Termites in the Schoolhouse: Stigmergy and Transactional Distance in
an E-learning Environment
Jon Dron PhD, School of Computing, Mathematical and Information Sciences, University of Brighton, UK,
<jon.dron@brighton.ac.uk>
Abstract: Transactional distance theory predicts an inverse relationship between
dialogue and structure in an educational transaction. It is a powerful theory, but it may
have exceptions. This paper discusses a class of computer-based educational
environments that anomalously seem to combine both high dialogue and high structure.
In such systems the behavior of users changes their environment, which in turn causes
changes in the behavior of its users. Such processes are a form of stigmergy, a word
originally used to describe this effect in termites, where it coordinates the formation of
termite mounds. Stigmergy in an e-learning environment can enable a self-organized
structure to arise out of dialogue, simultaneously providing both high and low
transactional distance. Environments built this way may be very flexible learning spaces.
A number of exemplars embodying the principle are described, followed by an
exploration of unresolved issues and directions for future research.
Introduction
This paper explores an approach to the design of e-learning environments whereby structured educational
activities can emerge automatically through computer-mediated dialogue-based processes. The
consequences of this approach are profound, leading to a justification from first principles that welldeveloped instances of such environments are potentially superior to traditionally designed e-learning
systems.
Transactional distance
Michael Moore’s theory of transactional distance postulates that for all educational activities, distance is a
pedagogical rather than a physical phenomenon. This implies that what is interesting to practitioners is not
physical or temporal separation, but the interplay of communication and interaction with the structure and
organisation of the experience (Moore & Kearsley, 1996). At the heart of the theory is a simple equation: in
any educational activity it is demonstrable that the greater the structure, the lesser the dialogue and vice
versa. There is a negative feedback loop driving this equation which makes this into one of the nearest
things in educational theory to a universal law. Founded in practical research and logical reasoning, it
makes clear predictions about any educational activity. Saba and Shearer have performed experiments that
seem to confirm the law to be true in practice (Saba & Shearer, 1994). The logical necessity of the
predictions of transactional distance theory is compelling. It is intuitively obvious that the more people talk
the less structured the experience will be, as people say unexpected things and express conceptions and
misconceptions in unpredictable ways. Similarly, the more control that a teacher exerts using elements such
as learning objectives, content themes, assessments, structured paths through learning resources, exercises
and presentations, the fewer the opportunities for discussion. Transactional distance theory applies whether
we like it or not and the relationship between structure and dialogue is (at least in broad terms) immutable.
Increase one, and the other decreases. It is probably impossible to achieve high levels of both
simultaneously.
Knowing the law of transactional distance can be very helpful when designing courses although, like the
law of gravity, it would be hugely beneficial were it possible to break it. Through the use of a special class
of networked application, this paper suggests a means of doing just that in order to achieve both high and
low transactional distance in the same learning environment.
Courses, teachers and dialogue
Moore and Kearsley describe dialogue as:
“a term that helps us focus on the interplay of words, actions, and ideas and any other interactions between
teacher and learner when one gives instruction and the other responds” (Moore & Kearsley, 1996).
Moore and Kearsley are clearly thinking of traditional forms of instruction which are mediated by one or
more individuals (teachers) and conceived of in terms of courses. This seems over-constraining. For
example, Darby splits e-learning into three generations. The first of these replicate (usually badly)
traditional modes of teaching. The second are designed from first pedagogical principles and make use of
the strengths of the medium, but still see education as course-based and instructor-led. The third generation
break free of these restrictions and involve things like just-in-time learning, navigation through knowledge
management systems and personalised curricula (Darby, 2003). If transactional distance is a feature of first
and second generation systems, it is likely to be equally valid in third generation systems. This is a good
thing as, in real life, many forms of educational transaction take place outside a formal course and without
the involvement of a teacher. One has only to stand in a common room, bar, coffee shop or smokers’ corner
in any modern university to hear a huge range of formative educational dialogues taking place. Even within
a formalised setting, student-led seminars are commonplace and groupwork activities, though set and
perhaps initially structured by teachers, are often largely organised, structured and sustained by the learners
themselves once they are underway. Similarly, many activities at academic or other conferences are
primarily learning experiences without necessarily being mediated by a teacher or even an expert – a group
of peers working in a SIG or a panel may (or may not) operate this way, for example. In the 1970s Alan
Tough discovered that the average adult spends approximately 200 hours each year on informal learning
activities, although his statistics admittedly included instructor-led evening classes (Tough, 1979). Just-intime learning does not always rely on a relationship between teacher and student for its structure – for
instance, a Google search or trawl through a knowledge base or even a flick through an encyclopaedia is at
best only distantly connected with a teacher role, even though the resource that eventually becomes the
object of learning may have been designed by someone with instructional intent. Educational transactions
are therefore not necessarily reliant on the course-centric trappings of traditional educational forms.
Structure does not have to be designed by an expert pedagogue, nor does dialogue need to be mediated by a
teacher.
Stigmergy
Moore’s definition of dialogue is broad, and admits a large number of interactions beyond verbal
discussions that may be significant contributors or constituents of a dialogue. For example, actions, nonverbal communication and tacit assumptions (i.e. information that it is unconsciously assumed to have
already been communicated) may form part of this process. Such components may be forms of implicit
communication, whereby the intention of the communication may be hidden, assumed, indirect, embodied
in an action or a by-product of another process. One such form of communication, stigmergy, has the
interesting characteristic of being concerned with an explicit relationship between structure and dialogue.
Though not discussed by Moore, from the point of view of transactional distance it might thus occupy a
very privileged position.
What is stigmergy?
The term stigmergy was originally coined by Grasse (Grasse, 1959) to describe the processes that lead to
the formation of termite mounds. It is a form of communication where signs left in the environment later
affect the behaviour of others. Termite mounds achieve their complex cathedral-like structures because
termites bind lumps of mud with pheromone-laced saliva and are more inclined to drop lumps where the
scent of pheromones is strongest. This leads not only to clusters of mud piles which grow upwards, but also
to the towers so-formed to grow towards each other, creating complex arches and ornate structures. The
same kind of process leads to ant trails. Ants wander aimlessly until they find food, after which they return
to the nest leaving a trail of pheromones. Other ants encountering a trail of pheromones are likely to follow
it. If they too find food, they too will return to the nest with it, leaving their own pheromone trails. The
cumulative pheromone trail becomes stronger and stronger, attracting more ants from further afield. The
system continues on this positive-feedback loop until the food runs out, after which the pheromone trail
fades. A significant feature of this process is that trails inevitably form along the shortest paths to the
largest and/or most accessible source of food. Like the formation of termite mounds, stigmergy thus results
in a kind of collective intelligence. The same process underlies many human activities. For example, stock
exchanges and money markets exhibit similar qualities, where money or stocks act as signs for others to
invest, strengthening the signal so that still more others follow. If all else is equal, stock, share and currency
prices are self-adjusting and not the product of individual plans. The most that can be done is to influence
their behaviour, not to determine it.
Stigmergy as dialogue
There are reasonable grounds for believing that stigmergy is a form of dialogue, as:
1
There is an exchange of information through signs left in the environment;
2
this exchange is two-way and can continue over a prolonged period (for example, termites do
not only drop a single ball of mud).
This may be controversial. Communication in the conventional sense is not just about an exchange of
information, but also about the intentions behind that exchange. Bobcats leaving footprints in the snow do
not mean to communicate their presence, but in contrast when they mark out their territory with urine there
is a definite intention to leave a message (Franklin, 1996). In stigmergic systems the relationship between
intention and message is always oblique. Individual termites do not intend to build cathedral-like structures
and it is doubtful whether they “intend” any form of communication at all. Such structures result from a
large number of local and unintelligent interactions, with any intelligence or intentionality residing in the
system as a whole, not the individuals that constitute it. The presence or lack of intelligence in individual
communicants is not a relevant factor in stigmergic systems. For instance, money markets are driven by
large numbers of intelligent and rational decisions of individuals, but each individual’s intention is to make
a profit, not (usually) to shape the market or to influence others. The stigmergic signals are thus not the
result of the intended communication, but are an emergent behavior of the system as a whole. Whatever the
original intentions of the individuals, structure in stigmergic systems arises as a direct result of their indirect
communication, interactions and behaviour. In other words, structure arises from dialogue.
Uses of stigmergy in e-learning environments – some examples
Some evidence of stigmergic behavior may be found in many online e-learning communication
environments. For example, users may be drawn to discussion forums with a lot of activity (or they may be
repelled if the threads are too deep and convoluted). The titles and structure of the messages act as signs
which influence other users. Where such forums allow the use of other cues such as icons to represent
broad classes of messages or message counts, there may be further layers of stigmergic signals to help
learners discern more structure in the discussion than that which is enabled by threads alone. There is also a
sense in which the reification of the discussion forum may sometimes be considered as a structured
resource in itself, although under normal circumstances this probably stretches the definition of structure
too far.
Google, a popular choice for information seekers, also exhibits some stigmergic effects. Its PageRank
algorithms make use of a process of latent human annotation, whereby the position of a page in the list of
returned results is (at least partly) determined by the number of links from other pages pointing back to it
(Kleinberg, 1998). Because users tend to only view results from the first page or two that are returned, this
mechanism is self-reinforcing. Users will only place links on their own pages to others that they know
about. If the primary means by which they come to know about such pages is Google itself, there will be a
self-organizing positive feedback loop that makes popular pages remain that way. The behaviour of users is
influenced by the signs (links) left in the environment and those signs themselves create the structure of that
environment – in other words, the system operates through stigmergy.
More interesting to this discussion are systems that have been explicitly designed to capitalise on the effect
to benefit learners. The five examples given below are merely representative illustrations of such systems
and none yet achieve the kinds of structure or dialogue that characterise more traditional educational
transactions. However, they point the way for systems that may follow.
Example 1: CoFIND
CoFIND is a system that explicitly attempts to generate structured groupings of learning resources through
self-organising processes of stigmergy and evolution driven by the collective behavior of users of the
system (Dron, Mitchell, & Boyne, 2003). Social navigation guides and is guided by the interactions,
combined with explicit and implicit ratings, and classifications provided by its users. It employs reusable
metadata described as qualities (a more accurate term might be “virtues”) which are added by users to
describe why particular resources are valuable. Evolutionary mechanisms driven by social navigation
continuously shift the relationships between these user-generated metadata in a constantly adapting dance
which adjusts to the needs of the group of users that make up its community. Because of the rich and
complex relationships between metadata used for ratings, CoFIND is capable of generating an intricate
structure where small ecosystems of related metadata co-evolve into an ever more refined pattern
determined by the interests and intentions of its users. The more it is used (the greater the dialogue) the
greater the structure.
Example 2: SEO
Like CoFIND, SEO is third-generation learning system based explicitly on stigmergic and evolutionary
principles. Using an agent-based architecture where software agents represent real people (experts and
others), in an explicitly ant-trail influenced manner it answers questions posed to it. Using an artefact
known as a Kempelen Box, an idea inspired by the eighteenth century “Mechanical Turk” chess playing
machine (Small, 2001), agents in the box (which represent/act on behalf of real people) are able to answer
questions. They cluster into stigmergically organised groups in which evolutionary processes constantly
replace weaker with stronger members. The box adapts to the kinds of question that are asked of it. Like
CoFIND, structure is determined by communication. Systems used by different groups with different needs
will develop into quite different forms.
Example 3: Jasper
Jasper is a VRML interface wrapped around a system known as the Information Garden (Crossley, Davies,
McGrath, & Rejman-Greene, 1999). It represents document URLs graphically as flowers in a garden, with
similar documents clustered together. Flowers that have been recently visited move slightly, as though in a
breeze. Flowers that are little used wither and die, or can be pruned by the users. Users are represented by
avatars within the garden which indicate levels of activity based on mouse clicks, keyboard presses and
emails, thus providing an indication of perceived availability. Users can take cuttings of flowers to grow in
their own gardens. Like CoFIND and SEO, the system adapts to the group of users who access it: the
simple act of using it results in an implicit dialogue with other users, especially through the movement of
flowers, the appearance of one’s avatar or the health of the blooms. Although there is a relatively low level
of explicit communication, the social navigation cues it provides are an especially powerful stigmergic
mechanism. Users are drawn to the colour and movement of flowers and repelled by those that have
withered. Structure arises from dialogue.
Example 4: EDUCO
EDUCO uses social navigation features to indicate both the historical popularity of documents and the
current activity of users of the system (Kurhila, Miettinen, Petri Nokelainen, & Tirri, 2002). In this way, the
actions of users influence the actions of others. Documents that have been popular are emphasized and thus
draw users to them. By showing the location of current users in the pool of available documents, people are
more inclined to join them. EDUCO provides a chat mechanism as a further lure, thereby giving more than
one reason to visit documents together. The more visitors that are present, the more interesting the
experience of joining them is likely to be (up to a point). This combination of both implicit and explicit
dialogue creates a self-adjusting embodiment of Moore’s law of transactional distance. Combining structure
and dialogue in a constantly changing environment, the system adapts to and its structure is created by the
interactions of its users.
Example 5: Epimethea
Though informed by different self-organising principles, Epimethea, formerly known as The Pavement
(Dron, 2003), bears some structural similarities to EDUCO. Like EDUCO, it is a real-time system using
social navigation to provide a communication-based approach to browsing. Like CoFIND, Epimethea is
designed to recommend sites, and to provide self-organizing structure through stigmergy. In some ways it
may be thought of as a collaborative web-browser, where users are able to look at sites together and
conduct conversations in real time while located at those sites. If the Web is thought of as a city,
Epimethea may be thought of as a sidewalk. This is unsurprising as the principles from which it is derived
are based on the dynamics of cities as described by Jacobs in The Death and Life of Great American Cities
(Jacobs, 1961), in particular drawing on community dynamics, the use of sidewalks and explicit
valorization of diversity in the resources that it brings together. Like EDUCO, the ever-changing interplay
of structure and dialogue forms an educational environment that constantly adapts to its community.
Discussion of the implications of stigmergy in e-learning environments
If it is true that structure in stigmergic systems can arise from dialogue, a learning environment based on
stigmergic principles may provide very tangible benefits. On the one hand, by definition stigmergy implies
that there is communication between learners, albeit indirectly. On the other, this communication actually
creates that environment, giving it structure and form. Because the processes are interlinked indirectly, the
two may occur in the same environment simultaneously. For instance, in most of the exemplars listed
above, the simple act of using the system is a form of communication and has direct impact on the structure
of the system itself. However, such communication may be unintentional or at best tacit and therefore, from
a cognitive and thus pedagogical perspective, pose little threat to transactional distance theory.
All the systems described above involve some explicit communication, be it through annotations (EDUCO,
CoFIND, Epimethea, Jasper), ratings (CoFIND, Epimethea), chat (EDUCO, Epimethea), publication of
links to websites (CoFIND, Epimethea, Jasper), answering questions (SEO) or providing recommendations
(CoFIND, Jasper, EDUCO, Epimethea). An individual experiencing learning in such a system will either be
involved in a dialogic relationship with others or will experience a structured view of it, but not both at
once, so the law of transactional distance is not broken. However, the learner will have the choice at any
moment to move between a dialogue-based learning experience and one determined by the resulting
structure. From the point of view of a teacher or instructional designer, this provides a kind of order for
free. From the perspective of the learners, it enables dialogue to occur in an undemanding and natural
manner combined with the ability to approach any part of the learning experience in ways that suit their
current (and ever changing) learning needs.
In a closed system and in accordance with the principles of transactional distance, the generation of
structure might lead to a state of stagnation, where structure dominates and communication comes to a halt.
However, if systems are designed with embedded stigmergic, evolutionary and other self-organising
processes, they may become what Prigogine calls complex adaptive systems (Hartwell, 1995). Such
systems are open, exchanging information (energy) with the environment. Generated by their users and
fuelled by the ever-changing Internet, they will only ever achieve meta-stability. Structure will necessarily
change according to use. They are not fixed systems but are instead learning ecologies (Seely Brown, 2000;
Siemens, 2003). Subject to constant perturbation and an influx of information, much as natural adaptive
systems are fed with energy and driven by change, they will never settle down to a single fixed state.
If this argument is sound, it suggests that well-developed instances of such systems should become a
central focus of research and development in learning technologies as, perhaps for the first time, from first
principles they have a demonstrable pedagogic benefit.
Problems: effectiveness, sequence and pacing
Although the exemplar systems described briefly in the previous section generate structure through
dialogue in self-organising ways, the structures they produce are mostly more to do with clustering and
implicit recommendation than with the richer kinds of structures provided by real teachers. Evolutionary
processes may help to ensure that clusters of resources or learning objects are high quality, reliable and
useful, but this is far from the end of the story. In particular:
 Just because there is structure and dialogue, there is no guarantee that it is pedagogically useful or
effective. Work is needed to design such systems so that the emergent structures generated through
stigmergy perform useful work for the participants in the community and dialogues can be guided
in ways that benefit learners;
 as yet, there appear to be no systems that can provide a genuinely self-organised guided path
through a set of learning objects or resources. Given the degree of understanding required to
generate such a structure this is unsurprising. Simply combining paths from the behaviour of
previous users is unlikely to provide a meaningful experience to new visitors to a system as the
emergent intelligence of a stigmergic system is not the sum of the intelligence of its participants.
Although stigmergic systems amplify the preferences of their users, the product (being emergent)
does not reflect the same level of intelligence as the individual interactions which created it in the
first place. For instance, a collectively synthesised narrative is unlikely to be coherent.
Collaborative filtering technologies may provide some of the tools that will make this possible by
matching paths of users with others exhibiting similar behaviours, but much research and
development is still needed in this area;
 Moore & Kearsley identify pacing as an important structuring role in educational systems (Moore
& Kearsley, 1996). Like sequencing, it is not easy to see how this could be achieved using
emergent processes of the sort considered so far.
Conclusion
The arguments presented here give some grounds for believing that there is something special about
systems that combine social navigation and self-organising principles to generate e-learning transactions.
There are hints that such systems are potentially capable of achieving an optimal mix of structure and
dialogue adapted to the individuals or groups that use them. This model of e-learning embodies a symbiosis
between human communities and the machines that support them, each compensating for the weaknesses of
the other while at the same time adding value to its strengths. Existing systems have begun to scratch the
surface of the world of possibilities that this presents but there is a pressing need for further development
and research.
As part of an instructional designer’s toolkit, the promise of systems derived from the likes of CoFIND,
EDUCO, SEO, Epimethea or Jasper is that they might one day provide a means of simultaneously reducing
and extending transactional distance. If even small inroads can be made into disrupting the inverse
relationship between structure and dialogue demanded by transactional distance theory, the potential value
to learners and educators may be immense.
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