Elaborating connectivism

This chapter draft describes the web of social software tools with its inhabitants as an evolving and ecological environment, discussing and elaborating the Connectivist framework coined by George Siemens in his book Knowing Knowledge. This new perspective to ecological learning in social software environments resides on the ideas of Gibson‘s and his followers approach to ecological psychology, the rising theory of embodied simulation and the Lotman’s ideas from cultural semiotics.

The full chapter is published in the Educational social software for context-aware learning book.

Full chapter

1. Introduction

Recently, the widespread public use of social software in Web has triggered for the need to theoretically ground the learning phenomena in this new environment. The theoretical framework developed by Web visionaries like John Seeley Brown (1999; 2002), George Siemens (2005; 2006) and others is directed towards information and artefacts, meanings and knowledge, networks and connections, in weaving ecologies of knowledge. In his book “Knowing Knowledge” George Siemens (2006) has suggested Connectivism as the learning theory for new Digital Age. He formulated that Connectivism is the assertion that learning is primarily a network-forming process (Siemens, 2006, p. 15). He relies on the ideas of Downes (2005) who wrote that: A property of one entity must lead to or become a property of another entity in order for them to be considered connected; the knowledge that results from such connections is connective knowledge. The act of learning is one of creating an external network of nodes – where we connect and form information and knowledge sources (Siemens, 2006, p. 29). Connectivism focuses on the knowledge, situated externally from people in the web. Siemens (2005; 2006) assumes that creating meanings and relations publicly in social software environments would aid through connective processes the formation of new knowledge ecologies and learning cultures.

In the Connectivism framework George Siemens takes an approach that is strongly tilted towards knowledge, meanings, communities and networks and their spaces – knowledge ecosystems. However, the Connectivism framework is inconsistent in elaborating the ecological role of tools, activities, and communities in the formation and evolvement of knowledge ecologies. Siemens writes: The pipe is more important than the content in the pipe. ‘Know where’ and ‘know who’ are more important today that ‘knowing what’ and ‘how’ (Siemens, 2006, p. 32). In this chapter we attempt to argue against this metaphoric claim. We suggest that the use of static ‘pipe’ metaphor, and diminishing the role of activities, the ‘knowing how’ part, may theoretically lead to losing the ecological nature of knowledge ecologies framework.

Studies of communities and networks assume that these are formations of people (Lin, Sundaram, Li, Tatemura & Cheng, 2006; Kumar, Novak & Tompkins, 2006) or their artifacts (Klamma, Spaniol, Cao & Jarke, 2006). What yet is missing is seeing Web 2.0 as a united ecological system with its inhabitants. The interrelations between communities, the environment and the culture left there by people – the traces of meanings (Lor, Yesui, Welge & Goldberg, 2006) and the traces of activities – are important in the ecological framework. Similar tiltedness towards artifacts and meanings appears in the development of most of the social software tools. In social software systems we can find several possibilities of organising and filtering content by socially defined meanings, however, to see what activities take place in the communities that use these systems is often possible only if participating in the communities. We assume in this chapter that the ecological formation of common places, where communities and networks exist and take action, needs to be integrated into the theoretical explanations about connectivist learning in these systems.

2. Knowledge ecosystems in the Connectivism framework: flowing knowledge in the connected pipes

Siemens (2006) wrote in his book Knowing Knowledge that Connectivism is a staged view of how individuals encounter and explore knowledge in a networked/ecological manner. The central concepts Siemens discusses are: knowledge, learning, spaces, networks and knowledge ecosystems. He illustrated his framework with the following metaphor: The pipe is more important than the content in the pipe. ‘Know where’ and ‘know who’ are more important today that ‘knowing what’ and ‘how’ (p. 32). Subsequently we introduce his position in concerns of these terms, asking also some questions, which reveal the areas where Connectivism framework must be elaborated. These questions will be further elaborated in the next chapters.

Knowledge: Knowledge rests in networks. Knowledge may reside in non-human appliances, and learning is enabled/facilitated by technology (p. 31). The act of knowing is offloaded onto the network itself – to a connected network of specialists. The network (or web) of connections is the structure, which holds the knowledge of individuals in a holistic manner (p. 33). Content is imbued with new meaning when situated in network (or is more accurate to say that the network acquires new meaning when new content is added?) (p. 43).

Learning: Learning is a network formation process of connecting specialized nodes or information sources (p. 31). The elements that create understanding are scattered across many structures and spaces. We ‘know’ when we seek and pull elements together – when we create a meaning-laden view of an entity (p. 45).

Q: How technology enables/facilitates ecologies?
Q: How network holds knowledge and acquires new meanings?

Spaces: We create spaces where we can dialogue about and enact knowledge (p. 4). Ecologies and networks provide the solution to needed structures and spaces to house and facilitate knowledge flow (p. 86). Understanding knowledge in a particular era is important in ensuring that we have aligned our spaces and structures with the nature of knowledge (p. 10). Spaces are themselves agents for change. Changed spaces will change practice (p. 87).

Q: How spaces enable enacting knowledge?
Q: Can we separate the knowledge flow from the structures and spaces – networks and ecologies – where knowledge flows?

Networks: Our mind is a network… and ecology. It adapts to the environment (p. 27). The network is a structure that individuals create on their own (p. 132). Content is imbued with new meaning when situated in network (or is more accurate to say that the network acquires new meaning when new content is added?) (p. 43). Better quality of networks and connections result in better quality knowledge sharing (p. 20). Networks occur within ecologies. Ecology is a living organism. It influences the formation of the network itself. The health of each personal learning network is influenced by the suitability of the ecology in which the learner exists (p. 92).

Q: What are networks: Personal learning environments (PLEs)? Connections between artifacts a person creates? Connections between people a person interacts with?

Ecology: Ecologies and networks provide the solution to needed structures and spaces to house and facilitate knowledge flow (p. 86). Ecology is a knowledge-sharing environment (p. 87). The ecology fosters connections to original and knowledge sources, allowing for currency. The ecology fosters rich interaction between disparate fields of knowledge, allowing growth and adaptation of ideas and concepts. Each participant in the ecology pursues his/her own objectives, but within the organized domain of knowledge of a particular field (p. 117). Ecologies permit diverse, multi-faceted concepts… and meanings to emerge based on how items are organized or self-organize (p. 87). The creation of the ecology permits a broad-scale implementation of differing knowledge and learning experiences, permitting employees to achieve knowledge-based needs in a multi-faceted manner, multiple ways, and through multiple devices (p. 132). Ecologies are nurtured and fostered…instead of constructed, organized and mandated (p. 90). Ecologies are capable of rapid growth, adapting to new competition, differing perspectives, and enabling innovative concepts and ideas to gain traction (p. 87). Ecology is a living organism (p. 92). Ecologies are: loose, free, dynamic, adaptable, messy, and chaotic (p. 90). The ecology influences the formation of the network itself. The health of each personal learning network is influenced by the suitability of the ecology in which the learner exists (p. 92).

Q: How does the ecology influence personal networks?

Siemens (2006, p. 87) also discusses the characteristics of ecologies that promote knowledge sharing. He emphasizes the freedom of choice to use different systems and tools that meet the needs of each person, and which they perceive easy to use. This suggests owning a personal learning environment (PLE), which is accommodated to certain person’s needs and is interconnected with other person’s PLEs. Secondly, the variety of systems and tools that individuals use is considered important. This may increase the possibility of making connections between people and between artifacts across the various borders. The personal choice in making connections is of importance to hold motivation and inquiry spirit. Because knowledge is supposed to situated in networks and connections, the deep and trusting connections between individuals, who uptake knowledge from the ecologies, and tolerance among these individuals must be achieved. Thirdly, the consistency of participating in certain practices with knowledge is suggested, which may increase the probability that patterns will emerge within ecologies, and that persons will notice them.

Individuals are active in the learning ecology/space in terms of consuming or acquiring new resources and tools. The learner begins to actively contribute to the network/ecology essentially, becoming a visible node. Time in the network has resulted in the learner developing an increased sense of what is happening in the network/ecology as a whole. She/he will become more adept at recognizing new patterns or changing winds of information of knowledge. Individuals are capable of understanding what do the emerging patterns mean. The learner is also focused on active reflection of the shape of the ecology itself. The learner may engage in attempts to transform the ecology beyond his/her own network (Siemens, 2006, p. 45).

In the practical implementation of Connectivism ideas into learning Siemens (2006, p. 140) suggests three key aspects of ecologies – they must be holistic, adaptive and result-focused. These concepts may also serve as the starting-points into taking the fresh look at the knowledge ecologies.
Siemens suggests that holistic ecologies represent the situation diversely, allowing multiple perspectives and views. We can further argue that holistic view means that we may find several subspaces in the ecologies, which differ from each other by perspectives. Ecologies are formed of many individuals who try to realize their personal objectives, often individually and without being consciously involved into group actions. The view at the ecology level permits to see these individuals forming various communities who share similar views or act in a certain way without even knowing each other or forming networks. However, the communities inhabit spaces in the ecology, which are evolving, and dynamically changing. Across the vaguely defined borders of community spaces, knowledge can be interpreted and translated, creating new knowledge. The abstract space concept, which we formulize as a niche for certain community, is central in the revisions of Connectivism framework.

Secondly, Siemens suggests that ecologies must be adaptive and able to adjust and change as the environment changes. These characteristics are elaborated further in the next subchapter, introducing the ecological idea of affordances that define niches. If the persons are linked to their existing habits, activities, processes and tools, like Siemens suggests, any change in their objectives and preferences would cause the changes in the whole environment, in these communities. People, activities, and tools what they find to fulfill their objectives are ecologically interrelated. People rely on the cultural behaviors that take place in certain social environments – eg. tagging of personal meanings or reflecting in public spaces etc. Thus, community activities influence, which perspectives of meanings, actions and tool functionalities and objectives would be actual for the learners. Everything what people do, remains as the feedback into the systems. It is interpreted as ecological knowledge, influencing not only this community, but also potentially other communities.

Thirdly, Siemens emphasizes the intended targets and desired outcomes that the ecologies might have. This view would obtain a new meaning if we stop seeing the formation of ecologies as the systems purposefully designed by groups, but as emergent and evolving activity systems. The mutual interrelations between individuals, their objectives, and what they see and use in the surrounding system, when constructing knowledge, are triggered ecologically. The ecological knowledge is always being formed and always influencing what is being formed, and how it is being formed. This ecological knowledge is not only content left into the systems, but also the process traces from actions taken with certain tools with certain artifacts, with certain people. Thus, the communities always shape their spaces and these spaces shape the communities.

3. Enactment when learning in knowledge ecosystems: communities construct niches

In the previous discussion several questions where raised when analyzing the Connectivism framework. These questions revealed that there are unclear aspects, suggesting the necessity to take a more in-depth look into the knowledge ecologies. We have reorganised the order of these questions to frame our argumentation about the nature of knowledge, networks, knowledge ecologies and their interrelations.

Q: What are networks: Personal learning environments (PLEs)? Connections between artifacts a person creates? Connections between people a person interacts with?
Q: How network holds knowledge and acquires new meanings?
Q: Can we separate the knowledge flow from the structures and spaces (networks and ecologies) where knowledge flows?
Q: How technology enables/facilitates knowledge ecologies?
Q: How spaces enable enacting knowledge?
Q: How does the ecology influence personal networks?

To answer these questions we introduce some more concepts to the ecological learning framework: niches as abstract community spaces, affordances that define niches, ecological knowledge as the feedback that communities create, enactment and embodied simulation as the possible processes that cause ecology formation. Siemens (2005, 2006) has built his Connectivist framework on the ecological understanding. However, deepening of the ecological approach enables to see activities in the more central position in the knowledge ecologies. We aim to elaborate the knowledge ecosystem idea, strengthening the role of activities and introducing the theoretical framework how activities are related to the knowledge ecosystems.

Knowledge ecologies framework

Network-knowledge interrelations

Q 1: What are networks: Personal learning environments (PLEs)? Connections between artifacts a person creates? Connections between people a person interacts with?

We do not want to criticise the main idea expressed by Siemens (2006) in Knowing Knowledge, declaring that knowledge rests and changes in the networks that connect people and their artifacts. Asking, what these networks are, we want to emphasise the role of tools and activities as an ecologically entwined parts of the network. We emphasise that knowledge, is more than information and meanings – knowledge has an activity- and tool-related dimension. Personal learning environments (PLEs) that people construct and use in their daily activities are not merely the mediators, ‘the inactive pipes’ that enable knowledge flow. PLEs are dynamically evolving activity systems in which the personal objectives and human and material resources are integrated in the course of action.

We want to emphasize the distributed nature of what we define as PLEs. Here, we do not mean only that each PLE may be constructed of many separate tools forming a distributed system. PLE is also distributed ecologically, integrating our minds with the environment. Hommel (2003), has written that action control to all behavioral acts is ecologically delegated to the environment – when planning actions in terms of anticipated goals, the sensory-motor assemblies needed to reach the goal are simultaneously selectively activated in the environment, and bind together into a coherent whole that serves as an action-plan, facilitating the execution of the goal-directed actions through the interaction between the environment and its embodied sensory-motor activations. In the frames of ecologically defined learning systems, we can assume that our embodied sensory-motor knowledge of previous meaningful actions and its environmental correlates that we find around us form one emergent distributed system. In the course of learning our PLE is always in change. We actualize certain dimensions from the environment around us integrating it to the action-plans, and simultaneously the environment extends certain dimensions to us changing and shaping our intentions. Deliberately, we do not talk of the environment as merely of tools and systems. Environment involves all kind of resources in PLEs – people, artifacts, software systems and services. Thus, the network in the ecological framework may be interpreted as a distributed system continuously constructed of our minds and the environment components.

Q 2: How network holds knowledge and acquires new meanings?

Applying the previous interpretation of networks in ecological framework we can assume that knowledge that the networks hold is pattern-like, distributed between the environment and people, and dynamically emergent in activities. Two perspectives are important about the nature of knowledge – knowledge is always developed within the distributed systems personally and culturally. These personal and cultural ways to create knowledge are interrelated.

Varela, Thompson & Rosch (1991, p. 149) wrote that knowledge is the result of ongoing interpretation that emerges from our capacities of understanding. These capacities are rooted in the structures of our biological embodiment but are lived and experienced within a domain of consensual action and cultural history. They coined the term embodied action to transmit the idea that cognition depends upon the kinds of experience that come from having a body with various sensorimotor capacities, and second that these individual sensorimotor capacities are themselves embedded in a more encompassing biological, psychological, and cultural context. The authors assumed that sensory and motor processes, perception and action are fundamentally inseparable in lived cognition (p. 172-173). Using the term enaction they focused on two points: 1) perception consists of perceptually guided action, and 2) cognitive structures emerge from recurrent sensorimotor patterns that enable action to be perceptually guided (Varela et al, 1991, p. 173).

Bereiter (2002, p. 57) framed and answered the question about the nature of knowledge as follows: Where is knowledge if it isn’t contained in individual minds? The kind of answer coming from activity and situated cognition theorists runs along the following lines: Knowledge is not lodged in any physical or metaphysical organ. Rather knowledge inheres in social practices and in the tools and artifacts used in those practices. Knowledge is regarded as distributed. This does not mean merely that it is spread around, a bit here and a bit there… knowledge does not consist of little bits…all the knowledge is in the relationships – relationships among the people engaged in an activity, the tools they use, and the material conditions of the environment in which action takes place. Yet, Varela et al. (1991) and Bereiter (2002) do not offer explanations of how network holds knowledge and how this knowledge can change.

Recently researchers have come up to the idea how this distributed knowledge emerges as a result of embodied simulation. Discoveries in cognitive and neuroscience about the functioning of mirror-neuron systems (Gallese et al., 1996), claim, that cognition is embodied through grounding knowledge directly in sensory-motor experiences without the mediation of symbolic representations (Pecher & Zwaan, 2005). Research indicates that from observation of others and the environment (Rizzolatti et al., 2001), from listening narratives (Rizzolatti & Arbib, 1998; Iaccoboni, 2005) or from reading narratives (Scorolli & Borghi, 2007) and looking everyday images of objects or works of art (Gallese & Freedberg, 2007) we perceptually activate certain multi-modal action-potentialites of embodied symbols that mediate our purposeful and goal-directed actions (see Gallese & Lakoff, 2005). When acting in social learning environments not only the meanings are newly created from found information, but also the action-related cues are picked up from different narratives and from the whole systems, and they are integrated into our action plans. These findings indicate, that besides possibilities of organizing meanings with various ways in social learning environments, much more attention needs to be put on these action-related cues individuals and communities interact with in the environment. Knowledge is always in change because of personal nature of embodied simulation processes and the influence or feedback that people make with their actions, action- and meaning traces, and their specific way of activation of PLEs on the environment, to other people.

Q 3: Can we separate the knowledge flow from the structures and spaces (networks and ecologies) where knowledge flows?

In the revised ecological framework knowledge and networks are integrated. Our ecological learning framework binds together three assumptions: i) network may be interpreted as a distributed system continuously constructed of our minds and the environment components in the course of action; ii) knowledge is pattern-like, distributed between the environment and people, and is dynamically emergent in activities, iii) knowledge emerges as a result of embodied simulation, when people perceptually activate certain multi-modal action-potentialites from the environment that mediate their purposeful and goal-directed actions, and leave action- and meaning traces as a feedback to the environment.

Network-ecosystem interrelations

Q: How technology enables/facilitates knowledge ecologies?

The concept of ecology plays an important part in the Connectivism framework of learning. However, Siemens (2006) is not very precise in explaining how ecologies and networks influence each other. In our main amendments to Connectivism we try to elaborate the emergent nature of ecologies with bottom-up social definition of learning niches, discuss what is the role of using software systems in these ecologies, and describe how feedback through ecological knowledge connects ecologies and networks.

Ecologies are formed as a result of many individuals taking actions. Thus, people with various perspectives are simultaneously at present in these ecologies and influencing them. Many abstract subspaces can be formed within ecologies. Such spaces emerge when parts of the environment are embodied and used similar way by many people. Spaces are more general than networks of one individual – they come to existence and can be identified only if many individuals actualize similar personal learning environments for the same purposes with certain frequency at the certain period of time. These groups of individuals have something in common in their identity. They form communities who inhabit the same abstract learning spaces in the ecology – niches.

The formation of learning spaces as niches for specific learning-related activities happens through the social definition of several factors that influence learning. Hutchinson (1957) defined a niche as a region (n-dimensional hypervolume) in a multi-dimensional space of environmental factors that affect the welfare of a species. He also made difference of fundamental and realized niche – the former exist as the complex of all necessary environmental characteristics for certain species, the latter is formed under the pressure of all the currently available environmental characteristics in the competitive conditions with other species.

Niches have been conceptualized as the environmental gradients with certain ecological amplitude, where the ecological optimum marks the gradient peaks where the organisms are most abundant. In the gradient concept structural ecosystem properties are comprehended as concentration gradients in space and time (Müller, 1998). Any niche gradient is a peak of the fitness landscape of one environmental characteristic (Wright, 1931), which can be visualized in two-dimensional space as a graph with certain skew and width, determining the ecological amplitude. The shape of the fitness graph for certain characteristic can be plotted through the abundance of certain specimen benefitting of this characteristic. All niche gradients are situated and establish a multi-dimensional hyper-room, which axes are different environmental parameters. Thus, any learning niche in social systems is determined as a set of characteristics that people perceive and actualize as useful for their activities and wellbeing individually or in groups. Each niche gradient defines one dimension of the space. The fundamental niche term applies for all the possibly usable software tools and services, artifacts and people, while the realized niches form under the constrained conditions of resource availability.

What is the mechanism how niches appear? Previously we have described the embodied simulation as a candidate of ecological emergence of knowledge and networks. In ecological psychology and recently in learning environment design the interrelated nature of people and the environment was explained using the affordance concept. This concept we use in our elaborated framework to describe the different dimensions people actualize in the course of action with the environment.

Gibson (1979) originally defined affordances as opportunities for action for an observer, provided by an environment. The mainstream view on affordances in educational technology settings considers them as objective properties of the tools, which are perceptible in the context of certain activities. Thus, it is commonly suggested that tools have concrete technological affordances for certain performances that can be brought into a learner’s perception with specific instructions (Norman, 1988; Gaver, 1996). This use of the concept tends to ignore its relativistic nature and observer-dependence, and seems to imply that affordances should be located in the environment or specific artifacts or tools.

The interactional affordance concept that supports the embodied simulation mechanisms appears in a number of studies. Chemero (2003), a researcher from the school of Gibsonian ecological psychology, has suggested that affordances are rather the relations between particular aspects of the animal and the situations. Gaver (1996) emphasized that affordances emerge in human action and interaction and, thus, go beyond mere perception. Chemero wrote that affordances are features of whole situations (meaning the actors are part of this situation). Michaels (2003) claimed that perceiving affordances is more than perceiving relations, but it brings attention to the action-guiding information and sets up action systems to act.

Barab and Roth (2006) have noted that connecting learners to ecological networks, where they can learn through engaged participation, activates the affordance networks. Affordance networks, in contrast to the perceptual affordances described by Gibson, are extended in both time and space and can include sets of perceptual and cognitive affordances that collectively come to form the network for particular goal sets. According to Barab and Roth (2006) affordance networks are not entirely delimited by their material, social, or cultural structure, although one may have elements of all of these; instead, they are functionally bound in terms of the facts, concepts, tools, methods, practices, commitments, and even people that can be enlisted toward the satisfaction of a particular goal. In this way, affordance networks are dynamic socio-cultural configurations that take on particular shape as a result of material, social, political, economic, cultural, historical, and even personal factors but always in relation to particular functions. Barab and Roth (2006) assumed that affordance networks are not read onto the world, but instead continually “transact” (are coupled) with the world as part of a perception-action cycle in which each new action potentially expands or contracts one’s affordance network.

Affordances emerge and potentially become observable in actions what people undertake to realize their goals. Actions of other people in the environment or traces of their action serve as the triggers of new action plans. Vyas and Dix (2007) distinguished 3 levels of affordances: personal, organization/community, and culture level, which differ also on the level of how rapidly they can change. They claim that affordances of different levels influence each other. For example affordances one person can perceive may depend on the affordances the community perceives or culture uses as norms. Heft (2001) wrote that: “we engage a meaningful environment of affordances and refashion some aspects of them… These latter constructed embodiments of what is known – which include tools, artifacts, representations, social patterns of actions, and institutions – can be called ecological knowledge. Ecological knowledge through its various structural, material culture, human setting manifestations becomes an integral social and cultural part of ‘the environment’, with these social and cultural affordances constituting effective, largely material, forms of knowledge with their own functional significance, cultural transmission, and adaptation implications.” Heft’s interpretation enables to view both the information from the artifacts but also the traces of action in social software systems as important components that define knowledge ecologies.

We can conclude that we in our elaborated framework of ecological learning we support the idea that affordances are the perceived possibilities for both thinking and doing, what learners evoke and signify during their actual interaction with an artifact or tool and with each other. People determine the personal learning affordances within their PLEs. Hence, the learning affordance descriptions involve the learning action verbs, people who are involved in action, and mediators of actions (various tools, services and artifacts). Any individual conceptualizes learning affordances personally, but the range of similar learning affordance conceptualizations may be clustered into more general affordance groups eg. ‘pulling social awareness information’ or ‘searching artifacts by social filtering’ etc. These affordance clusters we may interpreted and used as the abstract learning niche gradients.The affordances as niche gradients are socially developed.

Using the affordance conception for defining learning space dimensions for the communities, we can bring the emergent ecological properties from the individual network level to the new structural level that is niches in the ecologies. Ecologies integrate many niches of different communities. The awareness of different niches is obtained by tracing the meaning-spaces and activity patterns of other people twined between the distributed real and virtual places they inhabit. If the dimensions of learning niches become unfolded they become usable for our own self-directed learning. Two aspects here are important. The meaning centred aspect suggests to use distributed PLEs to be aware of more communities and their meaning niches, and to create conditions for transferring information from one conceptual dimension to another. This precondition for cross-border meaning-building activities has been focused both in cultural semiotics as well as in the theory of Connectivism. Second aspect is finding people to learn together with. To be involved in the similar activities, similar action niches need to be used for interaction. Learning affordances enable to characterize these action niches.

Q: How spaces enable enacting knowledge?
Q: How does the ecology influence personal networks?

Previously we have defined the spaces in the Connectivism framework as learning niches. Here we assume that niches enable to enact knowledge and influence personal networks because of ecological inheritance left as feedback to the social software systems. We suggest that this ecological inheritance is the particular set of affordances and meanings left into the systems by various communities in the form of meaning- and action-relevant cues.

A recent literature in evolutionary theory emphasizes the idea of niche construction (Odling-Smee et al., 2003) as an ecological factor. It is argued, the organism has a profound effect on the very environment as a feedback loop. Organisms have influence on their environment, and the affected environment can have a reciprocal effect on other organisms of this species or on other species, creating an environment different from what it would have been before it was modified. This view challenges the convention of a distinct separation between organism and its environment. The niche-construction perspective stresses two legacies that organisms inherit from their ancestors, genes and a modified environment with its associated selection pressures. The authors assume that the feedback must persist for long enough, and with enough local consistency, to be able to have an evolutionary effect. They introduce the term ecological inheritance. Genetic inheritance depends on the capacity of reproducing parent organisms to pass on replicas of their genes to their offspring. Ecological inheritance, however, does not depend on the presence of any environmental replicators, but merely on the persistence, between generations, of whatever physical changes are caused by ancestral organisms in the local selective environments of their descendants. If organisms evolve in response to selection pressures modified by themselves and their ancestors, there is feedback in the system.

In accordance with the ecological inheritance ideas social software systems demonstrate similar interdependency between user-generated environmental influence and the development of user culture. The activities in social systems make them into the arenas of ‘produsage’ where learners’ production and consumption cannot be separated from the surrounding environment (Bruns, 2008). The concept of ‘produsage’ as a term highlights the idea of embodied action, suggesting that within the communities, which engage in the collaborative creation and extension of information and knowledge, the role of consumer and even that of end user have long disappeared, and the distinctions between producers and users of content have faded into comparative insignificance. People actively participating in social web culture and technological systems form an ecological system.

It is generally accepted that learning, and tools used by certain culture from one side, and individuals of this culture and their learning and tool-using habits from another side, are influencing and shaping each other mutually (see Vygotsky, 1978). By definition, the more social software tools are used, the better they become adjusted to the cultural habits of their users. The more user-defined interrelations between the meanings exist and can be activated by social-software, the better the systems get for social retrieval of information. The more users‘ activities in social environments are externally marked by the users, for example with machine-readable formats describing people, the links between them, and the things they create and do, the better the access to the activity-related information and people becomes. The positive side effect of it is also, that the systems obtain new qualities for monitoring and getting awareness, that would open the gateway to the otherwise non-traceble communities in which the members are not personally related into social networks through shared activities. They may or may not have an awareness of each other, but they share similar meanings or perform same type of activities. Access to such people in new environments is potentially opening a multi-dimensional place where individuals can learn from each other or where shared group activities can be initiated for learning purposes. The more people get involved into the similar activities, while evoking for themselves certain functions the social tools offer, the stronger the pressure gets of developing the systems towards facilitating this activity, and the more this activity becomes part of the learning culture in this environment. This presumes the ecological relationships between people and their objectives for action in certain learning environments, and the personally differentiated perception of meanings and tools in their surrounding environments. Such relations would alltogether dynamically shape the social software environments as places for learning.

An interesting aspect about ecological knowledge is its influence to the subsequent members of the community or other communities. Niches and their communities have interdependence and they cannot exist without each other. Besides this, some communities benefit from the niches of other communities, but these may not be existential for their wellbeing.

Vandermeer (2008) explains that if organisms construct their environments, there must be ecological consequences in addition to the evolutionary ones. He distinguishes between obligate and facultative organisms and niches, formulating assumptions how these organisms are influenced by niche construction: a) In an obligate constructive niche the organism dies in the absence of niche construction; b) In a facultative constructive niche the organism survives even in the absence of niche construction, nevertheless will benefit further from the construction, c) A facultative organism survives even in a non-constructive niche, but benefits further from the construction, and d) An obligate organism does not survive unless a constructed niche becomes available. These assumptions can be transferred to the social web environments. For example: a) Wikis and microblogging environments can be considered obligate constructive niches, where single person without the community has very little benefit of the system; while b) Blogs or social bookmarking systems may be seen as facultative constructive niches, in which keeping individual diary or collecting bookmarks gives some additional value even without the community; c) A facultative user of web systems will not rely on its’ activities on the niche construction of the other users; but d) An obligate web user has constructed its personal learning environment of community tools and services eg. of pulling feeds, and cannot function effectively without this niche construction.

4. How ecologies enable learning and knowledge?

In this chapter we try to elaborate some ideas how learning happens within ecologies. We rely heavily on the model created by Lotman (1990) of the semiosphere to explain cultural semiosis. His model depicts interrelation and semiosis as a knowledge creation between cultural spaces on the basis of meanings. Our interpretation of affordances as the equally important triggers for niche formation enables to consider that similarly to meaning-creation also the action-related information is re-interpreted and translated, creating new possibilities for enactment.

Deeley (1990) defines semiosis as a process of applying signs to understand some phenomena, reasoning from sign to sign, and intervention of new signs to make sense of some new experiences. Processes of operating within the same or between different sign systems are characteristic to problem-based learning. The simplified way of interpreting semiotic processes is by claiming that there is a complete mutual translability between signs from different systems and all the information can be transformed from one system to another without any loss until new understanding of the phenomenon under investigation has reached learners’ minds. As an improvement, Eco (2000) suggested that semiotic processes are more complex. He interpreted signs as not fixed semiotic entities but rather the meeting ground for independent elements coming from different planes and meeting on the basis of coding correlation.

A cultural semiotic Lotman (1990) assumed that separate sign systems do not have mutual semantic correspondence. Lotman (1990) wrote that any cultural semiosphere and its text-generating mechanisms depend on otherness and its semiotic input in order to forge appropriate conditions for semiotic enrichment and change. He assumed that the dynamic reconstruction of context, the alteration of meanings, and the construction of new information happens only in the communication between differences when the lack of fit between languages creates the conditions for translation. According to his theory, fixed elementary semiotic systems are abstractions. Instead, semiosphere should be regarded as an initial unit where semiotic processes take place between inconsistent semiotic spaces that people create in their minds. Lotman (1990) has defined the conception of the semiosphere as a living space of dialogical events, in which the production of consciousness and meaning can only take place through contact with an ‘Other’. He explained that during semiotic processes people always focus on those aspects of the sign systems, which are important to them. They systematize their perceptions into structured descriptions of the system, by this distinguishing also the elements that are perceived as belonging to out-of-system area or to other systems for them. Thus, a dynamic binary structure is formed in their minds that Lotman described as the semiosphere.

Binary parts of semiotic spaces – common and align contexts – are connected by translation. Stecconi (2004) suggested that during semiosis the translator relies on his notion of similarity to find and generate intuitively equivalent relations between sign systems, using abduction to make certain elements of these systems that may not have similar meanings equivalent. By this, the dynamics of semiotic structures emerge from the involvement of the out-of-system elements to the system and the upstage of the system elements to the regions with less systematic nature.

Learning ecologies are similar to the semiosphere model. Niches support the formation of binary structures, the places where learners must apply different rule-systems and languages, and can yield knowledge or find new ways how to yield knowledge. Niches enable to translate between common and align contexts not only meaning-based, but also the affordances of different niches may be integrated temporarily into ones personal learning environment for performing certain actions. The formation of the dynamic ecology for the learners depends on whether their personal learning environment evokes different affordances from different niches enabling their interrelations, and if learners perceive and start using the interrelated binary structures manifested by these emerging affordances. The software use at different, non-familiar communities may in some cases attribute totally new affordances to the software that differ from the previous cultural use of this software. One example of how this translation of affordances has appeared may be taken from microblogging environments (Mackie, 2007). Integrating one new tool may restructure the whole set of affordances people perceive in concerns of other software in their PLE.

References

Barab, S.A., & Roth, W.-M. (2006). Intentionally-Bound Systems and Curricular-Based Ecosystems: An Ecological Perspective on Knowing. Educational Researcher, 35(5), 3–13.
Bereiter, C. (2002). Education and Mind in the Knowledge Age. Mahwah, NJ: Lawrence Erlbaum Associates.
Brown, J. S. (1999, 2002). Learning, Working & Playing in the Digital Age. URL. http://serendip.brynmawr.edu/sci_edu/seelybrown/seelybrown.html
Bruns, A. (2008). Blogs, Wikipedia, Second Life, and Beyond: From Production to Produsage. Peter Lang, New York.
Chemero, A. (2003). An Outline of a Theory of Affordances. Ecological Psychology, 15(2), 181–195.
Deeley, J. (1990). Basics of semiotics. Bloomington: Indiana University Press.
Downes, S. (2005). An introduction to connective knowledge. URL http://www.downes.ca/cgi-bin/page.cgi?post=33034
Eco, U. (2000). Experiences in translation. Toronto: Toronto U.P.
Gallese V., & Freedberg, D. (2007). Mirror and canonical neurons are crucial elements in esthetic response. Trends in Cognitive Sciences, 11, 411.
Gallese, V., & Lakoff, G. (2005). The Brain’s Concepts: The Role of the Sensory-Motor System in Reason and Language. Cognitive Neuropsychology, 22, 455–479.
Gallese, V., Fadiga, L., Fogassi, L., & Rizzolatti, G. (1996). Action recognition in the premotor cortex. Brain, 119, 593–609.
Gaver, W.W. (1996). Affordances for interaction: the social is material for design. Ecological Psychology, 8(2), 111–129. URL: http://www.cs.ubc.ca/labs/spin/publications/related/gaver96.pdf
Gibson, J.J. (1979). The ecological approach to visual perception. Boston, Houghton Mifflin.
Heft, H. (2001). Ecological psychology in context. : James Gibson, Roger Baker, and the legacy of William James’s radical empiricism. Lawrence Erlbaum Associates, Publishers.
Hommel, B. (2003). Planning and Representing Intentional Action. TheScientificWorldJOURNAL, 3, 593–608.
Hutchinson, G.E. (1957). Concluding remarks. Cold Spring Harbor Symposia on Quantitative Biology, 22,145–159.
Iaccoboni, M. (2005). Understanding Others: Imitation, Language, Empathy. In S. Hurley and N. Chater, (Eds.), Perspectives on imitation: from mirror neurons to memes, volume 1. Mechanisms of Imitation and Imitation in Animals. MIT Press.
Klamma, R., Spaniol, M., Cao, Y.,& Jarke, M. (2006). Pattern-Based Cross Media Social Network Analysis for Technology Enhanced Learning in Europe, In W. Nejdl and K. Tochtermann (Eds.): Innovative Approaches to Learning and Knowledge Sharing, Proceedings of the 1st European Conference on Technology Enhanced Learning (EC-TEL 2006), Hersonissou, Greece, October 1-3, LNCS 4227, (pp. 242–256). Springer-Verlag.
Kumar, R., Novak, J., & Tomkins, A. (2006). Structure and evolution of online social networks. Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining table of contents (pp. 611–617). Philadelphia, USA.
Lin Y.-R., Sundaram, H., Chi, Y., Tatemura, J., & Tseng, B. (2006). Discovery of Blog Communities based on Mutual Awareness. Proceedings of the 3rd Annual Workshop on the Webblogging Ecosystem: Aggregation, Analysis and Dynamics. URL: http:// http://www.blogpulse.com/www2006-workshop/papers/wwe2006-discovery-lin-final.pdf
Llor`a, X., Imafuji, N., Welge, Y.M., & Goldberg, D.E. (2006). Human-Centered Analysis and Visualization Tools for the Blogosphere. Illinois Technical Report No. 2006023. URL: http://www-discus.ge.uiuc.edu/discussite/2006/11/29/human-centered-analysis-and-visualization-tools-for-the-blogosphere/
Lotman, Y. (1990). Universe of the Mind: A Semiotic Theory of Culture, Ed. and trans. A. Shukman. Bloomington, IN: Indiana University Press.
Mackie, K. (2007). A brief history of microblogging. URL http://www.blogschmog.net/2007/11/17/a-brief-history-of-microblogging/
Michaels, C.F. (2003). Affordances: Four Points of Debate. Ecological Psychology, 15(2), 135–148.
Müller, F. (1998). Gradients in ecological systems. Ecological Modelling, 108(1–3), 3–21.
Norman, D.A. (1988). The Design of Everyday Things. New York: Basic Books.
Odling-Smee, F.J., Laland, K.N., & Feldman, M.W. (2003). Niche Construction: The Neglected Process in Evolution. Monographs in Population Biology, 37, Princeton University Press.
Pecher, D., & Zwaan, R.A. (2005). Grounding Cognition: The Role of Perception and Action in Memory, Language, and Thinking, Cambridge University Press.
Rizzolatti, G., Fogassi, L., Gallese ,V. (2001). Neurophysiological mechanisms underlying the understanding and imitation of action. Nat. Rev. Neurosci. 2, 661–670
Rizzolatti, G., & Arbib, M.A. (1998). Language within our grasp. Trends in Neurosciences, 21(5), 188–194.
Scorolli, C., & Borghi, A. (2007). Sentence comprehension and action: Effector specific modulation of the motor system. Brain Research, 1130, 119–124.
Siemens, G. (2005). Connectivism: A Learning Theory for Digital Age. URL http://www.elearnspace.org/Articles/connectivism.htm
Siemens, G. (2006) Knowing knowledge. URL. http://www.knowingknowledge.com/2006/10/knowing_knowledge_pdf_files.php
Stecconi, U. (2004). Interpretive semiotics and translation theory: The semiotic conditions to translation. Semiotica, 150(1/4), 471–489.
Vandermeer, J. (2008). The niche construction paradigm in ecological time. Ecological modelling, 214, 385–390.
Varela, F. J., Thompson, E. & Rosch, E. (1991) The Embodied Mind. Cambridge, MA: MIT Press.
Vyas, D., & Dix, A. (2007). Artefact Ecologies: Supporting Embodied Meeting Practices with Distance Access. In Proceedings of UbiComp (Ubiquitous Computing) 2007 Workshops, 16 Sept. 2007, Innsbruck, Austria (pp. 117–122). University of Innsbruck.
Vygotsky, L. S. (1978). Mind in Society. Cambridge: Harvard University Press.
Wright, S. (1931). The roles of mutation, inbreeding, cross-breeding and selection in evolution. In Proceedings of the Sixth International Congress of Genetics, 1, 356–366.