Strategies for Harnessing the Collective Intelligence of Cultural
Institutions’ Communities
Considerations on Supporting Heterogeneous Groups in Content Production
Taking the Quality Factor into Consideration
Leonardo Moura de Araújo
dimeb – Digitale Medien in der Bildung, University of Bremen, Bremen, Germany
Keywords: Content Production, Platforms, Collective Intelligence, Cultural Institutions, Scaffolding, Design Thinking.
Abstract: This support paper builds a theoretical model upon which computer platforms for cultural institutions can be
based upon. It analyses three landmark models in the Computer Science history that were capable of
harnessing the Collective Intelligence present on gravitating communities. Afterwards, conclusions are
drawn regarding their effectiveness in leveraging communities. Instructional Scaffolding and Design
Thinking are indicated as important strategies to provide the necessary support to heterogeneous groups.
1 INTRODUCTION
Due to the increase in popularity of social media
services and strategies across digital and physical
landscapes, there is growing expectation and
pressure for Cultural Institutions (CIs) to make the
transition from static providers of cultural content to
flexible facilitators of interaction, participation, and
collaboration among their audiences.
In order to meet those expectations e.g. some
museums started to incorporate 2.0 philosophies into
their venues to make their role more meaningful to
their communities. From interactive installations to
collective creation and remixes of content, those
initiatives represent an effort of museums to bring
students, professionals, hobbyists, aficionados, and
basically anyone to be part of the making process.
The outcomes of participatory attitudes that see
the public as creative agents can be considerably
significant. On one hand, CIs profit from the content
and knowledge produced by their audiences. On the
other hand, the public perceives CIs as compelling
spaces where they can express themselves.
One of the challenges in giving the public the
chance to express themselves regards the quality of
the content they produce using technology. Poor
outcomes can be originated not only by the lack of
clarity, clear instructions, and support from the part
of the museum app, but also individual deficiencies
such as limited experience and knowledge from the
part of the public. How can CIs support their public
in producing high-quality and reliable content with
technology?
This position paper examines successful models
in the Computer Science (CS) field that were
capable of harnessing the Collective Intelligence to
produce high-quality outcomes. They are: the open-
source model (OSM), collaboration applications
(CA), and software platforms (SP).
Those models offer hints of how to think
collaborative apps that take advantage of gravitating
communities effectively. However, apart from CAs
such as Wikipedia, those models are directed at
professionals from the CS field, and do not focus on
individuals with little or no formal training. Even
Wikipedia can be harsh with inexperienced users.
As a solution for attempting to support
inexperienced collaborators of CIs, this paper points
out to two well-known methodologies, namely
Design Thinking (DT) and Instructional Scaffolding,
that are capable of facilitating and supporting the
production of content by large and heterogeneous
groups when integrated in computer applications.
2 THE COLLECTIVE
INTELLIGENCE
Due to new communication technologies,
individuals collaborate in a diversity of ways never
80
Moura de Araújo L..
Strategies for Harnessing the Collective Intelligence of Cultural Institutions’ Communities - Considerations on Supporting Heterogeneous Groups in
Content Production Taking the Quality Factor into Consideration .
DOI: 10.5220/0004949000800086
In Proceedings of the 6th International Conference on Computer Supported Education (CSEDU-2014), pages 80-86
ISBN: 978-989-758-022-2
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)
possible before. On the Internet, the Collective
Intelligence is manifested not only by single and
collaborative works built upon previous knowledge,
but also in the human-human and human-computer
relationships on the network.
The vision of past about human-computer
symbiosis turned out to be to a certain extent
revealing. In 1960, Licklider (Licklider, 1960) in his
article Man-Computer Symbiosis predicts that
human brains and computers would be coupled
tightly together and that “the resulting partnership
will think as no human brain has ever thought and
process data in a way not approached by the
information-handling machines we know today”
(Licklider, 1960).
Man-made networks connect millions of
individuals, who consist of different kinds of
biological networks themselves. Neural networks of
the human brain share similarities with the Internet
regarding their structure and functionality. Eguiluz
et. al. describe super connected brain regions in
neural networks that appear to work as “hubs”
facilitating the communications between distant
“nodes” or specific and less connected brain areas
[see (Eguiluz et al., 2005)]. Those "hubs" operate in
a comparable way to search engines in that they do
not hold the information, but point to the location to
where it is.
Macro and micro resemblances might hold
answers why we are so comfortable with computers.
This configuration between biology and technology,
the “Global Brain”, holds the potential “to become
truly transformative in domains from education and
industry to government and the arts” (Bernstein et
al., 2012).
2.1 Landmark Models
The Global Brain and its collective intelligence
foundations, which are the result of human-computer
symbioses, can be better examined by looking at
landmark developments of the computer history
such as the OSM, CA, and SP architectures.
2.1.1 The Open-source Development Model
Open-source is perhaps one of the most well known
examples of collaborative work that uses collective
intelligence to produce high quality outcomes. Its
development model is focused on both the premise
of users being considered as co-developers and free-
license agreements.
Open-source projects are probably ideal examples of
almost non-hierarchical collaborative production
processes that are able to cope with highly
complicated and large amount of data. As Weber
(Weber, 2000) shows, those collaborative processes
raise questions regarding motivation of contributors,
coordination of projects, and complexity of
communities.
In most cases, the OSM does not work on the
premise of monetary rewards, but appeals to
people’s individual motivations, such as having fun
with programming puzzles, contributing to projects
that are socially relevant, gaining visibility regarding
programming skills, and profiting from more
experienced individuals [see (Weber, 2000)].
The Internet stands as a facilitating tool able to
deal with large numbers of collaborators. On one
hand, the virtual space the Internet provides is
capable to scale in a way that physical spaces are
not. Almost “unlimited” space can be allocated for
communication, data storage, working branches, and
individual and collective profiles. The stored data
can be picked up and worked further at anytime,
anywhere. Therefore, having enough space for
specific code branches is important to differentiate
and keep projects organized. On the other hand,
intelligent algorithms created for e.g. revision
control aid programmers to keep track of changes on
the code, and help to identify individuals responsible
for those modifications.
The distributed configuration of open source
projects presents challenges regarding management
and control of the work produced. Solving conflicts
within groups is also a concern that should be taken
into consideration. In the case of Linux, Linus
Torvalds is seen as an authority in that he was the
founder of the Linux Kernel project. In this sense,
Torvalds and programmers who are high in the
hierarchy have the last word in decisons. Apart from
that, and in most cases, the code decides.
2.1.2 Software Platforms
In Product and System Design, a platform is a
structuring foundation on top of which a set of
independent elements and interfaces can be
arranged, rearranged, and innovated upon [see
(Griffiths, 2010)]. Shared key components and
assets define the core of the platform and
diversification can be achieved by building upon and
extending capabilities to build new, but related
foundations. Baldwin et. al. (Baldwin and Woodard,
2009) point out that most platform definitions
identify the reuse or sharing of common elements as
core characteristics, and that all platforms are
“modularizations of complex systems in which
StrategiesforHarnessingtheCollectiveIntelligenceofCulturalInstitutions'Communities-ConsiderationsonSupporting
HeterogeneousGroupsinContentProductionTakingtheQualityFactorintoConsideration
81
certain components (the platform itself) remain
stable, while others (the complements) are
encouraged to vary in cross-section or over time“
(Baldwin and Woodard, 2009). Well-structured
platforms allow numerous advantages, such as cost
saving, increased production efficiency, ability to
evolve and produce variety in large scale.
In CS, this term was initially used to define the
computing hardware and later on the operating
system (OS) upon which programs would run.
Earlier computers had to be built from the ground up
always when new releases were planned. Not
infrequently, because of incompatibility with newer
systems, there was a costly process involved in
moving data to different formats.
As computer hardware was becoming modular
and increasing its complexity, systems without OSs
presented enormous challenges. Earlier computers
required the full hardware specification to be
attached to the application every time it ran.
Therefore, a program not only would be suitable for
just one machine, but also it had to be loaded every
time someone needed the program. As a way to
optimize computers, the industry realized that some
fundamental set of instructions could be loaded into
the memory and managed separately. The distinction
between applications and OS was then created.
The reuse of code and the modularization of
computer systems brought many advantages to the
field especially regarding cost, manageability, and
evolution of complex systems. According to
Baldwin et. al., “by promoting the reuse of core
components, such partitioning can reduce the cost of
variety and innovation at the system level. The
whole system does not have to be invented or rebuilt
from scratch to generate a new product,
accommodate heterogeneous tastes, or respond to
change in the external environment“ (Baldwin and
Woodard, 2009).
The modularity of computer systems became
even more robust with the advent of Object-Oriented
Programming (OOP) that took the reusability of
software components to a next level. Powerful
software development frameworks reduced the
complexity and cost of writing code. Frameworks
“mean a real breakthrough in software reusability:
not only single building blocks but whole software
(sub-)systems including their design can be
reused.”(Pree, n.d.)
The inexpensive and powerful strategies allowed
by frameworks create a rich ecosystem for
application development that lead to an enormous
variety and innovation, especially when it is popular
and open to a great number of developers.
2.1.3 Collaborative System Model
Collaborative systems are designed to support
individuals to accomplish tasks in a cooperative
manner. The free-content encyclopedia Wikipedia is
a successful example of a tool based on an openly
editable model that came from the open source
experience, which sees users as contributors.
Wikipedia covers an enormous amount of subjects.
More than 22,000,000 articles were written so far.
As in open source software projects, the outcome of
the collaborative process lead to the creation of
articles “of remarkably high quality“ (Malone et al.,
2010, p. 21).
Originally, Wikipedia was proposed as a
complementary project for its predecessor Nupedia
as a mean to generate faster and larger amounts of
content. Although also thought to be collaborative,
Nupedia was not able to release consistent amount
of articles during its existence. The main problems
Nupedia had were its highly bureaucratic publication
procedure, elitist selection of contributors, and non-
wiki platform. Nupedia’s content approval process
had seven complicated steps. Non-expert individuals
willing to contribute would most likely be vetted
with only few cases of exception.
Therefore, Jimmy Wales and Larry Sanger
decided to run Wikipedia to facilitate the
productions of articles that later would go for the
Nupedia’s reviewing process. Basically, the idea
was to find a way that uncredentialed people could
participate more easily. The differential of
Wikipedia relied on its deep open-source
philosophies, which considers everything as a “draft
in progress, open to revision” (Rettberg, 2005).
Impressively, the quality of the articles and the fact
the Wikipedia is not prone to amateurism and
vandalism is due to the community that is
“passionate about the topics they know and care
about”(Rettberg, 2005).
The wiki architecture is key to the success of
Wikipedia. Anyone is able to contribute including
anonymous users. Wikipedia allows contributors to
publish their unfinished drafts, so others can make
improvements on them. However, the decision of
either accepting or not unfinished contributions
depends on the patrol division which checks new
articles shortly after they are created. Sometimes
arbitrary decisions can be made and contributors
should engage in discussions to clarify uncertainties.
This process can be very localized and specific to
the people in charge of approval. In any case,
individuals are driven to cooperate if not with
writing new publications, then with linking
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keywords among articles, fixing spelling mistakes,
or improving clarity of sentences.
Nothing else holds Wikipedia from being just a
wiki than its policies and guidelines. The content
created is free for others to read and modify. This is
a strong motivation for people to work in something
they believe to be valuable for the good of the
society. However, Wikipedia has a different culture
from regular wikis, because “it’s pretty
singlemindedly aimed at creating an encyclopedia.”
(Sanger, n.d.). Although the architecture of wiki
software encourages openness and de-centralization
allowing deviant content being fed into the system,
the community of wikipedians is compliant with the
Wikipedia’s five fundamental pillars [see
(“Wikipedia:Five pillars - Wikipedia, the free
encyclopedia,” n.d.)].
2.2 The Building Blocks for Quality
What are the building blocks from those models that
can be applied to the design of systems capable of
harnessing communities’ collective intelligence to
generate new content with acceptable quality?
In the case of the OSM and CA, the community
is the force behind their success, because they see
users as co-developers and as part of the decisions.
In the case of the open-source, the easy access to the
code along with the licenses is one of the most
important aspects. Each member of the community
has unique needs that are met without them having
to reinvent the wheel. This is a direct benefit. At the
same time, new extensions, adaptations, and
improvements automatically appear in the process.
In the open-source movement, the product comes
from improving and building on other people’s
knowledge. And because there is no clear
hierarchical authority, in most cases, the quality of
the code decides whether it will be popular.
Other motivational aspects are important in
leveraging the community. Individual motivations
such as contributing with projects that are fun,
challenging, educationally beneficial, socially
relevant, and can improve one’s reputation play a
big role in the community. As for the Wikipedia,
however, the natural selection that takes place in the
case of open-source projects does not happen in the
same way. That is because not only the goal of this
model is different, but also Wikipedia is more
centralized and hierarchically structured. Wikipedia
architecture does invite users to create new articles
and modify existing ones, and doing so is easy to the
extent of not needing to create a user account on the
website in order to contribute. The facilitated
process of contribution generates an enormous
quantity of new content.
Differently from code, that needs to be logically
coherent in order to compile, textual information is
subtle in hiding factual inaccuracies and non-neutral
point of views. Besides having good structure and
style, Wikipedia articles need to gather support from
other textual information, which takes the form of
references, working in a similar way as in academic
texts. In order to check for inconsistencies and
errors, Wikipedia relies deeply in few contributors,
such as the administrators and patrollers. Because of
its textual, localized, and more hierarchical structure,
it allows certain contradictions inside the system.
Although Wikipedia accepts contributions from
anonymous users, it is up to the patroller e.g. to
accept or not to engage in a discussion about an
article that is about to be deleted depending on
whether or not the contributor has a user account.
Another example is that a contributor would be
willing to start a topic with a small contribution and
expect others to build on that. But once again, the
patroller can expect that a certain threshold to be
crossed regarding the amount of text in the article,
no matter if Wikipedia in fact incentives small
contributions. In any case, although frustrating for
newbies, the Wikipedia process is able to generate
high-quality content that comes primarily from the
large amount content being produced everyday
together with its hierarchical selection.
In the case of SPs, its power is in its modularized
structure, stable layer of components, and the
possibility of numerous configurations provided by a
set of compatible and independent elements. The
quality factor from platforms comes from the easy
and inexpensive experimentations that can be
produced. In all three examples, quantity seems to
be a determinative factor for quality. One of the
cores of the OSM is the fact that it is also based on
SPs and modularization is one of the aspects that
allow the reuse of code, which leads to cheap and
countless forked versions of software.
3 SCAFFOLDING AND DESIGN
THINKING
When thinking about harnessing the collective
intelligence of the public of CIs for producing
content, one should be careful to be as inclusive as
possible regarding the public. The three models
presented above offer many hints of how to leverage
the crowd. One of the most important of them is
StrategiesforHarnessingtheCollectiveIntelligenceofCulturalInstitutions'Communities-ConsiderationsonSupporting
HeterogeneousGroupsinContentProductionTakingtheQualityFactorintoConsideration
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undoubtedly seeing the members of the community
as active co-creators. But the primary focus of those
models is on the production of digital content.
Supporting and educating users is something that
can or not come along during the production process
in those models. Acquiring skills to write computer
programs or articles is usually seen as pre-
requirement in order to be a respected contributor of
those movements. CIs, on the other hand, have as
one of their primary focus educating their public.
Therefore, educating while producing content is a
desirable configuration for CIs.
The OSM is perhaps the model that offers the
most extensive support for its users. The GNU
project defines open-source software as a matter of
individual liberty and a right for the user “to run,
copy, distribute, study, change and improve the
software“ (“The GNU Operating System,” n.d.). In
this sense, educational aspects are considered when
talking into account that the user has the right to
analyze and study how a program works and how
the code should be written. The community plays
also an important role regarding educating new
generations of programmers in that there is a lot of
knowledge exchange in forums.
Open-source software usually goes along with a
strong community that provides extensive support.
In addition to that, because open-source is highly
decentralized, the need for consensus is not a
constant issue, as in the case of Wikipedia. That
means that the OSM gives more space for individual
contributions. That allows small groups of people
with the same interests to take further the
development of specific code that might not be of
interest to a large community.
The wiki architecture, on the other hand,
searches for consensus and does not give space for
beta versions of articles, what might be a good
strategy for supporting beginners. The higher the
degree of modularity, the easier it is for contributing.
This strategy is deeply used in programming
languages and SPs, but no good solution was
thought yet regarding text. The history strategy used
on Wiki articles fragments information by tracking
changes and creating small chunks containing the
modifications. Nevertheless the larger the article, the
more difficult it is to manage those changes.
In order to make the creation of content highly
inclusive, it is not only necessary to modularize and
give space to advanced users and beginners, but also
to ensure that they get proper support. Moreover, the
community should also be open with dealing with
poor contributions not by prompting them for
exclusion, but driving the contributors towards
refinement. Instructional scaffolding therefore is a
good strategy in this regard.
The concept of scaffolding was introduced by
Wood, Bruner, and Ross [see (Wood et al., 1976)]
but derives from the socio-constructivist theories of
Vygotsky on the “zone of proximal development”.
Scaffolding is the assistance provided by
experienced individuals that enable inexperienced
ones to succeed in tasks that otherwise would be too
difficult. Nowadays, this concept has been changed
and adapted taking into account computer-based
learning environments. Some scaffolding strategies
are automatically integrated in software, making it
unnecessary e.g. the presence of human assistance.
Those strategies can including measures that “induce
and stimulate cognitive, metacognitive,
motivational, and/or cooperative activities during
learning” (Raes et al., 2012). Scaffolding can also
support ways for individuals to keep track of overall
plans and progress, which are common obstacles
faced in tasks that require learning. One way of
doing so is automatically handling nonsalient and
routine tasks, reducing the cognitive load while
executing a task. This allows learners to focus only
on what is important.
As for CIs, Nina Simon (Simon, 2010) talks
about the importance of instructional scaffolding
when museums ask visitors to create content. One of
the problems, is that “open-ended self-expression
requires self-directed creativity“ (Simon, 2010).
That can be difficult especially for would-be
participants since it leads to the situation where
“participants have to have an idea of what they’d
like to say or make, and then they have to produce it
in a way that satisfies their standards of quality”
(Simon, 2010). By directing, scaffolding limits the
participation, but allows visitors to feel more
confident and confortable in engaging with CIs.
While instructional scaffolding is able to provide
necessary support, DT principles can be used to
drive individuals to advance their knowledge in
creative ways. As Welsh et. al. (Welsh and Dehler,
2012) point out, “design thinking’s emphasis is on
developing possibilities rather than satisfying
constraints“ (Welsh and Dehler, 2012). DT counts
on abilities such as intuition, pattern recognition, and
generation of ideas that are emotionally meaningful.
Furthermore, it eliminates the fear of failure,
because it is experimental and non-judgmental. It is
human-centered, meaning that it considers the point
of view of the community. It stimulates great
amount of input that is allowed by thinking out of
the box. In the context of CIs those features are
desirable, because they are inclusive, especially
CSEDU2014-6thInternationalConferenceonComputerSupportedEducation
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when taking children into account. The most
important contributions of DT in the context of CIs
are methods for defining important issues through
empathy and gathering insights in a non-critical
way, that can be later explored.
It can be hard to conciliate a methodology
bounded for innovation and experimentation with
instructional scaffolding that tries to limit open-
ended possibilities. Notwithstanding the
contradictions, DT can be seen in fact as a
scaffolding strategy for leading contributors towards
specific goals. And, because of its flexible nature, it
can be adapted to particular contexts regarding its
phases, and methods. From more strict approach,
when dealing to historical facts, to more associative
thinking, when trying to interpret an abstract
painting, those two methodologies combined hold
the potential to help the crowd to make sense and
produce original content based on their own
interpretation and research.
4 CONCLUSIONS
Contributing to the construction of knowledge, and
being inclusive and innovative concerning the
outcomes produced by the public of CIs is no easy
task. Creating content for CIs means dealing with
open-ended possibilities, heterogeneous groups, and
require significant disciplinary knowledge and
metacognitive skills. Those requirements are not
always met. In this sense, technology appears not
only as an instrument for inclusion, but also as a
facilitating tool to accomplish tasks.
In the CS field, the OSM, CAs, and SPs are three
landmark models for harnessing the collective
intelligence of gravitating communities to produce
reliable and high-quality outcomes. Some of their
most important features are:
Dealing openly and fairly with the community
they serve to.
Individuals are seen as co-creators and have their
say regarding the direction and shape of most
open-source projects and CAs.
Free access to the core is seen as a right
concerning open-source philosophies. This is
guaranteed by comprehensive licenses.
Building on other people’s knowledge is
supported by free access to code, text, and
structures those models offer.
Modularization is a key factor for producing
derivations, because it reduces costs by
promoting reuse of elements.
The capability of producing great amount of
outcomes lead to increase quality.
Those models however are focused on the
production of digital content. Support and education
of users are in many cases not considered. CIs, on
the other hand, have as one of their primary goals
informing and educating their public. Therefore, it is
a desirable configuration to include sense making
and knowledge building into the design of platforms
for CIs. Instructional scaffolding and DT offer
valuable hints in this regard. They are able to
organize the creative process, directing it towards
innovation and experimentation by providing the
necessary building blocks in the same way platforms
do. Scaffolding promotes focus. DT offers human-
centered strategies for empathy, need finding, and
generation of insights in a non-critical way.
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