five Best Places To Find Free Creative Commons Photos
• 5 More Places to Help You Find Quality Creative Commons Images
8Creative Commons website, 31 Jul 2018
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Evaluation and Assessment
Using secure technologies like the Blockchain, XLP tracks learner activity at dierent levels,
assessing how individuals contribute to their group and how a small group contributes in turn
to larger communities. This allows individuals and teams to receive personalized feedback and
improve over time. This in turn applies to grading and certification, with both micro-credentials
and full degrees stored on the Blockchain. Access rights can be granted to other universities or
employers to show tamper-proof evidence of achievement.
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6 Remix: The XLP Online Platform
Think of the world you live in: Imagine the classroom of the future:
In a world that is becoming increasingly digital, it is essential to teach the skills required to navi-
gate through the digital environment as early as possible. A gap is opening between those who
are technologically literate and others who are yet to be comfortable with handling soware.
The ones who are on the wrong side of this gap will eventually suer detrimental implications
to their careers and lives. Such individuals will not be able to take part in collaborative work,
thereby limiting their ability to increase their knowledge. Already, individuals and institutions
lack the tools to create new digital assets or work with the existing digital information, both of
which decrease their overall potential. Clearly, students need a solution to escape this situa-
tion. Imagine a classroom of the future that is modeled aer the reality outside the classroom.
If the reality outside the classroom is one pervaded by digital tools, so should the classroom.
Remix makes sure this happens. Students will no longer study for exams but prepare for the
challenges that await them in the future. It helps them work and self-manage teams with tools
like Phabricator and Git, while allowing teachers to track student progress and individual con-
tributions (captured using a digital data processing system) towards their respective projects
using GitLab. Without such digital tools, organizational consciousness can’t be brought to hu-
man attention and organizational learning can’t happen.
Trustworthy computing technologies such as Blockchain technology are integrated into Remix.
These ensure immutability while ensuring credit is given where credit is due.
Remix Tools
The Remix platform oers a large array of powerful tools, manageable by anyone and scalable
to any size.
These tools will be an important asset for any modern educational institution for which it can
fully develop the intellectual potential of its students and sta. The platform democratizes ser-
vices that were previously limited to such an extent that only established companies were able
to utilize their full potential. These services are now combined into a single platform allowing
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Sep 5, 2018 XLP Owner’s Manual
any individual or institution to start their digital transformation. Without the need for continu-
ous online connectivity, the platform can be brought to the farthest corners of the globe, where
a new generation of individuals can start fulfilling their computational needs. In short, Remix
can bring the tools used by established soware companies into any classroom or home en-
abling anyone to take part in the future of the digital world.
Together, participants can create new data using tools like Jupyter and OpenModelica, or ana-
lyze and optimize existing information using Elasticsearch and TensorFlow. Ultimately, every
individual can create or take part in a Digital Publishing Workflow – a cycle going from Data In-
put to Data Management to Data Publishing, all from their own laptop in one single application.
This is Remix.
What is a Microservice?
The central idea behind microservices is that some types of applications become easier to
build and maintain when they are broken down into smaller, composable pieces which work
together. Each component is continuously developed and separately maintained, and the
application is then simply the sum of its constituent components. This is in contrast to a
traditional, ”monolithic” application which is all developed all in one piece.
Applications built as a set of modular components are easier to understand, easier to test, and
most importantly easier to maintain over the life of the application. It enables organizations
to achieve much higher agility and be able to vastly improve the time it takes to get working
improvements to production. This approach has proven to be superior, especially for large en-
terprise applications which are developed by teams of geographically and culturally diverse
developers.1
1https://opensource.com/resources/what-are-microservices An Introduction Microservices, Opensource.com
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Remix Microservice Overview
Figure 6.1: Remix platforms microservices
Data Input
Data Input describes the dierent ways through which data may enter the Remix platform. In
the Digital Publishing Workflow, Data Input lies between Data Publishing and Data Manage-
ment, as previously published data can act as input for Data Management.
Generally, data may enter the system from three source types or combinations of them.
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Data Creation
Remix comes with microservices from which new data can be created. For instance, OpenMod-
elica enables users to create simulations of complex systems. The data produced by these sim-
ulations can then be saved for later use. Another service, Jupyter, allows for coding, solving
equations, and showing their visualizations that can then be shared in real time among dier-
ent users. Again, all the data created can be saved for later use.
Online Data
Remix also allows users to source data from the internet such as databases, wikis, or pictures.
Again, dierent microservices are available and integrated for this purpose. Data may be
accessed directly from the internet or downloaded first (for instance, to be brought to regions
where internet access is spare or Internet is slow). Kiwix, for instance, oers the entire
Wikipedia, WikiVoyage, TED Talks, and more for free to download on their website. This data
may also be used as input for Data Creation, subsequently representing a combination of data.
Private Data
Remix enables users to use their own private data as input for Data Management and Publishing.
For this purpose, the platform comes with microservices such as Nuxeo, which is a digital asset
library already used by institutions, companies, and individuals to manage their digital assets
and NextCloud for file storage in the cloud. Hence, they can tap into their existing data and
use it as input for other microservices to create new data, again representing a combination.
Generally, such private data may belong to an individual, an institution, or a company who can
scale up their data storage as required without having to scale the other microservices thanks
to the underlying system architecture.
Data Management
The data management part of Remix utilizes four dierent tools to perform a number of tasks.
In the Digital Publishing Workflow, Data Management lies between Data Input and Data Publish-
ing. The purpose of data management is to load the given information from the dierent data
inputs, then optimize it so that it becomes searchable and produces the best results, which in
turn can be visually presented to the user. This is possible through the use of the ELK stack
from Elastic, consisting of Logstash, Elasticsearch, and Kibana, in combination with the ma-
chine learning capabilities of TensorFlow. These tools are combined to allow users to perform
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queries on wide array of data that in turn, can be optimized based on an infinite number of char-
acteristics. The following section will describe each tool and how they are an integral part of
the of the Remix framework.
Logstash: Data extraction, transformation, and loading
Remix consists of a large number of data sources that each produce a large quantity of data, in
many dierent formats. It is therefore necessary to have a tool that can extract, transform and
load the input data into the next step of the process. This is where Logstash is used. Logstash is
an open source server-side data processing pipeline based on the extract, transform, load (ETL)
process.
Each step has varying degrees of complexity, that will be explained in the following sections:
The first job carried out by Logstash is the extraction of data from the dierent defined sources.
Extraction is conceptually the simplest task of the whole process but also the most important.
Theoretically, data from multiple source systems will be collected and piped into the system
for it later to be transformed and eventually loaded into the system. Practically however, ex-
traction can easily become the most complex part of the process. The process needs to take
data from the dierent sources, each with their own data organization format and ensure that
the extraction happens correctly so that the data remains uncorrupted. This is where valida-
tion is used. The extraction process uses validation to confirm whether the data that was ex-
tracted has the correct values, in terms of what was expected. It works by setting up a certain
set of rules and patterns from which all data can be validated. The provided data must pass the
Transform Load validation steps to ensure that the subsequent steps only receive proper man-
ageable data. If the validation step fails, then the data is either fully rejected or passed back to
the source system for further analysis to identify improper records, if they exist.
The data that is extracted then moves on to the data transformation stage. The purpose of this
stage is to prepare all submitted data for loading into the end target. This is done by applying
a series of rules or functions to ensure that all business and technical needs are met. Logstash
does this by applying up to 40 dierent filters to all submitted data. When filtering is completed,
the information is transformed into a common format for easier, accelerated analysis. At the
same time, Logstash identifies named fields to build structure from previously unstructured
data. In the end of the transformation process, all data in the system will be structured and in
a common format that is easily accepted by subsequent processes.
The last part of the ETL process is the load phase. The load phase takes the submitted and trans-
formed data and loads it into the end target. There are certain requirements defined by the sys-
tem that must be upheld. This pertains to the frequency of updating extracted data and which
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existing information should be overwritten at any given point. Logstash allows the system to
load onto a number of systems, Remix does however only require that Elasticsearch receives
the data.
Elasticsearch: Search and Optimize
Search and optimize are two key attributes of any data management system. It allows a sys-
tem to filter away all the unwanted data and prioritize the results based on a number of given
attributes. Search and optimize are not functions that are limited to basic keyword searches,
but can instead be used for a wide variety of possibilities. Everything from choosing the correct
strategy in a game of chess to simulating the trajectory of a moving vehicle. In all these cases,
the function utilizes the available information from the dierent data sources in combination
with machine learning intelligence to give the desired outcome To achieve this Remix uses Elas-
ticsearch and TensorFlow. Elasticsearch is a distributed, RESTful search and analytics engine
that stores data in a searchable manner. All the data that is passed through Logstash eventually
ends up in Elasticsearch. Here it is structured and analyzed to allow users to search based on
their chosen parameters. The given parameters are in turn used to filter away all the unwanted
results. What remains is a list of results that in one way or another are linked to the original
search criteria. This list is, in turn, handed to TensorFlow.
TensorFlow is a mathematical library using deep neural networks in order to analyze data. The
system takes in the data that was selected by Elasticsearch and prioritizes/orders it according
to the pre-determined criteria. This gives the user a selected number of results that should be
suited exactly to their defined needs.
When it comes to searching and optimizing, Remix’s key dierence compared to other services is
that results are purely based on the user. If a user specifies a certain interest or academic field
that they are studying, then the optimization will be created with that parameter as a focus
point. Thus, opening up focused research where all advertising-based rankings or unwanted
results are removed.
Kibana: Data Visualization
In certain scenarios, the outcome of the data management process doesn’t come in the form of
links or lines of text. In these cases, it is oen required that the data goes through some sort of
visualization in order to turn it into something that is manageable.
This is carried out by Kibana, the last tool in the data management process. Kibana is a data
visualization plugin that works with Elasticsearch to provide visualization on top of the content
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that has been indexed. It takes all the data that the user has asked for and gives a visualization
if it is applicable. Kibana can therefore also be seen as being part of the data creation aspect of
Remix.
Data Publishing
The final aspect of any standard research project concerns the publishing of results and conclu-
sions.
For this reason, the final part of the Remix framework is data publishing. The purpose of this
step is to ensure distribution of new data to a wide audience while guaranteeing rightful credit
and ownership of published research and findings. To do this, the platform uses two main tools,
MediaWiki and Hyperledger, in combination with the machine learning capabilities of Tensor-
Flow.
MediaWiki is a digital publishing tool created by the Wikimedia Foundation. It allows informa-
tion to be published in a structured and navigation-friendly way. Remix uses MediaWiki to allow
institutions or individuals to create closed or open wiki spaces in which all their information and
research can be published. Each publisher then creates a distinct name for each new published
article or piece of information. All the information on the given wiki space is then individually
connected using the deep neural network capabilities of TensorFlow, as mentioned in the previ-
ous chapter. TensorFlow analyses each piece of information and carefully links it together with
other related information. This, in the end, produces a wiki space which is full of research arti-
cles and other information, in combination with existing Wikipedia data, that is fully connected.
Furthermore, connections and recommendations of articles can be made based on user prefer-
ences. In other words, if a user is studying biology and is doing research on the flight patterns
of butterflies, then Remix will start creating more links and finding more research articles on
that topic specifically. In that scenario, it might connect the flight patterns of butterflies to the
evolution of airplane wing structures.6
Ultimately, a person can, through Remix, have access to a deeply interconnected network of
research, published articles, and existing data from the internet.
To ensure all information in the system is untampered with and that publishers are rightfully
credited, Remix uses trustworthy computing technologies such as Hyperledger. Hyperledger is
an open-source collaborative blockchain technology that ensures transparency and immutabil-
ity of all data in the system. This, in turn, ensures that any information for which there may be a
rightful owner is credited as such. These tools open up a new dimension of the digital publish-
ing process that allows institutions and individuals to contribute their knowledge to a greater
audience.
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Groupware
Remix provides Phabricator and GitLab as a platform for participants tocollaborate. GitLab is an
open-source web-based Git-repository manager with wiki and issue-tracking features, allowing
users to upload and share code and digital assets, while ensuring no conflicts occur between
versions.
Phabricator is is a suite of web-based soware development collaboration tools, including a
code reviewer, repository browser, change monitoring tool, bug tracker and wiki. Phabricator
integrates with Git, Mercurial, and Subversion. Participants can use it for project management
and coordination within (and among) teams.
Architecture
The interconnectedness of services in Remix is made possible using the Docker platform.
Docker uses container technologies to allow microservices and other digital assets can be
run in easily-replicable sandboxes and not interfere with each other. Unlike virtual machines,
containers do not require a guest operating system which makes them more lightweight,
allowing for more or bigger applications running on a server or single computer.
With Docker container technologies, we can re-define all digital assets into three main cate-
gories: content data, soware data, and configuration data. These categories can be tagged
using a hash code (similar to Git or Blockchain labels) and can be traded by swapping out ”to-
kens” or hash IDs of the asset. This allows participants to easily install dierent soware ser-
vices and start using the asset almost instantly. The end result is that participants and instruc-
tors can better manage learning activities, and use one consistent namespace to organize all
their assets.
Figure 6.2: Architecture of Remix platform
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Hence, a multitude of containers can easily be combined in a single application. This can be
done through Docker Compose. While Docker focuses on individual containers, Docker Com-
pose engenders scripting the installation of multiple containers that work together to create
a bigger application. Microservices in Remix talk to each other to modify and move data from
its creation, to its management, and publishing. At the same time, since the microservices are
still housed in their respective containers, any service may be added or removed at any time
without damaging other containers.
Remix also enables deployment, monitoring, and scaling microservices with Kubernetes, a tool
specifically designed for this task. Microservices can then be scaled individually and indepen-
dently from each other (thanks to their containerization), specific to the needs of the user.
Matomo (formerly known as Piwik) is an open-source analytics soware package (similar to
Google Analytics) for tracking online visitors, analyzing important information, and track key
performance indicators. Remix uses this soware to track usage of the platform by participants.
Finally, Mesosphere DC/OS acts as the foundation of the system and adds a layer of abstraction
between Kubernetes and Docker and the user’s underlying OS. This operating system for dat-
acenters works specifically well with microservices and takes care of resource allocation and
makes the system fault-tolerant.
In summary, Remix is an platform that is lightweight, modular, and easy to install, use, and
scale, enabling everyone to make use of the powerful microservices included. The platform
achieves this using a three-part structure with the microservices being the highest layer of ab-
straction followed by the combination of Kubernetes and Docker and completed by the Meso-
sphere DC/OS.
Education on the Blockchain
The blockchain is a decentralized technology that acts as a digital ledger for recording transac-
tions between dierent entities, both human and machine. Originally devised for the digital
currency Bitcoin, the blockchain is now being used for many other purposes, including in ed-
ucation. Below is our guide to making education fairer, deeper, and more accessible to all by
using the blockchain.
“The blockchain is an incorruptible digital ledger of economic transactions that can be
programmed to record not just financial transactions but virtually everything of value.” -
Don & Alex Tapscott, authors Blockchain Revolution (2016)
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Historical Context
Like many phenomena, over time education has moved from a centralized cathedral model to
a more decentralized bazaar model2:
Education 1.0: Traditional Education
Figure 6.3: Education 1.0: Centralized monoliths
Traditional education consists of physical university campuses, and students attending classes
on-site. Students do coursework, lab work, theses and exams, and these are graded by pro-
fessors, usually at the end of the semester. In education 1.0, students are generally passive
consumers of education, receiving information from academic sta3:
Because traditional education is based around a physical space and a limited number of profes-
sors, students are limited by number and location, and financial and academic requirements
for entry can be very high4 5.
Because assessment is done by humans, fraud and bias can creep in from both students and fac-
ulty. Indeed, A large-scale study in Germany found that 75% of the university students admitted
that they conducted at least one of seven types of academic misconduct (such as plagiarism or
2From Open Programming to Open Learning: The Cathedral, the Bazaar, and the Open Classroom
3Higher Education 1.0 to 3.0 and Beyond, Gilly Salmon, 27 March 2017
4How much would it really cost to write o student debt?, Jack Britton, Carl Emmerson and Laura van der Erve, 14
September 2017
5Is College Really Harder to Get Into Than It Used To Be?, Jacoba Urist, The Atlantic, 4 April 2014
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falsifying data) within the previous six months.6Some examples of dishonest behavior include:
• A woman using an impostor to take a college English test7
• A Japanese medical university manipulating entrance exam scores to limit the number of
women admitted8
• Thousands of UK nationals buying fake degrees from “diploma mill” in Pakistan9
• 50,000 UK university students were caught cheating in the previous three years, amount-
ing to a so-called “plagiarism epidemic”10
Summary
In Education 1.0:
• A student browses universities within physical proximity and signs up for a course, typi-
cally for several years
• The student physically goes to classroom and sits in front of professor
• The student writes thesis and sits exam
• The professor grades the thesis and exam
• The professor awards a grade to the student
Education 2.0: MOOCs
Education 2.0 moved education online, with Massive Open Online Courses, oered by sites such
as Coursera, Udacity, and EdX. These courses are open to anyone around the world, and stu-
dents are given regular feedback on their performance via the system.
6Patrzek, J.; Sattler, S.; van Veen, F.; Grunschel, C.; Fries, S. (2014). “Investigating the eect of academic procras-
tination on the frequency and variety of academic misconduct: a panel study”. Studies in Higher Education:
1–16.
7Chinese woman admits using impostor to take US college English test, amid crackdown on fraud by foreign stu-
dents, South China Morning Post, 3 April 2018
8Japanese medical university admits to discriminating against female applicants, Science Magazine, Aug 8, 2018
9“Staggering” trade in fake degrees revealed, BBC News, 16 January 2018
10UK universities in “plagiarism epidemic” as almost 50,000 students caught cheating over last 3 years, The Inde-
pendent, 4 January 2016
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Figure 6.4: Education 2.0: Networked monoliths
Education 2.0 is the age of networked monoliths. Whereas previously universities oered
courses only to their own students, now they oer courses on MOOC platforms too. However,
these MOOC platforms are themselves centralized monoliths. Students may take courses on
one more MOOC platforms.
Typically students sign up for a MOOC with their existing digital credentials like a Facebook login
or email address. While convenient, these are not solid proof of identity in the way that a secure
digital identity (like public/private key) would be. At best, some services oer biometric identity
via webcam.11
Interaction between students (if there is any at all, which is not oen12) is via the MOOC’s fo-
rum, and is typically centred around problem-solving and support, rather than content cre-
ation, project-based learning and digital publishing. Aer the course is finished students dis-
band (again, if they ever banded together) and go their separate ways. This limits the possibility
for collaboration and groupwork.
Courses are typically assessed by algorithm [citation needed], from students answering multi-
choice questions or writing a program that generates a specific output. This limits many MOOCs
in terms of flexibility and creativity.
Summary
In Education 2.0:
11Verified Certificates: How does verification work?
12How widely used are MOOC forums? A first look, Jane Manning, 18 July 2013
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• Student signs up for a course on Coursera, EdX or another platform oering educational
courses, typically for a few weeks or months
• Student works from wherever they are in the world
• Student coursework is graded by the MOOC system and assessors working for the MOOC
• MOOC system awards grade to student
But how do we ensure the student is actually the one doing the work?
Physically decentralized but central MOOC system
The Future: Education 3.0: Education on the Chain
With Education 3.0 we can modularize, granularize, democratize and decentralize education
further:
• The line between educator and student gets blurred, as anyone can directly oer courses
or tutoring and get paid for it
• Students can learn from anywhere in the world, from a single lesson to a series of courses
• Students and educators can monetize the materials they create, instead of them languish-
ing on a hard disk
• Educators can spend less time grading and more time doing valuable tasks
• Qualifications can be verified and trusted
Figure 6.5: Education 3.0: Mass P2P learning
We do this by leveraging the power of the blockchain, specifically Ethereum.
Ethereum is a blockchain that enables anyone to create decentralized applications and smart
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contracts.13 A smart contract is a legal contract in the form a computer program stored that en-
ables secure, verified transactions between two or more entities.14 This program is encoded on
the Ethereum blockchain, and typically takes cryptocurrency as input. Parties sign the contract
using their digital identity, typically in the form of a PGP private/public key pair.
We aim to create two kinds of token to make this possible. We are still working out some details,
but for now:
• A cryptocurrency called EducationCoin, an ERC20 token. Educators can oer courses
using this token, and students can purchase courses. It can also be used to purchase
student-created digital assets ( e.g. market reports, white papers) on a decentralized mar-
ketplace.
• Integrating currency too deeply into education is ethically dicey. For interactions on a
student-student marketplace we may need a closed loop non-currency cryptotoken. For
now let’s call this EducationToken.
Choosing a Course
The blockchain allows us to decentralize the MOOC concept further and allows decentralized
marketplaces for courses, enabling content creators to oer their own curriculum, and giving
users confidence with a built-in rating system. Students from anywhere in the world can browse
this marketplace and elect to take a course by signing a smart contract.
Since anyone can be a course provider in education 3.0, the line between educators and stu-
dents blurs considerably. Anyone can oer their materials and assistance (via one-on-one or
one-to-many personalized tuition) on this platform. Participants browse the oerings, find the
course that best suits them and pay via EducationCoins. They can purchase the whole course,
just certain units, or specific guidance from the course creator.
Because there is less human eort required in assessments, smaller machine-graded courses
can easily be oered. These “micro-qualifications” cover specific niche skills or disciplines, for
example the React Javascript framework.15
Course Signup
During course signup, students read through the course #constitution, which outlines their
rights and responsibilities. This is both a human-readable document and embodied digitally
13Ethereum smart contract development: build blockchain-based decentralized applications using Solidity,
Mayukh Mukhopadhyay, 2018
14Attack of the 50 Foot Blockchain: Bitcoin, Blockchain, Ethereum & Smart Contracts, David Gerard, 2017
15A Review of Udacity’s React Nano Degree, Bilal Tahir, 18 October 2017
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in the form of a smart contract. Students sign this smart contract with their digital identity to
show they have read their rights and responsibilities during the course.
Coursework
Depending on the type of course, dierent types of coursework may be done:
Individual Learning
May consist of watching videos, answering multi-choice questions, and writing code that cre-
ates a specific output. Similar to many programming courses in MOOCs. Students can oer
support to each other via the platform’s forum and social features, and the best forum answers
get paid in EducationCoins. This incentivizes students to contribute quality answers and build
community.
Group Learning
More project-based. Students do coursework on digital publishing platforms like MediaWiki
and WordPress, which they sign into using their digital identity, ensuring any data they create
is tied to them. These services have open APIs, so their data can be extracted and stored on a
blockchain (either private or the main chain) to ensure data integrity.16 Courses can be gam-
ified with cryptocurrency tokens as incentives, and an internal marketplace can be set up for
students to trade skills and knowledge with EducationCoins.
Crowd Learning
Any student can create a portfolio on a global student expertise exchange platform (similar in
concept to Upwork) and seek out other students around the world who need their skills. This
creates a marketplace for students to share knowledge and expertise, and enables large-scale
crowd learning. This expertise can be “paid” for using EducationTokens, a non-currency cryp-
totoken.
Many students can cooperate to create a single digital asset, on which they will be jointly as-
sessed, and they can then sell this asset (or subsections of it) on a decentralized digital asset
marketplace.
16In future, students may be able to completely switch to DApps (decentralized apps) to perform their coursework,
but the apps haven’t been built yet.
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Assessment
For assessment, student-created data is gathered and stored on the blockchain to prevent tam-
pering. It is then sorted using tools like the Elastic Stack, then processed, checked for plagia-
rism, and assessed by machine learning (with tools like TensorFlow). It can then be aggregated,
ranked, and visualized for professors to perform their own assessments if required.
Students can be awarded EducationCoins for quality work.
Grading and Qualification
As part of the assessment, a student’s qualification will be signed by the institution (for example,
Tsinghua University) and stored securely on the main blockchain, allowing access by employers,
institutions and anyone else to whom the student grants access via app or other means.
By tying every step of the course to a student’s verifiable digital identity and assessing by ma-
chine instead of humans, we greatly reduce fraud, bias, and human error in the system, and can
scale education to deal with thousands of learners. Qualifications can be verified and trusted
by students, universities, and employers.
Figure 6.6: Assessing and grading students
Access to these qualifications can be encoded as a QR code which could be embedded in a
badge via the OpenBadge standard (similar to Scout badges, but digital). A set of skills can
form a portfolio accessible via the web or dedicated app. As we transition to a model of lifelong
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learning, we can foresee people earning these badges throughout their life, and perhaps pro-
fessional or job-hunting networks (like LinkedIn or Monster.com) may one day have a function
to search by badge to find the best candidates.17
Figure 6.7: Example digital badges
Monetizing Coursework
In Education 1.0, students’ output was le to languish in filing cabinets or hard disks. In Ed-
ucation 2.0, it’s stored on a hard disk or in the cloud. Even for professors, they have to pay
publishers like Elsevier to publish their content.18 In Education 3.0, we aim to flip that model
and let anyone publish and monetize their academic content.
Coursework performed by students (for example, white papers, essays, industry analysis re-
ports) can be exported and stored on the blockchain via IPFS19 then oered to buyers or li-
censees via a decentralized content marketplace (like Steemit.)
[diagram]
1. Create and export content
2. Upload content to IPFS
3. Choose license
4. Set fees
5. Publish
Buyers sign a smart contract outlining their rights to use the content (for example, they may be
free to re-use the content but not to edit it), and payment is made to the student(s) via cryp-
tocurrency. Since the marketplace is decentralized, there is no middleman to take a cut and
17These badges could potentially be regarded as non-fungible, non-tradable tokens themselves - similar to what
0xcert are doing.
18Elsevier website, 23 Aug 2018
19Interplanetary File System
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creators receive payment in full. In addition, these student-created digital assets can be broken
down into their constituent parts, so if a buyer only wants a specific diagram and not the whole
text they can just license that.
[diagram]
1. Browse content based on keyword or publication number
2. Choose how you want to use content (use full content, use partial content, pay per use,
pay per impression, flat-rate fee)
3. Sign smart contract
4. Pay content creator
5. Download content
Figure 6.8: Monetizing students’ digital assets
In group-created works, a record of who created what can be kept on the blockchain, so pay-
ment can be shared equitably between creators.
Marketplaces
We have discussed four dierent marketplaces above:
Education Market
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Creators provide courses, resources, tutoring, and expertise for learners. Learners can create
coursework using built-in digital publishing tools, and this can be assessed (at least partially)
by algorithm.
• Example products: Astronomy 101; Psychology 305;
• Target customers: Students, learners
• Target providers: Educators
Digital Asset Market
A marketplace for white papers, market reports, theses, academic papers, etc. Like a decentral-
ized Elsevier.
• Example products: White paper on social media trends in China; photographs, data, and
maps of soil erosion around London
• Target customers: Business, academia
• Target providers: Students, professors, educators
Traditional competitors would be journal companies like Elsevier, who charge both for publish-
ing and for access
Talent Market
Learners can post their profiles and qualifications here for recruiters to see
• Example “products”: Student with 4-year degree in computer science; Student with nano-
degree in writing smart contracts
• Target customers: Recruiters
• Target providers: Qualified learners
Learner Market
An internal marketplace for learners to trade expertise, knowledge, and assistance. However,
since the line between creators and learners is blurred, do we need this?
• Target customers: Learners
• Target providers: Leaners, creators
User Experience
The EducationCoin App
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Initially, the EducationCoin app will focus on providing a high-quality marketplace experience
for learners (i.e. consumers, not creators), including:
Figure 6.9: App mockups
• Sign up for account
• Purchase EducationCoins
• Browse courses
• Sign up as student for a course
• Make payment for course in EducationCoins
• Taking (simpler) courses
More complex courses (which need extensive coursework and writing) are less suitable for a
smartphone experience and can be performed on the EducationCoin web platform.
The EducationCoin Web Platform
The web platform provides a more comprehensive set of services:
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Creators can:
• Create their courses and set prices
• Upload materials for their courses
• Send alerts to students of their courses
Learners can:
• Sign up for courses
• Use hosted MediaWiki/WordPress to do more complex coursework
• Contact creators and other learners to solicit advice or cooperate together
• Set bounties for questions to be answered or expertise given
Summary
EducationCoin and EducationToken enable:
•Fairer distribution of wealth to both students and educators
•Large scale crowd-learning through a student skill marketplace
•Democratised access for educators and students around the world
•Bias-free, fraud-free assessment of all student work
•Exposure to recruiters through verified qualifications and talent marketplace
Education 1.0 Education 2.0 Education 3.0
Location Physical university Centralized online
platform
Decentralized online
platform
Cost Thousands of
dollars
Free - 100 USD(?) Set by educator
Types of
courses
In-depth,
project-based
Multi-choice skill
tests
In-depth, project-based,
and skill tests
Methodol
ogy
Top-down Top-down, some
P2P
P2P
Who profits Institutions Institutions, course
marketplaces
Educators, students
Possibil ity
for fraud
High - bias, fraud,
human error
Low Very low
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Technical Analysis
Infrastructure
Education 3.0 is primarily digital - since everything boils down to zero’s and one’s, automation
and computation can be applied to create eicient, verifiable workflows.
Soware Stack
At present all of the soware stack we have used in XLP has been traditional server-based mi-
croservices. Decentralized Apps (DApps) are still some way o when it comes to capabilities.
• Digital media creation tools like MediaWiki, WordPress, Jupyter Notebook, etc
• Tools to extract, analyse and write that data to blockchain: Logstash, Elastic Search, Ten-
sorFlow
• Tools to visualize that data for human assessment (if required): Kibana
• A front-end to tie all of this together
Smart Contracts in Depth
We use smart contracts throughout the whole process outlined above:
• Educators putting their courses on the course marketplace
• Students electing to take courses
• Educators assigning grades to students
• Licensees buying access to student-created data
In addition, we use digital signatures to prove ownership and work on certain assets:
• Courses created by educators
• Coursework done by students
• Qualifications, signed by both student and educator
Signing a Smart Contract
The first contract signed by students is the constitution, which outlines their rights and respon-
sibilities. To do this they need to set up a digital identity, typically a public/private key pair using
the PGP standard:
OpenPGP is the most widely used encryption standard in the world. It is based on PGP (Pretty
Good Privacy) as originally developed by Phil Zimmermann. The OpenPGP protocol defines
standard formats for encrypted messages, signatures, and certificates for exchanging public
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keys. PGP & GPG is an easy-to read, informal tutorial for implementing electronic privacy on the
cheap using the standard tools of the email privacy field - commercial PGP and non-commercial
GnuPG (GPG)20
PGP uses two keys for encryption - a private key to encrypt messages, and a public key to de-
crypt them. Bruce Schneier writes21:
“Putting mail in the mailbox is analogous to encrypting with the public key; anyone can do
it. Just open the slot and drop it in. Getting mail out of a mailbox is analogous to decrypt-
ing with the private key. Generally it’s hard; you need welding torches. However, if you
have the secret (the physical key to the mailbox), it’s easy to get mail out of a mailbox.”
A file encrypted with PGP typically looks like this:
-----BEGIN PGP MESSAGE-----
Version:GnuPG v1.4.0 (FreeBSD)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===zr4l
-----END PGP MESSAGE-----
In the context of email:
• Alice and Bob agree on a public key algorithm.
• Bob sends Alice his public key.
• Alice encrypts her message with Bob’s public key and sends it to Bob.
• Bob decrypts Alice’s message with his private key.
Writing a Smart Contract
20PGP & GPG: Email for the Practical Paranoid, Michael W Lucas, 2006
21Applied Cryptography: Protocols, Algorithms and Source Code in C, Bruce Schneier, 2017
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Smart Contracts are oen written in the Solidity programming language, although LLL and Ser-
pent are also available. They are then run on the Ethereum Virtual Machine, which implements
a full stack Turing-complete computer on the blockchain.
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7 XLP Philosophy
Micro, Meso, Macro
The XLP curriculum has three tiers:
Macroscopic in Nature
Globally search and compile relevant information, and creatively tell a compelling story using
trustworthy data sources and presentation techniques.
Mesoscopic in Sorting Order
Apply optimization technologies and understand the principles of optimal limits, so that partic-
ipants and teams can apply optimization to all their learning activities.
Microscopic in Contexts
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Guide participants to be acquainted with domain-specific vocabulary and rules, so that they
can leverage existing bodies of knowledge in an organized manner.
The three categories of courses are built on top of our Remix platform, which provides a foun-
dation of industry-standard tools to help XLP participants achieve the goals of their curriculum.
The MD’s and ME’s learn individually and collectively. The community of sponsors, MD’s, and
ME’s is a microcosm of a larger context – for example, a university, a society, or a nation. XLP
challenges every learning team to be a focused, goal-oriented microscopic society in a digital
publishing/learning workflow environment.
Theory U
Theory U is a change management method created by Otto Scharmer, who has worked with
Tsinghua University and Xu Lili (Theory U’s China Coordinator) to refine XLP. The principles of
Theory U are suggested to help political leaders, civil servants, and managers break through
past unproductive patterns of behavior that prevent them from empathizing with their clients’
perspectives and oen lock them into ineective patterns of decision making.
Several of XLP’s steps correlate with Theory U:
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Figure 7.1: Theory U curve
By following these principles, we can achieve several beneficial outcomes:
Early Success
Provides resources and knowledge that enables participants to kick o their learning journey
with excitement.
Fail Early, Fail Safe
Ensures participant learning assignments are challenging enough, so they can observe their
shortcomings and correct their course of actions in the early stage of the mission.
Convergence
Guide participants to re-combine their team structures to create a synergistic product/service
with other teams.
Demonstration
Every learning program should end with a ceremonial event that allows participants to summa-
rize their learning experience and present it to other people who may be future XLP participants.
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Lessig’s Four Forces
Lawrence Lessig’s Code Version 2.0 states that a number of forces regulate the behavior of indi-
viduals in a society or community:
Figure 7.2: Lawrence Lessig’s Four Forces
Law: The Rules a Community Recognizes
• Imposes constraints on the behavior of members by explicitly threatening punishment or
sanctions that the community as an entity will enforce.
Social Norms: How a Community Expects You to Behave
• Similar to the law in that norms constrain behavior of community members
• Unlike the law, community members impose social norms on each other informally
• Whereas the law, and (prospective) punishment for breaking the law, is explicit, social
norms are understood by all, or most, of the community without being explicitly stated
or mandated.
Market: How Much Do You Pay?
• Enables buyers and sellers of goods, services, information, labor, and capital to exchange.
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• The market forces of supply and demand determine the equilibrium level of prices in each
respect market.
• Implicitly regulates behaviour of community members, for prices can fluctuate rapidly
dependent on consistency and reputation.
Architecture: The Way the World Is
”The way the world is, or the ways specific aspects of it are.”
• The way a product (not a service) has been designed, created, manufactured, or built.
• Regulates community members by imposing physical or technical/technological
constraints.
• Special due to ”agency” - does not require direct human intervention to operate
(whereas other forces require police force, community members, merchants, etc), so it is
”self-executing.”
While each of these regulating forces is separate and distinct, all four influence each other as
they regulate the behavior of community members.
Example: Smoking
In Code version 2.0, Lessig uses the regulation of smoking to illustrate the operation and inter-
dependence of these four forces. If you want to smoke, Lessig asks, what constraints do you
face?
Law
Federal, state, and local laws laws regulate:
• Minimum age and ID requirements
• Where you are permitted to smoke
• Tax on the purchase of cigarettes (aiming to reduce smoking incidence)
Social Norms
Social norms can constrain behavior even more than laws:
• Smoking in the house of a non-smoking friend
• Smoking near children in restaurants
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Market
• The higher the price of cigarettes, the more financially constrained you are by smoking
• Higher insurance premiums for smokers reduces the desire to smoke
Architecture
The way cigarettes are designed and manufactured.:
• Filterless cigarettes are more dangerous, so more pressure to reduce smoking. Ultralights
may tempt you to smoke more (thus costing more in terms of money and social norms)
How do the Four Forces Interact?
The four forces are interdependent; they interact, and influence each other as they regulate the
behavior of individuals in the community. A change in one may influence another. Using the
example of smoking:
Social norms → Market
Figure 7.3: How social norms aect the market for cigarettes
Market → Law/Social norms
Figure 7.4: How the market and laws aect social norms around cigarettes
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How do the Four Forces Relate to XLP?
Since XLP is a methodology for crowd-learning, these four forces also (by definition) regulate
the behavior of individuals in each micro-learning community, and ultimately increasingly large
macro learning communities.
Law
The law is constituted by XLP’s digital recording infrastructure (legal evidence collection mech-
anism), which allows the filing of complaints, patent filing, and law enforcement.
Social Norms
One of the most important forces shaping social norms in XLP is the idea that all learning out-
comes must be demonstrable. One of the most important end products is publishing the crowd-
learning results online using a digital publishing system.
Market
XLP’s transaction validation system records and validates transactions executed in the crowd-
learning environment.
Architecture
XLP’s technology architecture is one of the most important forces that regulate the behavior of
individuals in our crowd-learning environment. Architecture is the only one of the four forces
that, once created or enabled, does not require direct human intervention to operate. It func-
tions alone and directly; that is, it is ”self-executing.”
The architecture in XLP’s crowd-learning environment is the Remix Platform, a combination of
hardware and soware. A later section in this manual will describe it in detail.
The Four Forces, XLP, and The Real World
A noteworthy feature of XLP is how each force within a specific micro- or macro-learning commu-
nity interacts with the same force in the ”real world.” For example, much of XLP’s legal frame-
work interacts with that of the real world: It is diicult to divorce the two, given that the real
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world’s legal frameworks and mechanisms have evolved over centuries, and to regulate the in-
dividuals in a community. Patents filed in the XLP crowd-learning environment may very well
also be filed in the real world, for example. If XLP is internationally and legally recognised, then
this process of duplication may become automatic.
Similarly, given that one of the most important end products of an XLP activity is publishing the
crowd-learning results, it is natural that these results are published via a real-world means like
social media, other online media, or traditional media that is accepted by social norms.
In the market, a product or service might attract investment in the XLP environment – and might
attract real-world investment too. Intellectual property in XLP’s environment might also be
bought and sold in the real world.
Finally, XLP’s architecture has its roots in the public commons of universities, and specifically
physical campuses and other resources that enable the crowd-learning environment to emulate
the the real world to a large degree. This is an important factor in XLP enabling learning on a
large and public scale.
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8 Technical Analysis
Containerization
Containers are the foundation of XLP, the Remix platform, and XLP’s Digital Publishing Work-
flow:
• XLP creates replicable, containerized learning missions, which can then be deployed and
scaled up anywhere in the world
• Remix provides the infrastructure to perform this digitally - i.e. Docker and Kubernetes
• participants create containerized digital assets using XLP’s Digital Publishing Workflow,
as a record and proof of the work they have performed in the mission.
Docker Containers
Docker is an operating system abstraction layer, providing an abstraction boundary which man-
ages collective boundaries and experience for its users. A Docker container ’contains’:
• An operating system (oen Linux/Windows/MacOS)
• The programs you want to run on the operating system (for example, WordPress/Medi-
awiki)
• The application and configuration data for the program (for example, WordPress media
assets, WordPress configuration details)
• The data for the program (if WordPress, a database of MySql/Mariadb)
This container and its data(volume) can be save/exported from the Docker filesystem and be
loaded, for easy deployment anywhere.
Like an operating system, Docker:
• Authenticates the container via its hash
• Schedules priorities, for example what resources the container has access to
• Manages input and output, for example how many of the host machine’s resources it may
use.
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What do We Run in Docker?
Figure 8.1: Remix’s Docker infrastructure
Namespaces
Computers operate on levels of abstraction. Otherwise we would be dealing directly with ones
and zero’s. A common kind of abstraction is a namespace, which organizes and names objects.
Some examples include:
• Memory registers: Each register has it’s own unique address
• Filenames: Each file on a system has it’s own unique path and filename combination
• URLs: Each website is reached via dierent URL
Containers also have their own unique namespace, namely their 256-bit hash. An example hash
(shown in hexadecimal format) would be:
7f83b1657ff1fc53b92dc18148a1d65dfc2d4b1fa3d677284addd200126d9069
This hash acts as a digital fingerprint, and is highly secure since there are 25632 combinations
which would take 3x1051 years to crack if using fiy supercomputers.
Verification and Security
With filenames or URLs, you have no guarantee you’ll actually get what you think you’ll get.
Today *google.com* might take you to a search engine. Tomorrow Google may get hacked and
you could end up on a site that *looks* like Google but steals your login credentials.
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Containers are dierent. Since Docker hashes are unique and unforgeable, we can verify a
Docker container and add it to a database of other verified containers. When you’re then de-
ploying that container, you can check that hash matches the hash in our database, thus ensur-
ing the container will run consistently. This can be thought of as similar to the police comparing
fingerprints of known criminals with fingerprints at a crime scene.
Secure Concurrent Editing
A potential barrier with generating big data simultaneously across a distributed network is the
Byzantine Generals Problem5: Reliable computer systems must handle malfunctioning compo-
nents that give conflicting information to dierent parts of the system.
In an abstract sense, this can be expressed as a group of generals camped with their troops
around an enemy city. They can only communicate by messenger to agree on a common battle
plan. However, one or more of them may be traitors who will try to confuse the others. So, how
can we find an algorithm to ensure that the loyal generals will reach agreement?
It is shown that, using only oral messages, this problem is solvable if and only if more than
two-thirds of the generals are loyal; so a single traitor can confound two loyal generals. With
unforgeable written messages, the problem is solvable for any number of generals and possible
traitors.
In XLP, the problem can be seen as failing to process large amounts of data at the same time.
The solution is a distributed repository (like Git) allowing all participants to transparently see
what content others contribute. This increases everyone’s confidence in the trustworthiness of
their fellow participants, thus making them more likely to contribute and share content, and
that this content will be compiled into a consistent result.
XLP uses existing computing science techniques that improve the ability to process the
concurrent publishing of massive amounts of distributed intellectual content. Bitcoin also
ensures Byzantine fault tolerance – in other words, solves the Byzantine Generals Problem – by
incorporating a distributed database that lets any participant view the entire history of trans-
action records. This enables the processing and compiling of massive amounts of intellectual
resources on an Internet scale. Open-source version control soware, like Git, Concurrent Ver-
sions System (CVS), and Apache Subversion (SVN), also enable sharing of human-contributed
content – be it source code, novels, textual content, movies, or photographs – and enable the
processing and compiling of data on a massive scale.
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Decentralization
By using computer-generated smart contracts stored on technologies similar to Blockchain, or-
ganizations that practice XLP can run as a decentralized autonomous organization (DAO). This
means that participant performance can be assessed algorithmically and stored securely on
their lifelong digital learning profile. Using Blockchain ensures XLP abides by the principles of
Trustworthy Computing, giving participants, organizations, and employers faith in the quality
of work.
Tokenization
Tokenization goes hand in hand with the theory of containerization. Any kind of digital infor-
mation can be seen as a data container, and every container can be broken down into smaller
containers. For example, this XLP manual is a container, which contains the necessary informa-
tion for executing XLP. The XLP manual container consists of sub-containers - one of them is
this section.
Modern Blockchain (Distributed Ledger) technology can be used as a common representation
of any type of container. A token is simply all bundled information for uniquely representing a
container on a distributed ledger. This token uniquely identifies a distinct container and guar-
antees its authenticity. tokens can be used as a proof of authorship, as well as ownership and
hence used for trading and sharing containers.
This section will present the most important history and technical concepts which enable tok-
enization. Then, distributed ledger technology is discussed. Lastly, the necessary architecture
for the XLP-Token-System (XTS) is derived and presented.
Distributed Ledger Technology (Blockchain)
In 2009, Satoshi Nakamoto the paper ”Bitcoin: A Peer-to-Peer Electronic Cash System” 1. In his
work he describes a global decentralized system for exchanging tokens. The inherent tokens
digitally represent a monetary value and are labeled as Bitcoins.
This system, called a Blockchain or Distributed Ledger (DL) can be created by combining avail-
able technologies and algorithms such as:
• Public-private-key cryptography
1Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System. [online] Available at: https://bitcoin.org/
bitcoin.pdf [Accessed 7 May 2017].
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• Digital signatures
• Digital timestamps
• Peer-to-peer protocols
• Cryptographic hashes
• Merkle trees
Additionally, a DL system needs a consensus algorithm for reaching agreement between the
distributed participants. Such a consensus algorithm ensures that there is a global world state
of values, on which the majority of participants agree. In Bitcoin, this system is called Proof-of-
Work and relies on participants using their computing power for solving a randomized ”riddle”.
Four Forces
XLP activities are executed in a highly technical context, which takes into account the Four
Forces discussed previously. These forces require:
Legal Mechanisms
A dispute resolution process and patent filing process.
Market Mechanisms
Exchange of goods, services, information, and capital, and establishing prices for these through
supply/demand dynamics. Technical Architecture
Sophisticated technological infrastructure that allows transdisciplinary learning across space
and time.
Social Norms
Agreed-upon standards for what constitutes acceptable behavior – covered in orientation and
general university practices.
Participants need access to technology that enables the four forces to regulate behavior, and,
just as importantly, must learn its use before the XLP activity.
Through their digital identity, participants must be trained to (among other things):
• File patents
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• File complaints and sue other entities
• Defend their legal rights
• Buy and sell intellectual property and financial and other commodities
• Publish the products of their learning and their learning outcomes via social (or other)
media
The four forces are all present to an extent in traditional modes of learning, but their respective
and collective functions in crowd-learning is relatively minimal, and not systematic. A major
reason is the lack of a common digital infrastructure to track market transactions, patent ap-
plications, and refutation processes; nor has social media been systematically used to identify
and measure cultural norms in a classroom and how they relate to a specific learning scenario.
Therefore, XLP’s activity context is highly technical, and requires big data and other sophisti-
cated technologies and principles to collect, store, process, and analyze data.
From a technical perspective, XLP is:
• A crowd-learning distributed operating system that collects, stores, processes, and ana-
lyzes data and generates condensed and refined content with machine and human help.
• A learning ecology that combines organic entities with digital equipment and processes.
XLP leverages open-source technologies, distributed version control systems, and cryp-
tocurrencies to track learners’ individual and collective contributions to the collabora-
tive, collective learning process and learning outcomes.
Computer cycles for collecting, storing, processing, and analyzing data are clearly dierent
from human cycles. Thus enabling many people to simultaneously revise content, for example,
requires sophisticated engineering management practices and workflow management tech-
niques, which we generally don’t find in traditional educational settings. However, this tech-
nology is becoming increasingly mature and is being leveraged by XLP to become a distributed
crowdlearning operating system that provides a learning context – both for individuals and for
the crowd – that is very dierent from that of a traditional educational setting.
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9 Glossary
• Blockchain: Digital ledger in which transactions made in bitcoin or another cryptocur-
rency are recorded chronologically and publicly
• Campus, Physical: The physical elements of a campus, e.g. people, buildings, land, equip-
ment
• Campus, Virtual: Non-tangible aspects of a campus, e.g. distributed learning workflow
design team, cloud services and intellectual property, etc
• CCC: See Cognitive Construction Chart
• Cognitive Construction Chart: Improved, interactive version of logic model
• Container: Operating-system-level virtualization, also known as containerization, refers
to an operating system feature in which the kernel allows the existence of multiple iso-
lated user-space instances
• Containerized Digital Asset: Content data, soware data, or configuration data stored in
a Docker (or other) container
• DC/OS: Open-source operating system and distributed system
• Design Contract: One page document to ensure participants are cognizant of their own
actions. Covers context, inputs, activities, and outcomes.
• Digital Publishing Workflow: Cycle going from Data Input to Data Management to Data
Publishing
• Distributed Autonomous Organization: Organization that is run through rules encoded as
computer programs called smart contracts
• Docker: Computer program that performs operating-system-level virtualization also
known as containerization
• Elasticsearch: search engine that provides a distributed, multitenant-capable full-text
search engine with a web interface
• Fab Lab: small-scale workshop oering (personal) digital fabrication, typically equipped
with an array of flexible computer-controlled tools that cover several dierent length
scales and various materials, with the aim to make ”almost anything”. Similar to
hackerspace
• Four Forces: Lawrence Lessig’s four forces that constrain our actions: the law, social
norms, the market, and architecture.
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• Free Soware: See open source
• Git: Version control system for tracking changes in computer files and coordinating work
on those files among multiple people
• Github: The most popular web-based Git repository manager.
• GitLab: Open-source, user-hostable web-based Git repository manager
• GNU/Linux: Family of free and open-source soware operating systems built around the
Linux kernel. Typically packaged in a form known as a Linux distribution for both desktop
and server use.
• Hackerspace: A place in which people with an interest in computing or technology can
gather to work on projects while sharing ideas, equipment, and knowledge. Similar to
Fab Lab
• Hyperledger: Umbrella project of open source blockchains and related tools to support
the collaborative development of blockchain-based distributed ledgers.
• Jenkins: Automation server that helps to automate the non-human part of the soware
development process, with continuous integration and facilitating technical aspects of
continuous delivery.
• Jupyter Notebook: open-source web application that allows you to create and share doc-
uments that contain live code, equations, visualizations and narrative text. Uses include:
data cleaning and transformation, numerical simulation, statistical modeling, data visu-
alization, machine learning, and much more.
• Kiwix: Open-source oline wiki browser
• Kubernetes: Open-source container-orchestration system for automating deployment,
scaling and management of containerized applications
• Ledger: Used in blockchain. A database held and updated independently by each partic-
ipant (or node) in a large network
• Linux: See GNU/Linux
• Logic Model: One-page, seven item summary of project’s context, goals, eects, outputs,
processes
• Macroscopic: Category of XLP courses that lead participants to investigate contextual in-
formation of a system. Namely historical development trajectory of technologies, people
and relevant institutions
• Makerspace: A place in which people with shared interests, especially in computing or
technology, can gather to work on projects while sharing ideas, equipment, and knowl-
edge. Similar to hackerspace or Fab Lab, but oen more focus on education
• Matomo: A web analytics application
• Mediawiki: Open-source wiki soware used by Wikipedia
• Mesoscopic: Category of XLP courses that focuses on combinatorial nature macroscopic
opportunities and microscopic technical resources. Otherwise known as System Design
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in Computational Thinking
• Mesosphere: Mesosphere DC/OS is an enterprise grade datacenter-scale operating sys-
tem, providing a single platform for running containers
• Microscopic: Category of XLP courses that focuses on technical details of particular do-
main (e.g. quantum physics, biology, civil construction). Some subject content that re-
lates to highly-specialized fields
• Microservice: Soware development technique that structures an application as a collec-
tion of loosely coupled services. In a microservices architecture, services are fine-grained
and the protocols are lightweight
• Open Source: Soware for which the original source code is made freely available and
may be redistributed and modified.
• Phabricator: Suite of web-based soware development collaboration tools, including the
Dierential code review tool, the Diusion repository browser, the Herald change moni-
toring tool, the Maniphest bug tracker and the Phriction wiki.
• Piwik: A web analytics application (now renamed Matomo)
• Remix: XLP’s online platform of tools for participants
• Smart Contract: A computer protocol intended to digitally facilitate, verify, or enforce the
negotiation or performance of a contract. Smart contracts allow the performance of cred-
ible transactions without third parties.
• Test Driven Design/Development: Soware development process that relies on the repe-
tition of a very short development cycle
• Trustworthy Computing: Broad term that refers to technologies and proposals for resolv-
ing computer security problems through hardware enhancements and associated so-
ware modifications.
• U Theory: Change management method targeting leadership as process of inner knowing
and social innovation developed by Otto Scharmer
• WordPress: World’s most popular open-source content management system based on
PHP and MySQL
• XLP: Extreme Learning Process, a methodology that enables communities of learners to
design and conduct collaborative learning activities
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10 Appendices
Constitution
Preface: A New Kind of Constitution
Typically, constitutions are decomposed into the following mutually exclusive elements:1
1. Membership
2. Purpose
3. Responsibilities
4. Rights
5. How to change or dissolve the constitution
The subsequent shape of the constitution will be outlined by the specifics of the boundaries of
the above elements. Take the US constitution. The above elements are set as:
1. US Citizens, and eligibility for membership of Congress
2. To delineate the national frame of government
3. Of the Congress, Vice-President and President
4. Seen in a separate document, the US Bill of Rights, and in the Amendments to the Consti-
tution
5. Proposed by Congress and ratified by the unanimous vote of all thirteen state legislatures
For a dierent purpose, for instance, defining the practices of a firm, the constitution may have
the following boundaries of the above elements:
1. All full and part-time employees of the firm
2. To clearly define and govern the workflow, rights and responsibilities of all members
within the firm, serving as a useful reference point in the case of any disputes
3. To be punctual, treat others with respect, follow the order of command, and complete
allocated work
1Note that this list is not collectively exhaustive. The specific articles that are included within a constitution vary
depending on its purpose. A constitution for a country is very dierent to a constitution of a firm, which is very
dierent to a constitution of XLP.
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4. Equal opportunities; rights of life, liberty and property; freedom from bullying or physical
intimidation
5. A supermajority (of two-thirds of the total membership of the firm) at any meeting where
90% of total membership of the firm is physically present
The boundaries set by the XLP constitution, however, are of a dierent sort entirely. Let this be
defined by the following boundaries:
1. Accounts: any member who holds the correct login credentials
2. To clearly articulate the rights, privileges and responsibilities of all accounts in the XLP.
Useful to define the boundaries of practice, and to easily resolve any potential disputes
3. To be a fully-functional and productive member of the XLP and the Digital Publishing
Workflow, rather as a Challenge Designer, Mission Executor, or both
4. Of life, liberty and property of all accounts of the XLP; equal opportunities; freedom from
intimidation, bullying, or harassment of any kind
5. A supermajority of 80% of all accounts where at any gathering where at least 75% of the
total membership is virtually present
Where these examples dier is in the boundaries. Although membership is explicitly defined
and referred to only in one section, all five sections are in relation to an agent of some kind. The
first two are in relation to human beings, the third is in relation to accounts.
An account, as defined above, is a digital entity. This digital entity can belong to a human (such
as human’s banking account) or a machine. What this constitution sets to clearly articulate is
that the boundaries of membership lie not at the individual human but at the individual ac-
count. Since accounts can belong to both humans and machines, this constitution is unique in
its kind in two distinct ways:
1. It provides rights, privileges and responsibilities to machines
2. It treats machines and humans on an equal footing
This constitution makes no claim on the relative consciousness of machines or any non-human
entity, it merely permits for its possibility. By treating all accounts as homogenous and identi-
cal, it gives all accounts a unique identity that is on equal relation to all other accounts. This
process also allows for complete anonymity. By proving all accounts with the same rights, there
exists no agent who can decipher whether an account belongs to a human or machine at first
glance. This constitution, therefore, may go some way to passing the Turing Test. There will ex-
ist no unique feature belonging to any account that makes it below or above this constitution.
This constitution abides by the rule of law:
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“[W]ith us no man is above the law [and] every man, whatever be his rank or condition, is
subject to the ordinary law of the realm and amenable to the jurisdiction of the ordinary
tribunals.” Dicey, A.V., 1982 [1885], Introduction to the Study of the Law of the Constitution,
London: McMillan and Co.
This constitution, therefore, sets out the rights of accounts explicitly. It sets out the relations
between accounts, the privileges and responsibilities of accounts with other accounts, what
they owe for each other, and what they are guaranteed against each other. Whether a right of
a human or machine account is irrelevant in determining the unlawfulness of an act, what is
significant is that it was the jeopardy of the right in question was in relation to an account.
This constitution will be supplemented by a smart contract. The constitution provides the
framework, whereas the smart contract handles the specifics. The constitution is the overar-
ching set of rules, obligations, privileges and rights for the membership of accounts; the smart
contract is one defined and created by the parties involved in a particular digital publishing
workflow. That is, every account is to be governed by both this overarching constitution, and a
smart contract which defines the specifics of one’s involvement in the XLP.
Figure 10.1: Constitution to smart contract
This constitution sets out the relations within and between teams. Each team comprises of Chal-
lenge Designers and Mission Executers attempting to carry out their own publication within the
digital publishing workflow. In addition to each member’s role as a Challenge Designer or Exe-
cuter, each member will have a role in the team. These roles are Oicer (president), Treasurer
(chancellor), Secretary (administrator) and Contributor (Team member). Between teams, there
is a continuous red thread, representing the continuous communication and interconnected-
ness between Teams. Throughout, each team’s Oicer, Treasurers, and Secretaries will com-
municate to compare progress and ensure the smooth running of the XLP. Challenge Designers
and Mission Executers, moreover, will regularly communicate for the purposes of collaboration,
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comparisons of publications, and to provide help and feedback to others.
Figure 10.2: XLP team structure
This Constitution, moreover, is intended to be:
1. A specific constitution for the XLP
2. A meta constitution, providing a template for all societies and organisations worldwide
This constitution is worded such that any society or organisation will be able to apply this con-
stitution to their own structure simply, by replacing a few specific words and phrases in the
constitution. This constitution therefore is both specific and generic, and easily scalable.
Oicer Meetings (OMs), for instance, is a characteristic specific to the XLP, but can be gener-
alised to any organisation. There will be meetings held by Oicers (Smart Contract leaders) at
least once per month. They will have a quorum, a minimum attendance for the meeting to pro-
ceed. Every Oicer must (virtually) attend a minimum of 10 meetings per year in order to stay in
the position. This will be where all the Oicers will discuss any important changes to individual
teams and to the XLP as a whole, and welcome new Oicers. This will also be the case where
appeals can be formally discussed, debated and voted upon. This concept of a general meet-
ing of team leaders can be applied to any organisation with small teams, the only re-wording
required is the replacement of XLP with company-specific jargon.
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Figure 10.3: Oicer meeting structure
The Oicer of the team will be the one who creates the mission. She or he then edits the Smart
Contract template which will govern the specific responsibilities of every other member in the
team. Each member must digitally sign their smart contract with biometric authentication in or-
der to become members of this team. Once signed, any member of the team may self-nominate
to become Secretary or Treasury. By process of a Single Transferable Vote secret ballot across
the entire team, the Treasurer and Secretary will be elected.
The constitution, therefore, is the foundation of the XLP. It is over and governed by the consti-
tution that the Oicer writes the smart contract, and it is over both the constitution and the
specific smart contract that designers and executers create and complete the mission. The con-
stitution serves to be an overarching framework governing all eventualities and processes for
all members of the XLP. Should any equivocation arise or should alteration or dissolve of the
constitution prove necessary, the constitution outlines the mandatory steps for resolution. The
constitution is self-contained, and together with the smart contract, each member will have a
complete specification of all assignments, responsibilities, rights, and much more.
Figure 3: Smart Contract Process
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Figure 10.4: How XLP works
Figure 4: How the XLP works
The Constitution of The XLP
Last Revised: 28th August 2018
Article I – Objective
The Objective of the Extreme Learning Process, henceforth XLP, is to catalyse learning processes
by facilitating digital crowd-learning activities.
Article II – Purpose and aims
The XLP exists and aims to:
1. Measure and improve organisational learning
2. Implement Logic models at and within each stage of the learning process
3. Recursively adapt and improve the XLP through adjustment and review
4. Expand the boundaries of coverage to the geographical and technological frontiers of
learning
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Article III – The Constitution
This document serves as the constitution of the XLP. This Constitution is subject for review not
less than quinquennially. This constitution abides by the rule of law. All previous constitutions
are hereby revoked.
Article IV – Smart Contracts
1. In addition to this constitution, all team members shall be governed by a team smart con-
tract, and all Oicers shall be governed by an additional Oicer smart contract
2. Using a generic template, each Oicer, defined in Article VI, shall write the specifics of a
smart contract, to be agreed on by consensus with the other team members
3. The purpose of the team smart contract is to operate as a decentralised permission
ledger, whereby each member is given a public and private key pair in order to allow
function without an intermediary
4. To be a member of the team, a member must digitally sign their team smart contract with
biometric authentication
5. The Treasurer and Secretary will then be chosen by a Single Transferable Vote secret bal-
lot of all self-nominated members
6. Blockchain technologies shall be used to codify, automate, assign, and evaluate the spe-
cific privileges and responsibilities of each member within each contract. The operation
of smart contracts will therefore function as a decentralised autonomous organisation
7. Once codified and agreed upon, a team smart contract becomes autonomous, and can
only be amended by a majority of the team which includes the Oicer
8. The Oicer smart contract shall be written collectively by all Oicers and to be binding it
requires majority approval
9. Votes on the Oicer smart contract and its updates shall be by Oicers only
10. Unless specified otherwise, all votes on the contents, amendment, dissolution or other-
wise of a team smart contract shall be in proportion to a member’s ownership of the mis-
sion, and all votes on the Oicer smart contract shall be in proportion to the size of an
Oicer’s team
11. Once codified and agreed upon, the Oicer smart contract becomes autonomous, and
can only be amended by a majority of Oicers in any Oicer Meeting
12. All smart contracts operate in addition to, as opposed to in replacement of, this constitu-
tion; no smart contract may infringe on any liberty or responsibility laid out in this consti-
tution
13. This constitution shall always be consulted before any other document, and is of
paramount importance
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Article V – Membership
1. Membership of the XLP belongs to any agent (virtual or physical) who possesses the cor-
rect account credentials, verifiable by biometric identification
2. Membership belongs to accounts and only accounts of the XLP. Each account shall have
a unique character string in hash. This is the membership number of each account, and
cannot be replicated
3. If account details are somehow stolen, any subsequent transactions immediately become
null and void. A member shall give immediate public notice upon realising their account
interference
4. Membership has an identical lifespan to its associated account. An account expires aer
30 consecutive days without being governed by a smart contract. For Oicers this expiry
is aer 90 consecutive days
5. Members shall have the right to terminate their membership at any time, by publicly
declaring their intention so to do. Unless there is digital consent of at least three Oicers,
the smart contract will remain valid until its oicial expiry
6. Any individual can become a member of the XLP through oicial recognition of any XLP-
partner university, or by oicial appointment in an Oicer Meeting
7. Membership becomes oicial only through a digital signature below a most updated copy
of this constitution
Article VI – Roles
Every member of the XLP has two roles. Firstly, all members are either a Challenge Designer or
a Mission Executer; the responsibilities for both are consistent with the overall objective of the
XLP:
1. Challenge Designer: Members who design and test learning missions in accordance with
the goals of sponsors, tailored for Mission Executers based on the available resources and
requirements
2. Mission Executer: Members who participate in the missions designed by Challenge De-
signers, continuously learning to execute at a high level of complexity or speed, and guid-
ing others to perform each mission
In addition, each member has one of the following additional roles within each team:
1. Oicer: The leader and representative of the team in all communication
2. Treasurer: The operator of the team’s budget and finances
3. Secretary: The organiser of the team’s administration
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4. Contributor: Any and all members of the team who do not belong to any of the above
three categories
Article VII – Responsibilities
In addition to the responsibilities laid out in the relevant Smart Contact for a member’s team,
each member’s roles include generic responsibilities laid out in this constitution. In every in-
stance, the responsibilities laid out in this constitution are paramount. The responsibilities are
the following:
Challenge Designer:
1. To collectively design a challenge a learning opportunity that facilitates learning by repli-
cation
2. To begin by writing a logic model for the entire course
3. To follow a customised logic model for the design of the challenge specification
4. To create a mission that is challenging but rewardable for the Mission Executers
5. To provide regular updates and feedback of and to the progress of Mission Executers
6. To communicate with Challenge Designers across teams for mutual inspiration and ad-
vice
7. To follow instruction from the Oicer on designing the mission
8. To transfer the challenge to Mission Executers upon completion, continuously updating
the mission with fixes and feature upgrades
9. To conduct a review with Mission Executers at the end of the course, evaluating the course
eectiveness and opportunities for learning development
Mission Executer:
1. To follow the mission as set out by the Challenge Designers
2. To work collaboratively with other Mission Executers to follow the mission
3. To communicate with Mission Executers across teams for mutual inspiration and advice
4. To provide feedback to Challenge Designers on the quality and eectiveness of the mis-
sion
5. To work with the aim of eventually becoming a Challenge Designer
6. To follow instruction from the Oicer on best practices for completing the mission
7. To conduct a review with Challenge Designers at the end of the course, evaluating the
course eectiveness and opportunities for learning development
Oicer:
1. To lead the team and oversee all team work
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2. To begin by editing the Smart Contract template for the team. This sets out the specific
responsibilities of each team member
3. To chair fortnightly team meetings. These meetings allow all members of the team to
update every other team member on their progress on either the design or execution of
the mission, and allow the Oicer to update the team with new news or instruction
4. To virtually attend Oicer Meetings (OMs), as outlined in Article XI
5. To represent all members of the team in the case of any disputes
6. To implement and enforce the rules of the constitution and smart contract within the
team
7. To provide the Secretary with administrative tasks
8. To meet with the Treasurer to be updated on the team’s finances
Treasurer:
1. To oversee all spending and budget commitments by the team
2. To apply for funding to finance the spending of the team
3. To not overspend the finances given
4. To apply for loans, where necessary, whenever the budget is not balanced
5. To frequently meet with Treasurers from other teams. These Treasurer meetings are an
opportunity for Treasurers to monitor the accounts of the XLP as a whole, and to evalu-
ate individual requests for funding. Any member of the XLP is welcome to observe these
meetings
Secretary:
1. To cover the team’s administrative tasks as given by the Oicer
2. To make formal minutes in all team meetings
3. To monitor the membership of the team, updating relevant databases on member
changes and introducing new members to the team
4. To act as a bridge of communication between Challenge Designers and Mission Executers,
encouraging co-operating within and across teams
5. To publicise the mission and manage the logistics of digital publications
6. To investigate and report on appeals, where necessary, as laid out in Article XII
7. To act as the returning oicer in Oicer elections
Contributor:
1. To follow the command as instructed by the Oicer
2. To frequently communicate with the rest of the team
3. To attend all fortnightly team meetings with updates and questions
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Article VIII – Teams
1. The purpose and existence of each team within the XLP is to design and execute a mission
2. Each mission must be consistent with the objective, purpose and aims of the XLP as stated
in Articles II and III
3. Each team shall include exactly one Oicer
4. Each team shall include at least five members, which includes the Oicer
5. If at any time a team has fewer than five members, a new member shall be found with
high priority. If there exists fewer than five members for more than ten consecutive days,
the team is automatically disbanded, and the Smart Contract terminated
6. No team shall include more than 25% of the entire membership of the XLP
7. Any team member except the Oicer may belong to more than one team
8. A member can only hold the title of Secretary, Treasury or Oicer in one team only
9. Each mission shall begin with an Initial Coin Oering, whereby each team member shall
own a part of the mission
10. Each action by each team member into the mission shall be stored using Blockchain tech-
nologies for all to see
11. All major team decisions not covered by the smart contract shall be decided by secret-
ballot voting within the team. Each team member receives a vote in proportion to their
owner share of the mission
12. An Oicer need not own the largest share of the mission, though they must own a share
weakly greater than 5%
Article IX – Rights
These rights apply to every member of the XLP. Additional rights may be found in each member’s
binding smart contracts
1. Every member has the right to life
1. Once provided with membership, an account can only be terminated through the
processes laid out in Article V, or as an extenuating circumstance in Article XI
2. Termination of life is not in contravention of this Article only when essential and
strictly appropriate force is required to prevent a member intentionally acting in a
way that clearly breaches the right of another to life, liberty, or property. This will
occur only in exceptional circumstances
2. Every member has the right to end their life
3. Any member can relinquish their membership at any time as laid in in Article V
4. Any smart contract may still govern such a member until its oicial expiry
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3. No member shall ever be subject to physical or mental torture, or degrading treatment in
any way
4. No member may own any other account except their own
5. No member shall be held in slavery or solitude
6. No member shall be forced to perform any action that may be considered unsafe or
unlawful
7. No member shall be expected to work unreasonable hours, or in unreasonable con-
ditions, at any point
5. Every member has the right to liberty and security
8. Any member found in violation of these rights at any time is subject to compensation
6. Any member who believes to be in violation of any right may make a formal complaint as
laid out in Article XII. An Oicer may issue a complaint on a member’s behalf with prior
electronic consent
9. A member may make an appeal on the decision of their formal complaint
7. No member shall be charged with breaching this constitution if the action in question,
at the time at which the act was performed, was not a part of the constitution. Nor shall
a heavier punishment be imposed than one applicable at the time when the action oc-
curred
10. Any violation of this constitution, and appropriate punishment, shall be clearly ex-
plained to the member at the time of decision
8. Every member has the right to respect of their private life, family life, home and corre-
spondence
11. There shall be no interference with this right except when necessary and propor-
tional in order to prevent direct infringement with another right in this article
9. Every member has the right to freedom of thought, belief, and religion
12. Every member has the right to change their thought, belief, or religion at any time
13. Every member has the right to put their beliefs into action, except where they in-
fringe on any other right, public safety, or morality
10. Every member has the right to freedom of opinion and expression
14. Any member may give or receive information to any other member at any time, un-
less when the providing of such information infringes on another right, infringes on
this constitution, provides a risk to safety, or transmits the disclosure of information
received in confidence
11. Every member has the right of freedom of assembly and association
15. Every member has the right to form and be a member of a union, party, or another
association or voluntary group
16. This right applies in all instances except when the association is a risk to public
safety, the rights or freedoms of others, or health or morals
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12. No member shall be intimidated, bullied, or made to feel weak
13. Every member shall be treated with due respect
14. Equal Opportunities
17. There shall be no direct nor indirect discrimination on the grounds of gender, race,
colour, ethnic, national or social origin, sex, sexual orientation, pregnancy, mater-
nity, disability, religious or political belief, marital status, age, property, birth, or
other status’
18. The decision on the appointment of any new member, or the election of any new
position, shall not be made, partly or fully, on any of the above characteristics. This
includes, but is not limited to, discriminatively: altering the arrangements in decid-
ing to whom to give a position, altering the terms of appointment or election, and
not oering appointment or vote
19. No member may act in a way that discriminatively reduces or increases the current
or future potential direct or indirect opportunities another member has or will have
access to
20. No member may discriminate against another in a way that aords another access,
or by not aording another access, by oering or not opportunities for resources or
training, or for receiving or not any other faculty
21. Any member, when making any decision, shall have due regard for exercising it in
such as a way as to reduce the inequalities of outcome which result from socio-
economic disadvantage or otherwise
22. No Challenge Designer may design a mission that promotes harassment or discrim-
ination on any grounds
23. No Challenge Designer may discriminate against a Mission Executer in the way it
provides education, in the way it aords Mission Executers access to the mission or
any service, by not providing Mission Executers with education, by excluding or ex-
pelling a Mission Executer, or by subjecting Mission Executers to any other deterrent
24. Any member who feels to have suered discrimination on any grounds may issue a
formal complaint as specified in Article XII. If it is decided that discrimination on any
grounds did occur, the defendant shall be immediately expelled
25. There shall be no harassment under any circumstances
26. No decision of an oicial complaint or appeal may be based on any discriminatory
factor
27. A term of a smart contract is void and unenforceable against a person if it consti-
tutes, promotes or provides for treatment of that or another person that is discrim-
inatory. Where necessary and equivocal, this decision shall be made in an Oicer
Meeting
15. Every member and association has the right to their own property without interference
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28. No property owned by any member outside of the XLP can ever be taken away
through any activities associated with the XLP
29. Property within the XLP can be revoked only when it is necessary to remain consis-
tent with this constitution. Any revoked property requires suitable and proportional
compensation
16. No member shall be denied the right to education
Article X – Oicers
1. The initial Oicer of any team is the member who creates the mission
2. The initial Oicer faces election eleven months aer the creation of the mission
3. Every subsequent Oicer election within each term will occur biennially
4. Each Oicer election shall be held only within the team over which the Oicer leads,
and voting shall be conducted using the Single Transferable Vote secret ballot of all self-
nominated members
5. There shall be a period of one month where, if a dierent Oicer is to be elected, this
newly elected Oicer becomes Oicer-elect, and shadows the Oicer in their daily busi-
ness. An oicial transfer of power follows.
6. There exists no term limits on an Oicer
7. Any Oicer may resign with immediate notice. A by-election shall follow within two weeks
8. If an incumbent Oicer wishes to become Oicer of another team, they must resign in
their current team before they join and nominate themself in another
9. Any Oicer may be impeached through a vote of no confidence by the team. This vote
may be initiated by any team member at any time and requires a 50% majority in a secret-
ballot team vote for the Oicer to be impeached. In the case that an Oicer is impeached,
a by-election shall occur within two weeks
10. If in their most recent team they were Oicer, a former Oicer may remain a member,
but not an Oicer, for 90 consecutive days. If such a former Oicer finds another team or
starts their own within this window, they shall continue to be a member of the XLP. If aer
90 consecutive days they are without a team, their membership immediately expires
Article XI – Oicer Meetings
1. An Oicer Meeting shall occur Monthly, on the first Thursday of each Month, and shall last
for a minimum of 30 minutes
2. Each Oicer must virtually attend the entire duration of a minimum of ten Oicer Meet-
ings annually
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3. Oicer Meetings will function like a direct democracy, where any Oicer may propose
debates, motions, amendments, or dissolution. All Oicers can collectively vote on any
issue. The majority of 50% shall always be decisive, unless specified elsewhere in this
constitution
4. Any member of the XLP can observe any Oicer Meeting, and may participate only in Mem-
ber Questions
5. At any point during any Oicer Meeting, any member can call for quorum. If there exists
fewer than 75% of all Oicers present, the meeting immediately terminates, and will be
replaced with one the next Thursday at the same time. An inquorate meeting does not
count towards an Oicer’s minimum attendance of at least ten Oicer Meetings annually
6. In the event that quorum is not reached for three continuous Thursdays in one Month,
the fourth Thursday shall have compulsory attendance for all Oicers: any Oicer failing
to attend with adequate reasoning shall have their position immediately withdrawn
7. There exists no leader in an Oicer Meeting; the meeting shall be governed collectively by
all Oicers present
8. The order of every Oicer Meeting shall proceed as follows:
1. Welcoming. Any new Oicer shall be briefly welcomed
2. Updates. Any Oicer with significant updates, that cannot be distributed in text for-
mat at a dierent time, will update and discuss with the other Oicers
3. Complaints and Appeals. Any formed complaints and appeals shall be debated and
voted on
4. Miscellaneous items. Any items that do not fall into any of the above categories will
be discussed, and, where necessary, voted on
5. Member Questions. Members, selected by ballot, will have the opportunity to ask
unseen questions to any or all Oicers, for an immediate public response. This sec-
tion shall last for no fewer than twenty minutes. Each question, including appro-
priate time for answers and responses, is limited to a maximum of two minutes in
total
Article XII – Complaints
1. Should a member have cause for complaint about the administration of their team or
the XLP, the provision of services thereby, or the conduct of Oicers, and register that
complaint in the form of a letter to their Oicer, that Oicer shall constitute a tribunal to
investigate the complaint with all deliberate speed
2. If the complaint is directed at the behaviour or actions of a team’s Oicer, then the com-
plaint should be made known to the team’s Treasurer, who shall constitute a tribunal with
all expediency
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3. A tribunal shall consist of ten XLP members selected by sortation. Any member selected
has the right to decline if they so wish. The Tribunal shall investigate the veracity and
accuracy of the complaint, and shall present a report at the next Oicer Meeting. Should
the tribunal uphold the complaint, the next Oicer Meeting must ensure that action is
taken to resolve it
4. If the Tribunal concludes that a member has breached this Constitution in any way, a vote
of no confidence in that member must be held at the next Oicer Meeting
5. Should either party to the complaint wish to appeal, they may have recourse to their
team’s Secretary, who will investigate and report on the complaint at an Oicer Meeting
as soon as practicable.
Article XIII – Extenuating Circumstances
1. In the event that there is significant and unexpected damage or loss to a crucial part of the
operations of the XLP, there shall be called an Emergency Oicer Meeting at the earliest
opportunity
2. At any Emergency Oicer Meeting quorum is reduced to 50% of all Oicers present
3. An Emergency Oicer Meeting may trigger the first of two consecutive meetings to amend
or dissolve the Constitution. The second consecutive vote, however, may only occur in
the ordinary monthly Oicer Meetings as stated in Articles XI and XIV
4. The order of business in an Emergency Oicer Meeting is restricted solely to the events
and implications of the extenuating circumstances about which the meeting is formed
5. As each extenuating circumstance is unique, there is no fixed order of business. However,
the following must be discussed, and where necessary, voted upon:
1. Immediate Actions. Any subsequent processes of high priority must be discussed
and enacted
2. Long Term Actions. Processes of a direct or indirect result of the circumstance shall
begin to be discussed. No formal vote is necessary until the next Oicer Meeting
3. Disciplinary Actions (where appropriate). Any member intentionally contributing to
the increase in likelihood of success of the extenuating circumstance shall receive
appropriate penalisation
4. Honour (where appropriate). Any member intentionally contributing to the de-
crease in the likelihood of success of the extenuating circumstance shall receive
appropriate reward
5. Future Precautions. Any necessary steps to eliminate the potential for another sim-
ilar circumstance should be discussed and, where necessary, voted on
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Article XIV – Disciplinary Procedure
1. If any member is found to be breaching the rules in any article of this constitution or their
binding smart contract, disciplinary action shall occur
2. If a resolve of any smart contract breach is written into the smart contract, then the disci-
plinary procedure is automatic and machine-generated
3. If a member is found to be breaching their smart contract, and if no resolve is encoded
within the smart contract, the Oicer shall take appropriate action. This does not aect
the member’s right to make a formal complaint on the Oicer’s decision
4. If an Oicer is found to be breaching their team smart contract, and if no resolve is en-
coded, a vote of no confidence within the Oicer’s team shall be held within seven days
5. If an Oicer is found to be breaching their Oicer smart contract, and if no resolve is en-
coded, the Oicer shall defend their actions at the next Oicer Meeting. All other Oicers
shall vote on appropriate disciplinary action in a secret ballot, to have immediate eect
6. If any team member except the Oicer is found to be breaching the rules of this consti-
tution, the Oicer shall suspend such a member for a minimum of seven days. A second
constitution breach shall result in immediate XLP expulsion. Any breach of rights to any
other member in the XLP at any point will result in immediate expulsion
7. If an Oicer is found to be breaching the rules of this constitution, they must defend their
case in the next Oicer Meeting, whereby a secret ballot of all Oicer members will de-
cide the appropriate disciplinary action. If an Oicer infringed on the rights of any other
member, they face immediate expulsion, and a replacement shall be found in a team by-
election
Article XV - Amendments & Dissolution
1. Amendments to the Constitution shall be made in Oicer Meetings only. An amendment
can be proposed by any Oicer, and all members, not only Oicers, may vote on and
amend an amendment. The vote shall be held by secret ballot with the Single Transfer-
able Vote electoral system. Any amendment requires a majority vote in two consecutive
Oicer Meetings reaching quorum to be changed into the Constitution, and will apply im-
mediately once the second vote has a majority in proposition
2. Members shall leave the XLP at any point as set out in Article V
3. If a situation arises where the XLP must or wishes to dissolve, it requires two majority
votes of at least 80% in two consecutive Oicer Meetings reaching quorum. The vote will
be held by secret ballot with the Single Transferable Vote electoral system. Any member
virtually present may vote on the notion to dissolve the XLP. A proposition to dissolve the
XLP may be proposed by any Oicer in any Oicer Meeting
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How to: Use MediaWiki
You will use the wiki to group edit your report and other documents.
A wiki is a website on which users collaboratively modify content and structure directly from
the web browser. In a typical wiki, text is written using a simplified markup language.
Wikipedia is by far the most popular wiki-based website, and is one of the most widely viewed
sites of any kind in the world, having been ranked in the top ten since 2007. There are tens
of thousands of other wikis in use, both public and private, including wikis functioning as
knowledge management resources, notetaking tools, community websites, and intranets. The
English-language Wikipedia has the largest collection of articles; as of September 2016, it had
over five million articles.
We use Mediawiki, the same soware that runs Wikipedia, to allow participants to collabora-
tively create reports and other documents.
Log In
Click on OAuth2Login on the top right of your MediaWiki install. Your coordinator should have
given you the address.
Figure 10.5: Logging in to MediaWiki
Create a New Page
1. Go to http://yourwebsite.com/index.php/page_title where page_title is the name of the
page you want to create.
2. Click Create
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3. Write in your text as needed. Don’t worry about adding a title, since the title will be the
name of your page.
4. Write a one sentence summary in the Summary box, and then click Save changes.
Edit a Page
You can edit any page on the wiki, including the front page:
1. Go to the page you want to edit.
2. Click Edit at the top of the page.
3. Aer making changes, write a one sentence summary in the Summary box, and then click
Save changes.
Format Text and Insert Images
Mediawiki uses wikitext to format text, create lists, insert images, and so on. Instead of a graph-
ical editor like Microso Word, you use a plain text box with special wikitext codes to turn text
into headers or lists, and insert images:
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Bold and Italic
’’’Bold’’’
’’Italic’’
Headings
=Heading Level 1 =
=Heading Level 2 =
== Heading Level 3 ==
And so on...
Lists
*Bullet 1
*Bullet 2
** Sub bullet
*** Sub sub bullet
#Numbered list item 1
#Numbered list item 2
## Numbered list item 2.1
### Numbered list item 2.1.1
Links
External links:
[http://www.link.com Link Title]
For example:
[https://news.wisc.edu/curiosities-what-determines-the-colors-of-the-
sky-at-sunrise-and-sunset/ Curiosities: What determines the colors
of the sky at sunrise and sunset?]
Links on your own wiki
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[[Page title]]
For example:
[[Digital Wallet]]
Renaming a link on your own wiki:
[[Page name |Text you want]]
Citing a source:
The sky is blue<ref>Steven Ackerman,professor of meteorology at UW ‒
Madison</ref>
You can also embed links into citations (see above for link syntax)
Insert Images
1. Click Upload File on the le sidebar
2. Browse for your file and click the Upload file button.
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3. When you’re editing a page and want to insert the image, type: [[File:filename.png]]
If the image is too big, you can use
[[File:filename.png|500px]]
to make it 500 pixels wide, for example.
How to: Use WordPress and Elementor
A blog (short for ”weblog”) is a discussion or informational website consisting of posts (diary-
style updates, displayed newest-first) and pages (more permanent information).2
Our blogging soware is WordPress: a free and open-source content management system. It is
most associated with blogging, but supports other types of web content including more tradi-
tional mailing lists and forums, media galleries, and online stores. Used by more than 60 million
websites, including 30.6% of the top 10 million websites as of April 2018, WordPress is the most
popular website management system in the world.3. Our WordPress installation includes sev-
eral plugins to make editing easier, most notably Elementor.
Log In
Your coordinator should have given you a URL, username, and password for your WordPress
installation. Use this to log in.
2Adapted from Wikipedia, July 30, 2018
3Adapted from Wikipedia, July 30, 2018
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Figure 10.6: Logging in to WordPress
Create a New Report Page
One from person from each group should create the report page, based on what your group
wrote in MediaWiki:
1. On the le-hand sidebar, you should see a link to Pages. Hover over the link and click
Add New:
2. Enter a page title, then click Edit with Elementor to enable a richer editing experience:
3. Click the folder icon to select a template:
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4. Select one of the first two (free) templates:
5. Preview your template. If you’re happy with the overall look, click Insert:
6. Start editing the ”widgets” (i.e. components) of your template by clicking a widget and
editing on the le sidebar:
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7. Insert new widgets by dragging and dropping from the le sidebar:
8. When you’re happy with the result, click Publish:
If you need to go back to the widget menu, you can click the grid icon:
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Create a New Landing Page
All the groups should get together and nominate one person out of everyone to create a landing
page. This page gives an overview of the whole experience and links to each team’s report.
1. Follow the steps above to create a new page, but don’t publish yet
2. You will need to create a link to each report page. This isn’t a simple process unfortu-
nately. For each report you need to create a link to:
1. Hover over the Pages link on the le sidebar, then right-click All Pages and click
Open in New Tab then switch to that tab (this means we don’t lose our editing
work on our landing page)
2. Hover over the report page you want to create a link to. Below the title you should
see a link to view the page. Right-click this, and select Copy Link Location (or
whatever the menu item is called in your browser):
3. Go back to the tab you are using for editing your landing page
4. Drag and drop a button into the page, and paste the address you just copied into
the Link box:
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Note: If you want to create a link another way, feel free. Buttons are provided as an
example
3. Repeat this process for each report you need to link to
4. Click Publish:
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Edit a Page
1. Hover over the Pages link on the le sidebar, then click All Pages
2. Hover over the page you want to edit, then click Edit’ with Elementor
Back Up Your Work
Remember Murphy’s Law? Anything that can go wrong will go wrong. So backup your files!
On the WordPress sidebar, click Tools then Export:
Then click Download Export File:
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In case of data loss or some other catastrophe, you can import this data into a fresh WordPress
installation and get your data back.
For Participants Coming to China
• Download and register on WeChat. WeChat is THE chat app for China, and everyone you
meet will have it installed.
• Download and install a VPN if you want access to Google, Facebook, Twitter, Youtube,
WhatsApp, Line Messenger, and lots of other online services that are blocked in China
• Install Google Translate for iPhone or Android and the oline language pack for Chinese
• Install Pleco for Chinese character recognition
As mentioned above, many overseas resources can only be reached via a VPN. While using a VPN
for your research is fine, we suggest you assume your industry report, presentation anything
else you create will be accessed by users without a VPN. That means:
• No embedded YouTube videos
• No hosting your work on Google Drive, Dropbox, or other online services (OneDrive works
for now, but don’t assume it’ll always be the case)
• Disable Google Fonts in your WordPress theme (if you installed a theme yourself)
Also, wifi and network connections may be unreliable, so make sure everything will run oline
when you are presenting. Assume Murphy’s Law: ”Anything that can go wrong will go wrong.”
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How to: Install WordPress and MediaWiki
You will need
• A computer running Docker
• Access to your command line
• Internet access for the initial container pull
Optional First Step
Creating a Docker container requires first downloading the ”image” that the container is based
on. A Docker image isn’t a picture or photograph but rather a template containing all of the
files, code, settings, and libraries required to build a container. You can make as many Docker
containers as you would like from one Docker image; any container is just one instance of its
corresponding image.
The code in the following sections automatically download the required images, but if you have
limited access to internet and would like to download all of the images before trying to set up
containers, you can run the following lines in your command line.
docker pull tuitu/dind-wordpress
docker pull tuitu/dind-mediawiki
docker pull tuitu/dind-piwik
”pull” tells Docker that you want to download an image, ”tuitu” is the name of the repository
where the image is stored, and ”dind-wordpress”,”dind-mediawiki”, and ”dind-piwik” are
the names of the images.
MediaWiki
MediaWiki requires MariaDB database. From your command line:
docker run --name my_wiki -e DOCKER_DAEMON_ARGS=”-D” -e PORT=4444 --
privileged -d-p80:4444 tuitu/dind-mediawiki
Docker run creates a new container. The ”--name” flag sets the name of the container. The
first ”-e” flag sets the environment variable ”DOCKER_DAEMON_ARGS” to ”-D”. The 2nd ”-e”
flag sets the environment variable ”PORT” = 4444. The ”--privileged” flag gives the container
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administrative rights. The ”-d” flag is short for ”--detached”, this means that the container can
run without being directly controlled by a user. The ”-p” is short for ”--publish”, which sets the
port for the container and exposes the host port; the first number aer the ”-p” flag -- 80 -- can
be changed to any available port or it can be le as the default. The last phrase specifies which
image to use for the container.
docker exec -it my_wiki bash /TensorCloud/DockerInDocker/
mariadb_mediawiki_4444.sh
Docker exec runs a command on an already started container. The ”-it” flag is a combination
of ”--interactive” (allows for input) and ”--tty” (pseudo-terminal). The next phrase is where you
specify which container you are dealing with. In our case, this is ”my_wiki”. The last two phrases
say to use bash (a programming language) to run a script at the specified location. This is nec-
essary for setting up the internal containers.
Wordpress
The steps for Wordpress and Piwik are similar to those of Mediawiki.
From your command line:
docker run --name my_wordpress -e DOCKER_DAEMON_ARGS=”-D” -e PORT=4445
--privileged -d-p81:4445 tuitu/dind-wordpress
docker exec -it my_wordpress bash /TensorCloud/DockerInDocker/
mariadb_wordpress_4445.sh
Piwik
docker run --name my_piwik -e DOCKER_DAEMON_ARGS=”-D” -e PORT=4446 --
privileged -d-p82:4446 tuitu/dind-piwik
docker exec -it my_piwik bash /TensorCloud/DockerInDocker/
mariadb_piwik_4446.sh
And more, http://toyhouse.cc/wiki/index.php/Get_Started_with_Remix#Using_Remix
Accessing on your local machine
In your web browser, open:
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Service What is it? URL Default username Default password
Mediawiki Wiki 127.0.0.1:81 user bitnami1 <!-- |-
WordPress Blog 127.0.0.1:80 user bitnami
Piwik Analytics 127.0.0.1:82 user bitnami <!-- |-
Jenkins CI/CD Tools 127.0.0.1:87 admin 123456 OpenModelica 3D Modeling 127.0.0.1:84 N/A -->
How to: Crowd Learn with remote participants
While individual and group learning typically take place in just one location at a time, large-
scale crowd-learning involves participants from all around the world. This introduces several
challenges that need to be addressed to achieve worthwhile learning outcomes. This is espe-
cially the case when dealing with China, where many online services are blocked.4
Why Crowd Learning?
•New Perspectives: People from dierent countries and backgrounds bring new perspec-
tives to the table
•Clearer Documentation: Because all communication is electronic, your group learning
consciousness is stored in MediaWiki, WordPress, and other tools
Advice
For Remote/Local Teams
•Video chat by default: so no one feels less valued or le out
•Video team-building activities: play into the strengths of remote work, like sharing your
classroom view
•Assume good intent: Remember that the kinds of nuanced communication you get in a
physical classroom setting don’t necessarily translate online.
•Make rules: Establish communication rules in the constitution that includes teams and
their wishes directly in the creation. When to use chats? Why to write emails? At what
4Censored: Distraction and Diversion Inside China‘s Great Firewall, Margaret E. Roberts, Princeton University Press
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point to pick up the phone? Over time these will becomes social norms for your crowd
learning group.
•Build structure: When having meetings or giving updates, have clear structure, process
and agendas so everyone can follow along, no matter where they are. Assign a meeting
lead and a note-taker to ensure key points are captured in writing.
•Understand each others’ contexts: If Bob doesn’t get an instant reply from Alice, it
doesn’t mean that Alice doesn’t care - she may be running for a taxi in Rio!
•Asynchronous over synchronous: Being in dierent timezones makes it diicult to sync
up, so plan ahead and make no decisions last minute
For Remote Participants
Many remote participants feel the need to be ”visible” in their digital workspaces to ”prove”
that they are working.5. With this mind, remote participants can:
• Indicate ”deep work” times on their NextCloud (or other) shared calendar
• Update your status in RocketChat or other chat tool to show they’re working
5Trello: How to Embrace Remote Work
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108 $DATE
11 Bibliography
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Links
https://en.wikipedia.org/wiki/Holacracy
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https://www.holacracy.org/constitution
https://www.holacracy.org/wp-content/uploads/2015/07/Holacracy-Constitution-v4.1.pdf
https://steemit.com/eos/@dantheman/what-could-a-blockchain-constitution-look-like
https://www.platon.network/en/web/index.html
http://ec.toyhouse.cc:4445/
http://www.campuschina.org/index.html
http://undraw.co/illustrations
http://hitchain.org/
http://hitchain.org/pdf/HitChain-Whitepaper-en.pdf
https://www.equalityhumanrights.com/en/human-rights/human-rights-act
https://www.equalityhumanrights.com/en/equality-act/equality-act-2010
http://www.legislation.gov.uk/ukpga/2010/15/contents
https://www.youtube.com/watch?v=EJrPW3254wg
https://www.debian.org/social_contract
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http://bratton.info/
https://www.newtonproject.org/
https://www.newtonproject.org/whitepaper/
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