1. Ecological learning design
framework
Kai Pata
Center of Educa7onal Technology, Tallinn University
Email: kpata@tlu.ee
December, 2008

2. Based on ar7cles
• Pata, K. (submiIed) Modeling spaces for self‐directed learning at university
courses. Journal of Educa7onal Technology & Society.
• Pata, K. (accepted). Revising the framework of knowledge ecologies: how ac7vity
paIerns define learning spaces? In Niki Lambropoulos & Margarida Romero (Eds.),
Educa7onal Social SoVware for Context‐Aware Learning: Collabora7ve Methods &
Human Interac7on. IGI Global imprints in 2010. [ilmumas]
• Väljataga, T.; Pata, K.; Tammets, K. (2009). Considering learners' perspec7ves to
personal learning environments in course design. Mark J. W. Lee; Catherine
McLoughlin (Toim.). Web 2.0‐Based E‐Learning: Applying Social Informa7cs for
Ter7ary Teaching. IGI Global hIp://www.igi‐global.com/ [ilmumas]
• Fiedler, S.; Pata, K. (2009). Distributed learning environments and social soVware:
in search for a framework of design.In Stylianos Hatzipanagos & Steven Warburton
(Eds.),
Handbook of Research on Social SoVware and Developing Community Ontologies.
IGI Global hIp://www.igi‐global.com/[ilmumas]
• Tammets, K.; Väljataga, T.; Pata, K. (2008). Self‐direc7ng at social spaces:
conceptual framework for course design. In: Proceedings Ed‐Media 2008 (pp. 2030
– 2038). Vienna, 30th june‐4th july, 2008. AACE.
• Pata, K.; Väljataga, T. (2007). Collabora7ng across na7onal and ins7tu7onal
boundaries in higher educa7on – the decentralized iCamp approach. In:
Proceedings of Ed‐Media 2007 (pp. 353 – 362). Chesapeake, VA: AACE.

3. Star7ng from ecologies of knowledge…
• The theore7cal framework developed by Web
visionaries like John Seeley Brown (1999;
2002), George Siemens (2005; 2006) and
others is directed towards informa(on and
artefacts, meanings and knowledge,
networks and connec(ons, in weaving
ecologies of knowledge.

4. How ecology func7ons is not clear
From “Knowing knowledge” book by Siemens (2006):
• Ecologies and networks provide the solu5on to needed structures and spaces to house and
facilitate knowledge flow (p. 86). Ecology is a knowledge‐sharing environment (p. 87).
• Ecologies permit diverse, mul5‐faceted concepts… and meanings to emerge based on how
items are organized or self‐organize (p. 87).
• Ecologies are capable of rapid growth, adap;ng to new compe;;on, differing perspec;ves,
and enabling innova;ve concepts and ideas to gain trac;on (p. 87).
• Ecologies are nurtured and fostered…instead of constructed, organized and mandated.
Ecologies are: loose, free, dynamic, adaptable, messy, and chao;c (p. 90). Ecology is a living
organism (p. 92).
• The ecology influences the forma;on of the network itself. The health of each personal
learning network is influenced by the suitability of the ecology in which learner exists (p. 92).
• The ecology fosters connec;ons to original and knowledge sources, allowing for currency.
The ecology fosters rich interac;on between disparate fields of knowledge, allowing growth
and adapta5on of ideas and concepts. Each par5cipant in the ecology pursues his/her own
objec5ves, but within the organized domain of knowledge of a par5cular field (p. 117).
• The crea5on of the ecology permits a broad‐scale implementa;on of differing knowledge
and learning experiences, permiNng employees to achieve knowledge‐based needs in a
mul5‐faceted manner, mul5ple ways, and through mul5ple devices (p. 132).

5. ..towards deepening the ecological
approach
• Siemens (2005; 2006) assumes that crea7ng meanings
and rela7ons publicly in social soVware environments
would aid through connec7ve processes the forma7on
of new knowledge ecologies and learning cultures.
• This approach is strongly 7lted towards knowledge,
meanings, communi7es and networks and their spaces
– knowledge ecosystems.
• However, the Connec7vism framework is inconsistent
in elabora(ng the ecological role of tools, ac(vi(es,
and communi(es in the forma(on and evolvement of
knowledge ecologies.

6. Elabora7ng the framework
• Siemens (2005, 2006) has built his Connec7vist
framework on the ecological understanding.
• Deepening of the ecological approach enables to
see ac(vi(es in the more central posi(on in the
knowledge ecologies.
• It is necessary to:
– elaborate the knowledge ecosystem idea,
– strengthen the role of ac7vi7es, and
– introduce the theore7cal framework how ac7vi7es are
related to the knowledge ecosystems.

7. Components in the learning ecology
framework

8. Network‐knowledge interrela7ons
• Siemens (2006) wrote in “Knowing Knowledge”: knowledge rests
and changes in the networks that connect people and their
ar5facts.
• I elaborate this:
– Tools and ac(vi(es are an ecologically entwined parts of the
network.
– Knowledge, is more than informa7on and meanings – knowledge has
an ac(vity‐ and tool‐related dimension.
• Personal learning environments (PLEs) that people construct and
use in their daily ac7vi7es are not merely the mediators, ‘the
inac7ve pipes’ that enable knowledge flow. PLEs are dynamically
evolving ac7vity systems in which the personal objec7ves and
human and material resources are integrated in the course of
ac7on.

9. Distributed knowledge inheres in
social prac7ces
• Bereiter (2002, p. 57) framed and answered the ques7on
about the nature of knowledge as follows: Where is
knowledge if it isn’t contained in individual minds?
– The kind of answer coming from ac7vity and situated
cogni7on theorists runs along the following lines:
– Knowledge is not lodged in any physical or metaphysical
organ.
– Rather knowledge inheres in social prac7ces and in the tools
and ar7facts used in those prac7ces.
– 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 liIle bits… all the knowledge is
in the rela(onships – rela(onships among the people
engaged in an ac(vity, the tools they use, and the material
condi(ons of the environment in which ac(on takes place.

10. Network in the ecological framework
• The network in the ecological framework may be
interpreted as a distributed system con(nuously
constructed of our minds and the environment
components.
• Knowledge that the networks hold is paIern‐like,
distributed between the environment and people, and
dynamically emergent in ac(vi(es.
The tool has been incorporated into one’s body image as an extended hand or forearm.
Regarding it as a tool Not regarding it as a tool
Atsushi Iriki, and Osamu Sakura
The neuroscience of primate intellectual evolu7on: natural selec7on and passive and inten7onal niche construc7on
Phil. Trans. R. Soc. B (2008) 363, 2229–2241

11. Embodied ac7on and enac7on
• Varela, Thompson & Rosch (1991, p. 149) wrote that knowledge is
the result of ongoing interpreta(on that emerges from our capaci7es
of understanding. These capaci7es are rooted in the structures of our
biological embodiment but are lived and experienced within a
domain of consensual ac(on and cultural history.
• They coined the term embodied ac5on to transmit the idea that
– cogni7on depends upon the kinds of experience that come from having a
body with various sensori‐motor capaci7es
– individual sensori‐motor capaci7es are themselves embedded in a more
encompassing biological, psychological, and cultural context.
• Using the term enac5on they focused on two points (Varela et al.,
1991, p. 173):
– 1) percep7on consists of perceptually guided ac(on, and
– 2) cogni7ve structures emerge from recurrent sensori‐motor paAerns
that enable ac(on to be perceptually guided.

12. Conceptualiza7on of objects is
dependent of our bodily projec7ons
• Lakoff and Johnson (1999, p. 20) introduce the idea of embodiment, which
incorporates our experiences as an integral part in the forma(on of
concepts.
• Previously percep7on has been associated with movement and separate
from mental processes with concep7ons. Lakoff and Johnson claim that
categoriza7on is not a product of conscious reasoning or the intellect but
results instead as a product of embodied experiences.
• An embodied concept is a neutral structure that is actually part of, or makes
use of, the sensori‐motor system of our brains. From our daily experiences
we form understanding of events and cluster them under conceptual
metaphors (eg. ahead, under, forward), our experiences drive our
formula7on of complex metaphors (eg. argument is war)
• New, embodied view of concepts considers perceptual symbols as neural
representa7ons located in sensory‐motor areas in brain. This means
concepts are not perceived as arbitary symbols but rather concepts consist
of the reac(va(on of the same neural ac(va(on paAern that is present
when we perceive the objects or en((es they refer to and when we
interact with them (Pecher and Zwaan, 2005).

13. Cognitve iceberg from Adrian Paul Harris
extended cogni7on, percep7on
Habitus ‐ sets of
interrelated Complex
Metaphors
cogni7ve unconscious Complex Metaphors (CM)
Primary Metaphors (PM)
The whole 'iceberg' triangle represents the physical body, while the area below the wavy
line represents the quot;cogni7ve unconsciousquot; (Lakoff and Johnson, 1999: 10). This contains
the Primary Metaphors (PM) that underpin Complex Metaphors (CM), and sets of
interrelated Complex Metaphors (Lakoff and Johnson, 1999) which I interpret as habitus
seen from a different perspec7ve. The physical body is engaged in a dynamic rela7onship
with the local environment through extended cogni7on, percep7on and what Gibson calls
quot;affordancesquot; (Gibson, 1979). As 95 percent of embodied thought occurs below our
consciousness (Lakoff and Johnson, 1999), most of this processing never reaches everyday
awareness, which is at the iceberg's 7p.

14. Embodied simula7on
we simulate
ac7on and
emo7on
directly
without
cogni7ve
processing
We simulate the ac7on ‘context’ and ‘culture’ play a major role in taking par7cular ac7on
traces as if doing it
Ac7ons embedded in
contexts yield a significant
signal increase (Iaccoboni
et al., 2005).

15. Distributed knowledge emerges as a
result of embodied simula7on
• Cogni7on is embodied through grounding knowledge directly
in sensory‐motor experiences without the media7on of
symbolic representa7ons (Pecher & Zwaan, 2005).
• We perceptually ac7vate certain mul7‐modal ac7on‐
poten7alites of embodied symbols that mediate our
purposeful and goal‐directed ac7ons (see Gallese & Lakoff,
2005):
– from observa7on of others and the environment (Rizzolay et al.,
2001),
– from listening narra7ves (Rizzolay & Arbib, 1998; Iaccoboni,
2005)
– from reading narra7ves (Scorolli & Borghi, 2007)
– from looking everyday images of objects or works of art (Gallese &
Freedberg, 2007).

16. Ac7on‐related cues in social soVware
systems
• When ac7ng in social learning environments not
only the meanings are newly created from found
informa7on, but also the ac(on‐related cues are
picked up from different narra(ves and from the
whole systems, and they are integrated into our
ac(on plans.
• Besides possibili7es of organizing meanings with
various ways in social learning environments,
much more aIen7on needs to be put on these
ac(on‐related cues individuals and communi(es
interact with in the environment.

17. Ecological learning framework
• Network may be interpreted as a distributed system
con7nuously constructed of our minds and the
environment components in the course of ac7on;
• Knowledge is paIern‐like, distributed between the
environment and people, and is dynamically emergent
in ac7vi7es,
• Knowledge emerges as a result of embodied
simula(on, when people perceptually ac7vate certain
mul7‐modal ac7on‐poten7alites from the environment
that mediate their purposeful and goal‐directed
ac7ons, and leave ac7on‐ and meaning traces as a
feedback to the environment.

18. Ecological learning framework
• Self‐directed learners’ common cultural learning
spaces may be characterized as abstract niches,
and the facilitators may use these niche
descrip7ons in learning design instead of learning
environment proper7es and func7ons.
• Niche characteris7cs are collec7vely determined
through individually perceived affordances during
the applica7on of personal and collabora7ve
learning environments for self‐directed ac7vi7es.

19. Components in the learning ecology
framework

20. Personal learning spaces – learning
niches – learning ecology
• To take ac7on self‐directed learners develop abstract
individual cogni(ve learning spaces (Underwood &
Banyard, 2008) ‐ personal learning environments (PLEs).
PLEs contain various material and human resources that
they ac7vate in their goal‐directed ac7on.
• Ecologies are formed when many individuals with various
perspec7ves and goals would embody parts of the
environment selec7vely in the course of ac7on while they
compose PLEs as cogni7ve learning spaces.
• Many abstract subspaces – learning niches ‐ can be formed
within ecologies. Such spaces emerge when parts of the
environment are embodied and used similar way by many
people.

21. Niches
• Hutchinson (1957) defined a niche as a region
(n‐dimensional hypervolume) in a mul7‐
dimensional space of environmental factors
that affect the welfare of a species.
• Niches have been conceptualized as the
environmental gradients with certain
ecological amplitude, where the ecological
op7mum marks the gradient peaks where the
organisms are most abundant.

22. Niche gradients
• Any niche gradient is a peak of the fitness
landscape of one environmental characteris7c
(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
characteris7c can be
ploIed through the
abundance of certain
specimen benefiGng
of this characteris(c.

23. Affordances as learning niche gradients
• Gibson (1979) originally defined affordances as opportuni7es for
ac7on for an observer, provided by an environment. He suggested
that a niche is a set of affordances that constrains possible
behavior with respect to what we are able to do in a certain niche.
• The environment in affordance conceptualiza7on does not merely
involve material objects and tools in the environment.
• Barab and Roth (2006) have noted that connec7ng learners to
ecological networks, where they can learn through engaged
par7cipa7on, ac7vates the affordance networks, which are not
en7rely delimited by their material, social, or cultural structure,
although one may have elements of all of these; instead, they are
func7onally bound in terms of the facts, concepts, tools, methods,
prac7ces, commitments, and even people that can be enlisted
toward the sa7sfac7on of a par7cular goal.

26. Learning niches appear as social
collec7on or affordances
• Affordances emerge and poten7ally become
observable in ac7ons what people undertake to realize
individual or shared objec7ves.
• Any individual conceptualizes learning affordances
personally, but the range of similar learning affordance
conceptualiza7ons may be clustered into more general
affordance groups.
• Communi7es interac7ng similarly within certain
environmental surroundings for certain learning would
define various ideal or affordances and niches.
• The crea7on of these niches is of ecological nature and
they are not part of the material learning environment
per se.

27. Feedback from cultural knowledge
• Niches enable to enact knowledge and influence personal
networks because of ecological inheritance leH as
feedback to the social soHware systems.
• HeV (2001) wrote that: “we engage a meaningful
environment of affordances and refashion some aspects of
them… These laRer constructed embodiments of what is
known – which include tools, ar5facts, representa5ons,
social paRerns of ac5ons, and ins5tu5ons – can be called
ecological knowledge. Ecological knowledge through its
various structural, material culture, human seNng
manifesta5ons becomes an integral social and cultural part
of ‘the environment’, with these social and cultural
affordances cons5tu5ng effec5ve, largely material, forms of
knowledge with their own func5onal significance, cultural
transmission, and adapta5on implica5ons.”

28. Feedback as an ecological factor
• A recent literature in evolu7onary theory emphasizes the
idea of niche construc7on (Odling‐Smee et al., 2003) as an
ecological factor. They introduce the term ecological
inheritance.
• The niche‐construc7on perspec7ve stresses two legacies that
organisms inherit from their ancestors, genes and a
modified environment with its associated selec(on
pressures.
• The feedback must persist for long enough, and with enough
local consistency, to be able to have an evolu(onary effect.
• Social soVware systems demonstrate similar
interdependency between user‐generated environmental
influence and the development of user culture.

29. Social retrieval of ac7vity‐related
informa7on
• The more user‐defined ac7vity‐related informa7on an
ac7vity traces exist in social‐soVware, the beIer the
systems get for social retrieval of ac7vity‐related
informa7on and interac7on with similar people.
• The systems obtain new quali7es for monitoring and
geyng awareness, that would open the gateway to the
otherwise non‐traceble communi7es in which the
members are not personally related into social
networks through shared ac(vi(es, but they inhabit
similar ac(vity‐niches.

30. Communi7es may be influenced by
the niches of other communi7es
• Vandermeer (2008) has defined some niche rules what I have elaborated
for social systems:
– a) In an obligate construc(ve niche the organism dies in the absence of niche
construc7on; Wikis and microblogging environments can be considered
obligate construc7ve niches, where single person without the community has
very liIle benefit of the system
– b) In a faculta(ve construc(ve niche the organism survives even in the
absence of niche construc7on, nevertheless will benefit further from the
construc7on; Blogs or social bookmarking systems may be seen as faculta7ve
construc7ve niches, in which keeping individual diary or collec7ng bookmarks
gives some addi7onal value even without the community
– c) A faculta(ve organism survives even in a non‐construc7ve niche, but
benefits further from the construc7on; A faculta7ve user of web systems will
not rely on its’ ac7vi7es on the niche construc7on of the other users;
– d) An obligate organism does not survive unless a constructed niche becomes
available; An obligate web user has constructed its personal learning
environment of community tools and services eg. of ‘pulling feeds’, and cannot
func7on effec7vely without this niche construc7on.

31. Niches in a
learning space
• The learning space
term denotes an
abstract composi7on
of dynamically
changing learning
niches.
• Within one abstract
learning space for a
certain group several
learning niches may
appear, which may
be commonly
actualized in
different phases of
the learning ac(vity.

32. Changing niches in learning space
• In a learning space people construct inconsistent personal cogni(ve
spaces (PLEs) in their minds, which in community level are perceived
as niches.
• Learner’ appropriate personal learning environment and the current
niche is determined by the exclusion of the affordances that form the
align niches – thus, always binary structures of common and align
niches exist.
• The affordances from align niches must be integrated temporarily into
ones personal learning environment for performing certain ac7ons.
For this we must translate affordances from align to our own space.
This causes us to move from one niche to another.
My current niche
where I am with My PLE Niche affodances
my PLE Align niches
Niche affodances

33. Perceived learning affordances of using an aggregator ploIed on the learning space

35. Differences between the tradi7onal
and ecological learning designs

36. An ecological learning design
framework for suppor7ng self‐directed
learning in new social Web
Promo7ng self‐direc7on with self‐chosen tools at courses:
1. Define the learning and teaching niches for your students by collec7ng their
affordance percep7ons of their learning spaces.
• To support the conscious self‐managed development of learner‐
determined spaces, provide students with the tools of visualizing and
monitoring their ac7vity‐paIerns and learning landscapes, and enhancing
public self‐reflec7on and collabora7ve grounding of learning affordances.
• To maintain coherence of the current niche, introduce cycles of re‐
evalua7on of learning affordances of the learning space within your
course.
2. Try to influence the niche re‐emergence by embedding ac7vity traces and
ecological knowledge relevant to evoke affordances for certain niches or
select ac7vity systems where these traces are naturally present.
3. Use same social learning environments repeatedly to gain from feedback
leV as ac7vity traces and embodied knowledge of earlier learners.

37. Evolving design
• Theore7cally, in the self‐directed learning process students
should be promoted to use their own personal learning
environments. Thus, the learning environment as a system
of tools and resources cannot be ready when learning starts
but has to evolve as part of learners’ self‐directed individual
and collabora7ve ac7on process in which facilitator has a
guiding role.

38. Using niches in design
• To run emergent boIom‐up courses, facilitators would
need to establish some constraints and guidelines for
planning the learning process.
• Rather than composing a list of op7onal course tools,
resources and ac7vi7es, an abstract learning space might
be determined for the course design and made explicit to
the learners.
• Learners’ percep7on of ac7on poten7ali7es of their
personal and collabora7ve learning environments –
learning affordances ‐ could be dynamically collected in a
boIom up manner during learners’ public planning of their
goals, visualiza7on, and self‐reflec7on of their learning
ac7vi7es and learning environments.

39. BoIom up genera7on of niche affordances
Affordance ontologies for coupling ac7vi7es and tools
Ployng niches on
tool landscape

40. Using niche info for planning ac7vi7es
and choosing tools
• The affordance‐based learning space descrip7on might
be re‐used in the course design as a guideline for
students and the facilitator
• Knowing the learning niche characteris7cs enables to
develop par7cular list of suggested ac7vi7es and plan
appropriate instruc7ons during the course.
• When planning par7cipa7on at the courses and for
choosing tools and resources for personal learning
environments, self‐directed students might need
informa7on of the affordances that a par7cular course
community perceives in rela7on to certain tools.

41. Using feedback from niche for
adap7ve self‐direc7on
• Knowing niche’s learning affordances and making
the abstract learning space explicit for the
learners and for the facilitator would permit:
– i) the individualized learner‐specific integra(on of
their goal‐directed ac(vi(es with other perceived
components, resources and community ac(vi(es in
the environment; and
– ii) the reuse of the commonly perceived affordances
for environmentally adap(ve self‐direc(on.

42. Dynamic monitoring of niche
• The emergence of the course’s learning space would consist
of cycles of developing and monitoring the learning niches.
• Such dynamical monitoring and grounding of the mutually
used learning affordances is possible when learner can
draw schemes of ac7vity paIerns and tool landscapes and
write public reflec7ve pos7ngs in their weblogs.
• It is assumed that if some tools were available for learners
and facilitator to visualize the niche with less analy7cal
effort during the course of ac7on, this might increase the
use of affordances as niche gradients in adap7ve shaping of
self‐directed learning.

43. Acknowledgements to….
2008 september Peeter Normak Moving between niches