Learning

Definition: Learning

Learning has dramatically changed in the 21th century. Most essential theories are: Behaviorism, Cognitivism, Constructivism and Connectivism.

Fig A. Learning has relations to evolution and cultural change.

It is GoodReason’s core competence to connect and combine different theories, professions, disciplines and methods, not to deeply specialize. GoodReason seeks for holism to understand the big picture, outside of box.

Behaviorism learns from behavior of systems, cognitivism about building conceptions about them, constructivism by building new abstractions and implementations and connectism about relations.

All of them are systemic. Any of them has its drawbacks, but together they are most useful. GoodReason understands them all.


Intentionality of a Theory, Organization, Purposeful System

Every system that has a purpose, has a so called intentionality. GoodReason warmly suggests a specific way to draw it (Fig 1). This drawing contains most of the most important concepts of system: input, output and feedback. The novel extensions are the relation: from history to future (vertical), from theory to practice (fact, from 2 to 6) and from feedback to structure to organize (4 to 5).

This graph model is often used in these pages, using rather free analogies, depending on the context.

Fig 1: Intentionality, a Generic Metamodel with eight sectors.


Definitions: Interdisciplinarity and Metadisciplinarity

”Interdisciplinarity involves the combining several academic disciplines into one activity (e.g., a research). It draws knowledge from several other fields like sociology, psychology, economics etc. It is about creating something new by thinking across boundaries.”

Interdisciplinarity is one of the greatest challenges of modern science, with the best expectations, because at work we are speaking with the same meaning about multi-professionalism, multi-talented persons, artificial intelligence etc.

Meta-disciplinarity (modified from P. Batz) is a novel approach to compose a new academic discipline from the theoretical components of previously existing disciplines, and from the evidence and observations available. It is assumed to find new kind of contribution starting from

  • gathered from a phenomena which is entirely new or has gone previously unremarked or is a phenomena which has been studied at length.

The meta-disciplinary approach is expected to present recently emergent features or new tools of observation, inquiry, contemplation, simulation, etc. or new modes of action or execution.

Definition: Organizational Meta cognition (Wiki)

”Organizational metacognition is knowing what an organization knows, a concept related to metacognition, organizational learning, the learning organization and sensemaking. It is used to describe how organizations and teams develop an awareness of their own thinking, learning how to learn, where awareness of ignorance can motivate learning.”

There are four learning prototypes (Wijnhoven, 2001) best meet learning needs, the match between these needs and learning norms dictating an organization’s learning capabilities; deutero-learning is the acquisition of these capabilities.

  1. knowledge gap analysis
  2. classification of problems to select operationally required knowledge and skills
  3. coping with organizational tremors and jolts by anticipation, response and adjustments of behavioural repertoires
  4. decisional uncertainty measurement

 


MetaCognition

See more at:  Metacognition: A Practical Overview Ed Nuhfer.

”Metacognition is a way of reflecting on: “What am I really trying to do here?”

  • “Metadisciplinarity” is identifying groups of disciplines that hold in common an overarching framework of reasoning/way of knowing that unites them.

Metadisciplinarity at work, Information systems

Kerne, A., doing interface ecology: the practice of metadisciplinarity, Proc SIGGRAPH Art and Animation.

”Doing interface ecology means connecting theory and practice through metadisciplinary structures. Separating New Media Studies, or Internet Studies from practice would avoid the metadisciplinary nature of interface phenomena. Connecting disciplines promotes the creation of hybrid forms. As computational artifacts and their interfaces become tangible and pervasive, as they permeate a wider and wider range of human activities and environments, the need for metadisciplinary practice grows. Future work will explore how the practice of metadisciplinarity can play a new role in pedagogy and research among fields such as computation, information, graphics, interaction design, and “new” media.”


A Discipline as an Abstract Metamodel

Metamodels are the a clear step to the transdisciplinary and metadisciplinary direction.

Fig 2: A discipline as an intentionality graph.

Fig 1 has been slightly changed to Fig 2 for discipline:

  • History of science (1) to future findings (8).
  • Most relevant flows are shown in horizontal direction (3 to 7): students and users.
  • Theory is grounded into practice from 2 to 6.
  • Each discipline responds to stimulants (exogenous and endogenous reactions) by fixing a certain structure (4 to 5).

We can imagine that in each sector at a longer and longer distance there are other disciplines, systems and concepts relevant to the sector variables.


Purposeful systems

Ronald Ackoff has written (1972) a book about purposeful systems, which focused on the question how systems thinking relates to human behaviour. ”Individual systems are purposive”, they said, ”knowledge and understanding of their aims can only be gained by taking into account the mechanisms of social, cultural, and psychological systems”.

Any human-created systems can be characterized as ”purposeful system” when its ”members are also purposeful individuals who intentionally and collectively formulate objectives and are parts of larger purposeful systems”. Other characteristics are:

  • ”A purposeful system or individual is ideal-seeking if… it chooses another objective that more closely approximates its ideal”.
  • ”An ideal-seeking system or individual is necessarily one that is purposeful, but not all purposeful entities seek ideals”, and
  • ”The capability of seeking ideals may well be a characteristic that distinguishes man from anything he can make, including computers”.

Fig 4: Idea for the figure comes from Bloom’s taxonomy as verbs.

 

 

”Not everything that counts can be counted, and not everything that can be counted counts.”