Introduction
Hunt (100) says knowledge is justified and true. This definition has led to the introduction of measurement tools for assessing the correctness and factuality of knowledge. The simple interpretation shows that the factuality of information establishes if a person understands, or does not understand, something. From this nature, knowledge is intangible. It exists as personal experiences or memories. Certainly, the nature of knowledge is that which is unseen, but people may see its effects. Since people cannot see knowledge, there is little focus on its impact and importance. The invisibility of knowledge addresses an important fact – its measurement.
The measurement of knowledge reflects the relationship between unseen human potential and its observable effects. Through this relationship, many people fail to distinguish between knowledge and behavior. This inability questions the process through which people acquire, use, retain and manage information. This section of the paper relies on the above factors of knowledge management to demonstrate that knowledge cannot exist without measurement. Of central importance to this paper is the understanding that knowledge comes from thoughts, and thoughts are finite. Through this understanding, this section of the paper explores the certainty of knowledge and the limited nature of human thought, as possible pieces of evidence for the existence of measurement as a prerequisite for the existence of knowledge. This report explores the merits, problems, and ramifications of this argument.
Merits
Knowledge is Limited
Although knowledge operates in unlimited space, it is limited. This fact stems from the understanding that knowledge exists as experiences and memories. This fact also shows that knowledge is always in the past and not in the future. From this analysis, it is also crucial to point out that new knowledge develops from past knowledge. Based on an assessment of the role of knowledge in defining human relationships, Krishnamurti (31) establishes that knowledge is incomplete. Therefore, people store knowledge as a fraction of their memories. Since memory is definite, it is also important to point out that knowledge is also definite because it is limited to human thought. Furthermore, because scientific knowledge constantly improves, it is also crucial to point out that ignorance is part of knowledge development. Since thoughts outline the framework of new knowledge development, it is important to understand that any knowledge derived from thought should be finite and measurable. It is crucial to conceive this idea because thoughts also produce immeasurable ideas. For example, Krishnamurti (31) says people could invent god because it makes them feel secure in their thoughts. However, the idea of god is immeasurable, although it emanates from finite thought. Based on this understanding, Krishnamurti says, “We must be very clear on this point; you must see for yourself the fact, the truth that thought, always, whatever it is, whether of the scientist or the great philosopher, is always bound, narrow, and limited” (30). Thought tends to be divisive. For example, thoughts have created nationalities and divisions (such as religion, capitalism, communism, and so forth) within the society. Human rituals are also products of thoughts. These rituals have created cultures, which have subsequently created conflicts and wars (surprisingly, human thought still strives to find a solution to these problems).
The role of human thoughts in creating and solving conflicts shows that the world is complex and dynamic. Weisburd and Chester (14) perceive this situation as chaotic. The greatest problem with this situation is the misinformed belief that thought is limited and clear. This realization presents new and interesting questions regarding the nature of human thought. For example, people ask about the nature of thought and the existence of a reliable instrument for measuring it. Krishnamurti (30) seeks to answer these questions by saying thought is a material concept because it emerges from the human brain, which is material and definite. Therefore, thought processes are material and measurable.
To understand the importance of measurement in human thought, it is important to include a philosophical understanding of the human thought process. For example, people often compare themselves with other people, as a basis for improvement. People who do not do so are static because they remain who they are. However, those that compare themselves with other people seek improvement through additional knowledge gains. The comparison is therefore measurable. Thus, without measurement, there is no progress. Most of these measures are usually “no-facts.” For example, if a violent person compares himself with a non-violent person, and resolves that he would be non-violent, he has moved into a state of “non-fact.” In other words, the person knows the violent status but does not know the non-violent status. This assessment shows that the definite position (violence) creates progress (non-violence) (Krishnamurti 31). Again, to understand the limited nature of thought (and by extension, knowledge); it is important to investigate and understand the nature of our daily lives. Krishnamurti (21), for example, explores the purpose of human existence by saying many people live their lives working eight-to-five jobs for more than five decades, only to die later. He asks, is this the purpose of life? While exploring this question, he says nobody can change our lives; no authority or person can truly transform our thoughts unless we make a conscious decision to do so (Krishnamurti 31).
A deeper understanding of the nature of human life also shows that most people live fragmented lives. Indeed, small divisions of professionals (doctors, lawyers, mechanics, entertainers, and the likes) fragment society. Moreover, people are often different, regardless of how intimate their relationship could be. Therefore, small units that define personalities, societies, and nationalities characterize human societies. These divisions only reflect the fragmented and limited nature of human thought. This statement prompts Krishnamurti (40) to argue that human knowledge is limited and measurable. He says,
“Our thinking is the outcome of knowledge, and knowledge is always limited. Knowledge always goes hand in hand with ignorance. There is no complete knowledge about anything. Our thinking, which is born out of our knowledge, is always limited, whether you are a scientist or a psychologist or an engineer, and so on” (Krishnamurti 40).
From the above statement, it is important to acknowledge the limited nature of human thought and knowledge. The fragmented nature of human society, therefore, highlights the fragmented nature of human thought as well. To understand knowledge, it is therefore important to understand the fragmented nature of human thought because knowledge is a product of the latter. Thought is therefore an instrument for gaining and developing knowledge.
The limited nature of human thought also exists in the conception of physical time. Weisburd and Chester (14) say human knowledge exists as a fragment of time because people acquire knowledge through years of experimentation and thinking. Time and thought are therefore finite variables that outline the nature of human knowledge. However, thought is a product of time because time has created the idea of thought. For instance, when people have hopes of becoming something; say, when someone wants to become a pilot, doctor, or a mechanic, he refers to these goals as measurable variables. Thinking in terms of the concept of time, therefore, brings about societal division, the same way as human thought fragments society. This analysis shows that knowledge, by its nature, is limited and therefore measurable.
Certainty
Many researchers and philosophers have explained the role of certainty in defining knowledge (Weisburd and Chester 14). Prominent philosophers that have investigated such issues include Aristotle, Confucius, and Polanyi. They say the use of knowledge depends on a higher understanding of a belief. This understanding translates to certainty. Hunt gives an example of the following sentence as a depiction of uncertainty, “I do not know, but I think that if you walk four blocks north, turn right and go one block, you will find Jones’ bakery” (Hunt 101). He says through this statement knowing something should meet a higher requirement of believing. The merit of this argument exists in understanding the dimensions of knowledge. In this analysis, someone may ask what it means when a person says he is knowledgeable. The main interest in this question is the influence and power that a person’s knowledge has on human behavior. Indeed, because knowledge is intangible, people can measure it through performance. Ordinarily, tests measure performance. For example, an examiner may set questions to establish a students’ understanding of a scientific process (say by multiplying two digits).
Conventional wisdom dictates that the definition of knowledge only exists through facts. Therefore, a true belief exists in the direct representation of how the world works. Some researchers however dispute the use of the term “true” (because of its complexities) and therefore propose the use of the term “correct” in its stead (Weisburd and Chester 14). Therefore, explicit and agreed-upon criteria normally emerge from correct and factual issues. Therefore, knowledge is not a belief that fails to meet the agreed-upon criteria. However, the correctness of a belief is not enough to meet the threshold of defining knowledge because knowledge should also be justified. From this analysis, the main question that arises here is the establishment of the criterion that would allow correct beliefs to be justified. For more than 2000 years, philosophers have pondered over this issue. To answer this question, Hunt says,
“If I say that I know it is raining, then, for this to be a claim of real and certain knowledge, it must be raining. I must believe it to be raining (merely to say that it is, out of whim, and for it to be raining at the time of the whimsy, would not constitute knowledge that it is raining), and I must be justified in having that true belief” (103).
From the above statement, an epistemological understanding of a justifiable statement reveals that knowledge needs to be reasonable (in addition to being correct). For example, someone could genuinely believe that it is raining; however, an unreliable source could inform his belief. Such a belief would fail to meet the criterion of defining knowledge because unreliable sources equate to unjustifiable sources. This analysis replicates instances where examiners give their students multiple-choice answers and students score marks, based on correctly guessed answers. Although their answers may be true, it does not mean they are knowledgeable about the question. This analysis highlights the importance of using measurable indices to determine certainty in knowledge acquisition.
Certainty and Self-Assessment
Knowledge should exist on the premise that something is correct and justifiable. For many people, to know something often comes with the understanding that someone is sure of what he says. This provision is important because human knowledge often doubtful. This assertion comes from the teachings of Aristotle, which show that the correctness of human belief is a critical component of knowledge (Weisburd and Chester 14). Because of the relationship between knowledge and certainty, Hunt (101) questions how people understand “certainty” as a true measure of knowledge. From this assertion, he explains the word, “know” to mean a degree of measure (Hunt 101). Indeed, although knowledge connotes firm and true beliefs, the firmness of these beliefs often exists in our ability to measure knowledge. Historically, people have failed to incorporate measures of certainty to understand people’s beliefs about something. Some researchers say the ascertainment of people’s certainty regarding personal beliefs is a question of boundaries. Stated differently, it is important to ask how people understand what is certain and what is uncertain. For purposes of practicality, it is important to establish the degree of certainty to enable people to rely on knowledge. This certainty is especially important in decision-making, problem-solving, and other practical uses of knowledge. The uses of certainty also show that the practical uses of “certain knowledge” depend on the consequences of their use. In other words, it is important to establish the possible ramifications of decisions that depend on certain and uncertain knowledge.
Ayer (cited in Hunt 104) has explored the problem of knowledge and certainty extensively because most of his work underscores the importance of certainty as a prerequisite for knowledge acquisition. He says, if someone successively predicted the winning numbers of a lottery game, it would be correct to assume that the person was certain about his predictions. Here, it would be important to understand the difference between such a person and another person who makes random guesses about the winning numbers because certainty is the only difference between both persons. Based on this assessment, Hunt (104) says certainty is a function of three preconditions. The first precondition is the understanding that whatever information is uttered is correct. The second precondition stems from the understanding that a person is sure of whatever he says, and the last precondition is the right for a person to be sure. This discussion differs from the requirement that all knowledge should be certain. Indeed, the dominant view of knowledge management usually does not include the need for surety. For example, the “multi-choice answer” example shows that most examiners still consider a guessed answer as correct, even though a student is unsure of it. Such answers constitute reliable knowledge, even when they do not have any real practical uses. However, if such answers are incorrect, examiners assume the student does not know.
“Surety” is also an important issue to consider is the utilization of knowledge. Incorporating certainty to the definition of knowledge shows that although a belief may be justifiable, the lack of surety may erode the definition of the belief as knowledge (Weisburd and Chester 14). This requirement underlines the need for measurement when defining knowledge. To affirm this view, Hunt (104-105) says,
“To expand the concept of knowledge to include certainty and to provide a method for its measurement, it is required that there be criteria for determining the factuality of a person’s answer and a method to measure how sure the person is of its factuality, along with a criterion or boundary above which qualifies as a sure response” (Hunt 104-105).
To understand knowledge, it is important to introduce units of measurement; otherwise, it would be impossible to know if a person knows something or not. Hunt (104) also affirms the importance of using units of measurement to understand if somebody knows something, or not (this should however occur within a set of rules). Understanding knowledge through a set of rules is important because the rules define numbers. For example, the provision of multiple-choice answers outlines a set of rules for the operational definition of knowledge. Most measurement rules that exist in educational circles ordinarily aim to compose test items. Such rules are fair and unbiased because they are not supposed to consider the demographic characteristics of the students. For example, such questions do not address gender or ethnic differences. The focus is therefore to assess the knowledge presented by the test-taker. Therefore, to understand knowledge, examiners should provide simple measurable questions, such as the answer for a mathematical question (say, 1+1). In the provision of multiple-choice tests, the main aim of an examiner is to assess the student’s answer by evaluating the options selected. This way, it would be easy to ascertain what a student knows, or does not know. In multiple-choice tests, the surety is not a criterion for understanding a person’s knowledge. Therefore, people that choose the correct answer by chance and those that choose the correct answer because they are sure of their choices are similar.
Problems
The greatest problem associated with the relationship between knowledge and measurement is the difficulty in measuring knowledge. Weisburd and Chester (14) say that although knowledge affects different facets of society, it is difficult to measure it. This problem stems from the difficulty of understanding the boundaries of knowledge. However, because this paper says without measurement, there is no knowledge, the use of different measurements to understand knowledge poses a problem to the entire understanding of the concept. For example, many researchers have explored the reliability of the use of a standardized concept to assess knowledge (Kanwar 603). This inquiry stems from reports that suggest the use of one knowledge measurement is as good as another (Kanwar 603). Stated differently, some studies suggest that measurement tools are equivalent to one another because all of them rely on one construct – measurement. Some researchers affirm this fact after ascertaining a positive correlation between specific measures of knowledge assessment, such as self-reports and questionnaires (Weisburd and Chester 15).
Understanding knowledge through the adoption of self-assessment techniques has provided many benefits to educators around the world. For example, self-assessment techniques introduce objectivity, and reliability in understanding new information. This benefit eases the administration of new knowledge. However, as Weisburd and Chester (14) say, human knowledge has more characteristics than those represented by the measurement tools discussed in this paper. From this observation, Weisburd and Chester (14) say it is more important for educators to include broader and more representative tools of assessment. The use of easily measurable techniques, such as multiple-choice tests, is insufficient for educators to conclude that the students have acquired new knowledge. Moreover, through an incorrect answer, it is difficult to distinguish between a misinformed and uninformed person.
Nonetheless, some researchers dispute the relationship between self-assessment techniques by affirming no correlation between such measures (Weisburd and Chester 15). The varied research views also emerge from the failure of such measures to predict the nature of human behavior. Such realizations predict that knowledge measures fail to rely on one construct. Kanwar (603) has used the same logic to explain the inconsistencies of consumer behavior. She reported that the self-perceived nature of customer knowledge failed to reflect the knowledge acquisition strategies of the customers (Kanwar 603). These inconsistencies have prompted some researchers to claim that knowledge measurement criteria may be using other constructs, besides knowledge, to measure knowledge (Weisburd and Chester 15). For example, subjective reports that measure consumer behaviors suggest that knowledge measurement techniques may have measured consumer confidence, as opposed to consumer knowledge (Kanwar 603). The realization that knowledge measures produce conflicting results has caused some people to believe these knowledge measures produce conflicting results (Weisburd and Chester 15).
Ramifications
Knowledge measures normally fail to provide accurate results because of methodological issues. For example, an assessment of indirect and direct methods of knowledge measurement, such as user experience and self-reports shows that these measures depend on student knowledge and learning. However, this methodological approach is false. For example, a customer who has no user experience with a product may still be highly knowledgeable about the product. Stated differently, a teenager who does not have any prior knowledge about a bicycle, but wants to own one, may have abundant knowledge regarding the bicycle. Therefore, there may be flawed operations of knowledge measurement techniques because they may classify people as less knowledgeable when they are knowledgeable. Relative to this assertion, Kanwar (603) says self-assessment reports may fail to portray the correct picture of a person’s knowledge because they may fail to reflect the correct performance of a person’s knowledge base. A discussion of the inconsistencies depicted through actual and perceived self-reports shows that knowledgeable people are likely to provide an accurate self-report, while less knowledgeable people tend to exaggerate their assessments. Particularly, this observation is true for people who have little formal education. The same findings mirror similar educational findings, which show that highly knowledgeable students are likely to provide accurate knowledge assessments, after evaluating the feedback from their learning processes (Kanwar 603). Therefore, erroneous self-reports are not likely to exist only in situations where the respondents are less knowledgeable, but also in instances where such people use the little knowledge they have acquired, through informal means, to answer the reports. This analysis reveals two testable outcomes that could evaluate the reliability of measures for analyzing knowledge. The first outcome shows a direct correlation between knowledge measurement techniques and the objective requirements of the process. This correlation is only significant for people who have undergone formal training. The second outcome shows no correlation between both variables, for people who have not experienced this formal training. For example, there is an insignificant correlation between knowledge and objective requirements for people who have acquired knowledge through experience and not formal means of knowledge acquisition.
Weisburd and Chester (14) say that measurement lies at the heart of gaining new knowledge because he believes knowledge would not exist without the inclusion of measurement values. He also says measurement is an integral part of human life (Weisburd and Chester 14). Indeed, sometimes, people assign measurement values to other people, issues, and objectives without thinking much of it. In knowledge management, this process has to occur systematically because there are clearly defined ways for developing and using different measures for knowledge management. Although it is crucial to focus on the products of knowledge acquisition, it is also crucial to understand that measurement forms an integral part of knowledge acquisition. Weisburd and Chester (14) say even the most sophisticated forms of knowledge are only important to the extent that they are measurable. They extrapolate this fact to research processes by saying, “Researchers can build a very complex structure of analysis. But if the measures that form the foundation of research processes are inappropriate for the analyses that are conducted, the findings cannot be relied on” (Weisburd and Chester 14).
The understanding that measurement is a fundamental building block of knowledge management is important in different professional fields. Particularly, education provides a good example of this understanding because it is at the center of knowledge acquisition. Knowledge acquisition develops and occurs in different ways. For example, students could gain knowledge through action, observation, interviews (and the likes). They could also gain knowledge by examining routine information from earlier researchers. Similarly, based on an analysis of the works of previous researchers they may also understand new information. The methods for undertaking knowledge acquisition may therefore vary, but one common denominator here is an understanding of how to gain knowledge (positivism). At the center of this philosophy is the understanding that science depends on facts and not values, to acquire and develop new knowledge. New knowledge does not provide decisions regarding the existence of individual elements in the world, but it helps to inform such decisions. Therefore, new knowledge helps us to investigate human reality; thus focusing on measurement as a practical tool of doing so.
Weisburd and Chester (14) say it is important to conceive the idea that all forms of measurement aim to distinguish groups or phenomena from one another. The implicit ramification of this fact is the classification of new knowledge into easily understandable facets. This process leads to the creation of variables because the measurements of these variables ascertain the reliability of new knowledge. This process also implies the easy categorization of units of knowledge into definite categories. Weisburd and Chester (14) find it important to highlight the differences between scientific measurement and other types of measurement because scientific measurement uses systematic criteria as the basis of gaining new knowledge.
Conclusion
Based on the assessment of the nature of knowledge, this paper affirms that without measurement, there is no knowledge. To comprehend, use, and improve knowledge, people need to include measurement tools to manage and understand knowledge. The failure to do so may mean that knowledge cannot exist in an identifiable way for human use, or understanding. The limited nature of human thought (which births knowledge) also explains why measurable instruments define knowledge. Indeed, because thoughts are fragmented, knowledge also exists in a fragmented and limited form. It is incomprehensible to imagine that knowledge is boundless, when human thought (which causes its existence) is fragmented and limited. Therefore, although human thoughts could produce boundless ideas, they are still fixated on material elements (the human brain), which are finite and limited.
The main problem associated with understanding human knowledge as a function of human measurement is the inconsistencies that these human measurements produce when they evaluate knowledge and predict human behavior. This paper shows that this argument has dominated most criticisms for knowledge measurement techniques, such as self-reporting. However, a deeper assessment of this issue reveals that methodological flaws explain most of the problems associated with these measurement tools. Nonetheless, the importance of measurement techniques in knowledge acquisition stems from understanding the nature of knowledge and its constituents. Stated differently, knowledge is a finite concept that develops from finite elements that outline its limits.
Works Cited
Hunt, Darwin. “The Concept of Knowledge and how to Measure it.” Journal of Intellectual Capital 4.1 (2003): 100-113. Print.
Krishnamurti, Jiddu. Mind Without Measure: The Root Cause of Confusion. 2013. Web.
Weisburd, David and Britt Chester. Statistics in Criminal Justice, New York: Springer, 2007. Print.