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This week we want to look at the idea of knowledge, firstly as a disposition that is associated with intelligent activity, and secondly as a phenomena we can identify and represent. Notice that we are careful not to try to define knowledge, but in common with others, concentrate in characterizing it in a number of ways. In this way, knowledge can be said to reside, or be displayed in a variety of different phenomena, including individuals, groups and artifacts such as computers.
(Blackler, F., 1995, Knowledge, Knowledge Work and Organizations: An Overview and Interpretation, Organizational Studies, 16(6): 1021-1046)
The idea of storing knowledge is radically different to the normal computing idea of storing data. Knowledge can be expressed in two forms (similar to the types already encountered).
Procedural knowledge (knowing 'how'): This explains what to do in order to reach a certain conclusion. For example: to determine if Peter or Robert is older, first find their ages.
Procedural knowledge is knowledge about how to do something and this knowledge is held by individuals in a way which does not allow it to be communicated directly to other individuals.
One view of procedural knowledge is that it is knowledge that manifests itself in the doing of something. Eg, in motor or manual skills and in cognitive or mental skills, and we cannot reduce to words that which we obviously know or know how to do. Attempts to do so are often recognized as little more than after-the-fact rationalizations.
Another view of procedural knowledge is that it is knowledge about how to do something. This view of procedural knowledge accepts a description of the steps of a task or procedure as procedural knowledge. This view is very similar to declarative knowledge except that tasks or methods are being described instead of facts or things.
Examples: rules, strategies, agendas, procedures. Also models.
Declarative knowledge (knowing 'what', knowing 'that'): This takes the form of relatively simple and clear statements which can be added and modified without difficulty. It is knowledge of facts and relationships. For example: a car has four tyres, Peter is older than Robert.
declarative representations have knowledge in a format that may be manipulated, decomposed and analyzed independent of its content.
The primary advantages of declarative knowledge is the ability to use knowledge in ways that the analyst did not foresee.
Declarative knowledge has much in common with explicit knowledge in that declarative knowledge consists of descriptions of facts and things or of methods and procedures. For most practical purposes, declarative knowledge and explicit knowledge are articulated knowledge and may be treated as synonyms.
Examples: concepts, objects, facts, propositions, assertions, semantic nets, logic.
Also descriptive models such as ontologies.
Newell and Simon introduced the concepts of problem space and task environment.
The problem space is a person’s internal (mental) representation of a problem, and the place where problem-solving activity takes place. The task environment is the physical and social environment in which problem solving takes place. The reason for this distinction is that individual behaviour influences problem solving; this influence is greater the less structured the task is.
Situations which do not influence individual behaviour can be studied by only analysing the task environment. Eg., economic theory is based on the task environment only, assuming that humans are always motivated to maximise their utility; they are expected to behave rationally towards this goal, and everything of importance for problem solving is given by the task environment. Therefore, economics is a science about the task environment.
Where behavioural aspects of problem solving are closely related to the decision maker and not to the task environment, we have to look inside the person’s mind to explain this behaviour. Unstructured environments are open for individual behaviour, well-structured environments encourage common behaviour.
Newell and Simon call the model of the task environment a task model (sometimes also known as a competence or epistemological model) and the model of the problem space a performance model:
Both task and performance models are required to enable problem solving behaviour to be adequately modelled within a specific domain.
The problem space is seen as consisting of knowledge states, and problem solving proceeds by a selective search within the problem space, according to Newell and Simon using rules of thumb (heuristics) to guide the search.
The knowledge level hypothesis was introduced by Allen Newell in 1982. Newell formulated this hypothesis in a tentative to solve the confusions in the use of the knowledge and representation terms. He defined a representation as a symbolic system which codes a body of knowledge. His hypothesis advocates the existence of knowledge independently of its representation.
The original aim of the knowledge level was to clear up confusion concerning the usage of the terms 'knowledge' and 'representation'. The idea immediately resonated with ongoing research toward understanding and building knowledge systems from a knowledge content (epistemological) perspective. Clancey's model of heuristic classification illustrated the power and scope of competence models that make explicit the kinds of knowledge embodied in a system and their roles in an overall pattern of reasoning.
Rob Stephens
Room 2P27
Tel: 3136
Robert.Stephens@uwe.ac.uk
