Ecological principles usable in sociotechnical systems

1. Digital learning ecosystem
principles in socio-technical
systems
Kai Pata
Research group seminar, May, 2nd, 2017

2. Socio-technical system definition
• Socio-technical system is an open system where self-
organized users conduct collective operational tasks and
the system undertakes the operational delivery of task
objectives using the co-optimized social and technical
sub-systems for task performance (Maquire, 2014)
• Socio-technical affordances are the relational properties
in particular situations of a specific user-technology
system – these are action-taking possibilities and
meaning-making opportunities in an actor-environment
system with reference to actor competencies and
technical capabilities of the socio-technical system
(Vatrapu, 2009).
• M. Maquire, (2014). Socio-technical systems and interaction design – 21st century relevance. Applied
ergonomics, 45, 162-170.
• R.K. Vatrapu (2009). Towards a theory of socio-technical interactions. Learning in the Synergy of
Multiple Disciplines. LNCS 5794, 694-699
User agents
Functionalities
Flows
FEEDBACK
SUPPORT
AGGREGATE
INTERACT
CONSTRUCT
affordances

3. Examples of socio-technical systems that may
be considered digital learning ecosystems
• Portfolio-based learning communities (Tammets, Pata, Laanpere,
2013), we could see eDidaktikum as one
• Professional practice sharing forums (Pata et al., 2016)
• LePlanner authoring system (Pata et al., 2017; Beliajev, 2017), further
we could see socio-technical systems composed around eSchoolbag,
eDiary systems, authoring learning scenarios etc.
• Open learning ecosystems (Laanpere, Pata, Normak, Põldoja, 2014;
Pata & Bardone, 2014) such as we use for teachig
• Digital service provision in schools (papers with Quaicoe, Jeladze) –
example case in the end provides generalized approach in progress.

4. Teachers’ (T) and domain
experts’ (O) socialization
activities were categorized as
S_T and S_O.
Externalization activities were
divided into ‘writing a blog
entry’ E(Entry)T or
‘commenting on a blog’
E(Comment)T or
E(Comment)O.
Combination activities in the
forum were categorized as
C_T and C_O.
In addition, the activity ‘view’
was categorized as View T and
View O and this included
viewing the weblogs, forums
and materials.
Bayesian network model of dependencies - Interdependence of teachers’ and domain experts learning and
knowledge building interactions in Tammets, Pata, Laanpere, 2013

5. Interaction in professional forums indicating the
communicative flows ( Based on Pata et al., 2016)
Common for nurses
Common in building sector

6. Digital Learning Ecosystem principles: components
• Diversity of DLE components (broad definition of DLE community):
variability within each type:
• Humans (and digital agents) as DLE species - variability in characteristics and
behavior due to their intentions, perceptions and cultural belonging ( narrow
definition of a community)
• Digital tools, artifacts as DLE species – variability in functionalities, content
and form
• Services as DLE species (lichen-like symbionts)
• Kinds of components (relates with their positioning in transforming
knowledge similar to autotrophes, heterotrophes, decomposers): may
be agent interaction levels with DLE like consume, react, interact,
expand, create etc.

7. Digital Learning Ecosystem (DLE) principles:
structure
• Network of kind of components, such as DLE services and agents
• The permeability of a natural ecosystem for the circulation of energy and
materials will depend on the nature of the 'architecture' of the
components of the system, the connections in the trophic chains and the
side-paths and hubs in the trophic web and characteristics of individual
species.
• Types of flows. Information flow, networking, learning flow, data flow
• Agent level view: agent-agent interaction; agent-system interaction
• System level view: structural (density, closeness of components), flows
within the system,
• Agent-system feedback loops: niches, signals, traces

8. DLE principles: communication- and
transformation related flows
• Agents’ attention and interaction to DLE creates different tool-, artifact-, service-
activation and triggers flows (less services is more attention)
• Agents use DLE services for passing knowledge (between same type of agents, across
different types of agents – cross cultural agent communication) (hubs within DLE)
• Agents use services for transforming knowledge in DLE (locational closeness of services,
reactiveness across services)
• Agents offloading some knowledge temporally to the DLE
• Agents’ guided attention using DLE services to enact the offloaded signals, traces of
knowledge
• DLE piping the transformative flows between the service nodes
• Transformation of information to new energy rich states and levels – maturing
knowledge
• Note. In ecology energy flow refers to the flow of energy through the trophic levels of
food chain. At each trophic level about 90 % of energy is lost at metabolistic
transformations. How much energy would DLE knowledge transformation loose at
different knowledge maturity levels?

9. Affordance preferences of LePlanner as a socio-technical system (Beliajev, 2017)

10. DLE principles: transformation flow
• DLE agents and services enable to permeate the transformative flow
through the learning ecosystem
• From “information” to “knowledge” (Frielick, 2004; Reyna, 2011).
• Services may be differently activated by different types of agents, this may
cause different temporal transformative flows to pass the DLE.
• For different communities of agents different temporal niches may be
activated within the DLE.
• Niches within DLE provide areas of fitness for certain types of agents’
behavior, productivity (distance, coverage, overlap of niches)
Frielick, S. (2004) Beyond constructivism: An ecological approach to e-learning. Proceedings ASCILITE 2004, 328-332.
Reyna, J. (2011). Digital Teaching and Learning Ecosystem (DTLE): A Theoretical Approach for Online Learning Environments.
Proceedings ASCILITE 2011, 1083-1088.

11. Affordance niches of LePlanner defined by users (Beliajev, 2017; Pata et al., 2017)
Functionalities at different screens of LePlanner

12. DLE services - creativity, innovation
• Innovation in the service system requires transforming the current
communicative and transformative flows between the agents/ service nodes
in DLE.
• Creativity arises from an novel message translation/transformation between
the agents/service nodes of the ecosystem, from creating new knowledge
transformation paths
• DLE agents and Service nodes possess volatility – reactivity of nodes
• Service nodes can create a new service if there is high volatility, reactiveness
• Reactiveness increases interconnectivity between agents/service nodes
which in turn increases the transformation flow permeability in DLE
• It requires extra energy being spent to reorganize, stabilize the DLEs

13. DLE principles: maturity states
• Ecosystems undergo ecological succession (Golley, 1994).
• Succession is a kind of DLE maturing process
Succession of biological community
• Odum (1969) proposed several energy-related
trends to be expected in the growth and
development of ecosystems from early to mature
stages.
• its physical structure increases
• feedback increases (including recycling of energy and
matter);
• entropy production decreases at mature states
• Information increases
• Note. A measure to quantify maturity in
ecosystems is proposed based on the analysis of
flows of biomass (Perez-Espania, 1999). What
flows could DLE use for maturity indicator? How
to quantify measuring those flows?

14. Ecosystem effectiveness
• Productivity - the ability of systems to accumulate energy in matter
in time
• Permeability - Lotka–Odum’s hypothesis states that an ecosystem
develops towards maximizing power (Lotka, 1922; Odum and
Pinkerton, 1955), interpreted as the highest possible throughflow of
energy.
• Entropy is kept lower within the system than beyond its borders,
entropy (disorder)production is minimized
• Smartness – directedness to successive changes

15. Ecosystem effectiveness: entropy
• Entropy – a measure of “disorder” - is a measure of how organized or
disorganized a system is, of the number of ways in which a system may be
arranged (the higher the entropy, the higher the disorder).
• Note. Biosystems may maintain local order (low entropy) within their system
boundaries compared with the space around them.
• Schrödinger (1944): Fairly high level of orderliness (= fairly low level of entropy)
really consists of continually sucking orderliness from its environment”.
• Energy needs to be spent to create order in DLEs, then entropy level decreases.
Naturally, if systems increase and evolve (that is accompanied by innovation),
there is more disorder, entropy level increases.
• Note: To what extent, how frequently DLEs can afford innovation to restructure
them, not that it results in energy overconsumption or new disordered system?

16. Ecosystem effectiveness: entropy
• Ecosystems grow and develop in four progressive growth forms reflected in boundary, structure,
network, and information relationships.
• Boundary growth brings the input of low-entropy material into the system.
• Exergy dissipation is dependent on the exergy capture or the ability of the ecosystem to divert a greater amount
of low-entropy energy across its border.
• Structural growth as a result of the increase in the amount, number, and size of components in the
ecosystem
• System with greater exergy is moved further from its reference state.
• Exergy dissipation refers to the energy given off by breaking down the high quality, low-entropy energy
(orderliness) for both growth and maintenance of the system.
• Network growth is growth in connectivity of the system through additional energy–matter
transactions and internal organization of the system
• System connectivity and cycling increase through additional network transactions retains the energy–matter
within the system boundaries for a longer time and further increases the throughflow and structure (exergy
storage) in the system. As a result, specific entropy production decreases.
• Exergy storage increases during ecosystem development (Jørgensen et al., 2000; Jørgensen, 2002; Fath et al.,
2001).
• Increased performance within the system by qualitative growth in system behavior from exploitative
patterns to more conservative patterns, which are more energetically efficient

17. DLE effectiveness: Smartness
• Smartness as DLEs effectivity to be adaptive to dynamic changes – monitoring and
reorganising, closing services and resources that do not get agent attention are not
fit to their needs; predicting agent behaviors that are fit to future DLE states and
boosting up new relevant services (but these in turn require energy to be spent).
• Smart specialization – creating within a socio-technical regime and sustaining by
design niches for special fitness (such as adaptiveness ecological energy crisis,
human-machine society) of certain kind of agents.
• Giovanella, C. (2014) : The smartness or attractiveness of an ecosystem does not
depend exclusively on its ability to run “all gears” in an effective and efficient
manner. It, rather, depends on its ability to create an environment able to meet
the individuals’ basic needs and keep them in a state of positive tension in which
their skills are stimulated by adequate challenges, to favor the achievement of
the self-realization (that is a Flow state)
• Note. How can DLEs discover the potentially more stable, agent-environment fit
future states and validate these? (monitoring chance seeking agents…) Which
niches do the futuse states require? Which agents do future DLEs host?
• Giovannella C. (2014). Smart Territory Analytics: toward a shared vision. In: SIS 2014, CUEC.

18. Case: School as a digital learning ecosystem
• Based on digital learning services
data from Ghanan, Georgian,
Estonian internal and external DLEs
cases were clustered to 3 types
(assuming discovering DLE
maturity types)
• Structural components: digital
infrastructure, computer class,
mobile tools, digital resources
• Transformative components: ICT
training, ICT incentives, ICT
support, ICT rules, ICT change
management
• Flow components: digital
information management,
networking among teachers,
learning with ICT, analytics with ICT Cluster 1 – 12 cases, Cluster 2 – 27 cases and Cluster 3 - 13 cases

19. Case: School as a digital learning ecosystem
• Type I. Digitally starting but
still mostly non-digital
• Applying transforming
components with low
connectivity to other DLE
components, ICT training is
the main transformative
process that has impact in DLE
on and is influenced by Digital
information management and
Learning with ICT in schools,
as well as on Digital
Infrastructure of schools.
Transforming components Flow componentsStructural components
Boundary growth brings the input of low-entropy material ( training) into the system.

20. Case: School as a digital learning ecosystem
• Type II. Between
not digital-digital
successive states.
• Low level of
transforming
components, low
level of flow
components,
more
interconnected
DLE components.
Transforming components Flow componentsStructural components
Network growth is growth in connectivity of the system through additional energy–matter transactions and
internal organization of the system. The energy is given off by breaking down the high quality, low-entropy
energy (orderliness) for both growth and maintenance of the system.

21. Case: School as a digital learning ecosystem
• Type III. Digitally
transformed.
• High level of
structural
components and
flow components
is achieved with
moderate level of
transformation
components that
are well
connected with
both.
Transforming components Flow componentsStructural components
Increased performance within the system by qualitative growth in system behavior from exploitative patterns
to more conservative patterns, which are more energetically efficient

22. To do: Ecologically informed metadesign in
DLEs.
• Metadesign is providing the DLE design elements that enable to
lessen the degrees of freedom of agents’ behaviour
• Meta-design requires data from DLEs.
• Meta-design promotes constrained self-organization of DLEs.