Procedural knowledge, also known as imperative knowledge, is the knowledge exercised in the performance of some task. See below for the specific meaning of this term in cognitive psychology and intellectual property law.
Procedural knowledge, or implicit knowledge is different from other kinds of knowledge, such as declarative knowledge, in that it can be directly applied to a task. For instance, the procedural knowledge one uses to solve problems differs from the declarative knowledge one possesses about problem solving because this knowledge is formed by doing.
In some legal systems, such procedural knowledge has been considered the intellectual property of a company, and can be transferred when that company is purchased.
One limitation of procedural knowledge is its job-dependence; thus it tends to be less general than declarative knowledge. For example, a computer expert might have knowledge about a computer algorithm in multiple languages, or in pseudo-code, whereas a Visual Basic programmer might only know about a specific implementation of that algorithm, written in Visual Basic. Thus the 'hands-on' expertise and experience of the Visual Basic programmer might be of commercial value only to Microsoft job-shops, for example.
One advantage of procedural knowledge is that it can involve more senses, such as hands-on experience, practice at solving problems, understanding of the limitations of a specific solution, etc. Thus procedural knowledge can frequently eclipse theory.
In artificial intelligence, procedural knowledge is one type of knowledge that can be possessed by an intelligent agent. Such knowledge is often represented as a partial or complete finite-state machine or computer program. A well-known example is the Procedural Reasoning System, which might, in the case of a mobile robot that navigates in a building, contain procedures such as "navigate to a room" or "plan a path". In contrast, an AI system based on declarative knowledge might just contain a map of the building, together with information about the basic actions that can be done by the robot (like moving forward, turning, and stopping), and leave it to a domain-independent planning algorithm to discover how to use those actions to achieve the agent's goals.
In cognitive psychology, procedural knowledge is the knowledge exercised in the accomplishment of a task, and thus includes knowledge which, unlike declarative knowledge, cannot be easily articulated by the individual, since it is typically nonconscious (or tacit). Many times, the individual learns procedural knowledge without even being aware that they are learning (Stadler,1989). For example, most individuals can easily recognize a specific face as "attractive" or a specific joke as "funny," but they cannot explain how exactly they arrived at that conclusion or they cannot provide a working definition of "attractiveness" or being "funny." This example illustrates the difference between procedural knowledge and the ordinary notion of knowing how, a distinction which is acknowledged by many cognitive psychologists (Stillings, et al. Cognitive Science: An Introduction, 2nd edition, Cambridge, MA: MIT Press, 1995, p. 396). Ordinarily, we would not say that one who is able to recognize a face as attractive is one who knows how to recognize a face as attractive. One knows how to recognize faces as attractive no more than one knows how to recognize certain arrangements of leptons, quarks, etc. as tables. Recognizing faces as attractive, like recognizing certain arrangements of leptons, quarks, etc. as tables, is simply something that one does, or is able to do. It is, therefore, an instance of procedural knowledge, though it is not an instance of know-how. Of course, both forms of knowledge are, in many cases, nonconscious. For instance, research by a cognitive psychologist Pawel Lewicki has demonstrated that procedural knowledge can be acquired by nonconscious processing of information about covariations.
In the classroom, procedural knowledge is part of the prior knowledge of a student. In the context of formal education procedural knowledge is what is learned about learning strategies. It can be the "tasks specific rules, skills, actions, and sequences of actions employed to reach goals" a student uses in the classroom (Cauley,1986). Cauley give the example for procedural knowledge as how a child learns to count on their hand/fingers when first learning math. The Unified Learning Model< explicates that procedural knowledge helps make learning more efficient by reducing the cognitive load of the task. In some educational approaches especially working with students with disabilities educators perform a task analysis followed by explicit instruction with the steps needed to accomplish the task.
Intellectual property law
In intellectual property law, procedural knowledge is a parcel of closely held information relating to industrial technology, sometimes also referred to as a trade secret which enables its user to derive commercial benefit from it. It is a component of the intellectual property rights on its own merits in most legislations but most often accompanies the license to the right-of-use of patents or trademarks owned by the party releasing it for circumscribed use. Procedural knowledge is not however solely composed of secret information that is not in the public domain; it is a "bundled" parcel of secret and related non-secret information which would be novel to an expert in the field of its usage.
- Koedinger, K.R. & Corbett, A. (2006). Technology Bringing Learning Sciences to the Classroom. In Sawyer, R.K. (Ed.), The Cambridge Handbook of the Learning Sciences (61-75). New York: Cambridge University Press
- Shell, Duane (2010). The Unified Learning Model. Springer. ISBN 978-90-481-3215-7.
- Glaser, 1984
- Stadler, M.A.(1989). On Learning Complex Procedural Knowledge. Journal Of Experimental Psychology: Learning, Memory, and Cognition, Vol.15, No.6 pgs. 1061-1069.
- Cauley, K.M. (1986). Studying Knowledge Acquisition: Distinctions among Procedural, Conceptual and Logical Knowledge.
- FAQ of the Know-how Wiki for How to Solve It
- Google Video - Will Wright's Game Developers Conference senimar/lecture in March 2006 about procedure vs. data, featuring his upcoming game Spore