Archive for the ‘communities’ Category


Book: Mass collaboration in education is soon out

July 7, 2015

Mass Collaboration and Education

Cress, Ulrike; Moskaliuk, Johannes; and Jeong, Heisawn (Eds.)

Table of Contents


Chapter 1: Ulrike Cress; Heisawn Jeong; and Johannes Moskaliuk. Mass Collaboration as an Emerging Paradigm for Education? Theories, Cases, and Research Methods

Part I: Theoretical Approaches to Mass collaboration

Chapter 2: Allan Collins. A Brief History of Mass Collaboration: How Innovations over Time have Enabled People to Work Together More Effectively

Chapter 3: Gerhard Fischer. Exploring, Understanding, and Designing Innovative Socio-Technical Environments for Fostering and Supporting Mass Collaboration

Chapter 4: Mark Elliott. Stigmergic Collaboration: A framework for understanding and designing mass collaboration

Chapter 5: Ulrike Cress; Insa Feinkohl; Jens Jirschitzka; and Joachim Kimmerle. Mass Collaboration as Co-Evolution of Cognitive and Social Systems

Chapter 6: Aileen Oeberst; Joachim Kimmerle; and Ulrike Cress. What is Knowledge? Who Creates it? Who Possesses it? The Need for Novel Answers to Old Questions

Chapter 7: Wai-Tat Fu. From Distributed Cognition to Collective Intelligence: Supporting Cognitive Search to Facilitate Online Massive Collaboration

Part II: Cases of Mass Collaboration

Chapter 8: Tobias Ley; Paul Seitlinger; and Kai Pata. Patterns of Meaning in a Cognitive Ecosystem: Modeling Stabilization and Enculturation in Social Tagging Systems

Chapter 9: Aileen Oeberst; Ulrike Cress; Mitja Back; and Stefen Nestler. Individual versus Collaborative Information Processing: The Case of Biases in Wikipedia

Chapter 10: R. Benjamin Shapiro. Toward Participatory Discovery Networks: A Critique of Current Mass Collaboration Environments and A Possible Learning-Rich Future

Chapter 11: Deborah A. Fields; Yasmin B. Kafai; and Michael T. Giang. Coding by Choice: A Transitional Analysis of Social Participation Patterns and Programming Contributions in the Online Scratch Community

Chapter 12: Ricarose Roque; Natalie Rusk; and Mitchel Resnick. Supporting Diverse and Creative Collaboration in the Scratch Online Community

Chapter 13: Brigid Barron; Caitlin K. Martin; Véronique Mertl; and Mohamed Yassine. Citizen Science: Connecting to Nature through Networks

Chapter 14: Sabrina C. Eimler; German Neubaum; Marc Mannsfeld; and Nicole C. Krämer. Altogether now! Mass and Small Group Collaboration in (Open) Online Courses – A Case Study

Chapter 15: Thomas Herrmann. Socio-Technical Procedures of Facilitated Mass Collaboration for Creative E-Participation

Part III: Methods to Empirically Analyze Processes of Mass Collaboration

Chapter 16: Iassen Halatchliyski. Theoretical and Empirical Analysis of Networked Knowledge

Chapter 17: H. Ulrich Hoppe; Andreas Harrer; Tilman Göhnert; and Tobias Hecking. Applying Network Models and Network Analysis Techniques to the Study of Online Communities

Chapter 18: Ivan Habernal; Johannes Daxenberger; and Iryna Gurevych. Mass Collaboration on the Web: Textual Content Analysis by Means of Natural Language Processing

Chapter 19: Olga Slivko; Michael Kummer; and Marianne Saam. Identification of Causal Effects in the Context of Mass Collaboration



Social recognition in pattern networks among professionals

April 22, 2015

This paper paper Pata, K., Santos, P., Burchert, J.”Social recognition provision patterns in professional Q&A forums in Healthcare and Construction” has been accepted to Computers in Human Behavior.


We recently studied with colleagues Patricia Santos and Joanna Burchert several professional forums from the point of view of learning, maturing and recognition.

We used SNA to reveal the patterns and their interrelations.


Here is an example pattern network figure based on one healthcare practitioners forum discussions.

Based on those pattern networks we composed a model of social recognition provision in forums.

This model relates practicing and learning at work, peer-support practices in forums, the validation practices with knowledge maturing and formalizing loop.


Increasing validation practices can improve the credibility accumulation of persons as experts in the network and the credibility of shared resources, and allow crowds to initiate sharing and localising practices, maturing of guidelines and rules.

Yet, in current professional forums, such recognition practices happen quite seldom, and forums are not very good places for discovering which practices are credible based on social recommendation. Bringing some practices to the maturing and formalising loop would require particular orchestrated effort from the networks.

Noticeable is that in face-to-face practices among professional quite similar pattern trends could be modelled. For example based on interviews with construction workers the following dependency model between actions was found.



The Set as an ecological concept

April 20, 2015

Today Terry Anderson
had a lecture of open education in Tallinn University.

He mentioned a genial and catchy The Set concept they have started using in MOOCs that i became quite facinated of.

“The Learning in Sets” chapter in the book Teaching Crowds ( 2014) by Terry Anderson and Jon Dron.

A set is defined by intentional engagement around a topic.

Much set-based learning occurs “just in time,” concerned with finding out something of value to the learner now, rather than a continuing path.

The set will represent a range of perspectives and views of the subject, which together will offer diverse opportunities to connect existing knowledge to new discoveries.

The Set may be a set of students who have similar preferences to courses they take in MOOCs, also i think in general on what they choose as resources. So in this way it resembles user profiles in recommender systems.

Terry mentioned they now try putting contacts between those in the Set.

The main reason i like the Set concept is it is pre-cultural, assuming that self-organised people will not necessarily discover each other, and supporting this intentionally is a meta-design principle that helps learning ecosystems to develop kind of culturally similar “species” who can then dedicate intentional efforts in communicating to learn from each other.

It is a question, when actually one becomes aware of certain Sets and identifying his belonging to this or that Set. And what will by the person’s awareness of other Sets.

Exposing ( discovery) of different sets and opposing different Sets for some problem-solving or other purposes can probably be done only with meta-design using analytics’ based feedback.

Going back home with tram from Terry’s lecture i was thinking of the Set as kind of distributed cognitive phenomenon – manifesting its existence through its externally created behavioural niche. Terry and Jon write:

Another way that sets can aid serendipitous discovery is when we spot trends or patterns in behaviour.

The set has proven to be surprisingly effective for connecting those in need with those who wish to give.

We have recently discussed of those niches containing the patterns (as culturally defined solutions to problems) developed by certain “cultures” or in other words by Sets, as well as how individual pattern formation in epistemic distributed cognition happens embedded to the cultural pattern formation.

set distributed cognition

I was also thinking if the formation of Sets was promoted in open educational courses, what way it would change the currently too much individualistic MOOCs. And what kind of learning analytics and learner focused feedback could be given for Set formation as another meta-design element that promotes learning ecosystem management. Terry and Jon write:

Self-referentially, the Set itself can provide resources and clues about the reliability of information found within it, particularly if it incorporates collective tools that emphasize reputation, provide ratings, or show other visualizations that give hints about the value of a contribution or individual.


thesis: Learning and knowledge building practices for teachers’ professional development in an extended professional community

July 7, 2013

Kairit Tammets, my first doctoral student will defend her thesis at 21st of August.

Now her dissertation is available from here

Tammets, Kairit (2013) Learning and knowledge building practices for teachers’ professional development in an extended professional community.

The purpose of her PhD research project is to investigate the process of the learning and knowledge building (LKB) in the extended professional community that is supported with the socio-technical system.

Learning and knowledge-building in extended organizations

May 20, 2012

The IntelLEO project is going to its end, and we are looking back at what we achieved.

In the project we assumed that to support organizational responsiveness, cross-organizational learning and knowledge-building should be supported. Our assumption was that learning and knowledge-building (LKB) activities across organizational borders as well as within organizations would create conditions for organizational responsiveness to appear.

We adopted the knowledge conversion model by Nonaka & Takeuchi (1995) into cross-organizational settings,

identified learning and knowledge-building enablers and inhibitors,

and developed technological services that support those learning and knowledge-building activities that support responsive organization to emerge:

  • the competence-based reflections in the format of the construction of learning paths and monitoring personal development in socially and organizationally embedded context (externalization and internalization activities) (see Siadty et al. 2011)
  • the competence-annotated sharing and searching of knowledge (externalization, internalization)
  • the competence-annotated searching for other learners or working partners and team-building (socialization and combination activities)
  • the construction, accumulation and provision of organizational knowledge to its employees using the semantic web technologies and ontology framework (externalization and internalization activities)

We assumed that extended organizations are connected with temporal learning and knowledge building activities, and we may conceptualize such an extended organization (an IntelLEO – intelligent learning extended organization) as a distributed cognitive system.

Socially distributed cognition, where cognitive processes are distributed across members of a social group by knowledge exchanges also contains mutual awareness, communicating and socially provided support as an external locus of control for cognition. The forms of socially distributed cognition are:

– monitoring peers’ activities for mutual awareness, social surveyillance (such as friend-feeds, wall, mashups)

– peer-scaffolding (commenting, rating, favouriting)


Distributed cognition involves coordination between internal and external (material and environmental) structures through causal coupling (an embodied cognition) that enables adapting one’s actions to fit to environmental conditions.

These also associate with the distributed intelligence and dispersed learning processes carried out in a loosely coupled way. Such distributed intelligence creates a distributed cognitive system that also contains a feedback loop to community/organizational culture – cognitive processes can be distributed through time in such a way that products of earlier events (of the same person, of other community/organization members or members from different community) can transform the nature of later events.

This may take different formats:

– creating and using personal knowledge aggregations

– using the external knowledge organization of peer’s (tags, annotations to the resources they have used)

– using bottom-up or top-down aggregated organizational knowledge (tagclouds, semantic search)

– creating and organizing personal reflections (blog posts)

– using externalized peer’s knowledge (blog posts)

– creating personal networks (mashing feeds to monitor)

– benefitting from community browsing (from shortcuts the personal networks create in the community).

Here are some results from the interviews with workplace learners about using the IntelLEO framework for learning and knowledge-building (LKB):

The temporal LKB activities that have been identified as the prerequisites of organizational responsiveness These acts create distributed cognition possibilities across EO in IntelLEO Examples of temporal LKB acts perceived by workplace learners

1. The presence of knowledge exchanges among employees

Cognitive processes are distributed across the members of a social group (a socially distributed cognition).

Better communication

Becoming open

Exchanging knowledge and experiences

Acknowledging that someone might read and learn from my reflections.

Sharing, asking and commenting to support the development of learning partners

Helping my colleagues to discover interesting online resources

Cross-organizational  collaboration on research projects

Starting and sharing new learning areas in the company

Sharing relevant information with a group

Shared goal or experience supports LKB

Sharing information complements each other’s knowledge and increases group synergy

2. The opportunity for employees within an organisation to use knowledge to adapt their actions to appropriately fit environmental conditions

Cognitive processes involve coordination between internal and external (material or environmental) structure through causal coupling (an embodied cognition)

The continuously changing and evolving job requirements impose the need for constant learning of new things

Autonomy  for deciding when and how to learn

Performing LKB primarily for oneself

Organising learner’s current/planned knowledge is increasing the willingness to get involved in LKB

Giving the big picture – what have you done, how have you done it and what else you should learn

Reflection makes to analyse development and think thoroughly about the activities

Showing the learning progress motivates others’ learning

Documenting one’s knowledge increases the others’ motivation to learn within the organization

Reading colleagues’ entries  help to realize that my contribution can also be useful for my colleagues

Seeking external solutions for internal challenges

Seeing what and how others have learnt  – that makes to think should I learn it as well, how could I learn it

Reusing the „lessons learned“ of my colleagues for planning learning

Peers’ contributions influence to see own things from different viewpoint

Providing the organisational goals on what to learn

Can take a look at the example-learning paths, created by organization

Benefiting and learning from the crowd-sourced knowledge and annotations gathered by the entire organization

Organizational goals may be harmonized with input from personal goals and work-practces

3. Distributed intelligence and dispersed learning processes carried out within loosely coupled different organisations

Processes are distributed through time in such a way that the products of earlier events can transform the nature of later events (feedback loop to organizational culture).

The sufficient mass of initial content in the system increases motivation to add

Looking back/finding at own entries and annotated resources

Identifying potential learning and/or research partners

Getting an insight into others’ interests and goals

Following resources or persons

Associating the discovered resources with the task

Letting others to know of new contributions

Seeing the activities in interesting topics and of colleagues

Better structuring and organizing of the collective knowledge

The collaborators can easily access task-relevant resources

Collaboration between organizations influences positively the development of individuals

It influences the growth of the organizational and individual knowledge


connectivity through (digital)ecosystem engineering that influences niche construction of communities

October 7, 2010

I found a nice paper in which Kevin Laland, the author of influential book Niche Construction: The Neglected Process in Evolution (2003) has co-written the paper of human niche construction from the archeological perspective. Thanks to Emanuele Bardone from Pavia Computational Philosophy Lab i got the file in the morning!

It is interesting from the point of view of explaining the niche construction effects of humans using the long-lasting and cultural “traits” that humans transfer to the next generations as mediators or carriers which have the indirect accumulative modification pressure on environments and thereby on the other organisms that can affect human life and human gene evolution.
He highlights the indirect interactions between species and the organism connectivity by the engineering web and not by the food web:

The ecosystem engineers can regulate energy flows, mass flows, and trophic patterns in ecosystems to generate an “engineering web”—a mosaic of connectivity comprising the engineering interactions of diverse species.

On my opinion, this is exactly what happens in human-artifact networks that represent this kind of connectivity in engineering web.

Basically the process is:
Human cultural traits = human behaviour as ecosystem engineering for increasing their fitness to the niche
-> changing the niche for other organisms associated with humans
-> evolutionary response of other organisms to the changing niche
-> evolutionary changes in humans in response to other organisms
-> human behaviour changes or consistency = modifying or strenghtening certain cultural traits

A meme (Dawkins, 1976) is a unit of cultural ideas, symbols or practices, which can be transmitted from one mind to another through writing, speech, gestures, rituals or other imitable phenomena.
Memes evolve by natural selection (in a manner analogous to that of biological evolution) through the processes of variation, mutation, competition, and inheritance influencing an individual meme’s reproductive success. Memes spread through the behaviors that they generate in their hosts.

And possibly by niche generation as well!
Dawkins noted it as a condition which must exist for evolution to occur: differential “fitness”, or the opportunity for one element to be more or less suited to the environment than another

In order to use ecology principles for explaining interactions of humans and human communities with social software systems the following analogy may be used:

specimen of one species = human

species with certain gene frequency = specimen with similar range of identity perception, a community (note that identity is based on shared meanings or actions / /memes??/cultural traits??/)

niche as a range of environmental factors that allow fitness to the species = niche as a range of affordances perceived and frequently used in actions by certain community in their interactions with each other and with their environments (virtual or real) that allow their semiotic or cultural fitness

The semiotic fitness, should ideally measure the semiotic competence or success of natural systems in managing the genotype-envirotype translation processes (Hoffmeyer, 1998).
Semetic interactions refer to interactions in which regularities (habits) developed by one species (or individual) successively become used (interpreted) as signs by the individuals of the same or another species, thereby eliciting new habits in this species eventually to become – sooner or later – signs for other individuals, and so on in a branching and unending web integrating the ecosystems of the planet into a global semiosphere (Hoffmeyer, 1993).
The semiotic adaptability is a process, in the course of which the subject
correlates self-related and environment-related information, thereby localising
itself in the environment (Maran, 2005).

community (a number of species) in certain environmental locations = several human communities who coexist in certain virtual social software or hybrid environments

co-adaptive niches apply for such communities which consist of a number of species who may be connected by food-webs or by engineering webs= several human communities connected mainly by engineering webs create co-adaptive niches for each other and may influence each other

Ecosystem ecology that studies how matter and energy circulates in ecosystems,should also consider how ecosystem (entropy, succession, networks, communities, interactions) is influenced by the ecosystem engineering done by co-existing species in this ecosystem as part of connectivity comprising the engineering interactions of diverse species. The same applies for communities in this digital or hybrid ecosystem.

Can such co-existing human communities in social software environments or hybrid environments engineer their niches so that this niche starts to constrain or facilitate other community?
Can such pressure influence some ways the individuals in each community to perceive certain affordances as useful for their cultural or semiotic fitness in the niche and influence the community identity?

For example if we take the long tail phenomenon, which reveals little niche artifacts, meanings, conceptions of certain communities. Can interaction in the same social software ecosystem (eg. shelfari for choosing books; delicious for choosing resources by tags) influence some communities to become more fit to their environment by broadening or narrowing their activity choices as a result of other community’s actions and niche construction (eg. choosing particular books or resources introduced by other community)


Niche Construction Theory and Archaeology
Kevin N. Laland & Michael J. O’Brien
J Archaeol Method Theory
DOI 10.1007/s10816-010-9096-6

Their basic idea is:
Niche construction is “the process whereby organisms, through their metabolism, their activities and their choices, modify their own and/or each other’s niches” (Odling-Smee et al. 2003, p. 419). The conceptual leap that niche construction theorists embrace is to regard niche construction as an evolutionary process in its own right. Some organism-driven changes in environments persist as a legacy to modify selection on subsequent generations, which Odling-Smee (1988) called an “ecological inheritance.”
Niche Construction Theory is sometimes referred to as “triple-inheritance theory” (genetic, cultural, and ecological inheritance; e.g., Odling-Smee et al. 1996, 2003; Laland et al. 1999, 2000, 2001; Day et al. 2003; Shennan 2006).
Rather than slipping into the assumption that the external environment (e.g., climate change) triggers an evolutionary or cultural response, NCT enthusiasts are from the outset inclined to consider those additional hypotheses stressing self-constructed (and other organism-constructed) conditions that instigate change.

Jones et al. (1994, 1997) uses concept of “ecosystem engineering,” as a relevant synonym for niche construction to describe the focus on organisms’ modification of environments.

Jones and his collaborators point out that many species of ecosystem engineers can regulate energy flows, mass flows, and trophic patterns in ecosystems to generate an “engineering web”—a mosaic of connectivity comprising the engineering interactions of diverse species, which regulates ecosystem functioning in conjunction with the well-studied webs of trophic interactions (Wilby 2002).

Organisms do considerably more in ecosystems than compete with each other, eat, and be eaten (trophic interactions). Organisms also produce, modify, and destroy habitat and resources for other living creatures, in the process driving co-evolutionary dynamics.

From the niche construction perspective, the connectivity in ecosystems is massively increased.

Hardesty (1972) stated that culture is the human ecological niche.
There are several examples of culturally induced genetic responses to human agriculture (Odling- Smee et al. 2003),
The best known being the co-evolution of the gene for lactose absorption and dairy farming (Durham 1991);
The Kwa-speaking yam cultivators in Africa who modified the environment and increased the amount of standing water which provided better feeding grounds for mosquitoes and increased the prevalence
of malaria and induced the increase in the frequency of the sickle-cell (HbS) in Kwa-speakers population that provides protection against malaria (Durham 1991).
The evolution of the human amylase gene which is responsible for starch consumption is a feature of agricultural societies and hunter–gatherers in arid environments, whereas other hunter–gatherers and some pastoralists consume much less starch (Perry et al. 2007).

Odling-Smee et al. (2003) describe as inceptive niche construction all cases in which organisms initiate changes in any factor, through either perturbation or relocation. Organisms express inceptive niche construction when by their activities they generate a change in the environment to which they are exposed. Conversely, if an environmental factor is already changing, or has changed, organisms may oppose or cancel out that change, a process labeled counteractive niche construction. They thereby restore a match between their previously evolved features and their environment’s factors. Counteractive niche construction is therefore conservative or stabilizing, and it generally functions to protect organisms from shifts in factors away from states to which they have been adapted.

Niche construction provides a non-Lamarckian route by which acquired characteristics can influence the selection on genes. Whereas the information acquired by individuals through ontogenetic processes clearly cannot be directly (genetically) inherited, processes such as learning can nonetheless still be of considerable importance to subsequent generations because learned knowledge can guide niche construction in ways that
modify natural selection acting on future generations.
This route is considerably enhanced by social learning, which allows animals to learn from each other.
There should be a significant relationship between the pertinent environmental state and the recipient character only when the niche-constructing activity is also present.
The same logic applies at the cultural level, and the same methods can be applied to hominins or to contemporary human populations, where they may shed light on the relationship between different kinds of cultural niche construction and their different consequences.

Laland et al. (2001) concluded that, because cultural processes typically operate faster than natural selection, cultural niche construction probably has more profound consequences than gene-based niche construction.
It also has driven coevolutionary interactions with other species, including domesticated animals and plants, commensal species adapted to human-constructed environments (e.g., rats, mice, and insects), and microbes (Boni and Feldman 2005; Smith 2007a, b).
There are no genes for domesticating dogs, manufacturing cheese, or cultivating rice (using “genes for” in the sense of Williams (1966) and Dawkins (1976) to mean alleles specifically selected for that function), and these activities, while frequently adaptive (increasing fitness in the present), are not adaptations (traits directly fashioned by natural selection).
If human activities have imposed selection on mice, houseflies, or mosquitoes is it because we are their competitors or predators, or even because we are linked in an elaborate food chain. Such co-evolutionary episodes are probably driven by nontrophic and indirect interactions between species—that is, by the engineering web (Jones et al. 1994) and not by the food web.

Cultural niche-constructing processes that contribute to plant domestication include selective collecting of reproductive propagules; transporting and storing of propagules; firing of grasslands, either intentionally or accidentally; cutting of trees; incidental tilling; and creating organically rich dump heaps, all of which are
potent forms of niche construction. Plants that are involved may undergo a series of phenotypic changes such as a general increase in size, an increase in the size of propagules, loss of delayed seed germination, simultaneous ripening of the seed crop, and so on. These changes occur as interaction with human agents increases the fitness of the plant community, which, in turn, increases the yield of the plant community. Increasing yield in turn generates selection favoring those cultural traits that maintain or increase productivity of the plants. This reinforcing mutualistic relation between plant and human populations is one process by which plant domestication, and human coadaptation, evolves.

Because of our habitat degradation as part of our niche construction we destroy the (engineering) control webs that underlie ecosystems.

Wilby, A. (2002). Ecosystem engineering: A trivialized concept? Trends in Ecology & Evolution, 17, 307.
Jones, C. G., Lawton, G. H., & Shachak, M. (1994). Organisms as ecosystem engineers. Oikos, 69, 373–386.
Jones, C. G., Lawton, G. H., & Shachak, M. (1997). Ecosystem engineering by organisms: Why semantics matters. Trends in Ecology & Evolution, 12, 275.


Hoffmeyer, J. (1998). The Unfolding Semiosphere. In Gertrudis Van de Vijver, Stanley Salthe and Manuela Delpos (eds.), Evolutionary Systems. Biological and Epistemological Perspectives on Selection and Self-Organization. Dordrecht: Kluwer 1998, pp. 281-293.


An Ontospatial Representation of Writing Narratives in Hybrid Ecosystem

August 29, 2010

Tomorrow i will be at 3rd International Workshop on Social and Personal Computing for
Web‐Supported Learning Communites, DEXA 2010, Bilbao


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