Understanding Knowledge

2.  Definitions
 Cognitive psychology
 Data, information and knowledge
 Kinds of knowledge
 Expert knowledge
 Thinking and learning in humans

3.  Intelligence: the capability to acquire and apply appropriate knowledge.
 Memory: the ability to store and retrieve relevant experience according to the will.
 Learning: to represents the skill of acquiring knowledge using the method of
instruction/study.
 Experience: the understanding that we develop through years of actions.
 Knowledge can be developed over time through successful experience, and
experience can lead to expertise.
 Common sense: refers to the natural and mostly unreflective opinions of humans.
It implies a type of knowledge that almost every human being possess in varying
forms/amounts.
 Learning is: Knowledge acquired by instruction or study; as a result of intelligent
problem solving

4.  Cognitive Psychology: tries to identify the structures and processes that closely
relates to skills performed within an area of operation.
 It provides a strong background for understanding knowledge and expertise.
 It is the study of human intelligence.
 The two major components of cognitive psychology are:
 Experimental Psychology: This studies the processes that constitute human intelligence.
 Artificial Intelligence (AI): This studies the Computer-based intelligent systems.
 Knowledge developer and human experts (domain experts):
 Involves in process of extracting and representing expert’s knowledge by:
 Interviews: The experts are asked for information regarding a specific area of their expertise,
because it is difficult to provide the completely accurate reports of their mental processes

5.  Data: represents unorganized and unprocessed facts. Its properties
 Usually data is static in nature.
 It can represent a set of separated facts about events.
 Data is need for information.
 An organization sometimes has to decide on the nature and volume of data that is required
for creating the necessary information.
 Information: Is an aggregation of data (processed data) which makes decision making
easier.
 Information has usually got some meaning and purpose.
 Knowledge is: The understanding obtained through the process of experience or
appropriate study. It is usually based on learning, thinking, and proper understanding
of problem.
 Knowledge is not information and information is not data.
 Knowledge is derived from information in the same way information is derived from data.

6. Image source: http://www.knowledge-management-tools.net/knowledge-information-data.html

7.  Deep Knowledge: Knowledge gained through years of proper experience.
 Shallow Knowledge: Minimal understanding of the problem area.
 Know-How Knowledge: Accumulated lessons of practical experience.
 Reasoning and Heuristics:
 Reasoning by analogy: indicates relating one concept to another.
 Formal Reasoning: indicates reasoning by using deductive or inductive reasoning.
 Deduction: uses major and minor premises. New knowledge is generated by using
previously specified knowledge.
 Inductive reasoning revel reasoning from a set of facts to a general conclusion. Is the
basis of scientific discovery.

8.  Knowledge classification “based on if it is procedural, declarative, semantic, or
episodic”.
 Procedural knowledge represents the understanding of how to carry out a specific
procedure.
 Declarative knowledge is routine knowledge about which the expert is conscious. It is
shallow knowledge, resides in short-term memory. Can be readily recalled, it consists of
simple and uncomplicated information
 Semantic knowledge is highly organized, “chunked” knowledge that resides mainly in
long-term memory. Can include major concepts, vocabulary, facts, and relationships.
 Episodic knowledge represents the knowledge based on episodes (experimental
information). Each episode is usually “chunked” in long-term memory.
 Knowledge is also classified on its location as:
 Tacit knowledge embedded in human mind through experience.
 Explicit knowledge is codified and digitized in documents, books, reports, spreadsheets, memos
etc.

9.  It is the information inside an expert mind for accurately and quickly solving
complex problems.
 Knowledge Chunking
 Stored in expert’s long-range memory as chunks. Helps experts to optimize their memory
capacity to process the information quickly.
 Chunks are groups of ideas that are stored and recalled together as a unit.

10.  Humans do not usually receive and process information exactly as the machines do.
 Humans can receive information via seeing, smelling, touching, hearing (sensing) etc.,
this promotes thinking and learning for humans.
 Humans and Computers can receive inputs from a multitude of sources. Both human
brain and CPU of a computer receive information as electrical impulses. But the
computers must be programmed to do specific tasks. Performing one task does not
necessarily transcend onto other tasks as it may be with humans.
 Human learning: they learn new facts, integrate them in some way which they think
is relevant and organize the result to produce necessary solution, advice and decision.
Human learning can occur in the following ways:
 Learning by experience: a function of time and talent
 Learning by example: more efficient than learning by experience
 Learning by Discovery: undirected approach in which humans explore a problem area with
no advance knowledge of what their objective is.