Dynamic Theory of Organizational Knowledge Creation, by Ikujiro Nonaka (Part I)


as in a continuous dialogue between tacit and explicit knowledge: the distinction represents the epistemological dimension to organizational knowledge creation; while individuals produce develop new knowledge*, organizations still play a critical role in articulating and amplifying that knowledge. communities of interaction (pe informal) contribute to this through social interaction,  (ontological dimension of knowledge creation)

*the role of the individuals: they are committed to recreating the world in their own perspectives through

  • intention: any consciousness is a consciousness of sth; it creates the possibility of meaning and limits its form
  • autonomy: by allowing people to act autonomously the org may increase the possibility if introducing unexpected opportunities; connected to higher motivation; it gives individuals the freedom to absorb knowledge
  • fluctuation: as in the continuous interaction with the external world; chaos or discontinuity can generate new patterns of interaction; order without recursiveness; periodic break downs are triggered by env fluctuation;

the dominant organization paradigm: a system that ‘processes’ information or ‘solves’ problems, its task being making decisions in an uncertain environment. the input-process-output sequence, however, leaves out the important part of what is created by the organization in the process of problem-solving. the view of knowledge in traditional epistemology is absolute, static, and non human expressed in propositional forms of logic. in the theory of knowledge creation knowledge is a dynamic human process of justifying personal beliefs.

  • information: commodity capable of yielding knowledge; a flow of messages; information, seen from the semantic standpoint, literally means that it contains new meaning; information consists of differences that make a difference
  • knowledge: information produced belief that the information a person receives is relative to what he or she already knows about the possibilities at the source; it is created and organized by the flow of info; explicit or codified is knowledge that is transmittable on formal, systematic language,it is discreet or digital; tacit is when knowledge has a personal quality which makes it hard to communicate, it is rooted in action, it involves both cognitive (mental models) and technical (concrete know-how) elements.


four patterns of interaction between tacit and explicit knowledge_knowledge conversion

  • tacit to tacit: otherwise referred to as socialization; happens through interaction between individuals, no language required but observation, imitation, practice; the key to acquiring it is experience, in fact it is the shared experience
  • explicit to explicit: otherwise referred to as combination; use of social processes to reconfigure existing information  (aka modern computer systems)
  • tacit to explicit: otherwise referred to as externalization; by recognizing contraddictions or by resolving them through analogy
  • explicit to tacit: otherwise referred to as internalization;

The interactions between tacit knowledge and explicit knowledge will tend to become larger in scale and faster in speed as more actors in and around the organization become involved. Thus, organizational knowledge creation can be viewed as an upward spiral process, starting at the individual level moving up to the collective (group) level, and then to the organizational level, sometimes reaching out to the inter-organizational level.


Nonaka, I., 1994, A Dynamic Theory of Organizational Knowledge Creation, Organization Science, Vol. 5, No. 1. (Feb., 1994), pp. 14-37.

Images available here 

Virtual Design Studios


Bradform, Cheng and Kvan describe their impressions of a VDS realized in early 1994 between the University of Hong Kong, MIT, ETSAB Barcelona, Cornell University, Washington University of St Louis and UBC in Vancouver.

Authors describe VDS as an experimental environment for design education that allowed students to work collectively with colleagues from different cultures. Content was exchanged through a shared server. Communication mostly occurred via e-mail (asynchronous). Real time collaboration (synchronous) occurred less often via teleconferencing software and various interacting whiteboards.

The Virtual Design Studios main tools that were used were:

  • CAD
  • Internet
  • Teleconferencing
  • Whiteboards

The main problems noted were: lack of constant interactivity, student poor representational skills through digital media, lack of collaborative attitudes.



Bradford, J.W., Cheng, N., Kvan, Th., 1994, Virtual Design Studios_eCAADe Proceedings, available here

Image available here

The Not-Yetness term.

Openness as transparency between students; communication between students and the outside world; interdependent relationships between educational institutions and external practices ( Dalsgaard and Thestrup). This paper asks if openness is a absolute positive.

The authors claim that:

  • a. the binary between open and closed is false: closed is associated with hierarchy and repression while openess represents creativity and innovation, a total liberation from the constraints of formal study (…) all forms of openess entail forms of closed-ness (Edwards), educators decide what forms of openess are justifiable pedagogically and ideologically.
  • b. the overemphasis on access homogenizes learners and contexts: not all individuals require simply access to content in order to learn; OER emphasis on replication presumes uniformity of learners (…) complexity reduction is problematic (McArthur)
  • c. open does not attend issues of power and inclusion: OERs could be reproducing asymmetric power relations between those who produce and those who passively assimilate the offerings (…) access is not enough unless it is seen in a context of social inclusion and justice

Not-Yetness is a response to dominant discourse of using technology in education: accepting risk and uncertainty of practices in flux while setting boundaries and looking for alternative modes of openness in digital education where there is an emphasis on the learners’ connections and not just content. Openness as a quality of relationship amongst students, teachers, technologies, texts and an unknown audience.

Example No 1: while wikis promote consensus around dominant voices, a federated wiki allows individuals to manage and control content, they resolve to multiple servers

Example No 2: blogging provokes an awareness of audience and voice but student bloggers rarely have the option to experiment with identity or set their own limits of exposure

Example No 3: exposing learning to an unknown and therefore unpredictable audience (the agents beyond the course) may lead students to making decisions based on the awareness of that audience.



Collier, A., Ross J. 2016. For whom, and for what? Not-yetness and thinking beyond
open content. Open Praxis, vol. 9 issue 1, January–March 2017, pp. 7–16 (ISSN 2304-070X), available here

Blog analysis


Blogs: open space for reflection/ forum for discussions/ portfolio of completed assignments/ opening up courses to a wider group of participants.

Blogs’major applications: maintaining a learning journal; recording personal life; expressing emotions; communicating with others; assessment and; managing tasks.

Blogosphere: blog interconnections as a. a social network and b. an ecosystem

Blog Benefits in learning environments: reading other blogs; receiving feedback on one’s own blog

Blog and Personal Learning Environment (PLE): use for personal info management; use for social interaction and collaboration; info aggreggation and management

Blog problems: fragmented discussions/ a lack of coordination structures/ weak support for awareness/ danger of over-scripting



Poldoja, H., Duval, E. & Leinonen, T. (2016). Design and evaluation of an online tool for open learning with blogs, in Australasian Journal of Educational Technology, Vol 32, No 2, pp. 61-81.

Image available here


A Nomad…

  1. is an apt metaphor for the learner
  2. exists only in becoming and in interaction
  3. is intrinsically motivated toward the pursuit of learning
  4. is another phase of becoming
  5. appropriates the authority of some distant figure who often holds over it
  6. thinks of knowledge not as static, but rather as a flexible element to be alchemically interacted with
  7. is unconstrained
  8. is in constant movement
  9. is not as “losing one’s way” but is as “losing the way”
  10. is restrained from prefixed and definite articles
  11. space is smooth, open-ended
  12. mode of distribution is nomos (=arraying oneself in space), not logos
  13. moves in amorphous, informal spaces, nonlinear structures
  14. finds a viable milieu in the complex and chaotic structure of the web


Remembering Umberto Eco’s A Componential Analysis of the Architectural Sign /Column semiotic analysis through this stunning paper entitled; “Community Tracking in a cMOOC and nomadic learner behavior identification on a connectivist rhizomatic learning network” by : Bozkurt, A., Honeychurch, S., Caines, A., Bali, M., Koutropoulos, Ap., Cormier, D.


The human-technology relationship


Examining Rejection, Acceptance and Symbiosis

Technology Acceptance Model (TAM): Theory of Reasoned Action (TRA)/ Theory of Planned Behavior (TPB). Acceptance depends on perceived ease of use and usefulness; the effort, high performance scheme. TAM also depends on contextual factors such as gender, consequence measures such as attitude etc. TAM is useful in understanding the early stages of the human-technology relationship.

Symbiosis:technology, user and context share an equivalent role in forming a relationship. Techs and human co-evolve. The more the technology is perceived as skillfully completing human capacities, the more it leads to symbiosis. To achieve a state of symbiosis an adjustment period is needed during which the humans gain 01. a sense of control, 02. a perception of a benefit of mutual adaptation and 03. a perception of utility and efficiency. The transition to symbiosis happens for two reasons: the growth of a close relationship with technology and the intricate connection of activity and use of the technologies.



Adelé S., Brangier E., “Evolutions in the human technology relationship: rejection, acceptance and technosymbiosis”, IADIS International Journal on WWW/Internet, Vol. 11, No 3, pp 46-60, ISSN: 1645-7641, available here

Image available here

Seven Sins of Memory (2003)


Our self is based on memories of past experiences while the retrieval, recollection and reconstruction of the past is reciprocally influenced by the self. Memory’s imperfection is classified in this book in seven sins (intended here as in transgressions fatal to spiritual progress/ ways in which the normal, everyday operations of our mind may occasionally produce suboptimal or flawed memory experiences):

  • Forgetting: 01 transience/ 02 absent-mindedness/ 03 blocking
  • Distortion: 01 misattribution/ 02 suggestibility/ 03 bias
  • Intrusive memories: 01 persistence


  • Image 01 available here
  • Image o2 available here

See also; Joseph LeDoux, 2002, Synptic Self: In the absence of learning and memory processes the self would be an impoverished expression of our genetic constitution

Mapping in Education


In the 2016 discussion on the Future of OERs, MIT’s Karen E. Willcox and Luwen Huang discussed the complexities of navigating the “data-rich” world of online education.

In their paper entitled: “Mapping Unbundled Open Education Resources: Pathways Through the Chaos”, they introduced the Xoces project which catalogs, structures, and visualizes learning outcomes within a curriculum. By creating visual analogues they are trying to:

determine the nature of what is being mapped—for instance, which entities are defined as points, what relationships can be defined as “roads” or pathways between points, and what clusters or “suburbs” of points may exist.

A structured approach to educational mapping, the two authors claim, can offer a data driven future for open education, cartography being one major discipline that can help them to achieve this goal.

The FutuOER project was conceived of by Norman Bier and Brandon Muramatsu.

Didactic/Reflexive Pedagogies


Cope and Kalatzis use this pair of terms to describe alternative pedagogical systems, and by using their special characteristics they demonstrate how technology in itself cannon produce change in pedagogy, it is pedagogically neutral. In fact, technology features such as flipped classroom and e-textbooks often reproduce didactic pedagogy principles. So,

Didactic Pedagogy:

  • balance of control is with the instructor
  • focus on cognition
  • focus on the individual learner
  • the learners must demonstrate that they can replicate discipline knowledge

Reflexive Pedagogy

  • the learner has considerable scope and responsibility for epistemic action (knowledge is dialogical)
  • focus is on the artifacts and knowledge representations constructed by the learner and the process of their construction
  • focus is on the social sources of knowledge
  • wider range of epistemic processes

In  their forthcoming book “e-Learning ecologies” the two authors present the reader with seven new learning affordances (see image above). They explore the way new media can be used to serve the reflexive model of education. At the moment they run the e-Learning ecologies, MOOC in the Coursera platform.



Kalatzis, M., Cope, B., 2015, “Learning and New Media“, in The SAGE Handbook of Learning, edited by David Scott and Eleanore Hargreaves, Thousand Oaks CA: Sage, Pp. 373-387

Cope, B.,Kalatzis, M., 2015,”Assessment and Pedagogy in the Era of Machine-Mediated Learning” Pp. 350-374 in Education as Social Construction: Contributions to Theory,
Research, and Practice, edited by T. Dragonas, K. J. Gergen, S. McNamee, and E.
Tseliou. Chagrin Falls OH: Worldshare Books.

Image available here

Bruce Edmonds and Contextual Cognition in Social Simulation


How does individual behavior influence the social behavior and vice versa? Social Simulation models (remember eigenbehaviors and Gero’s Situatedness) capture this interplay through various aspects of cognition. (eg social norms) Edmonds argues that in order to better understand this process it is best to contextualize the cognitive processes of the interacting agents. Below the author distinguishes among different types of context:

  • Situational Context: time, location, who was there, the knowledge of the people, the history of the place and all the objects present, “those factors that are relevant to understand this particular occurrence”
  • Linguistic Context: the words that surround an utterance or phrase, elements of the relevant culture, very common as social interactions are composed of linguistic communications. [Peter Gardenfors: Action is primary, pragmatics consists of the rules for linguistic actions, semantics is conventionalised pragmatics and syntax adds markers to help disambiguation (when context does not suffice]
  • Cognitive Context and Framing: some knowledge is acquired in a particular situation and then made available in similar situations and this abstraction is what we refer to as cognitive context, coincides with Goffman’s frames seen as schemata of interpretation used by individuals to locate, perceive, identify and label experiences, the “framing” is a cognitive context of opinion and choice
  • Social Context: events, habits, conventions, norms, a situation that has its own characteristics associated with it.

Learning and Reasoning Edmonds claims, “are far more feasible when their scope is restricted to a particular context“. If, however, one wishes to generalize a thesis, then he/she must be able to appropriately change this focus as the external context, that is the context we inhabit in and thus assess the relevance of knowledge via identifiable “contexts“. This is how we deal with complexity: our limited learning is efficient because many of the possible causes or affects of events that are important remain relatively constant.

The figure above, illustrates what Edmond proposes the architecture of a simulation model should be. There are four modules:

  • Context Identification System (CIS): takes the inputs and learns in a flexible and imprecise way an indication of context
  • Context Dependent Memory (CDM): takes the indication of CIS and identifies all the memory items stored in that context, it evaluates the current truth of these and returns negative feedback to the CIS which will then identify another context
  • Local Learning Algorithm (LL): performs a local update of the knowledge in the memory, propagates successful items towards focus, deletes or corrects items that were false, inserts new items
  • Inference System (IS): it tries to deduce some decisions as to the actions or plans to execute, two common problems, under-determination (not enough info) or over-determination (contradicting info), in the first case the context is expanded, in the second case, the context is reduced.

Edmond’s analysis on the general heuristics are: Formation, Abstraction, Specialization, Content Correction, Content Addition, Content Restriction, Content Expansion, Content Removal

Back to Gero, the heuristics were: Formulation, Synthesis, Analysis, Evaluation, Documentation, Reformulation type 1, Reformulation type 2, Reformulation type 3



  • Edmonds, B., 2014. Contextual Cognition in Social Simulation. In Context in Computing, Patrick Brézillon & Avelino J. Gonzalez (Eds.) New York: Springer DOI 10.1007/978-1-4939-1887-4_18, full paper available here
  • Downes, St., Commentary on Contextual Cognition in Social Simulation, available here




In this excellent article Kauffman attempts to illustrate how the Heinz von Foerster theory of eigenforms works. It is very well written and so easy to read. And it has great implications on how we perceive, map and attempt to understand the complexity of our surrounding urban landscapes.

Objects: quantum or classical. quantum objects are subject to the constraints of the uncertainty principle. they dominate the the world of the very small. classical objects live in the dream of objective existence. they have a location at a given time, if they break into parts one can tell where their parts are. Heinz von Foerster says: “objects are tokens for eigenbehaviors” thus that there is a behavior between the perceiver and the object perceived and a stability or repetition “that arises between them”. It is this stability that constitutes the object says Kauffman, “the perceiver and the perceived arise together in the condition of observation”.

Eigenforms: what results from eigenbehavior, eigenbehavior being the process while eigenform is the resulting object of this process.(…) The key concept in the understanding of eigenform is its placement in the reciprocal relationship of the object (the “It”) and the process leading to the object (the process leading to “It”) (…) Just so, an object in the world (cognitive, physical, ideal,…) provides a conceptual center for the investigation of a skein of relationships related to its context and to the processes that generate it.

Back to the object: an object in itself is a entity, participating in a network of interactions, taking on its apparent solidity and stability from these interactions. An object in this view is an amphibian between the symbolic and imaginary world of the mind and the complex world of personal experience. The object when viewed as process is a dialogue between these worlds. The object when seen as a sign for itself, or in and of itself, is as imaginary as a pure eigenform.

Kauffman then poses the question von Foerster left out:

if the world is a world of eigenforms and most of them are in time oscillatory and unstable, must we insist on stability at the level of our present perception of that world? In principle, there is an eigenform, but that form leads always outward into larger worlds and new understanding (…) If you give a person an undecidable problem, the action of that person in attempting to solve the problem reveals the identity of the person and the nature of his/her creativity

*In quantum mechanics observation is modeled not by eigenform but by its mathematical relative the eigenvector.



Kauffman, L., 2003, ‘Eigenforms — Objects as Tokens for Eigenbehaviors’ in Cybernetics And Human Knowing. Vol. 10, nos. 3-4, pp. 73-90, full paper available here


eigenbehaviors 02

For  Eagle and Petland eigenbehaviors are a set of characteristic vectors that represent behavioral structures and they can be used to predict human behavior with high accuracy. The authors claim that despite individual, idiosyncratic, random behavior people typically have identifiable routines. By applying a reserach methodology that collected data from 100 subjects over a period of 9 months, they were able to recover information that proved that:

(…) communities within a population’s social network tend to be clustered within the same behavior space. It seems reasonable that this type of behavioral homophily is present in a variety of social networks. It should be possible  for practitioners, using virtually any type of longitudinal behavior data, to similarly quantify the behavior space of a particular group or individual of interest using the eigenbehaviors technique described above. If strong behavioral homophily is present in the data, it should equally be possible to infer an individual’s affiliations by quantifying the individual’s distance from a community’s behavior space.

The two authors show how knowledge is socially constructured Stephen Downes comments; “groups of friends can have their own collective ‘behavior space’ which corresponds to the common behaviors of the community.”



Eagle, N., Pentland, A.S., 2009, ‘Eigenbehaviors: identifying structure in routine’, in “Social Networks: new perspectives” (Guest Editors: J. Krause, D. Lusseau and R. James), Behav Ecol Sociobiol (2009) 63:1057–1066, DOI 10.1007/s00265-009-0739-0

Image and paper available here

Stephen Downes commentary available here