Conversation theory

Collective intelligence Collective action Self-organized criticality Herd mentality Phase transition Agent-based modelling Synchronization Ant colony optimization Particle swarm optimization Swarm behaviour Social network analysis Small-world networks Centrality Motifs Graph theory Scaling Robustness Systems biology Dynamic networks Evolutionary computation Genetic algorithms Genetic programming Artificial life Machine learning Evolutionary developmental biology Artificial intelligence Evolutionary robotics Reaction–diffusion systems Partial differential equations Dissipative structures Percolation Cellular automata Spatial ecology Self-replication Conversation theory Entropy Feedback Goal-oriented Homeostasis Information theory Operationalization Second-order cybernetics Self-reference System dynamics Systems science Systems thinking Sensemaking Variety Ordinary differential equations Phase space Attractors Population dynamics Chaos Multistability Bifurcation Rational choice theory Bounded rationality Conversation theory is a cybernetic approach to the study of conversation, cognition and learning that may occur between two participants who are engaged in conversation with each other.

[1][2][3] It presents an experimental framework heavily utilizing human-computer interactions and computer theoretic models as a means to present a scientific theory explaining how conversational interactions lead to the emergence of knowledge between participants.

[21] Because of this, participants engaging in a discussion about a subject matter make their knowledge claims explicit through the means of such conversational interactions.

The theory is concerned with a variety of "psychological, linguistic, epistemological, social or non-commitally mental events of which there is awareness".

[22] Awareness in this sense is not of a person-specific type, i.e., it is not necessarily localized in a single participant.

[22] While there is an acknowledgment of its similarities to phenomenology, the theory extends its analysis to examine cognitive processes.

[23] However, the concept of cognition is not viewed as merely being confined to an individual's brain or central nervous system.

[24] Instead, cognition may occur at the level of a group of people (leading to the emergence of social awareness), or may characterize certain types of computing machines.

Using computer theoretical models of cognition, conversation theory can document these intervals of understanding that arise in the conversations between two participating individuals, such that the development of individual and collective understandings can be analyzed rigorously.

[31] In this way, Pask has been argued to have been an early pioneer in AI-based educational approaches: Having proposed that advances in computational media may enable conversational forms of interactions to take place between man and machine.

is treated as an unrestricted language used between a source (say a participant) and an interrogator or analyst (say an experimenter).

[34] For this reason, it may be considered a language for general discussion in the context of conversation theory.

and denotes various constructive processes that have been acquired by a student through maturation, imprinting and previous learning.

lines of inquiry such that an object language is the ordered pair of such discourse types

[39] A concept in conversation theory, is conceived of as the production, reproduction, and maintenance of a given topic relation

[45] This notion of a concept has been noted as formally resembling a TOTE cycle discussed by Miller, Galanter and Pribram.

They are encapsulated through entailment structures, which is a way by which we may visualize an organized and publicly available collection of resultant knowledge.

Finally: Represents two solid arcs permitting alternative derivations of the topic T. This can be expressed as

below denotes analogy relation that can be claimed to exist between any three topics of each entailment mesh.

This is a virtual machine for selecting and executing concepts or topics from an entailment mesh shared by at least a pair of participants.

It features an external modelling facility on which agreement between, say, a teacher and pupil may be shown by reproducing public descriptions of behaviour.

A succinct account of these operators is presented in Pask[48] Amongst many insights he points out that three indexes are required for concurrent execution, two for parallel and one to designate a serial process.

These structures exist in a variety of different levels depending upon the extent of the relationships displayed.

[33] Pask identified two different types of learning strategies:[33] The ideal is the versatile learner who is neither vacuous holist "globe trotter" nor serialist who knows little of the context of his work.

In learning, the stage where one converges or evolves, many Cyberneticians describe the act of understanding as a closed-loop.

Furthermore, Gordon Pask emphasized that[49] conflict is the basis for the notion of “calling for'' additional information (Pangaro, 1992).

[54] However, it has been noted that while Pask and associates work on learning styles has been influential in both the development of conceptual tools and methodology, the Spy Ring History test and Smuggler's test may have been biased towards STEM students than humanities in its implementation, with Entwistle arguing that the "rote learning of formulae and definitions, together with a positive reaction to solving puzzles and problems of a logical nature, are characteristics more commonly found in science than arts student".

[55][56] One potential application of conversation theory that has been studied and developed is as an alternative approach to common types of search engine Information retrieval algorithms.

In doing this, the search engine interface highlights snippets of webpages corresponding to a neighbourhood terms that help provide meaning to the first.

[57] The aim of this design, is to provide just enough information for a user to become curious about a topic in order to induce the intention to explore other subtopics related to the main term input into the search engine.