Procedural Knowledge

Procedural knowledge or know-how is the knowledge of how to perform some task. It focuses on the “way” needed to obtain a result. Typical examples are procedural programming languages, which allow the specification of the actions or operations needed to obtain something. Remember that procedural knowledge is typically incorporated in an algorithm or a program.

Procedural knowledge comes in many forms, for example, in legal systems, procedural knowledge or know how is considered intellectual property. This property can be transmitted, transferred, or sold. One limitation of procedural knowledge is that it is job dependent; thus, it tends to be less general in nature.

The following are other aspects of procedural knowledge: It can involve more senses, such as hands-on experience, practice at solving problems, understanding of the limitations of a specific solution, etc. Know-how can frequently eclipse theory. Has high efficiency. Has low modifiability. Has low cognitive adequacy (which is considered better for knowledge engineers).

Knowing how the strategy works or is implemented is called procedural knowledge. What are the steps, the process, and the procedure? What do I do first, then next, and then following? Knowing that a strategy exists does only so much good if we do not know how to implement it.

The following are aspects of procedural representation: Control information that is necessary to use the knowledge is embedded in the knowledge itself (e.g., how to find relevant facts, make inferences, etc.). Requires an interpreter to follow instructions specified in knowledge.

Procedural issues are commonly relegated to ways to change representations rather than to be representations of the actions themselves. Logic is stuck with logical inference, which is a set of syntactic rules that map onto commonly accepted natural inference results. Perhaps modus ponens is the most obvious and useful of these, but there are many others.

Inference rules are permissive, which means that they can be applied whenever the knowledge engineer chooses. They are inadequate for capturing the intricacies of human thought, but they have formed the basis of many problem-solving systems that do operate to produce a sequence of actions that mimic human problem solving in some aspects.

Actually, it is a testament to the true universality of the rules of inference that this is possible at all. We should marvel at a system that solves a puzzle just by proving a theorem, which is a way to characterize the applications of inference rules to achieve a desired result.

The generalization of inference into the rule set of an expert system also follows this pattern. Now a rule does not change the logical form of a representation, but a rule is allowed to change the state of objects and their relationships. The sequencing of the application of rules in the rule set can again be mapped onto sequences of actions, but again the temporal aspect arises out of the behavior of the rule engine and is not represented explicitly.

The attempt to represent and control the behavior of the rule engine (so-called control knowledge) did not really solve the temporal problem, because what was being represented was the rule engine itself (a program), not real-world actions.

Frame systems also fall into this category. Typically a frame system will do well in representing declarative relationships, some of an epistemological nature, such as the ISA link, but then introduce actions, and therefore time, through add-on functions, or demons, which are programs much like the rules in a rule system.

In fact, the hybrid knowledge representation system was very popular for a time, combining a declarative frame system and an attached rule system using the demon notion to provide procedural capability knowledge engineering environment (KEE), a frame-based expert system.

We perceive an imbalance between declarative and procedural issues, not only in the amount of effort applied, but also in the nature of the solutions. We believe this stems from the nature of human cognition and its emphasis on visual, therefore spatial, and thus declarative issues.

Process Maps A hierarchical method for displaying processes illustrates how a product or transaction is processed. It is a visual representation of the workflow within a process or an image of the whole operation. Process mapping comprises a stream of activities that transforms a well-defined input or set of inputs into a predefined set of outputs.

A good process map should: Allow people unfamiliar with the process to understand the interaction of causes during the workflow. Contain additional information per critical step about input and output variables, time, cost, DPU value.

Process Defined A process is a transformation; it transforms its inputs into its outputs. It is a picture showing how the transformation is carried out. It shows the inputs and outputs (best described using nouns), the activities in between (best described using verbs), and for each of the activities, the inputs and outputs used and produced.

A process is not just about what people do; it is also about what people produce. Historically, there has been a lot of emphasis attached to the study of the way people perform their jobs (i.e., the activities they carry out) or the verbs in the process map.

In other words, procedural knowledge is skill knowledge. A simple example of human procedural knowledge is the ability to ride a bike. The specifics of bicycle riding may be difficult to articulate but one can perform the task. One advantage of procedural representations is possibly faster usage in a performance system. Productions are a common means of representing procedural knowledge.

Declarative and Procedural Knowledge Knowledge is often expressed in two forms: Declarative knowledge (knowing “what”) 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 tires; Peter is older than Robert.

Procedural knowledge (knowing “how”) This explains what to do to reach a certain conclusion. For example, to determine if Peter or Robert is older, first find their ages.

Declarative Knowledge and Procedural Knowledge Difference There is a fundamental difference between declarative and procedural knowledge. Declarative knowledge refers to factual knowledge and information that a person knows. Procedural knowledge is knowing how to perform certain activities.

According to John Anderson of Carnegie-Mellon University, all knowledge starts out as declarative information and procedural knowledge is acquired through inferences from already existing knowledge. This is not to say that all procedural knowledge is higher-order knowledge.

It is often done without any attention to what we are doing or why we are doing it, for example, driving a car. Any skill being learned starts out as declarative knowledge.

For example, when learning to play tennis, we first learned all about the rules of the game, where to come into contact with the ball on the racket, how to make the ball go where we wanted to by the follow-through, and how to position our body for a backhand stroke. This is a set of factual information.

Putting those facts into practice will help us gain the skills to transform a series of declarative knowledge into procedural knowledge. Simply being told would not enable us to learn the necessary skills. We can gain the skills only after actively putting them into practice and being monitored by a coach who was constantly providing feedback.

In education, there is a mix of declarative and procedural knowledge being presented. It is important to remember that declarative knowledge has to be present to form procedural knowledge, but it should not be the only type of knowledge taught. Learning the declarative knowledge helps set the stage for the procedural knowledge. Teaching students to use the facts and information they have gained in context helps ensure long term retention.

Declarative knowledge and procedural knowledge differences

The connection of declarative and procedural knowledge

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