knowledge is more important than marks essay

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In This Article Expand or collapse the "in this article" section Value of Knowledge

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Value of Knowledge by Erik J. Olsson LAST REVIEWED: 26 August 2013 LAST MODIFIED: 26 August 2013 DOI: 10.1093/obo/9780195396577-0008

Everyone agrees that it is good to know. If you know that it will rain tomorrow, you can adapt your traveling plans accordingly; if you know that the euro crisis will soon be over, you can make a fortune buying euros; if you know a lot about philosophy, you can become a highly regarded teacher; and so on. Knowledge is clearly valuable in the sense of securing success in practical life, or at least making success more likely. Even philosophers, who disagree about many other things, do not normally debate the proposition that knowledge is of great value in practical terms. Moreover, they normally do not dispute the claim that knowledge is, in some ways, more valuable than other, lesser things, such as mere true belief. But this is where agreement usually ends. Philosophers disagree widely over what it is that makes knowledge more valuable than mere true belief. The question of why knowledge is more valuable than mere true belief, raised with characteristic clarity by Plato in the dialogue Meno , has therefore been in the focus of the epistemological debate. The value of knowledge was long not considered to be a serious epistemological concern until it emerged, in the late 1990s, as the central problem of a new research program with contributions from, among others, Jonathan Kvanvig, Ernest Sosa, Richard Swinburne, and Linda Zagzebski. Other authors followed, for example, John Greco, Wayne Riggs, and Duncan Pritchard, marking what has been referred to as a “value turn” in epistemology. A characteristic feature of this movement is that the value problem is used to guide inquiry into the traditionally more debated issue regarding the nature of knowledge. Thus, authors in the value tradition tend to think that any reasonable definition of knowledge should satisfy the condition that knowledge comes out as being distinctively valuable. These authors generally believe, moreover, that the reliabilist account of knowledge, according to which knowledge amounts to reliably produced true belief, does not satisfy this condition because of the so-called swamping problem: if a belief is true, the fact that it was reliably acquired does not seem to add value. Hence, they are inclined to reject the reliabilist theory in favor of other definitions of knowledge, such as a definition that explicates knowledge in terms of intellectual (epistemic) virtue or some variation on that theme.

There are not too many books that deal exclusively with the value of knowledge. The most well-known book-length study is Kvanvig 2003 . Kvanvig’s book was instrumental in setting the agenda for the value debate, and it continues to be one of the most cited texts in this area of epistemology. Published in 2003, it is still a useful introductory text starting with classical approaches and leading up to contemporary work. Classical and early responses to the value problem are dismissed in the first chapter (for reasons that later authors have sometimes contested). It can also be used as a textbook if supplemented with articles that provide different outlooks on the topic, such as the overviews Olsson 2011 , Pritchard 2007 , and Pritchard and Turri 2011 .

Kvanvig, Jonathan. The Value of Knowledge and the Pursuit of Understanding . Cambridge, UK: Cambridge University Press, 2003.

DOI: 10.1017/CBO9780511498909

Kvanvig argues that virtue epistemology can solve the value problem as that problem was understood by Plato. But he also thinks that the problem in its most general form—showing why knowledge is more valuable than its conceptual parts—does not admit of a plausible solution. Instead, he argues that understanding, not knowledge, is what has distinctive value.

Olsson, Erik J. “The Value of Knowledge.” Philosophy Compass 6.12 (2011): 874–883.

DOI: 10.1111/j.1747-9991.2011.00425.x

This article provides an overview of the area, starting with historical figures and early work. The contemporary debate is surveyed and some recent developments are highlighted, including recent criticisms of virtue epistemology. The emphasis is on classical and reliabilist-externalist responses.

Pritchard, Duncan H. “ Recent Work on Epistemic Value .” American Philosophical Quarterly 44 (2007): 85–110.

Focusing on virtue epistemology, Pritchard’s extensive survey covers most works on the value of knowledge that had been published up to 2007. It also treats some nonstandard, though related, subjects such as the relation between epistemic value and the problem of skepticism, and the value of true belief.

Pritchard, Duncan H., and John Turri. “ The Value of Knowledge .” In The Stanford Encyclopedia of Philosophy . Edited by Edward N. Zalta. 2011.

This is a useful overview of the problem of the value of knowledge, covering a number of the most significant and useful debates and positions.

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The Psychology and Philosophy of Imagination

With enough imagination, we would never have to work again..

Posted November 1, 2018

[Article updated on 17 June 2019]

Einstein held that imagination is more important than knowledge: 'I am enough of the artist to draw freely upon my imagination. Knowledge is limited. Imagination encircles the world.'

I define imagination as the faculty of the mind that forms and manipulates images, propositions, concepts, emotions, and sensations above and beyond, and sometimes independently, of incoming stimuli, to open up the realms of the abstract, the figurative, the possible, the hypothetical, and the paradigmatic or universal.

Imagination comes in many forms and by many degrees, ranging from scientific reasoning to musical appreciation; and overlaps with a number of other cognitive constructs including belief, desire, emotion , memory , supposition, and fantasy . Belief, like perception, aims at according with reality, while desire aims at altering reality. Like belief, emotion also aims at according with reality, but more particularly at reflecting the significance of its object, or class of object, for the subject—an aspect that it shares with many forms of imagination. Like imagination, memory can involve remote imagery. But unlike imagination, memory is (or aims to be) rooted in reality and serves primarily to frame belief and guide moment-by-moment action. Memories are often more vivid than imaginings, which are, in turn, more vivid that mere suppositions. Suppositions tend to be cold and cognitive, and lacking in the emotional and existential dimensions of imagination, and in its vividness. Finally, fantasy may be understood as a type of imagination, namely, imagination for the improbable.

I say the improbable rather than the impossible, because there is a theory that, just as perception justifies beliefs about actuality, so imagination justifies beliefs about possibility (or at least, metaphysical as opposed to natural possibility). To quote Hume, ‘it is an established maxim in metaphysics, that whatever the mind clearly conceives, includes the idea of possible existence, or in other words, that nothing we imagine is absolutely impossible.’ Could ghosts, the devil, time travel, and other imaginary things really be possible? I think inconceivability may be a better guide to impossibility than conceivability to possibility. But what does it mean for something to be conceivable or inconceivable, and by whom? It is easy to conceive of something other than oxygen in the place of oxygen, if one does not know anything about oxygen. In that much, knowledge and science constrain imagination—although, no doubt, also help to focus it. The interplay between knowledge and imagination is most problematic when the ‘knowledge’ is wrong.

In any case, until very recently, most human societies did not mark a strict divide between imagination and belief, or fiction and reality, with each one informing and enriching the other. In fact, it could be argued that, in many important respects, the fiction primed over the reality—and even that this has been, and no doubt still is, one of the hallmarks of homo sapiens . Today, there are pills for people who confuse imaginings and beliefs, but back in the day no one ever thought that life, despite its much harder hardships, might be meaningless—which I think tells us quite a bit about imagination and its uses, and also, incidentally, about mental illness and its causes.

The uses of imagination are many, more than I can enumerate. Most children begin to develop pretend play at around 15 months of age. What are children doing when they pretend play? And why are they so absorbed in works of imagination? When I was seven years old, I would devour book after book and plead with my parents for those not already in the bookcase. By playing out scenarios and extending themselves beyond their limited experience, children seek to make sense of the world and find their place within it. This meaning-making is full of emotion—joy, excitement, awe —and finds an echo in every subsequent act of creation.

Whenever we look at an object such as the Mona Lisa, we see much more than just the frame and the brushstrokes. In fact, we barely see the brushstrokes at all. In imagination as in our dreams , we ascribe form, pattern, and significance to things, and then reflect them back onto those things. Without this work of interpreting and assimilating, the world would be no more than an endless stream of sense impressions, as it might sometimes seem to those who lack imagination, with no hope of escape or reprieve.

More than that, by imagination we are able to complete the world, or our world, by conjuring up the missing parts, and even to inhabit entirely other worlds such as Middle-earth or the Seven Kingdoms. Imagination remains highly active throughout adulthood, and what is chick lit or even pornography if not an aid to the adult imagination? In one year (2018), Pornhub recorded 33.5 billion visits, equivalent to more than four times the world population—and that’s just on the one site.

If imagination lets us feel at home in the world, it also enables us to get things done in the world. Science advances by hypothesis, which is a function of imagination, and philosophy makes frequent use of thought experiments such as the brain in the vat, the trolley problem, and Plato’s Republic. More than that, imagination enables us to form associations and connections, and thereby to apply our knowledge to real life situations. It opens up alternatives and possibilities and guides our decision-making by playing them out in our mind. So many of our failures—and, dare I say, a few of our successes—are in fact failures of the imagination.

Imagination also enables us to talk to one another, understand one another, and work together. Without it, there could be no metaphor, no irony, no humour, no past or future tense, and no conditional either. Indeed, there could be no language at all, for what are words if not symbols and representations? By imagination, we can put ourselves in other people’s shoes, think what they think, feel what they feel, and project them and our relationship into the future. Problems in autism , which can be understood as a disorder of imagination, include abnormalities in patterns of communication, impairments in social interactions, and a restricted repertoire of behaviours, interests, and activities.

knowledge is more important than marks essay

As I argue in my new book, Hypersanity: Thinking Beyond Thinking , imagination is the highest form of thought, and almost divine in its reach. With enough imagination, we could identify and solve all of our problems. With enough imagination, we would never have to work again—or, at least, not for money. With enough imagination, we could win over, or defeat, anyone we wanted to. But our imagination is so poor that we haven’t even imagined what it would be like to have that kind of imagination.

I’m lucky to have received a decent education , but one thing it certainly didn’t do for me is cultivate my imagination. In fact, medical school in particular did everything to destroy it. In recent years, I’ve been trying to recover the bright and vivid imagination that I left behind in primary school. For that, I’ve been doing just three things, all of them very simple—or, at least, very simple to explain.

Being aware of the importance of imagination.
Making time for sleep and idleness.
Taking inspiration from the natural world.

I’ll conclude briefly with these few words from William Blake, which point to the significance of the natural world and the transcending power of imagination:

The tree which moves some to tears of joy is in the eyes of others only a green thing that stands in the way. Some see nature all ridicule and deformity… and some scarce see nature at all. But to the eyes of the man of imagination, nature is imagination itself.

Albert Einstein, in an interview by George Sylvester Viereck for the Saturday Evening Post, October 26, 1929.

David Hume (1738), A Treatise of Human Nature, I.2.2.

Pornhub Insights, 2018 Year in Review. December 11, 2018.

William Blake (1799), Letter to Revd. Dr Trusler.

Neel Burton, M.D. , is a psychiatrist, philosopher, and writer who lives and teaches in Oxford, England.

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7.2 Knowledge

Learning objectives.

By the end of this section, you will be able to:

Identify and explain the elements of Plato’s traditional account of knowledge.
Describe the Gettier problem.
Recall a Gettier case and explain how it is a counterexample to the traditional account of knowledge.
Identify and explain a way of thinking that attempts to solve the Gettier problem.

What does it mean to say that one knows something? Knowledge is an important concept in all areas of thought. Knowledge is the goal and therefore enjoys a special status. Investigating the nature of knowledge reveals the importance of other concepts that are key to epistemological theorizing—justification in particular.

Plato and the Traditional Account of Knowledge

Plato , one of the most important of the Greek philosophers, hypothesized that knowledge is justified true belief. Plato’s analysis is known as the traditional account of knowledge . Plato’s definition is that a person S knows proposition P if and only if

S believes P, and
S is justified in believing P (Plato 1997b).

Plato’s hypothesis on knowledge, often referred to as the JTB account (because it is “ justified true belief ”), is highly intuitive. To say “John knows P, but he does not believe P” sounds wrong. In order to know something, a subject must first believe it. And one also cannot say “Ali knows P, but P is false.” A person simply cannot have knowledge of false things. Knowledge requires truth. Last, someone should not claim to know P if they have no reason to believe P (a reason to believe being justification for P).

Problems with the Traditional Account of Knowledge

Amazingly, Plato ’s view that knowledge is justified true belief was generally accepted until the 20th century (over 2,000 years!). But once this analysis was questioned, a flurry of developments occurred within epistemology in the latter half of the 20th century. This section discusses the counterexample method at play in the dialectic concerning what knowledge is. Plato’s JTB analysis was the first to come under scrutiny.

In 1963, American philosopher Edmund Gettier (1927–2021) published a short paper titled “Is Justified True Belief Knowledge?,” which upended the JTB canon in Western philosophy. Gettier presents two counterexamples to Plato’s analysis of knowledge. In these counterexamples, a person seems to have a justified true belief, yet they do not seem to have knowledge. While Gettier is credited with the first popular counterexample to the JTB account, he was not the first philosopher to articulate a counterexample that calls into question Plato’s analysis. But because Gettier published the first influential account, any example that seems to undermine Plato’s JTB account of knowledge is called a Gettier case . Gettier cases illustrate the inadequacy of the JTB account—a problem referred to as the Gettier problem .

Dharmakīrti’s Mirage

The earliest known Gettier case, long predating the term, was conceived by the eighth century Indian Buddhist philosopher Dharmakīrti . Dharmakīrti’s case asks one to imagine a weary nomad traveling across the desert in search of water (Dreyfus 1997). The traveler crests a mountain and sees what appears to be an oasis in the valley below, and so comes to believe that there is water in the valley. However, the oasis is just a mirage. Yet there is water in the valley, but it is just beneath the surface of the land where the mirage is. The traveler is justified in believing there is water in the valley due to sensory experience. Furthermore, it is true that there is water in the valley. However, the traveler’s belief does not seem to count as knowledge. Dharmakīrti’s conclusion is that the traveler cannot be said to know there is water in the valley because the traveler’s reason for believing that there is water in the valley is an illusory mirage.

Russell’s Case

Perhaps you’ve heard the phrase “Even a broken clock is right twice a day.” The next case relies on this fact about broken clocks. In 1948, Bertrand Russell offered a case in which a man looks up at a stopped clock at exactly the correct time:

There is the man who looks at a clock which is not going, though he thinks it is, and who happens to look at it at the moment when it is right; this man acquires a true belief as to the time of day, but cannot be said to have knowledge. (Russell 1948, 154)

Imagine that the clock the man looks at is known for its reliability. Hence, the man is justified in believing that the time is, for example, 4:30. And, as the cases supposes, it is true that it is 4:30. However, given that the clock is not working and that the man happens to look up at one of the two times a day that the clock is correct, it is only a matter of luck that his belief happens to be true. Hence, Russell concludes that the man cannot be said to know the correct time.

Fake Barn Country

The last Gettier case we will look at is from American philosopher Carl Ginet (b. 1932) (Goldman 1976). Henry is driving through a bucolic area of farmland and barns. What he doesn’t realize, however, is that the area is currently being used as a movie set, and all the barns save one are actually barn facades. While looking at one of the barns, Henry says to himself, “That is a barn.” Luckily for Henry, the one he points to is the one true barn in the area. Again, all the conditions in Plato’s analysis of knowledge are met. It is true that Henry is looking at a real barn, and he believes it is a barn. Furthermore, he has come to this belief utilizing justifiable means—he is using his vision, in normal lighting, to identify a common object (a barn). Yet one cannot reasonably say that Henry knows the barn is a barn because he could have, by chance, accidentally identified one of the fake barns as a true barn. He fortunately happens to pick the one true barn.

Table 7.2 summarizes the Gettier cases discussed in this chapter.

Fixing Plato’s Traditional Account of Knowledge

Gettier cases demonstrate that Plato ’s traditional account of knowledge as justified true belief is wrong. Specifically, Gettier cases show that a belief being true and justified is not sufficient for that belief to count as knowledge. In all the cases discussed, the subject seems to have a justified true belief but not knowledge. Notice that this does not mean that belief, truth, or justification is not necessary for knowledge. Indeed, when speaking of propositional knowledge, all philosophers grant that belief and truth are necessary conditions for knowledge. A person cannot be said to know a proposition if they do not believe that proposition. And clearly, if a belief is to count as knowledge, then that believe simply cannot be false. Accordingly, attempts to solve the Gettier problem do one of two things: either they replace the justification condition with something more robust, or they add a fourth condition to JTB to make the account sufficient.

No False Premises

In Dharmakīrti’s case, the nomad believes there is water in the valley based on the false belief that a mirage is an oasis. And in Russell’s case, the man bases his true belief about the time on the false belief that the clock he’s looking at is working. In both cases, the inference that leads to the true belief passes through false premises. In response to this fact, American philosopher Gilbert Harman (1928–2021) suggested adding a condition to the JTB account that he termed “no false lemmas” (Harman 1973). A false lemma is a false premise, or step in the reasoning process. Harman’s fourth condition is that a person’s belief cannot be based on an inference that uses false premises. According to Harman, S knows P if and only if (1) P is true, (2) S believes P, (3) S is justified in believing P, and (4) S did not infer P from any falsehoods.

Harman theorized that many counterexamples to the traditional account share a similar feature: the truth of the belief is not appropriately connected to the evidence used to deduce that belief. Going back to Dharmakīrti ’s case, what makes the statement “There’s water in the valley” true is the fact that there is water below the surface. However, the nomad comes to believe that there is water based on the mistaken belief that a mirage is an oasis, so what makes the belief true is not connected to the reason the nomad believes it. If Harman’s condition that the reasoning that leads to belief cannot pass through false steps is added, then the nomad’s belief no longer counts as knowledge.

Harman ’s emendation explains why the nomad does not have knowledge and accounts for the intuition that the man in Russell’s case does not actually know what time it is. However, this cannot take care of all Gettier cases . Consider the case of Henry in fake barn country. Henry comes to believe he is looking at a barn based on his perceptual experience of the barn in front of him. And Henry does look at a real barn. He does not reason through any false premises, such as “All the structures on my drive are barns.” His inference flows directly from his perceptual experience of a real barn. Yet it is a matter of luck that Henry isn’t looking at one of the many barn facades in the area, so his belief still does not seem to count as knowledge. Because Harman’s account is vulnerable to the barn counterexample, it does not solve the Gettier problem.

Ruling Out Defeaters and Alternatives

While driving through fake barn country, Henry happens to form the belief “That is a barn” when looking at the only real barn in the area. While Henry’s belief is not based on false premises, there still seems to be something wrong with it. Why? The problem is that certain facts about Henry’s environment (that it is filled with barn facades), if known, would undermine his confidence in the belief. That the area is predominantly filled with barn facades is what is known as a defeater because it serves to defeat the justification for his belief. Contemporary American philosophers Keith Lehrer and Thomas Paxson Jr. suggest that justified true belief is knowledge as long as there are no existing defeaters of the belief (Lehrer and Paxson 1969). S has knowledge that P if and only if (1) P is true, (2) S believes P, (3) S is justified in believing P, and (4) there exist no defeaters for P. The added fourth condition means that there cannot exist evidence that, if believed by S, would undermine S’s justification.

The “no defeaters” condition solves all three Gettier cases discussed so far because in each case, there exists evidence that, if possessed by the subject, would undermine their justification. Henry cannot be said to know he’s looking at a barn because of the evidence that most of the barns in the area are fake, and Russell’s man doesn’t know the time because the clock is stopped. The “no defeaters” condition thus helps solve many Gettier cases. However, we now need a thorough account of when evidence counts as a defeater . We are told that a defeater is evidence that would undermine a person’s justification but not how it does this. It cannot be that all evidence that weakens a belief is a defeater because this would make knowledge attainment much more difficult. For many of our justified true beliefs , there exists some evidence that we are unaware of that could weaken our justification. For example, we get many beliefs from other people. Research indicates that people tell an average of one lie per day (DePaulo et al. 1996; Serota, Levine, and Boster 2010). So when someone tells you something in conversation, often it is true that the person has lied once today. Is the evidence that a person has lied once today enough evidence to undermine your justification for believing what they tell you?

Notice that because a defeater is evidence that would undermine a person’s justification, what counts as a defeater depends on what justification is. Of the theories of knowledge examined so far, all of them treat justification as basic. They state that a belief must be justified but not how to measure or determine justification.

The Problem with Justification

The traditional analysis of knowledge explains that knowledge is justified true belief. But even if we accept this definition, we could still wonder whether a true belief is knowledge because we may wonder if it is justified. What counts as justification ? Justification is a rather broad concept. Instead of simply stating that justification is necessary for knowledge, perhaps a thorough account of knowledge ought to instead spell out what this means. The next section looks more deeply at how to understand justification and how some theorists suggest replacing the justification condition in order to solve the Gettier problem.

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6 The Value and Importance of Knowledge

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There has been a recent renewal of interest — inspired in part by Jonathan Kvanvig — in questions about whether knowledge is of distinctive epistemic value and, more general, what exactly is of distinctive epistemic value. One implication of the literature is that if knowledge is not of distinctive epistemic value, it doesn't deserve its central place in epistemology. After arguing that what should matter for epistemological attention is the importance, rather than the value, of knowledge, the chapter turns to arguing that conclusions in earlier chapters show a way toward explaining the distinctive importance of knowledge: unless knowledge requires certainty, earlier conclusions can be used to construct a biconditional account of knowledge that explains its distinctive importance better than rival accounts. Along the way the chapter argues that true belief is not particularly valuable.

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Knowledge How

In introductory classes to epistemology, we are taught to distinguish between three different kinds of knowledge. The first kind is acquaintance knowledge : we know our mothers, our friends, our pets, etc., by being acquainted with them. The second kind is knowledge of facts, propositional knowledge, or knowledge-that : this is the sort of knowledge we acquire when we learn that, say, Ithaca is in New York State or that Turin is located in Italy. It is customary to add to the list a third kind of knowledge that is supposed to be distinct both from acquaintance knowledge and from propositional knowledge. One possesses this knowledge when one can be truly described as knowing how to do something: play the piano, make a pie, walk, speak, create, build, and so on.

The distinction between knowledge-how and knowledge-that was brought to scrutiny in analytic philosophy by Ryle in his seminal The Concept of Mind (1949), where he raised some of the now classical objections to the so-called “intellectualist legend”: the view that knowledge-how amounts to knowledge-that. Ryle instead advocated an “anti-intellectualist” view of knowledge-how according to which knowledge-how and knowledge-that are distinct kinds of knowledge, and manifestations of knowledge-how are not necessarily manifestations of knowledge-that. This anti-intellectualism has been the received view among philosophers for a long time. Even psychologists and neuroscientists have explicitly appealed to Ryle’s classical distinction when discussing their empirical findings (e.g., Cohen & Squire 1980; Anderson 1983). Nevertheless, in the last twenty years, a renewed interest by epistemologists in the nature of knowledge-how has brought new life to the debate, where new versions of intellectualism and anti-intellectualism have been developed and argued for. The debate is partly epistemological: is knowledge-how an altogether distinct kind of knowledge, different from knowledge-that? But it is also about a psychological question: what kind of psychological state is knowledge-how? The goal of this entry is to overview the debate between intellectualists and anti-intellectualists, while highlighting the implications of this debate for related questions concerning intelligence, cognition, language, and skills.

This entry starts by looking at some classical arguments against intellectualism about knowledge-how: the regress argument (section 1), the insufficiency argument (section 2), and the gradability argument (section 3). Then two motivating arguments for intellectualism are considered: the linguistic argument (section 4) and the action theory argument (section 5). Section 6 overviews the recent epistemological debate on whether knowledge-how and propositional knowledge have the same epistemic profile. Section 7 discusses the cognitive science argument against intellectualism. Section 8 surveys what forms anti-intellectualism about knowledge-how has taken in the recent literature. Section 9 looks at the relation between knowledge-how and skills. Section 10 discusses knowledge-how and other related topics.

1.1 The Contemplation Argument

1.2 the employment regress, 1.3 a revival of the regress argument, 1.4 lewis carroll’s regress, 2. the sufficiency argument, 3. the gradability argument, 4.1 the details of the intellectualist proposal, 4.2 first group of objections, 4.3 second group of objections, 4.4 third group of objections, 5. the action theory argument and the question of joint action, 6.1 knowledge-how and belief, 6.2 knowledge-how and gettier, 6.3 knowledge how, defeasibility, and testimony, 7.1 the argument, 7.2 improving the argument, 7.3 articulability, 7.4 knowledge-how in preverbal children and nonhuman animals, 8.1 revisionary intellectualism, 8.2 ability based anti-intellectualism.

8.3 Knowledge-How and Skill

9.1 Skill Across Cultures

9.2 intellectualism and anti-intellectualism about skill, 9.3 skills in epistemology, 9.4 the nature of skilled action, 10. knowledge-how and other related topics, other internet resources, related entries, 1. the regress argument.

Ryle’s most famous objection to intellectualist accounts of skills and knowledge-how is that they lead to a vicious regress:

The consideration of propositions is itself an operation the execution of which can be more or less intelligent, less or more stupid. But if, for any operation to be intelligently executed, a prior theoretical operation had first to be performed and performed intelligently, it would be a logical impossibility for anyone ever to break into the circle. (1949: 19)

Ryle concludes:

“Intelligent” cannot be defined in terms of “intellectual” or “knowing how” in terms of “knowing that”, (1949: 20)

on pain of a vicious regress (see also Ryle 1946: 22). Exactly how to reconstruct Ryle’s argument is a matter of controversy (Stanley & Williamson 2001; Stanley 2011b; Bengson & Moffett 2011a; Cath 2013; Fantl 2011; Kremer 2020). The next sections discuss different possible ways of understanding the regress challenge and possible responses on behalf of intellectualism.

The contemplation argument assumes for reductio that for any action to be intelligently executed, a prior theoretical operation of “contemplating” has to be performed first :

Contemplation premise (CP): In order to employ one’s knowledge that p , one must contemplate the proposition p .

Assume in addition the following definition of intellectualism:

Strong intellectualism (SI) : For an action Φ, knowing how to Φ consists in knowing some proposition p .

And assume further that in performing an action Φ, one employs one’s knowledge-how to Φ:

Action premise (AP) : For an action Φ, if one Φs, then one employs one’s knowledge-how to Φ.

With these premises the regress goes as follows. Suppose that one performs an action Φ:

By AP, one employs one’s knowledge-how to Φ.
By SI, one employs the knowledge that p , for some p .
So, by CP, one contemplates p .
But contemplating p is an action.
So by AP, if one contemplates p, one employs one’s knowledge-how to contemplate p .
By CP, one ought to contemplate another proposition q , for some q .

The contemplation argument aims at showing the falsity of SI, by showing that its truth, together with the truth of AP and CP, triggers an infinite regress. If SI were true, then performing any action would require contemplating an infinite number of propositions of ever-increasing complexity. On the assumption that this cannot be done in a finite amount of time, the argument goes, accepting SI would lead to the clearly absurd conclusion that no agent could ever perform an action within a finite time (see Fantl 2011: 122).

The question is whether AP and CP are plausible premises. Following Ginet (1975), Stanley & Williamson (2001) argue that AP is plausible only if the relevant Φ is an intentional action. To use one of Ryle’s (1949: 33) own examples, if a clumsy person inadvertently tumbles, it does not follow that in doing so, they employ their knowledge-how to tumble. By contrast, the clown employs their knowledge-how when they tumble on purpose. Nevertheless, if we restrict AP to intentional actions, then the regress can be stopped by observing that contemplating a proposition might happen non-intentionally. For example, when I employ my knowledge that there is a red light ahead by applying the brakes, I need not intentionally contemplate the proposition that there is a red light ahead. Correspondingly, if contemplating a proposition can be done non-intentionally, such contemplation is not the kind of action that requires us to know how to perform it—therefore, it does not trigger the restricted AP and the regress is blocked altogether. Some object that the contemplation in this example might be intentional but unconscious (as suggested by Noë 2005: 282). But it is unclear what reasons there are for thinking that every time one employs one’s knowledge, one intentionally contemplates the relevant proposition (Cath 2013: 365–366).

The Contemplation Argument also assumes CP—i.e., that in order to employ propositional knowledge when acting, one ought to contemplate the relevant proposition. Against CP, Ginet (1975: 7) observes that one might manifest one’s knowledge that one can get the door open by turning the knob and pushing it (as well as my knowledge that there is a door there) by performing that operation quite automatically as one leaves the room; and one may do this without formulating (in one’s mind or out loud) that proposition or any other relevant proposition. Ginet concludes that Ryle’s original argument does not teach us that intellectualism about knowledge-how is false but only that knowledge can be acted upon and manifested without requiring any contemplation on the part of the agent. Indeed, some scholars think that this last weaker claim was the only goal of Ryle’s original argument (Rosefeldt 2004; Sax 2010).

However, CP is not needed in order to trigger a regress. Perhaps the argument can be salvaged by replacing contemplation with a weaker relation. Consider replacing CP with EP:

The Employment Premise (EP): If one employs knowledge that p , one employs knowledge-how to employ one’s knowledge that p (and one’s state of knowledge that p is distinct from one’s state of knowing how to employ one’s knowledge that p ). (Cath 2013: 367–8)

The regress is triggered as before. Suppose one Φs:

By SI, that amounts to employing one’s knowledge that p , for some p .
By EP, one needs to employ one’s knowledge-how to employ one’s knowledge that p .
But employing one’s knowledge-how is an action.
By AP, one employs one’s knowledge-how about employing our knowledge-how to employ one’s knowledge that p .
By SI, that amounts to employing one’s knowledge of q , for some q .

Intellectualists might object to EP in ways similar to how CP was resisted—i.e., that not every action requires for its performance the employment of one’s knowledge-how: only intentional actions do, as the clown example suggests. According to this line of reply, employing one’s propositional knowledge might be more like a reflex in response to stimuli, rather than an action. Further, this version of the regress challenge may be accused of assuming that knowledge-that is “behaviorally inert” and needs to be intentionally selected or employed in order to be manifested. Yet, intellectualists have independent reasons to resist this picture (Stalnaker 2012). On the other hand, if Ryleans insist that employments of knowledge-that are actions of sort, it seems there is no principled reason why employments of knowledge-how would not be subject to the same requirement. Therefore, it looks like any regress generated for the intellectualist is generated for Ryle as well (Stanley 2011b: 14, 26; though see Fantl 2011 for a possible difference between the regress generated for Ryle and the regress generated for intellectualism).

A variety of actions—say, remembering to check the car’s blindspot when reversing—can be intelligent even though they are not intentional. Or one might manifest intelligence through processes —e.g., by coming to understand a difficult proposition, without them even being actions. If one accepts that intelligent performances, whether intentional or not, are necessarily guided by knowledge-how, one might try to recast the regress argument by replacing AP with IPP (Weatherson 2017):

Intelligent performance premise (IPP): For a performance Φ, if one Φs intelligently, one manifests one’s knowledge-how to Φ.

Now it seems plausible that one’s manifestation of propositional knowledge can be intelligent in some cases but not in others. For example, one might manifest one’s knowledge intelligently by bringing to bear one maxim that is appropriate instead of any other that is not to the particular situation which the agent faces. By IPP, if one’s manifestation of knowledge-that in a particular situation is intelligent, it requires one’s manifesting one’s knowledge-how. If intellectualism is true, that would in turn require manifesting one’s knowledge-that. If this manifesting of propositional knowledge is intelligent too, though unintentional, it requires knowledge-how. And so on. We get an infinite regress if one accepts that manifesting propositional knowledge can be an intelligent performance, also when it is not an intentional action. (For similar lines of argument, see also Fridland 2013, 2015; Löwenstein 2016: 276–80; Small 2017: 62–3).

Intellectualists might respond by distinguishing two senses in which a performance can be intelligent and two corresponding senses of manifestation, only one of which gives rise to the regress. First, an intelligent action might manifest one’s knowledge-how in the case that it is guided by this knowledge-how. On this reading, the regress is triggered. But there is also another—epistemic—sense in which an intelligent action manifests knowledge-how as long as it provides evidence for that knowledge-how. For example, the rings on a tree provide evidence for the tree’s age (hence manifest its age in the epistemic sense) but the rings on a tree are not guided by its age. Crucially, the regress does not arise on the epistemic sense of manifestation. Checking the blindspot might be intelligent in this epistemic sense of manifesting —providing evidence of—knowledge-how. Yet, this epistemic manifestation itself is not something that qualifies as intelligent or unintelligent.

A less discussed regress that can be found in Ryle (1946: 6–7) is an adaptation of Lewis Carroll’s (1895) regress. Suppose a student understands the premises of an argument and also its conclusion but fails to see that the conclusion follows. In order to help him, the teacher teaches him another proposition P —i.e., if the premises are true, then the conclusion is true. The student understands this and yet fails to see how from the premises and the additional premise P the conclusion follows. A second hypothetical proposition is added to his store, the proposition that if the premises is true, the conclusion is true too. The student still fails to see. And so on. Ryle concludes:

Knowing a rule of inference is not possessing a bit of extra information but being able to perform an intelligent operation. Knowing a rule is knowing how. It is realized in performances which conform to the rule, not in theoretical citations of it. (1946: 7)

One might respond (cf. Stanley 2011b) to this regress challenge that the student does not really understand the premises of an argument by modus ponens ( p , if p then q ), for that involves grasping the concept of a conditional, and on an inferentialist understanding (Boghossian 1996, 2003), that would dispose one to accept the conclusion of an inference by that rule. Inferentialism about meaning is, however, a controversial doctrine (for several criticisms, see Williamson 2011, 2012). Other replies might be available. Maybe the student does not represent the rule practically (see next section), or she is simply incapable of granting that the rule applies to this case, for that would explain her failure to be appropriately disposed to arrive at the conclusion, given the truth of the premises. (For yet other versions of the regress challenge, see Noë 2005: 285–6 and Hetherington 2006).

The claim that knowledge-how is a kind of knowledge-that encounters an immediate incredulous stare: how could propositional knowledge be sufficient for knowing how to do something? Ryle (1946: 5) himself poses this challenge as a starting point for his argument:

Obviously there is no truth or set of truths of which we could say “If only the stupid player had been informed of them, he would be a clever player”, or “When once he had been apprised of these truths he would play well”.

Certainly, one might know all the propositions that are relevant to how to perform a task, and yet fail to know how to perform it: knowledge-that does not seem sufficient for knowledge-how (see also Ryle 1940: 38–9).

In order to assess this objection, it is helpful to start with a toy intellectualist theory, on which knowledge-how is a matter of knowing, for some way or method to perform a task w , that w is in fact a way to perform it. In section 4 , we will see in more detail a linguistic argument for identifying knowledge-how with this sort of propositional knowledge (Stanley & Williamson 2001; Snowdon 2004). How could, the insufficiency objection goes, one know how to perform a task just in virtue of knowing a proposition about a way to perform it? Consider the following counterexample to intellectualism:

Swimming : Suppose I look at a swimmer’s swimming, and my swimming instructor pointing to the swimmer says to me, “That is a way in which you could swim too”. I believe my instructor and we may suppose that what she said is in fact true. I may thereby come to know a true answer to the question “How could I swim?” However, in the relevant sense, I may not have come to know how to swim. If I took a swimming test, I might still fail it. If thrown in the swimming pool, I might still drown. I do not know how to swim in the relevant sense and yet I do know a true proposition about how to swim.

In response to this sort of counterexample, intellectualists often appeal to “practical modes of presentation”: knowing a proposition observationally or demonstratively is not the same as knowing it practically. Knowledge-how is, at least in part, a matter of representing propositions about tasks and ways of executing tasks in a distinctively practical fashion. For one to know how to swim, in the relevant sense, one must know of a way to swim represented under a distinctive practical mode of presentation, which is essentially different from the observational or demonstrative mode of presentation in Swimming . This kind of practically represented propositional knowledge is what (some) intellectualists call knowledge-how and is what is absent in the example above.

The notion of practical modes of presentation has received several criticisms (Schiffer 2002; Koethe 2002; Noë 2005; Fantl 2011; Glick 2015), on the ground that it seems excessively obscure or even question begging. Koethe (2002: 327) worries that practical modes of presentation smuggle in an antecedent notion of knowledge-how (though see Fantl 2008: 461 for a response). This widespread skepticism about practical modes of presentation has led some intellectualists to explore ways of responding to the insufficiency objection that do not appeal to practical modes of presentation. For example, Stanley (2011b: 126) considers answering the sufficiency challenge in Swimming by appealing to the context-sensitivity of the ability modal “could”. According to Stanley, depending on how the context for the modal is restricted, “That is how you could swim” could mean either that that is how you can swim given your current physical state or that that is how you could swim after training . But coming to know that that is how I could swim after training is clearly not enough for me to come to know how to swim now. Instead, the argument goes, what one needs to know is the former proposition: that that is a way to swim given my current physical state .

Yet, it is unclear that even this response works. Consider a variant of the previous scenario, where Mary is a skilled swimmer who is one day affected by memory loss and so forgets how she is able to swim (Glick 2015). Nothing has changed in Mary’s physical state: she is still able to swim but she just has forgotten how she is able to swim. Suppose she is told, by looking at a recording of her swimming the day before, that that is how she can in fact swim given her current physical state. She might come to know how she is in fact able to swim (just like that!). Yet, she would still fail to know how to swim in the relevant sense and still drown if thrown into the pool.

So, practical modes of representation are hard to escape if intellectualism is to be defended against the sufficiency objection. To assuage concerns about the intelligibility of practical modes of presentation, Pavese (2015b) proposes we think of them along the lines of practical senses, which in turn can be modeled after computer programs. Programs determine an output, just like Fregean senses determine a referent; and they are practical in that they break down a task into the smallest parts that the system can execute (the primitive operations of the system as well as into primitive ways of combining those parts) so they ground the ability to perform a complex task in terms of the ability to perform all of its parts. On this view, if one represents a task practically, one represents all of its parts, and the combination of those parts, through instructions that one has the ability to execute. So representing practically a task entails that one has the ability to perform the corresponding task. (For a critical discussion of practical ways of thinking, see Mosdell 2019. Habgood-Coote 2018c argues that the classical generality problem for reliabilism (Feldman 1985; Conee & Feldman 1998) arises for intellectualism.)

The notion of distinctively practical concepts is motivated by work outside the debate on intellectualism about knowledge-how. Other scholars have discussed concepts that are practical in that they dissociate from semantic and observational concepts and play a central role in explaining behavior. Peacocke (1986: 49–50) talks of “action-based ways of thinking”, Israel, Perry,and Tutiya (1993: 534) of “executable ideas”, and Pacherie (2000, 2006) of “action concepts”. Mylopoulous and Pacherie (2017) suggest that executable action concepts might be needed to overcome the interface problem—the problem of how cognitive representations (intentions) interact with motor representations (Butterfill & Sinigaglia 2014). Pavese (forthcoming-b) advances an empirical-functional case for practical concepts, arguing that they are needed to explain a distinctive sort of productive reasoning. Yet, other intellectualists argue we can dispense with practical modes of presentation altogether and instead appeal to ways of knowing that are distinctively practical or executive (Waights Hickman 2019; Cath 2020).

Levy (2017) argues that a form of intellectualism that only invokes practical ways of thinking and practical concepts might not be able to explain skillful motor behavior, for motor representations of the sort required for skilled action and posited by cognitive psychologists are non-conceptual. Along similar lines, Fridland (2014, 2017) argues motor control and motor representation cannot be countenanced by Stanley & Williamson’s (2001) and Stanley’s (2011b) forms of intellectualism. So, more promising forms of intellectualism might have to invoke, in addition to practical ways of thinking, non-conceptual practical representations (Pavese 2019; Krakauer 2020). Just like perceptual concepts are distinguished from non-conceptual perceptual representations, we might distinguish between practical conceptual representations and practical non-conceptual representations. Motor representations would fall under the latter heading. Nonconceptual motor representations also represent practically, as they break down a task in terms of the most basic operations that a system can perform.

Ryle (1949: 46) formulates the argument from gradability thus:

we never speak of a person having partial knowledge of a fact or truth … it is proper and normal to speak of a person knowing in part how to do something. Learning how or improving in ability is not like learning that or acquiring information. Truths can be imparted, procedures can only be inculcated, and while inculcation is a gradual process, imparting is relatively sudden.

As Kremer (2020: 102) points out, here Ryle is making two distinguishable points: (i) ascriptions of knowledge-how are gradable, whereas ascriptions of know-that are not; (ii) the gradability of these ascriptions is explained by the fact that knowledge-how must come in degrees, because learning-how brings improvement in knowledge-how. There is no parallel phenomenon in learning-that, and so no need for degrees of knowledge-that. Others have followed Ryle in thinking that the gradability argument shows intellectualism wrong. For example, Bengson and Moffett (2011b) argue that because knowledge-how is gradable, knowledge-how is more similar to acquaintance knowledge, which also comes in degrees (see also Ryle 1949: 46; Wiggins 2012; Santorio 2016; Kremer 2020: 102).

Pavese (2017) distinguishes between two kinds of gradability of knowledge-how ascriptions: one might know how to do something in part or entirely (quantitative gradability) or one might know how to do something better than somebody else (qualitative gradability). Crucially, these two kinds of gradability are also present more generally in other knowledge-wh (knowledge-when, who, why, where) ascriptions, which do seem to reduce to propositional knowledge. For instance, one might know in part who came to the party (Lahiri 1991, 2000; Roberts 2009) or know a better answer to that question than somebody else (see also Stanley 2011b: 31–5). If parts of an answer are propositions, then knowing an answer might still amount to knowledge of all of its parts. Knowing in part an answer would then amount to knowing at least one of the propositions that is part of that answer. Similarly, knowing a better answer amounts to knowing a proposition that better answers the relevant question. If this is true of other knowledge-wh ascriptions, it is certainly plausible that it is true for knowledge-how. One might know how to Φ in part by knowing only certain (propositional) parts of the answer to “how does one Φ?” and one might know a better answer to that question than someone else.

This response to the first part of the gradability objection inspires a further response to the second part concerning learning-how. Suppose that knowledge-how is a matter of knowing a practical answer, where a practical answer encompasses a practical representation for a task or a way to Φ ( section 2 ). As we have seen, practically representing requires possessing certain practical capacities and entails certain sorts of abilities. On this picture, one might gradually learn how to perform a task by gradually learning a practical answer to that question, for one requires time and practice to master a practical representation of how to perform the task. Thus, gradual learning may be compatible with the intellectualist picture, if it amounts to gradually coming to learn more parts of a practical answer.

4. The Linguistic Argument

Intellectualism has been motivated on the basis of a linguistic argument concerning knowledge-how ascriptions in English (Vendler 1972; Stanley & Williamson 2001; Snowdon 2004; Stanley 2011b, 2011c). Begin by noticing that (1) is remarkably similar to (2)–(3) (“finite knowledge wh ascriptions” as they embed a complement with a finitival verb) and to (4)–(5) (“infinitive knowledge-wh ascriptions” as they embed a complement with an infinitival verb):

According to the standard syntactic analysis, (2)–(5) have an interrogative as complement—“where is her piano located in the house?”, “who can play the piano?”, “what to do in case of an emergency?” are all interrogatives. Having said this, in broad outline, the linguistic argument for intellectualism has three steps. The first step is to follow the syntactic cues from (1)–(5) and identify the logical form of “ S knows how to Φ” with that of “ S knows + interrogative Q (= “how to Φ”). Call this premise Logical Form . The second step is to accept the orthodox semantics of knowledge-wh ascriptions, according to which in “ S knows + interrogative Q ”, Q denotes a question (C. Baker 1968) and according to which “ S knows + Q ” is true just in case S knows a proposition answering to the question expressed by Q . Call this premise Semantics for Knowledge-Wh (cf., among many others, Hamblin 1958, 1973; Hintikka 1976; Karttunen 1977; Heim 1994; Groenendijk & Stokhof 1982, 1997; and Higginbotham 1996). Finally, the third step is to extend this semantics to knowledge-how ascriptions, such that knowing how to Φ requires knowing a proposition that answers the question “how can one Φ?”

Next section (4.1) looks in some more detail to the intellectualist analysis of the truth conditions for knowledge-how ascriptions. The section after next ( 4.2 ) discusses several objections to the linguistic argument.

The linguistic argument concludes that Intellectualism is true:

Intellectualism about knowing how S knows how to Φ just in case S knows a proposition answering the question “how to Φ”.

But what is the proposition that one knows by knowing how to Φ?

First, note that the subject of the infinitival construction (“How to Φ”), or PRO, can either be interpreted de se ( de se PRO) or generically (generic PRO). According to the first interpretation, that an agent knows how to perform a ski stunt requires their knowing how to perform a ski stunt themselves . According to the latter interpretation, it requires knowing how one (as a generic agent or any other agent) would perform a ski stunt. When it comes to ascriptions of knowledge-how, we care about de se , and not generic, readings of knowing how. If an agent knows how to Φ in the relevant sense, they know how to Φ themselves.

Secondly, infinitival interrogatives such as “how to Φ” and “what to Φ” are ambiguous between a deontic reading ( how to Φ = how one should Φ; what to Φ = what one should do ) and an ability reading ( how to Φ = how one could Φ; what to Φ = what one could do ). The deontic reading does not seem relevant when we ascribe knowledge-how. Hence the relevant reading must be an ability reading. Joining these two disambiguations, the truth conditions of knowledge-how ascriptions are (cf. Schroeder 2012):

( Truth conditions ) “ S knows how to Φ” is true just in case S knows a proposition answering the question “How could they themselves Φ?”

Now, what counts as an answer to the question? Linguists distinguish between different kinds of answers that one might give to a question. An exhaustive answer to “How could S Φ?” would specify all the ways in which S could Φ; a mention-some answer , instead, would specify only one way in which S could Φ. For example, an exhaustive answer to the question “How could S make pasta?” would specify all different recipes for making pasta. A mention-some answer to the same question, instead, would specify (at least) only one recipe. When we ascribe knowledge-how, we don’t expect people to know all the possible ways of performing the relevant task. For example, “Mary knows how to make pasta” can be true, even if Mary only knows one recipe for pasta. This gives us the following truth conditions:

Intellectualism* “ S knows how to Φ” is true just in case S knows, for some way w of Φ -ing , that w is a way he himself could Φ.

As we have seen in section 2 , in addition to knowing that a way to Φ is a way to Φ, one needs to think of that way under a practical mode of presentation. Let Pr be a practical way of thinking of a way and let way of Φ -ing be a way of thinking of the property of being a way of Φ-ing; finally let ⦼ be a way of composing ways of thinking into a proposition. Then <Pr ⦼ way of Φ -ing > is the practical proposition that one comes to know when coming to know how to Φ. On how to implement Fregean senses in the compositional semantics, see Yalcin (2015).

Several philosophers have objected that intellectualists are giving undue weight to linguistic considerations and that other considerations, coming from the cognitive sciences, should be taken into account too, when thinking about the nature of knowledge-how (Noë 2005, 2011; Devitt 2011; Brown 2013; Johnson 2006; Glick 2011; Roth & Cummins 2011). It does not follow from this worry that the linguistic argument ought to be dismissed as lacking any evidential value. Consider an analogy. Arguably, the best theory of beliefs and desires is one on which these are propositional attitudes. This theory is compatible with how we ascribe beliefs and desires (i.e., ascriptions of beliefs are of the form “ S believes that p ”, where “ p ” is standardly taken to stand for proposition). But it is also compatible with folk psychology, according to which thinking of beliefs and desires as propositional attitudes helps explain behavior. By parity of reasoning, ideally, the best theory of knowledge-how should presumably be compatible both with our best psychological theory and our best linguistic theory of knowledge-how ascriptions (cf. Stanley 2011a, 2011b, 2011c; Cath 2015a for a defense of the linguistic methodology).

Among those engaging with the linguistic argument, many have objected that it fails to adequately capture the truth conditions of knowledge-how ascriptions (Roberts 2009; Brogaard 2009, 2011; Michaelis 2011; Bengson & Moffett 2011a; Ginzburg 2011; Abbott 2013; Santorio 2016; Hornsby 2016). Some have argued against the claim that knowledge-wh is a matter of knowing a proposition that answers a question ( Semantics for knowledge-wh) . For example, Carr (1979, 1981) argues that when you know how to do something, you have an attitude that essentially takes an act as its object. But when you know that something is the case, you have an attitude that essentially takes a proposition as its object. Yet, intellectualists might reply that knowledge-how might be an attitude towards an act in virtue of being an attitude towards a proposition about that act.

Others have questioned whether the complement “which team is winning” in “ S knows which team is winning” is, semantically, just like an interrogative (Brogaard 2009, 2011; Ginzburg 1995a, 1995b, 1996, 2011; Ginzburg & Sag 2000). One argument against this assumption is that, if, e.g., “which team is winning” denoted a question, we would expect it to co-refer with “the question of which team is winning”. Yet we cannot substitute such expression-pairs salva veritate . Suppose Jenny knows/discovered/revealed an interesting question and suppose the interesting question discovered by Jenny is “who left yesterday?”. Even so, it does not follow that Jenny knows/discovered/revealed who left yesterday. A response to this objection might be that these examples exploit a subtle equivocation (Stanley 2011b: ch. 2, following King 2002). Consider “Jamaal discovered a new element”. In it, “discovered” denotes a relation between Jamaal and an object, a chemical element. On the other hand, in the sentence “Jamaal discovered who left yesterday”, “discovered” denotes a different relation, one that holds between Jamaal and something of a different sort, namely, the proposition answering the question expressed by “who left yesterday”. It is this second relation which is relevant for the intellectualist. This is supported by the fact that the “[t]he former relation would be expressed in German by ‘ kennen ’, and the latter by ‘ wissen ’” (Stanley 2011b: 66). (For more relevant discussion, see Parent 2014.)

Others have questioned Logical form —the claim that in knowledge-how ascriptions, the embedded complement is an interrogative. Objectualists claim that the complement of knowledge-how ascriptions (“how to Φ”) is not an interrogative but an “objectual” complement—one denoting ways to Φ instead of propositions representing these ways (Bengson & Moffett 2011a). Objectualism is motivated by the consideration that “knowing how to Φ” seems to be equivalent to “knowing a way to Φ” in pretty much every context and by the apparent gradability of “knows-how” ascriptions (cf. section 3 ). An objectual semantics is in a good place to explain the gradability of knowledge-how ascriptions, since objectual knowledge ascriptions also permit degree modifiers—one can have partial knowledge of Paris, or know Paris better than someone else. Along similar lines, Bach (2012) and Abbott (2013) argue that in knowledge-how ascriptions “how to Φ” might work as a free relative . A free relative is a wh-phrase that denotes an individual. So for example, “what I was given for dinner” can be used as an interrogative in “I asked what I was given for dinner” but also as a free relative in “I ate what I was given for dinner”. In the latter ascription, it denotes some food that was given to me for dinner. In that sense, “how to Φ” according to this proposal, in “ S knows how to Φ” should be interpreted as a free relative denoting a way to Φ, rather than an answer to the question “how to Φ?”

To this proposal, some respond that knowledge-how ascriptions do not pass the standard tests for detecting free relative complements (Schaffer 2009: 486–91; Habgood-Coote 2018a). Take the coordinated use of knowledge-how and other knowledge-wh ascriptions in “ S has always known how to swim and never has wondered how”. This coordination suggests that both kinds of ascriptions have an interrogative as a complement (Bresnan & Grimshaw 1978: 332; M. Baker 1996: 204–7). Further, knowledge-how ascriptions can be extended to embed a multiple interrogative, as in “Mark knows how to do what?” , whereas free relative complements do not tolerate multiple wh-phrases (C. Baker 1968; Bresnan & Grimshaw 1978: 335). Moreover, infinitival wh phrases, such as “what to do”, “how to do”, “who to ask” never allow for free relative reading (Huddleston & Pullum 2002: 1070–3). Finally, a standard test for telling apart free relatives and interrogatives is to see if they embed under “believe”, for “believe” does not take interrogatives as complements but it does tolerate free relatives. (For example, “Mark believed who was charged guilty” cannot mean “Mark believed the answer to the question “Who was charged guilty?””. Rather, it means that Mark believed the person who was charged guilty.) However, interestingly, “believe” can never embed infinitival constructions such as “what to do”, “how to do”, or “who to ask”.

Finally, some have questioned whether Semantics for knowledge-wh applies to ascriptions embedding infinitival complements, like knowledge-how ascriptions. Roberts (2009) argues that, as opposed to other wh complements, the meaning of “how” denotes a property rather than a proposition when embedded in infinitival clauses. Santorio (2016) defends a Gibbardian semantics for knowledge ascriptions embedding infinitive interrogatives, on which these ascriptions ascribe maximal performance plans compatible with an agent’s plans (for more objections to Semantics for knowledge-wh , see also Sgaravatti & Zardini 2008 and George 2013).

The perhaps most serious objection to the linguistic argument is that it ignores cross-linguistic evidence about how knowledge-how is ascribed in languages other than English (Rumfitt 2003; Roberts 2009; Glick 2012; Wiggins 2012; Abbott 2013; Douskos 2013; Ditter 2016). Rumfitt (2003) argues that the linguistic facts on behalf of intellectualism are overstated. Many languages—e.g., French, Italian, Spanish, and Russian—ascribe knowledge-how not just through ascriptions embedding interrogatives (“ S knows how to Φ”) but also through ascriptions embedding bare infinitivals (“ S knows + (bare infinitive) to Φ” (= “ S knows to Φ”)) as in “ Marie sait nager ” and “ Maria sa nuotare ”. Stanley (2011b, 2011c) responds that these ascriptions are to be analyzed as embedding an implicit interrogative—one where the question word “how” is not explicitly articulated. However, Abbott (2013), Hornsby (2016), and Ditter (2016) have observed that this response does not help with yet other languages, such as Russian, in which knowledge-how ascriptions—of the form “ S (attitude verb) V s + (infinitive) to Φ”—feature an embedding verb V (“ umetj ”) that never licenses an interrogative complement nor a declarative complement (i.e., a that -clause).

In order to assess what this cross-linguistic evidence really establishes, consider a new version of the linguistic argument. Let “ S V s Φ” be an ascription of knowledge-how in an arbitrary language L that is correctly translated in English by “ S knows + (interrogative) how ( de se ) to Φ”. Assuming that translation preserves at least truth conditions, “ S V s Φ” will be true in L just in case “ S knows + (interrogative) how ( de se ) to Φ” is true in English. Call this the Interpretation Premise. By the Disquotational Schema, “ S knows how to Φ” is true in English just in case S knows how to Φ; so, we have that “ S V s Φ” is true in L just in case S knows how to Φ. This conclusion, together with the Semantics for knowledge wh , the Logical Form , and the Interpretation Premise , yields that “ S V s Φ” is true in L just in case S bears a knowledge relation towards an answer to the question “How he himself could Φ”. Through this argument, the truth conditions of any knowledge-how ascription, whether in English or in any other language, are reduced to propositional knowledge, whether the relevant knowledge-how ascription has or not the interrogative form.

Proponents of the cross-linguistic argument might challenge Logical Form : the different ways of ascribing knowledge-how (through the infinitival form and through the interrogative form) in these languages indicate that knowledge-how ascriptions in English are ambiguous between two not truth-conditionally equivalent logical forms: an interrogative form and a bare infinitival form ( Ambiguity Hypothesis ) (Rumfitt 2003; Wiggins 2012; Setiya 2012; Glick 2012; Ditter 2016; Hornsby 2016). The main piece of evidence for the Ambiguity Hypothesis is that in languages employing both the interrogative form and the infinitival form, those different ascriptions can come apart in their truth conditions. For example, it is claimed that the Italian sentence “ Mario sa come nuotare ” (interrogative form = “Mario knows how to swim”) may be usedly true, while the sentence “ Mario sa nuotare ” (infinitival form = Mario knows to swim) is false. This would be the case, for example, if Mario lacks (in some sense) the ability to swim (so too for its French and Spanish translations). Similarly, Ditter argues that in Russian, the interrogative construction must ascribe a different state from the “ umetj ” ascription (+ infinitival), on the ground that one can coherently use in Russian sentences of the following form:

John znaet kak igrat’ na pianino, no on ne umeyet igrat.

John knows + (interrogative) how to play the piano, but he does not know (“ umetj ”) + (infinitival) to play the piano.

“John knows how to play the piano, but he doesn’t know how to do it”.

According to these authors, this difference between interrogative embedding constructions and infinitival embedding construction shows up also in English locally for the verb learn : “ S learnt to swim” differs from “ S learnt how to swim” in that the former, but not the latter, is ability-entailing (Rumfitt 2003; Glick 2012).

This argument for the Ambiguity Hypothesis might be in certain ways too quick. The only way to make (6) intelligible in English is to translate it as (7), where the generic interpretation of the first knowledge-how ascription and the de se interpretation of the second ascription are made explicit:

However, (6) cannot be interpreted as (8) on pain of contradiction:

If so, the fact that (6) is acceptable in Russian does not establish that the interrogative form in Russian cannot also have an interpretation (the de se interpretation) on which it is truth conditionally equivalent to the Russian’s infinitival form. Here is a competitive explanation of the available cross-linguistic evidence that does not commit us to the Ambiguity Hypothesis . Just like English’s ascriptions, the interrogative form in Russian is ambiguous between a de se interpretation, on which it is truth conditionally equivalent to the infinitival form, and a generic interpretation of the subject of the infinitival embedded verb, on which it comes apart from the infinitival form. This explains why (6) is felicitous and why it can be translated as (7) but not as (8). On this explanation, this evidence might be compatible with English knowledge-how ascriptions univocally having the same logical form (the interrogative form), even though the embedded interrogative can receive either the generic or the de se interpretation, depending on the subject of the infinitival embedded verb.

Ryle is often interpreted as claiming that knowledge-how ascriptions are nothing more than ascriptions of an ability or a complex of dispositions to act in a skilled or intelligent manner (though see Hornsby 2011: 82 and Waights Hickman 2019 for dissent). This interpretation is based on passages in the Concept of Mind , such as the following:

When a person is described by one or other of the intelligence epithets such as “shrewd” or “silly”, “prudent” or “imprudent”, the description imputes to him not the knowledge or ignorance of this or that truth, but the ability, or inability, to do certain sorts of things. (Ryle 1949: 27)

Early intellectualists argued that knowledge-how does not entail ability (Ginet 1975; Stanley & Williamson 2001; Snowdon 2004). For example, a pianist who lost their arms in a car accident may have lost her ability to play but still preserve her knowledge-how to play the piano (cf. Snowdon’s 2004: 8 expert omelette maker); or a ski instructor might know how to do a ski stunt and, according to Stanley & Williamson (2001), still fail to have the ability to do it. By contrast, anti-intellectualists argue that it is important to distinguish between knowing how to perform a task, which corresponds to a general ability, and being (actually and circumstantially) able to perform it (Noë 2005; Glick 2012; Setiya 2012). So the pianist might have both general ability as well as knowledge-how, though they lack circumstantial ability. By contrast, the ski instructor does not clearly have knowledge-how to perform the ski stunt themselves, while they know how one , in general, can do it. Recent intellectualist views also take knowledge-how to go together with abilities (understood along Hawley’s 2003 notion of counterfactual success) and argue that rightly construed intellectualism can vindicate this connection (Pavese 2015b; Cath 2020).

Yet, everybody agrees that while knowledge-how might entail ability, ability is not sufficient for knowledge-how, as demonstrated by an example from Hawley (2003):

Annoyance. Susie is attempting to annoy Joe; she thinks smoking will do the trick. Whenever she smokes, she unconsciously and inadvertently taps on her cigarette pack. Unbeknownst to Susie, Joe does not mind cigarette smoke, but finds her tapping obnoxious.

Susie has the ability to annoy Joe, since she has the disposition to annoy Joe whenever she attempts to do so. But, intuitively, she does not know how to annoy him. A natural explanation of this is that she cannot annoy him intentionally (for structurally similar cases, see Carr 1979, 1981 and Bengson, Moffett, & Wright 2009). Pretty much all sides of the dispute agree on the following claim (Ryle 1949; Stanley & Williamson 2001; Hawley 2003; Hornsby 2004, 2011; Stanley 2011b; Setiya 2012):

( Knowledge-how/Intentionality ): If S intentionally Φs, S knows how to Φ.

Many also endorse the biconditional ( Knowledge-how/Ability Intentional ) (Hawley 2003; Setiya 2012):

( Knowledge-how/Ability Intentional ): S has the ability to intentionally Φ if and only if S knows how to Φ.

Now, suppose that knowing how to Φ does require the ability to intentionally perform Φ. If so, whether knowledge-how requires a propositional attitude depends on whether or not one can intentionally Φ without having a propositional attitude about how to Φ. But according to many influential views of intentional action, intentionally Φ-ing does require a propositional attitude, namely a belief about how to Φ. In particular, intentionally Φ-ing requires having an action plan, which is characterizable in terms of a belief about how to perform Φ. For example, on Goldman’s (1970) view, one intentionally Φs when one has a plan to Φ, where a plan to Φ is a belief that specifies the means to Φ (see, also, e.g., Harman 1976; Audi 1986; Bratman 1987; Velleman 1989; Ginet 1990; Mele & Moser 1994; Gibbons 2001). From this, we get:

( Intentionality/Belief ): If S intentionally Φs, then there are some means \(m_1\), …, \(m_n\) to Φ such that S truly believes that \(m_1\), …, \(m_n\) are means for oneself to Φ.

Some intellectualists have argued on these bases that knowledge-how to Φ requires at least a propositional attitude about the means to Φ (Cath 2015b).

But is propositional knowledge of means to ends required for intentional action, over and above true belief? Gibbons (2001) provides several examples to buttress the necessity of knowledge for intentional action. For example, one cannot plausibly intentionally win a fair lottery , nor can one intentionally defuse a bomb if one unintentionally and fortuitously chooses the correct wire; in both cases, a plausible explanation for the lack of intentionality is that the subjects does not have the relevant propositional knowledge about how to accomplish those tasks. These cases buttress the claim that intentional action requires knowledge of the means to execute it:

( Intentionality/Knowledge ): If S intentionally Φs, then there are some means \(m_1\), …, \(m_n\) to Φ such that s knows that \(m_1\), …, \(m_n\) are means for oneself to Φ.

With these assumptions in the background, here is a non-linguistic argument for intellectualism. Start from ( Knowledge-how/Intentionality ): if S intentionally Φs, S knows how to Φ. Furthermore, suppose that ( Intentionality/Knowledge ) is true so that the intentionality of an action is to be explained at least in part in terms of propositional knowledge. Then, by these two premises, we get that if one intentionally Φs, one both knows how to Φ and one has propositional knowledge of the means to Φ:

( Knowledge-how, Intentionality, Knowledge ): If S intentionally Φs, S both knows how to Φ and for some means \(m_1\), …, \(m_n\), S knows that means \(m_1\) , …, \(m_n\) are means for oneself to Φ.

Now, according to standard formulations of intellectualism, one knows how to Φ only if, for some means m to Φ, one knows that m is a means for one to Φ:

( Intellectualism about Knowledge-How ): S knows how to Φ is at least in part of a matter of knowing, for some means m to Φ, S knows that m is a means for oneself to Φ.

So, the argument from intentional action for intellectualism maintains that the intellectualist picture provides the best explanation for why ( Knowledge-How, Intentionality, Knowledge ) should hold. According to this explanation, ( Knowledge-How, Intentionality, Knowledge ) is true not just because of a coincidental alignment of propositional knowledge and knowledge-how in intentional action. Rather, its truth is grounded on the very nature of knowledge-how: one knows how to Φ in virtue of knowing, for some means m to Φ, that m is a means for oneself to Φ.

The view that intentional action requires belief has been challenged for the particular case of basic actions . Setiya (2012) observes that one can perform a basic action of clenching one’s fist without even having the belief that one can succeed at doing it. For example, someone might have had a paralyzing injury, fail to believe they have healed, and still form the intention to clench their fist. Intellectualists might reply that, although that subject does not believe that one will succeed, they might have a sufficiently high credence and that credence can amount to knowledge too (Pavese 2020). (For other possible responses to the idea that intentional action requires knowledge or belief, see Elzinga forthcoming).

A further related question is how to think of knowledge-how in the case of joint actions. When two agents act jointly towards a goal, as when they row a boat together, they responsively coordinate and monitor each other’s movements in ways that produce a joint action. What kind of knowledge-how is manifested by successful joint action? It must be possible for the agents to coordinate without each having to know the different ways in which each must act to achieve their common goals: you and I can jointly make risotto even if I do not know how to season it and you do. Correspondingly, Birch (2019) suggests that joint knowledge-how must be accounted for distributively . If this is correct, then the agents can jointly know how to do something without each having a belief about how they jointly do it, but only in virtue of having a collective, or group, belief about how to do it. (For more discussion on group knowledge-how, see Palermos & Tollefsen 2018 and Strachan, Knoblich & Sebanz 2020)

6. The Epistemology of Knowledge-How

Some have observed that knowledge-how may differ from propositional knowledge in that, whereas the latter plausibly entails belief, knowledge-how does not (Dreyfus 1991, 2005; Wallis 2008; Brownstein & Michaelson 2016). For example, consider Brownstein & Michaelson (2016)’s example. When catching a ball, ball players make anticipatory saccades to shift their gaze ahead of the ball one or more times during the course of its flight towards them. These players know how to catch a ball, and their way of catching a ball requires making anticipatory saccades when watching the ball as it falls. Yet, the players do not believe that making anticipatory saccades is part of how they catch the ball. Rather they believe that they are tracking the ball the whole time. However, from the fact that the subject has false beliefs about how she catches the ball, it does not follow that the subject does not also have correct beliefs about it. So, a natural response is that there is some sense in which the player correctly believes that his manner of tracking the ball has a chance of resulting in success.

Whether this response is compelling might depend on what one takes beliefs to be. On this topic, philosophers widely disagree. On an “intellectualist” account of belief, on which believing that p requires the subject to acknowledge that p , it is implausible that the athletes have the relevant belief. But intellectualists about knowledge-how might advocate replacing this intellectual notion of belief with a less demanding one. According to a prominent functional characterization of belief, to believe that p entails being disposed to act in ways that would tend to satisfy one’s desires, whatever they are, in a world in which p (together with one’s other beliefs) are true” (cf. Stalnaker 1984: 15; Stalnaker 2012). Now, suppose that in game after game, Athena catches the ball using a certain method m , and that whenever she does so, her behavior is intentional. From this it seems to follow that Athena is disposed to perform the actions specified by m . Since, ex hypothesi , m is a way of catching the ball, it follows that in all the worlds where she performs these actions, she satisfies her desire of catching the ball (or at least is sufficiently likely to do so). By the previous functional characterization of belief, it follows that Athena believes that m is a way for her to catch the ball. The lesson of this debate might be, following Stalnaker (2012), that intellectualism about knowledge-how is best construed as a form of anti-intellectualism about knowledge, belief, and the mental.

Another way of challenging the intellectualist claim that knowledge-how is a species of knowledge-that is to question whether knowledge-how can be Gettiered. If knowledge-how survives Gettierization, that would be evidence that knowledge-how is not a species of knowledge-that, on the assumption that Gettiered justified true belief cannot constitute propositional knowledge (Gettier 1963). Stanley & Williamson (2001) argue that knowledge-how cannot be Gettiered. However, Cath (2011) responds by proposing the Lucky Light Bulb case, where Charlie wants to learn how to change a lightbulb, but he knows almost nothing about light fixtures or bulbs. Charlie consults The Idiot’s Guide to Everyday Jobs . Inside, he finds an accurate set of instructions describing the shape of a light fixture and bulb, and the way to change a bulb. Charlie grasps these instructions perfectly. And so there is a way such that Charlie now believes truly that that way is a way for him to change a light bulb, namely, the way described in the book. However, unbeknownst to Charlie, he is extremely lucky to have read these instructions, for the disgruntled author of The Idiot’s Guide filled her book with otherwise misleading instructions. Cath (2011) argues that intuitively Charlie still knows how to fix the light bulb, despite his belief being Gettiered (cf. also Poston 2009: 744).

Stanley replies that knowledge-wh in general seems to be Gettierable and that might be explained in terms of features having to do with knowing the answer . For example, consider Hawthorne’s (2000) example of a teacher giving each child in their class a note with the name of a city. “Vienna” is written only on one of the notes. In this context, it seems true that one child knows the correct answer to the question “what is the capital of Austria”, even though the child’s belief is true by luck. (Though see Carter & Pritchard 2015c for a reply that while knowledge-how is similar to knowledge-that and knowledge-wh in that it is incompatible with intervening luck, it differs with these kinds of knowledge in being compatible with environmental luck.) Others still have responded that intuitions are subtle and not all of them favor anti-intellectualism (Marley-Payne 2016; Pavese forthcoming-a). For a recent experimental study with mixed results, see Carter, Pritchard, and Shepherd (2019). Hawley (2003: 28) argues that knowledge-how, like propositional knowledge, requires “warrant” on the ground that success on the basis of a lucky guess does not seem to manifest one’s knowledge-how. A similar theoretical argument for thinking that lucky belief cannot suffice for knowledge-how starts from the thesis that knowledge-how enters in explanations of success and that satisfactory explanations must be “modally robust”. From this, the argument concludes that the sort of belief that robustly explains intentional success must be knowledge, for knowledge has the relevant modal profile (Sosa 1999; Williamson 2000; D. Greco 2016). Another line of argument starts from the observations that knowledge-how to Φ explains the ability to intentionally Φ (see section 4 ) and that only knowledge can explain intentional action (Gibbons 2001: 589–590). On these bases, some argue that knowledge-how cannot fall short of non-getteriable knowledge (Cath 2015b for objections to this line of argument).

Some object that while knowledge-that can be defeated by misleading evidence, not so knowledge-how (see Carter & Navarro 2017 for this line of argument and Pavese 2021 for a reply). Finally, some object that knowledge-how cannot be knowledge-that because the latter is acquirable by testimony and the former is not. While the following argument (A–C) is valid, the following (i–iii) is not (Poston 2016):

Mark knows that Turin is in Northern Italy.
Mark tells that to John, who believes him.
John comes to know that Turin is in Northern Italy.
Mark knows how John could swim.
Mark tells John.
John comes to know how to swim.

Following Stanley’s (2011b: 126) modal restriction proposal (cf. section 3 ), Cath (2017, 2019) responds that depending on how the context for the modal is restricted, (i) could mean either that Mark knows how John could swim given his current physical state or how John could swim after training . If only the latter, that is not the sort of proposition that John needs to know in order for (iii) to be true: for that, John ought to know that that is how he could swim under his current physical state. (Though see section 2 for qualms about this intellectualist strategy.) Another avenue for reply to the challenge from testimony may be to insist that not every propositional knowledge is transferable through testimony. A comparison: visual knowledge that Mark murdered Tina differs in content and mode of presentation from the knowledge that of the murder obtained by being told by his prosecutor. The former observational knowledge is not transferable through mere testimony but (exactly because of that!) it is more helpful for the purpose of convicting Mark than second-hand knowledge. That does not mean that observational knowledge is not propositional. Like in the case of perceptual knowledge, the proposition that one knows by knowing how to do something involves distinct modes of presentation of ways of doing things ( section 2 , section 3 ). We should not expect propositions under this mode of presentation to be transferable through testimony. (For a response to Poston 2016, see also Peet 2019).

7. The Argument from Cognitive Science

The argument from cognitive science against intellectualism starts by pointing out that cognitive scientists distinguish between different kinds of cognitive systems: It is often held that the declarative system is responsible for encoding propositional knowledge, whereas knowledge-how is encoded in the procedural system . Given empirical evidence that the declarative and procedural systems are separate (about which more below), it would seem to follow that knowledge-how is not reducible to propositional knowledge (Wallis 2008; Devitt 2011; Roth & Cummins 2011):

The Cognitive Science Argument

The usual evidence marshaled in favor of C1 relies on amnesiac case studies (Milner 1962; see Cohen & Squire 1980 for discussion). A typical example is HM. After bilateral removal of the hippocampus, parahippocampal gyrus, entorhinal cortex, and most of the amygdala to relieve debilitating symptoms of epilepsy, HM was unable to form new memories of facts or events and he could no longer access memories he acquired in the few years leading up to his surgery. Nevertheless, it was found that over 10 trials, HM tuned his motor skill to trace the outline of a five-pointed star based only on looking at reflection in a mirror. Since he could not store new memories, HM’s declarative knowledge of the means of performing the task did not change from one trial to the next. But his performance improved. So, the reasoning goes, the improvement of motor skills is governed by a distinct cognitive system from that which governs the retention of declarative facts.

Many embrace C2 (e.g., Lewicki, Czyzewska, & Hoffman 1987: 523; Devitt 2011; Wallis 2008). But some object that a closer look at the details of HM’s case (as reported in Milner 1962) supports a different diagnosis, on which knowledge-how is realized by a combination of the procedural and the declarative system (Pavese 2013; Stanley & Krakauer 2013). At the beginning of each trial, prior to being given verbal instructions on how to perform the motor task, HM lacked the ability to intentionally perform it: HM was able to perform the motor task only after being reminded of what the task consisted in . This suggests, against C2, that there was an important declarative component to HM’s ability to perform the motor task (for the role of declarative knowledge in skillful action, see also Christensen, Sutton, & Bicknell 2019).

Here is a possible way to patch up the Argument from Cognitive Science (Fridland 2014, 2017; Levy 2017). Replace C2 with:

With C2*, the argument goes on as before. Stanley & Krakauer (2013) seems to accept this conclusion (for more discussion and critiques, see Krakauer 2019; Springle 2019; De Brigard 2019; Schwartz & Drayson 2019). Other intellectualists reply that this argument misses the intellectualist target. Cath (2020) argues that procedural representation might be a prerequisite for knowledge-how rather than a constituent. Pavese (2019) develops an account on which procedural representations, of the sort studied by motor scientists when giving an account of the procedural aspect of skill (Wolpert 1997; Jeannerod 1997), can be understood as practical, albeit nonconceptual, representations—the sort of representations that intellectualism independently requires for knowledge-how ( section 2 ).

According to C3, propositional knowledge corresponds to “declarative” knowledge—to a sort of knowledge that is, at least in principle, verbalizable. Opponents of intellectualism often uses C3 in a novel argument against intellectualism: if propositional knowledge has to be verbalizable, then knowledge-how cannot be propositional knowledge, for often subjects know how to perform tasks even though they cannot explain how they do it (Schiffer 2002; Devitt 2011; Adams 2009; Wallis 2008). On behalf of intellectualism, there do seem to be cases in which you come to know how to do something precisely by consulting a manual and learning some propositions (see, e.g., Snowdon 2004: 12; Bengson and Moffett 2011a: 8; and Katzoff 1984: 65ff). Moreover, it is not clear that the anti-intellectualist demand that propositional knowledge be always verbalizable is motivated. In fact, it seems to conflate knowing how to perform a task with knowing how to explain how the task is performed (cf. Fodor 1968: 634; Stalnaker 2012). Stanley (2011b: 161) points out that there is a sense in which knowledge-how is always verbalizable. A punch-drunk boxer who can at best demonstratively refer to his re-enactment of the way of boxing against southpaws, and says, “This is the way I fight against a southpaw” intuitively knows that this is the way he fights against southpaws. This knowledge has an essential demonstrative or indexical component. But the same goes for much other propositional knowledge like, for example, the knowledge we express by saying, “This is the tool for the job”, or “That is going to be trouble”. This reply assumes that ways to execute tasks are ostensible and as such can be picked up by a demonstrative. This does not need to be so: on any single occasion, one may only act on parts of a way. So, one will not thereby be able to pick up the general way one’s knowledge-how is about. Another reply on behalf of intellectualism is to point out that practical concepts for tasks differ from “semantic” concepts for the same tasks precisely in that, even if propositional, they are not necessarily verbalizable.

A final objection is that intellectualism overintellectualizes knowledge-how in a way that is incompatible with what we know about animals’ cognition (Noë 2005; Hornsby 2007; Dreyfus 2007; Elzinga forthcoming). According to this objection, unsophisticated and non- (or pre-) linguistic agents such as babies and non-human animals can know how to perform certain tasks, while lacking the concepts that are required for propositional knowledge. Some intellectualists respond that ordinary speakers routinely also ascribe propositional knowledge to animals and babies, as we say that Fido knows that its owner is arriving or that a baby knows that their mother is present (Stanley & Williamson 2001). Thus, while propositional knowledge may require concept possession, our ordinary knowledge ascriptions suggest that we regard relatively unsophisticated agents as possessing the relevant concepts. Comparative psychologists do routinely credit many non-human and non-linguistic animals with the possession of concepts. (See Allen & Bekoff 1999 for a comprehensive overview).

This response might be less plausible, though, when it comes to lower animals, or insects. Here too, we might describe ants as knowing how to carry food back to their nest. And yet, there is less evidence from cognitive science that insects are capable of concepts too (though see Gallistel & King 2009). In response, a different line of argument might be more promising (cf. McDowell 2007): it does not follow from the fact that we are disposed to ascribe knowledge-how to lower animals that what explains their goal-directed behavior is the same sort of psychological state that underlies human knowledge-how and human action. For from the fact that their behavior resembles humans’ in some respects (for example, in its goal-directedness) does not entail that it resembles humans’ skilled behavior in all respects that matter (for example, in the susceptibility of the relevant behavior to rational revision).

8. Varieties of Anti-Intellectualism

According to orthodox intellectualism, knowledge-how is a species of propositional knowledge. Revisionary intellectualism, instead, contends that although knowledge-how is a kind of knowledge-that, the relevant knowledge is sui generis and differs from standard propositional knowledge in some important ways. For example, Brogaard (2009, 2011) argues that, in general, knowledge can have cognitive abilities or practical abilities as its justificatory grounds. In the latter case, agents know in virtue of ability states that are not subject to the usual epistemic constraints that characterize belief states generated by cognitive abilities. Correspondingly, knowledge-how fits the bill for this practically grounded knowledge. Cath (2015b) argues that we should distinguish between theoretical knowledge-that and practical knowledge-that. The former is subject to the usual epistemic constraints, like being sensitive to Gettierization (cf. also Zardini 2013). The latter, instead, is not sensitive to the usual epistemic constraints of theoretical knowledge-that—and can therefore constitute knowledge-that even if Gettierized. Waights Hickman (2019) suggests that knowledge-how is a distinct kind of knowledge-that relation, characterized by knowing something in “the executive way”, which requires

possession of (a) dispositions to attend to features of an action-context on which one’s knowledge (how) bears; and (b) dispositions to adjust one’s use of that knowledge accordingly. (2019: 333).

As we have seen ( section 4 ), Bengson & Moffett (2007, 2011b) defend Non-propositional (or Objectualist) Intellectualism . On this view, knowing how to Φ necessarily involves having objectual knowledge of a way of Φ-ing but having objectual knowledge of a way of Φ-ing is not sufficient to know how to Φ. For example, a tropical swimmer may be acquainted with a way of escaping an avalanche, namely making swimming motions. Yet, if this swimmer had no conception whatsoever of an avalanche or of snow, he would not know how to escape an avalanche. This suggests that there must be some propositional/representational aspect of knowing how to Φ. Hence, according to this view for one to know how to Φ, (i) one must have objectual knowledge of a way of Φ-ing and (ii) one must grasp a correct and complete conception of this way.

As we have seen, Ryle is often interpreted as claiming that knowledge-how ascriptions are nothing more than ascriptions of an ability or a complex of dispositions to act in a skilled or intelligent manner (Hornsby 2011). (For a recent defense of knowledge-how as an ability, see Markie 2015.) Anti-intellectualism of this sort has been voiced by Lewis (1990) and has been thought to undercut the so-called “knowledge-argument” in the philosophy of mind (see Jackson 1986 for a classic formulation. For further discussion, see Nemirow 1990 and Alter 2001). However, Cath (2009) argues that similar worries about the argument survive even on some prominent intellectualist views. For a survey of other consequences thought to follow from the various positions in the knowledge-how debate, see Bengson and Moffett (2011b: 44–54).

However, few theorists nowadays identify knowledge-how with bare abilities. Setiya (2012) holds that to have knowledge-how is to have the disposition to act guided by one’s intention; Constantin (2018) argues that knowing how to Φ is to have the disposition to have the ability to Φ. Neo-Rylean views are also developed by Craig (1990), Wiggins (2012), and Löwenstein (2016). Craig suggests that knowledge-how to Φ amounts to the ability to teach others how to Φ. Wiggins argues that genuine knowledge-how stems from a bundle of practical abilities that constitute the ethos of a practice and, while interrelated with propositional knowledge, cannot be reduced to it. In turn, Löwenstein argues that knowledge-how to Φ is the ability to Φ intelligently guided by the understanding of the activity of Φ-ing.

Carter and Pritchard (2015a,b,c) develop an alternative view which does not equate knowledge-how with an ability, but it still gives ability a central theoretical role. In their view, knowing how to Φ is a cognitive achievement, given our abilities to Φ: if one successfully Φs because of one’s ability, then one knows how to Φ. And if one knows how to Φ, then one is positioned to successfully Φ because of one’s ability. Therefore, for them, knowledge-how does not reduce to the mere possession of abilities but it essentially involves the successful enactment of these abilities. Habgood-Coote (2019) defends the view that knowing how to Φ just is the ability to generate the right answers to the question of how to Φ. Although on this view, knowledge-how is a relation an agent bears to a proposition—one that answers the relevant practical question—this relation to a proposition is not understood in epistemic terms but in terms of dispositions (see also Audi 2017 and Farkas 2017).

8.3 Radical Anti-Intellectualism: Practicalism

While the intellectualist holds that knowledge-how must be understood in terms of knowledge-that, radical anti-intellectualism holds that knowledge-that must be understood in terms of knowledge-how or skill. As Hetherington puts it:

Your knowing that p is your having the ability to manifest various accurate representations of p . The knowledge as such is the ability as such. (2011: 42, original emphasis)

An agent knows that, for instance, she is in France whenever she is able to produce the corresponding true belief, to assert that she is indeed in France, provide justification, answer related questions, etc. (see Hartland-Swann 1956; Roland 1958 for classic formulation and Hetherington’s 2006, 2011, 2020 “practicalism” for a more recent form of radical anti-intellectualism).

9. Knowledge-How and Skill

The most recent debate on knowledge-how has intertwined with a debate on the nature of skills. While there is no consensus on what counts as a skill, by and large people take skills to manifest in purposeful and goal-directed activities and to be learnable and improvable through practice (Fitts & Posner 1967; Stanley & Krakauer 2013; Willingham 1998; Yarrow, Brown, & Krakauer 2009). Skills are usually contrasted with knacks (or mere talents). Some contrast them with habits (Pear 1926; Ryle 1949) in that these are performed automatically, whereas the exercise of intelligent capacities involves self-control, attention to the conditions, and awareness of the task. Others, instead, argue that understanding skill requires a better understanding of what habits amount to (Gallagher 2017; Hutto & Robertson 2020).

The topic of skill and expertise is central since ancient philosophy through the notion of technē . Although both Plato and Aristotle took technē to be a kind of knowledge, there is significant controversy about their conceptions regarding the nature of this kind of knowledge and its relation to experience ( empeiria ) on one hand, and scientific knowledge ( epistēmē ) on the other (Johansen 2017; Lorenz & Morison 2019; Coope 2020). Annas (1995, 2001, 2011) develops an interpretation on which skill and virtue (or phronēsis ) are closer in Aristotle’s action theory than usually thought and they are both conceived along a broadly intellectualist model.

In contemporary times, the notion of skill is central to the philosophy of the twentieth-century French phenomenologist Maurice Merleau-Ponty. Merleau-Ponty (1945 [1962]) distinguishes between motor intentionality —the sort of intentionality relevant for motor skills—and cognitive intentionality . While the latter is conceptual and representational, Merleau-Ponty thought that motor intentionality is non-representational and non-conceptual. Central to Merleau-Ponty is the role of motor skills in shaping perceptual experience: in paradigmatic cases of perception, the flow of information taken in by perceivers is inseparable from the way they move through a scene. On this view, even superficially static perceptions engage motor skills, such as seeing the color of a table as uniform when different parts of it are differently illuminated (see Siegel 2020 for an helpful introduction).

This phenomenological tradition inspires Dreyfus’ (1991, 2000, 2002, 2005, 2007) critique of standard action theory. According to Dreyfus, theories on which an action is intentional only if the agent is in a mental state that represents the goal of her action (cf. Searle 1980, 2001) or on which actions are permeated by conceptual rationality (cf. McDowell 2007) are not supported by the phenomenology of purposive activity. Paradigmatic examples of these purposive activities are, for Dreyfus, skillful activities like playing tennis or habitual activity like rolling over in bed or making gestures while speaking. In this sort of skillful coping, Dreyfus thought that the mind does not represent the world as detached from it. Rather, it is fundamentally embedded, absorbed, and embodied (see Gehrman & Schwenkler 2020 for an helpful introduction to Dreyfus on skills).

The notion of skill is central also in Eastern philosophy. Garfield and Priest (2020) examine the various roles that the notion of skill plays in the Indian school of Mahayana Buddhism, in Daoism, and in Chan/Zen thought. In Daoism as well as in Chan/Zen Buddhism, the emphasis on skill is also connected, fundamentally, to concerns about living a good and ethical life. Sarkissan (2020) argues that two prominent types of expertise often encountered in ancient Chinese thought from the sixth to third centuries BCE: The first is expertise at a particular craft, occupation, or dao , as is most famously presented in the Daoist anthology Zhuangzi . The second is ethical expertise in the Ruist (Confucian) and Mohist schools (cf. for more on skill in Buddhism, see also MacKenzie 2020).

What is the relation between knowledge-how and skill? For many tasks at least, it is intuitive that one cannot be skilled at it without knowing how to perform it. At first, it also seems as if knowledge-how entails skill: one does not really know how to swim if one does not have the skill to swim; and one cannot know how to tell apart birds without the skills of a bird watcher. One might object to the sufficiency of knowledge-how for skill on the grounds that it is natural to say things such as “John may know how to make risotto, but I would not say he is skilled at it”. However, knowing how to make risotto sufficiently well (relative to contextually determined standards) might entail being skilled at it (relative to the same standards) (Cath 2020).

Ryle (1946, 1949) used “skill” and “knowledge-how” interchangeably in his criticism of the “Intellectualist legend” (for discussion, see Kremer 2020). In fact, Ryle’s view of knowledge-how is stated, literally, as the view that “skill” is a complex of dispositions (Ryle 1949: 33; see also Ryle 1967, 1974, 1976 for his views on how skill as a form of knowledge is distinguished by the forms on how it is taught and learned through training). This discussion brings us to whether intellectualism about knowledge-how and intellectualism about skill stand or fall together. Should intellectualists about knowledge-how identify skill too with propositional knowledge? While Stanley and Williamson (2001) embrace the view that knowledge-how is propositional knowledge, in a recent paper (Stanley & Williamson 2017), they refuse to think of skill as a standing propositional knowledge state. Rather, they argue that skills are dispositions to know. One motivation for this view is that this addresses the novelty challenge raised by Dreyfus (1991, 2005). According to this challenge, propositional knowledge cannot explain the ability to respond intelligently to situations that have not been encountered by the agent before. If skills are dispositions to know, it is no mystery how novel situations can be handled by skillful agents. Stanley & Williamson (2017) claim that the resulting view is still broadly intellectualist in a sense, because on it, skillful action manifests propositional knowledge (for a criticism of this response to the novelty objection, see Pavese 2016 in Other Internet Resources ).

Some authors argue that while skills may be related to propositional knowledge, they do not reduce to it. Dickie (2012) suggests that an agent is skilled at Φ whenever her intentions to Φ are non-lucky selectors of non-lucky means to Φ; while, in turn, these means might manifest propositional knowledge. Some argue that control is necessary for skills, and control cannot fully be understood in terms of propositional knowledge (Fridland 2014, 2017a, 2017b). In order to provide a theory of skill that makes room for control, Fridland (2020) develops a “functional” account of skills. In this view, a skill is a function from intentions to action, implemented through certain “control structures”, which include attention and strategic control. Among these control structures, there is also propositional knowledge, which is required for strategic control. In contrast, intellectualists about skills argue that being in control is not intelligible unless it is understood in terms of knowing what one is doing in virtue of knowing how to perform that action. Therefore, they argue that agentive control itself is best understood in terms of the capacity for propositional knowledge.

Understanding the nature of skill and its relation with knowledge is of crucial importance for virtue epistemology—the view that knowledge is to be defined in terms of the success of our cognitive skills (Zagzebski 2003, 2008; Sosa 2007, 2009; J. Greco 2003, 2010; Pritchard 2012; Turri 2013, 2016; Beddor & Pavese 2020; Pritchard 2020). Nevertheless, if it turns out that skill must be explained in terms of knowledge, virtue epistemology would be trying to account for knowledge in terms of knowledge and so would be viciously circular (see Millar 2009; Stanley & Williamson 2017 for an argument in this spirit). Some virtue epistemologists have responded by offering an anti-intellectualist account of knowledge-yielding cognitive skills. Sosa and Callahan (2020) describe the relevant skills as dispositions to succeed when one tries—such that knowledge is obtained when agents in the right shape and in the right situation enact these skills appropriately.

Recent discussions on skill include a renewed debate on the nature of skilled action—i.e., on the sort of processes that are involved in the manifestation of skills. The most recent discussion on skilled action concerns the extent to which they are automatic or under conscious control. A long tradition has taken skilled action to be paradigmatically a matter of “absorbed coping” (Heidegger 1927; Merleau-Ponty 1945 [1962]; Dreyfus 1991)—characterized as immersion in the situation and intuitive response to its demands, with little awareness of the body, tools or even possibly the activity itself. Following Dreyfus and the phenomenological tradition, some enactivists (e.g., Noë 2004) highlight the analogies between skillful behavior and perception; other enactivists (e.g., Gallagher 2017; Hutto & Robertson 2020) argue that in order to understand the automaticity and unreflectiveness of skilled action, we ought to better understand habitual behavior. Even outside the phenomenological tradition, people have emphasized the unreflective aspect of skilled action. For example, Papineau (2013) argues that skilled actions are typically too fast for conscious control. One important argument for the unreflectiveness of skilled action starts from the phenomenon of choking under pressure, where an individual performs significantly worse than would be expected in a high-pressure situation. This phenomenon has been taken to be evidence that skillful action proceeds without conscious attention, because choking episodes are thought to arise from the fact that anxiety leads one to focus and direct one’s mind on the performance, which would proceed smoothly if mindless (Baumeister 1984; Masters 1992; Beilock & Carr 2001; Ford, Hodges, & Williams 2005; Jackson, Ashford, & Norsworthy 2006; Gucciardi & Dimmock 2008). Some argue that unreflectiveness also characterizes skillful joint action (Høffding 2014; Gallagher and Ilundáin-Agurruza 2020).

In recent years, however, some have emphasized the role of attention and consciousness in skillful performance (Montero 2016, 2020; Wu 2016, 2020). Montero argues against the Dreyfusian idea of skillful and mindless coping, by noting that online conscious thought about what one is doing is compatible with expertise and by surveying empirical evidence that suggests revisiting the choking argument. Christensen, Sutton and McIlwain (2016) and Christensen, Sutton, and Bicknell’s (2019) argue for the centrality of cognition in explaining the flexibility of skilled action in complex situations and advance a “mesh theory” of skilled action, according to which skilled action results for a mesh of both automatic and cognitively controlled processes (for a survey of some of these issues, Christensen 2019. See also Sutton 2007 and Fridland 2017b).

Knowledge-how is related to but distinct from practical knowledge (Anscombe 1957). Practical knowledge is occurrent during intentional action: when one intentionally acts, one knows what one is doing while knowing it. While being capable of practical knowledge might require knowledge-how, knowing how to perform an action does not entail performing that action, and so does not entail practical knowledge (Setiya 2008; Schwenkler 2019; Small 2020). Some have argued knowledge-how is the norm of intention (Habgood-Coote 2018b), so that one can properly intend to perform an act only if one knows how to perform it.

An important question is whether knowledge-how is connected to distinctive kinds of epistemic injustice (Fricker 2007; Dotson 2011; Collins 1990, 1998; Medina 2011). Hawley (2011) discusses the phenomena whereby people ascribe less knowledge-how and ability to female musicians (Goldin & Rouse 2000) and whereby standards for judgments of success due to ability rather than luck or “instinct” tend to be higher for women and non-white men (Biernat & Kobrynowicz 1997). In these cases, agents may be transmitting knowledge by being direct sources of information, rather than by testifying to the truth of a proposition. If so, the harms that they suffer might call for a different account than standard cases of epistemic injustices like Fricker’s (2007), which focus on testimonial transmission of knowledge-that.

A final topic of interest is the relation between knowledge-how and faith. While most views on faith focus on its doxastic aspect, Sliwa (2018) argues that faith essentially involves agents acting in the right way with respect to the object of their faith. Having faith in a person, for instance, requires knowing how to interact with them so as to trust them, help them, and ensure their autonomy in general. Religious faith, similarly, requires faithful agents to know how to enact the relevant practices like going to mass, declaring one’s faith, and praying.

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Waights Hickman, N., 2019, “Knowing in the ‘Executive Way’: Knowing How, Rules, Methods, Principles and Criteria”, Philosophy and Phenomenological Research , 99(2): 311–335. doi:10.1111/phpr.12488
Wallis, Charles, 2008, “Consciousness, Context, and Know-How”, Synthese , 160(1): 123–153. doi:10.1007/s11229-006-9103-3
Weatherson, Brian, 2017, “Intellectual Skill and the Rylean Regress”, The Philosophical Quarterly , 67(267): 370–386. doi:10.1093/pq/pqw051
Wiggins, David, 2012, “Practical Knowledge: Knowing How To and Knowing That”, Mind , 121(481): 97–130. doi:10.1093/mind/fzs026
Williamson, Timothy, 2000, Knowledge and Its Limits , Oxford: Oxford University Press.
–––, 2011, “Reply to Boghossian”, Philosophy and Phenomenological Research , 82(2): 498–506. doi:10.1111/j.1933-1592.2010.00400.x
–––, 2012, “Boghossian and Casalegno on Understanding and Inference”, Dialectica , 66(2): 237–247. doi:10.1111/j.1746-8361.2012.01295.x
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Wu, Wayne, 2016, “Experts and Deviants: The Story of Agentive Control”, Philosophy and Phenomenological Research , 93(1): 101–126. doi:10.1111/phpr.12170
–––, 2020, “Automaticity, Control, and Attention in Skill”, in Fridland and Pavese 2020: 207–218.
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How to cite this entry . Preview the PDF version of this entry at the Friends of the SEP Society . Look up topics and thinkers related to this entry at the Internet Philosophy Ontology Project (InPhO). Enhanced bibliography for this entry at PhilPapers , with links to its database.

Weatherson, Brian, 2006, “Ryle on Knowing How ’, blog post at Thoughts Arguments and Rants.
Links in Phil Papers to recent work on knowledge-how , edited by John Bengson.
“ Know-how ,’ by Charles Wallis in Dictionary of Philosophy of Mind .
“ Knowledge ,” by Stephen Hetherington in Internet Encyclopedia of Philosophy .
Pavese, Carlotta, 2016, “Comments on “ Knowledge-How, Abilities, and Questions ” by Joshua Habgood-Coote”, Minds Online (blog), 5 September 2016.
Fantl, Jeremy, “Knowledge How”, Stanford Encyclopedia of Philosophy (Spring 2021 Edition), Edward N. Zalta (ed.), URL = < https://plato.stanford.edu/archives/spr2021/entries/knowledge-how/ >. [This was the previous entry on this topic in the Stanford Encyclopedia of Philosophy — see the version history .]

Acknowledgments

The author would like to acknowledge the contributions of Alejandro Vesga to this entry. He brought to my attention recently published papers on knowledge-how; brainstormed with me about the structure of the entry and the order of the topics to be discussed; provided substantial criticisms of, and suggestions for, drafts of the content; contributed the idea of adding a final section that related knowledge-how to other related topics; and compiled the bibliography once the bulk of the entry was finished.

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Knowledge Is Power Essay for Students and Children

500+ words essay on knowledge is power.

Knowledge Is Power Essay- Knowledge is something that will serve you your whole life. The most powerful thing in the world is knowledge because it can create and destroy life on earth . Moreover, knowledge helps us distinguish between humans and animals . Knowledge is the ability to use your knowledge to help others.

Importance of Knowledge

There are very few people out there who truly understand the importance of knowledge. Every educated person is not knowledgeable, but every knowledgeable person is educated. This statement may sound weird but it’s true. In today’s world, almost everyone is educated still they do not have knowledge of the subject that they have studied.

Besides, Knowledge is something that helps you drive a car, ride a bike, solve a puzzle, etc. Knowledge is something that prevents us from making the same mistake twice. It is not something that you can buy from you have to earn it.

Benefits of Knowledge

The knowledge is something that increases the more you share it. It protects your intellectual capital that is your knowledge. Likewise, humans have used their knowledge to create things that we can’t imagine a few centuries back. It helps us to convert our ideas into reality and also it helps us to reach the success that we desire in our life.

Moreover, knowledge assists us to differentiate between what is right and what is wrong. It helps us to overcome our faults, weaknesses, and dangerous situation in life. Also, a person with knowledge is more mentally and morally sound than people with money and less knowledge.

Besides, Knowledge is a very important tool to get positive changes in society or country. Knowledge gives us a vision of our future and what we can do in it. All the countries in the world that use technologically developed tools and machinery and many other things is the result of the knowledge. Weapons and bomb do not make a country powerful but knowledge does.

The growth and development of a nation do not depend on the arms and weaponry the country has. But with the amount of knowledgeable person it has and it is possible only because of the power of knowledge.

Get the huge list of more than 500 Essay Topics and Ideas

Prospective of Knowledge

Knowledge is something that is so powerful that it can destroy the whole earth and on the other hand is a tool that can restore balance on the earth. The knowledgeable person is the richest person on earth because no one can steal his/her knowledge. But anyone can easily steal your money and power from you any time.

Moreover, it never decreases on use and only increases with time. Accordingly, a knowledgeable person is more important than a rich person because a rich person can give money to the nation but a knowledgeable person can give knowledge to the nation and this knowledge can also increase the wealth of the nation .

In conclusion, we can say that true knowledge help person to bloom. Also, it keeps people away from fights and corruption. Besides, knowledge brings happiness and prosperity to the nation. Above all, knowledge opens the door of success for everyone.

FAQs about Knowledge Is Power

Q.1 Why knowledge is power? A.1 It is the power because it can solve any issue, also it can influence anyone to do any work. Besides this, knowledge s power because it can create and destroy anything that is present on the earth.

Q.2 Why little knowledge is dangerous? A.2 It is dangerous because persons with less knowledge do not know things completely but still gives his/her opinion on everything. Moreover, little knowledge is a ticking bomb which an explosion causes damages to people around it.

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Imagination is More Important than Knowledge: Essay Example

Imagination is more important than knowledge: essay introduction, imagination is better than knowledge: essay body, imagination is more important than knowledge: conclusion.

“Imagination is more important than knowledge,” is a famous quote of Albert Einstein. There are only a couple of words in this line, but if we think logically, it encloses the whole world. Imagination is a bequest of life and is indeed far more significant than knowledge. If we have the capability of imagining things, we can craft our world.

Imagination is not significant just for us as individuals but also for the community in general. It can also be interpreted as the fundamental element of theology and can be better articulated through contemplation. There have been great philosophers in the past who imagined the unattainable, and today our societies have certain values that are very relevant.

Simultaneously to be very dominant, imagination is also very risky. It all depends on the direction towards which we orient our imagination. Just like in the case of fire, if it becomes uncontrollable, it spells havocs, but if it is harnessed properly, it contributes to the development and wellbeing of the people. So our imagination should be oriented towards the positive or constructive direction rather than the negative or destructive one.

On the one hand, where positive approach in imagination improves life values, standards and progress, the negative approach is bound to lead the individuals towards fake things and feelings such as panic, intolerance, nervousness, etc. In the negative imagination, people lose their interface with the truth.

All the inventions and developments that have today become inseparable parts of our lives are results of positive imagination only. Some people imagined these things and converted them into reality. Human beings owe the transformation from Stone Age to being civilized to positive imagination. This is what positive imagination can do.

Knowledge is also important because simply by imagining things, one cannot convert them into reality. An intellectual mind is required for such tasks. But without imagination, knowledge would be of no use. We would be stagnant as far as development is concerned.

Like for instance, if Thomas Alva Edison were aware of the light (current) generating system but didn’t have the foresight to make useful things, then today we would not have the so important thing called bulb. Imagination is the foundation of contentment and pleasure in our lives. It provides us with lots of amusement, leisure and above all makes us more lively and humane.

Knowledge can be gained from various textbooks and lectures, but what about innovation? Unless we combine innovation and knowledge, there is no point in studying. Innovation comes from imagination, and imagination cannot be learned at schools or colleges. To put it more strongly, imagination is a revolution – in a good sense – and dominant, whereas knowledge is merely an attained instrument.

It is always good to acquire knowledge, but having the ability to imagine is far more important and inevitable. By acquiring knowledge, we learn things, but my imagination, we learn how to comprehend the things that we have learned. This comprehension further increases our knowledge.

Above all, the knowledge that we acquire is again a result of imagination. We don’t get knowledge out of knowledge but out of imagination that guides us to knowledge. So imagination is a sort of concierge to knowledge. We cannot gain knowledge unless we have imagination. So imagination is more important than knowledge.

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“Why Knowledge Counts More Than Skill”

Our blog post title above is in quotation marks because it is quoted from an article hot off the online press. Here are three quotations from that article:

To help students master nonfiction reading, we must design instruction that builds their background knowledge.
Prior knowledge affects comprehension—in many cases, far more than generic “reading skills” do.
The ability to build knowledge by reading and to learn from texts is a crucial driver of student success. … It is crucial to equity because many students’ lack of background knowledge causes them to fall further and further behind.

The source? “ How Knowledge Powers Reading ,” in the February 2017 issue of Educational Leadership , published by the Association for Supervision and Curriculum Development (ASCD). The author? Doug Lemov, author of Teach Like a Champion , the book about effective teaching that has grown into a professional development movement .

If you’re familiar with Core Knowledge, then Lemov’s statements will strike you as eminently sound. Indeed, Core Knowledge founder E. D. Hirsch, Jr. has been making the case for the importance of prior knowledge and the need for knowledge-based reading instruction since the publication of Cultural Literacy in 1987.

Lemov clearly explains that “how information is presented” is less important than what students know, since the text assumes (as all texts do) prior background knowledge. Lemov goes on to offer practical suggestions for “ways to weave prior knowledge into our students’ reading of nonfiction throughout the process of engaging them with texts.” (For more teaching strategies, see Lemov’s 2016 book from which his ASCD article is derived, Reading Reconsidered: A Practical Guide to Rigorous Literacy Instruction .)

One suggestion: “Ask knowledge-based questions.” Lemov is aware that many teachers have been “trained to think of such questions as second-rate or ‘not our job’”—after all, they’re at the bottom of Bloom’s taxonomy, mere facts as opposed to the higher-order skills of making inferences or interpreting motivations, right? Not quite, says Lemov. Through thoughtful examples, he shows how well-crafted “fact-based questions are actually surprisingly rigorous.”

Moreover, says Lemov, “if we don’t ask any such questions, we may be tacitly socializing students to believe that facts are irrelevant. By asking some fact-based questions, we can chip away at the knowledge deficit and teach our students how to unlock knowledge from what they read.”

Demonstrating by example that facts are relevant. Chipping away at the knowledge deficit. Filling in gaps in prior knowledge. These, we agree, are truly ways to teach like a champion.

Rating Content

Skill vs knowledge: understanding the differences and why they matter.

Share this article.

In today's fast-paced world, skill and knowledge are often used interchangeably, but they are distinct concepts with unique roles in personal and professional development.

Knowledge refers to the information and understanding we acquire through education and experience, while skills are practical abilities developed through practice and application.

Understanding the differences between skill vs knowledge is crucial for maximizing growth and success.

Knowledge expands our intellectual capacity, empowers us to adapt to change and make informed decisions. Skills, on the other hand, equip us with the tools to apply knowledge practically and achieve goals.

Recognizing the importance of both skill and knowledge is vital in today's competitive landscape.

This article will explore the distinctions between skill vs knowledge, their significance, and practical implications, enabling readers to make informed choices about their personal and professional development.

What Are Skills?

Skills refer to practical abilities or proficiencies that individuals possess and develop through practice, experience, and active application of knowledge.

They are the practical manifestation of knowledge, enabling individuals to effectively perform specific tasks or activities.

In a recent survey by SHRM, 83% of participants expressed challenges in finding suitable candidates for recruitment in the past year. Among those facing recruitment difficulties, 75% believed that the issue stemmed from a shortage of skills among the applicants.

This shows the increasing importance of skills in the ever-changing world.

Skills can be acquired and honed in various domains, including technical, interpersonal, cognitive, and creative areas.

Types Of Skills

In a survey conducted, 87% of the workforce expressed their belief in the necessity of continuously developing new skills throughout their careers to adapt to the evolving demands of the workplace.

Following are the different types of skills.

1. Technical Skills

Technical skills are specific expertise and knowledge required to perform tasks in a particular field or industry.

These skills are often job-specific and can include proficiency in using tools, equipment, software, or performing specialized tasks.

Examples of technical skills include programming, data analysis, engineering, carpentry, graphic design, or operating machinery.

2. Interpersonal Skills

Interpersonal skills, also known as soft skills, are essential for effective communication, collaboration, and interaction with others.

These skills are crucial in building relationships, fostering teamwork, and navigating social dynamics.

Examples of interpersonal skills include communication, active listening, empathy, conflict resolution, leadership, teamwork, and networking.

3. Cognitive Skills

Cognitive skills involve mental processes and abilities related to thinking, analyzing, and problem-solving.

These skills are critical for logical reasoning, decision-making, and strategic thinking.

Examples of cognitive skills include critical thinking, problem-solving, decision-making, analytical skills, attention to detail, creativity, and adaptability.

4. Creative Skills

Creative skills involve the ability to think innovatively, generate original ideas, and express oneself artistically.

These skills are essential in fields such as art, design, writing, music, and other creative endeavors.

Examples of creative skills include artistic expression, ideation, imagination, storytelling, graphic design, and creative problem-solving.

Skills are practical abilities developed through practice and active application of knowledge.

They encompass technical, interpersonal, cognitive, and creative proficiencies that contribute to individual success and professional growth.

Possessing a diverse range of skills enhances performance, employability, adaptability, and resilience.

By recognizing the importance of skills and actively investing in their development, individuals can unlock their potential and thrive in various personal and professional endeavors.

What Is Knowledge?

Knowledge refers to the information, facts, concepts, and theories that individuals acquire through education, experience, and exposure to various sources of information.

It encompasses understanding and awareness of a subject matter, including its principles, history, and applications.

Knowledge provides individuals with a foundation to comprehend and interpret the world around them.

As per a study conducted by Econsultancy, it was found that 51% of customers have a preference for utilizing a knowledge base for technical support.

Types Of Knowledge

According to a survey, a significant majority of customers, 91%, expressed their willingness to utilize an online knowledge base if it was accessible and customized to meet their specific requirements.

Let’s have a look at the different types of knowledge.

1. Explicit Knowledge

Explicit knowledge refers to formal, codified, and easily articulated information. It is tangible and can be easily expressed in words, documents, or diagrams.

Examples of explicit knowledge include textbooks, scientific articles, manuals, databases, and instructional videos. Explicit knowledge can be readily shared, communicated, and transferred among individuals.

2. Tacit Knowledge

Tacit knowledge is personal, experiential, and deeply rooted in an individual's intuition, insights, and expertise.

It is challenging to articulate and codify into explicit forms, making it highly subjective and context-dependent.

Tacit knowledge is acquired through observation, practice, and hands-on experience. Examples of tacit knowledge include skills, expertise, intuition, insights, and personal beliefs.

3. Procedural Knowledge

Procedural knowledge relates to knowing "how" to perform specific tasks or activities. It involves understanding the step-by-step procedures, methods, or techniques required to complete a task.

Procedural knowledge is practical and often associated with technical skills and expertise.

Examples of procedural knowledge include knowing how to drive a car, cook a recipe, operate machinery, or perform a specific surgical procedure.

4. Declarative Knowledge

Declarative knowledge encompasses factual information, concepts, and theories. It focuses on knowing "what" something is, its properties, attributes, or characteristics.

Declarative knowledge is based on facts, rules, principles, or theories.

Examples of declarative knowledge include understanding historical events, scientific concepts, mathematical formulas, or theories in various fields.

Skill Vs Knowledge: The Difference Between Skill And Knowledge

Skill and knowledge are two distinct but interconnected concepts that play significant roles in personal and professional development.

Understanding the differences between skill and knowledge is crucial for maximizing growth and success.

Let's delve into the differences between skill and knowledge and explore how they complement each other in various contexts.

1. Definition And Nature

Knowledge refers to the information, facts, concepts, and theories that individuals acquire through education, experience, and exposure.

It involves understanding and awareness of a subject matter, providing a theoretical foundation to comprehend the world.

Knowledge can be acquired through reading, studying, research, observation, and discussions.

On the other hand, skills are practical abilities or proficiencies that individuals develop through practice, experience, and active application of knowledge.

Skills are the tangible manifestation of knowledge, allowing individuals to effectively perform specific tasks or activities.

They require hands-on experience, repetition, and refinement to become proficient in a particular area.

2. Acquisition

Knowledge is acquired through various means such as formal education, self-study, research, and exposure to different sources of information.

It involves learning and understanding theoretical concepts, principles, and facts.

Knowledge can be obtained from books, lectures, online resources, or interactions with knowledgeable individuals.

Skills, on the other hand, are acquired through practical application and hands-on experience.

They are developed through deliberate practice, repetition, and active engagement in real-world scenarios. Skills require active learning, doing, and refining through practice and feedback.

3. Application

Knowledge forms the foundation for developing skills. It provides the necessary understanding and information required to perform tasks effectively.

Without a basic knowledge of a subject, it becomes challenging to acquire the skills associated with it.

For example, knowledge of musical notes, scales, and rhythm is essential before acquiring the skill to play a musical instrument.

Skills, on the other hand, involve the practical application of knowledge.

They are the abilities that individuals demonstrate when performing specific tasks or activities.

Skills allow individuals to translate theoretical knowledge into action and achieve desired outcomes.

4. Interplay And Importance

While knowledge and skills are distinct, they are interconnected and complement each other.

Knowledge provides the theoretical framework and understanding, while skills enable practical application and execution.

They work in tandem to enhance performance, problem-solving, and decision-making.

In many domains, possessing both knowledge and skills is crucial for success. A deep understanding of concepts and theories (knowledge) combined with the ability to apply them effectively (skills) enables individuals to excel in their fields.

For instance, in a professional setting, having technical knowledge (e.g., programming languages) and the corresponding programming skills allows a person to develop software applications.

Introducing Oreed: The Education Intelligence Platform You Have Been Looking For

Are you in search of a comprehensive education intelligence platform to upskill your employees or implement knowledge management in your organization?

Look no further – Oreed is here to provide you with the solution you need.

1. Boosting Employee Awareness

With Oreed, you can gain a 360-degree view of your workforce, boosting employee awareness and enabling you to make informed decisions that benefit both your employees and your company.

2. Developing Custom Training And Courses

Oreed goes beyond enhancing employee awareness; it also facilitates the development of custom training and courses tailored to your employees' specific needs.

By gaining a deeper understanding of their training requirements, you can design effective programs that foster growth and success.

Moreover, Oreed empowers you to create personalized learning paths that address individual skill gaps, providing targeted development opportunities for each employee.

3. Measuring Impact And Effectiveness

One of the standout features of Oreed is its powerful analytics and reporting capabilities.

With these tools, you can easily measure the impact and effectiveness of your training initiatives.

Oreed provides you with valuable insights into the progress and performance of your employees, allowing you to continuously improve your training and development programs.

By monitoring key metrics and analyzing the data, you can ensure that your initiatives deliver maximum value and drive meaningful results.

4. Achieving Unprecedented Levels Of Success

Oreed doesn't just promise improvement; it delivers unprecedented levels of success.

Our platform is designed to generate a remarkable 10x increase in customer revenue and engagement.

Furthermore, Oreed boosts employee productivity and enhances organizational efficiency. With Oreed, you can trust that you'll achieve the best possible return on investment (ROI) for your business.

So what are you waiting for? Book a demo with Oreed today and find out more about our features.

Promote lifelong learning through Oreed by experiencing the most powerful all-in-one training and development intelligent platform that streamlines all your organization's learning, training, and development activities in one place.

Final Thoughts

In conclusion, when it comes to skill vs knowledge, they are two interconnected yet distinct elements that play vital roles in personal and professional development.

While knowledge provides the theoretical understanding and foundation, skills enable the practical application and execution of that knowledge.

Both are essential for success, as knowledge provides the necessary information and concepts while skills empower individuals to effectively use and apply that knowledge.

Recognizing the differences and fostering a balance between skill vs knowledge is key to unlocking one's full potential and achieving excellence in various areas of life.

By continually expanding knowledge and honing skills, individuals can enhance their performance, adaptability, and growth, setting themselves up for success in an ever-evolving world.

1. What is a skill training program?

A skill training program is a structured educational initiative designed to enhance individuals' practical abilities and proficiency in a specific skill or set of skills.

These programs aim to equip participants with the knowledge, techniques, and hands-on experience required to excel in a particular field or occupation.

Skill training programs often involve a combination of theoretical instruction, practical exercises, simulations, and real-world applications.

They are typically developed and delivered by subject matter experts or training professionals who possess expertise in the target skill area.

The objective of these programs is to provide participants with the necessary tools and resources to acquire, develop, and refine their skills, ultimately enabling them to succeed in their chosen profession or pursue new career opportunities.

2. What are the benefits of knowledge?

The benefits of knowledge are truly transformative.

Firstly, knowledge empowers individuals with the ability to understand and navigate the world around them. It provides a solid foundation for critical thinking, problem-solving, and decision-making.

Secondly, knowledge fuels personal and professional growth by opening doors to new opportunities and expanding intellectual horizons.

With knowledge, individuals can stay informed, adapt to changes, and continuously learn and evolve.

Moreover, knowledge enhances creativity and innovation by providing a diverse range of perspectives and insights.

Lastly, knowledge is a catalyst for success, enabling individuals to excel in their fields and make meaningful contributions.

The benefits of knowledge are manifold, shaping individuals into informed, capable, and accomplished individuals.

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Thomas Jefferson's Monticello

Research & Education
Thomas Jefferson Encyclopedia

Knowledge is power (Quotation)

The phrase "knowledge is power" is often attributed to Francis Bacon, from his Meditationes Sacrae (1597). [1]

Thomas Jefferson used the phrase in his correspondence on at least four occasions, each time in connection with the establishment of a state university in Virginia.

In an 1817 letter to George Ticknor, Jefferson equated knowledge with power, safety, and happiness:

[T]his last establishment [a state university] will probably be within a mile of Charlottesville, and four from Monticello, if the system should be adopted at all by our legislature who meet within a week from this time. my hopes however are kept in check by the ordinary character of our state legislatures, the members of which do not generally possess information enough to percieve the important truths, that knolege is power, that knolege is safety, and that knolege is happiness. [2]

In two 1820 letters to Joseph Cabell, Jefferson again emphasized the importance of knowledge:

Kentucky, our daughter, planted since Virginia was a distinguished state, has an University, with 14. professors & upwards of 200 students. ... all the states but our own are sensible that knolege is power. [3]

[I]t is unquestionable that [Virginia] has more influence in our confederacy than any other state in it. whence this ascendancy? from her attention to education unquestionably. there can be no stronger proof that knolege is power, and that ignorance is weakness. [4]

Continuing to write on the subject of a state university, Jefferson referred to the power of knowledge in an 1821 letter to John Taylor:

[Northeastern] seminaries are no longer proper for Southern or Western students. the signs of the times admonish us to call them home. if knolege is power we should look to it's advancement at home, where no resource of power will be unwanting. [5]

^ John Bartlett, Familiar Quotations , 10th ed. (Boston: Little, Brown and Co., 1919), 168 . The entry for this quotation is available online at Bartleby.com .
^ Jefferson to Ticknor, November 25, 1817, in PTJ:RS , 12:204. Transcription available at Jefferson Quotes & Family Letters .
^ Jefferson to Cabell, January 22, 1820, in PTJ:RS , 15:344-46. Transcription available at Founders Online.
^ Jefferson to Cabell, December 25, 1820, Special Collections , University of Virginia Library. Transcription available at Founders Online.
^ Jefferson to Taylor, February 14, 1821, Washburn Collection, Massachusetts Historical Society . Transcription available at Founders Online.

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Grades vs Educational Knowledge

By Madeleine on March 26, 2021 |Tagged with: learning , motivation , skills for class , Student Reflections

As a university student it is important to recognize that there is a difference between grades and educational knowledge. While the two do go hand in hand quite nicely, there is a fine line that separates them and it is important to understand what differentiates the two. It took me a long time to really understand this. I remember getting back exams and seeing a grade that was lower than what I expected, and resorting to thinking that I really did not know anything. Sometimes it was true that I did not understand it, but other times it was just one too many simple mistakes that landed me with a grade that did not represent how much I really knew. It was a really important lesson for me to learn that what I actually knew and understood was not always the same as the grade I got. Similarly, I learned the hard the way that getting a good grade on something does not necessarily mean that I actually know it. Just because I got a good grade on my homework did not mean I actually understood it, and sitting clueless in my midterm exam really showed me that. I realized there is a very important distinction between grades and knowledge, and I am going to explain it to you.

This post will discuss the difference between grades and knowledge, how to reflect on when and how you may have gained knowledge, and to explain the relationship between achieving good grades and gaining knowledge. While most people know that you can achieve both of these things together, it is also important to understand that you can achieve grades without knowledge, and gain knowledge without achieving good grades. And most importantly, gaining knowledge can help you achieve good grades, and the effort you put into achieving good grades can help you gain knowledge. If knowledge helps you get good grades, and working to get good grades help you gain knowledge, you might find yourself thinking which came first? The knowledge or the grade?

But what are grades and what is knowledge? The Oxford Languages dictionary has several definitions for both. I’d like to share the first two of each with you.

Acts, information, and skills acquired by a person through experience or education; the theoretical or practical understanding of a subject.
Awareness or familiarity gained by experience of a fact or situation.
A particular level of rank, quality, proficiency, intensity, or value
A mark indicating the quality of a student’s work.

Now, if I may, I would like to share MY personal definitions for each, or rather, what each means to me.

The information that is in your head that you really understand and know, that you can apply to other things and use in your life, for any purpose. Proper dribbling technique in field hockey is very important knowledge to me, even if I would never be graded on it.

A representation of how well you can learn a lot of material, in any way possible, often in a short amount of time. To me this represents my study habits, my ability to stay on track of my workload, my notetaking, and frankly just how well I study. Typically grades represent your performance in a program or course.

The biggest difference, in my opinion, is that grades can be measured concretely, while knowledge is much harder to calculate. You know very easily what your grades are simply by looking at your transcript, or by getting your tests, quizzes, projects, or papers back. It is also quite easy to feel overwhelmed by your grades, whether they are what you were expecting or not. Knowledge, however, goes much more frequently unrecognized. However, while it may be difficult to measure, it is not the case that we should therefore not seek to recognize our knowledge. Educational knowledge comes in forms such as organizing your time, keeping up with your workload, and managing your stress. It is important not to assume that these skills are less important than your grades.

I think it is very important to reflect on our knowledge so when can understand just how much we have learned. In my personal experience, it tends to take me a long time to fully understand that I have actually learned something, that I have gained knowledge. I often feel like after all my final exams I immediately forget everything I have just learned, and I think, what a waste of time that was, seeing as I learned nothing. But I did not learn nothing! That is the tricky part to realize, which requires reflection. For me I find it helps to talk to a friend or a family member, and explain to them what I did in a certain course. Usually what happens for me is that the person I am talking to goes, “slow down, what was that word you just said? I’ve never heard of that before,” and a lot of the time I think “hey, I did not know that word before this term either,” in which case, I realize I MUST have learned something.

Knowing when you have gained knowledge is something you have to think about, and it is something you realize much more easily and more quickly over time. A fun way of knowing, in my opinion, whether you have gained knowledge, is to write a list of questions you have about a course or concept at the beginning or middle of term. Note a number of things that you do not fully understand, from words, to symbols, to whole processes and concepts. Then, at the end of term, just see how many of those things are so obvious to you now. To me, it is a very positive and uplifting way to reflect on what you know now that you did not know before.

The importance of educational knowledge

Educational knowledge is important because it stays with you forever. There are a few ways to think about this, and they are all extremely valuable. The most obvious, I think, is the fact that if you learn a lot in your 102 class, you will be very well prepared for your 202 class in the same subject. The material you learned gets carried over and built upon, and how well you actually know the material, regardless of your grade, will help you with the new material. So, if you got a 90% but it was because there was a really smart person in your group project, or you got lucky on the multiple choice, this grade will not help you going forward if you do not really know the material. On the other hand, if you really knew the material really well but you got a terrible sleep the night before the final and wrote a terrible exam, that bad grade does not stop you from knowing the material. This has been a really important thing for me to realize, after not doing well on exams I really thought I should have done well on. It is important for me to go over the exam and ask myself if I could have gotten the answer correct. Was I completely lost or was I just missing one little thing? Accessing your knowledge is really important.

Another way to think about this is the experiential knowledge you gain. Even if you do not gain factual knowledge, like above, you might have gained knowledge in regard to your skills and technique. This is not surprising at all, since for every year of school, since we were five, our workload increases more and more each year. There are bigger projects and longer essays and harder books to read. This is because we learn from doing. Even if you got a 55% grade on your term, you still had really great practice in writing the essay. Your study habits get better every year just from continuing to study, and this is extremely valuable knowledge. However, if you just memorize something rather than take the time to practice or understand it, once you forget it, it is as though you never had that information. If you fully understand something, even if you forget it, you still have that knowledge, and this is why knowledge is so important.

Importance of grades

Many of us have heard, for all our lives, “your grades are very important”. For me, when I was applying to university, all I ever heard about was how my grades are of the utmost importance. While it is important to also consider educational knowledge, there is also a lot of truth in that grades are of equal importance. If I had not cared about my grades, even if I was learning, and let them drop, I may not have gotten into university. Then, even if I did want to keep learning, I would have no choice since I would not have been accepted into school. Grades are highly important once you are in university too. There are many situations in which your grades are highly dependent on what you are able to do next. Your major might require a certain average to get into it, or a course might require that you got a certain grade in the prerequisites. Grades are a very good concrete way to measure where you stand with respect to other students in your class, or how much you have improved since last year’s grades. Grades matter in the bigger picture too. If you want to apply to graduate school, you apply with your grades. And if you are in a special program, you know that you must keep your grades up to stay in the program. I am sure many of you know that, at UBC, if you want to participate in an exchange program, you must have a certain average to apply. Once you graduate, your degree will allow you to get a good job, and you only receive your degree by getting good enough grades. So now you know that knowledge is very important, but that grades are also very important. So how do they work together?

How grades and knowledge complement each other

Grades act as a key to get in the door for opportunities, and they continue to act as that whether you learned the material or not. As long as you receive a certain percentage, that is good enough to be accepted to whatever your next step is. But once you are through the door, you must rely on your knowledge. Not having knowledge could prevent you from getting the grades to act as the next key to the next step in your education or career path. To give a more concrete example: if you graduate with good grades, you present yourself with many work opportunities with your degree. Of course, your personality and professional experience plays a significant role, but your degree- and, depending on your field, the grades you receive in important courses- also acts as a key in the door. Supposing you get hired but you do not really know the material well that applies from your degree to your area of work, it will not be long before you are forced to look for a new job. Contrarily, if you happen to have fantastic knowledge but no grades to prove it- perhaps you were self-taught in this field- it might be challenging to find a good job that takes your word for it and does not require any academic or professional experience to attest to it. I think everyone knows that grades and knowledge work together, but it is really important to understand how different they are and in what ways they complement each other.

I think a good way to summarize things is as follows: grades and educational knowledge are of equal importance, but at different times and for different things. Grades are short term important, while knowledge is long term important. Grades matter at certain times and are essential to making bigger steps in your academic path. Knowledge matters consistently through time, and helps you get good grades, but knowledge is also an authentic reflection of your genuine learning. It is important to understand the differences between them and to appreciate how they complement each other. If you are unsure about the difference between your grades and your personal knowledge in a subject, I challenge you to reflect on your grades and ask yourself if you feel your grade is reflective of your knowledge on the subject, or if (and, if so, why) there are discrepancies between the two.

2 responses to “Grades vs Educational Knowledge”

Amazing essay. lately i have bene thinking about this topic, and I agree with you on your point of view of grades and knowledge. One example from my life to support you essay is I had to learn English to get into college (English isn’t my native language), and I followed the same approach regarding focusing on grades and knowledge, and it benefited me a lot in later unrelated course. On the other hand, I have seen people Soley focus on grades, and now they lack in many aspects of acquiring new knowledge. I think this example really shows the importance of having a good understanding of the material because English is of these course that you could pass easily without actually being able to acquire it.

Super fantastic bruh

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Why Focusing on Grades Is a Barrier to Learning

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Classroom Management
Experiential Learning
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Student Engagement

I n his book Drive , Daniel Pink suggests that we operate today with a misguided understanding of what really motivates us. Often, we assume that the only way to get people to perform is to incentivize them through external rewards and punishments, or extrinsic motivation, rather than focusing people on a desired behavior, or intrinsic motivation.

As a seasoned educator who has taught in the classroom for nearly 40 years, I see this paradigm consistently. Students have become more focused on the rewards and punishments, namely grades (an extrinsic motivator), and less on the desired behavior, learning (an intrinsic motivator). Students often refer to themselves as “A” students, “B” students, or “C” students in conversations with each other and feel a sense of shame when they get failing grades. When they refer to their classes, they say things like, “That class is an easy A,” or, “It’s hard to get a good grade in that class,” or, “Don’t take that class because it will ruin your GPA.” When students ask questions about assignments, quizzes, exams, or absences, it’s almost always in reference to points and grades. A favorite question is, “Can I get any extra credit to raise my grade?”

What’s apparent in all this focus on grades is that there’s no real emphasis on learning—the true purpose of education. It is a rare occurrence that students come to talk with me about concepts or new material presented, and even in learning-focused discussions, the topic of grades almost always arises. When I encounter students after they have graduated, they almost always remember what grade they received in my class; yet when I ask about what concepts they learned, they hesitate before answering.

“What’s apparent in all this focus on grades is that there’s no real emphasis on learning—the true purpose of education.”

What can we as educators do to refocus students on the learning and get away from this emphasis on grades? I’ve found Montessori educational principles can provide us with some useful ways to rethink our current grading system and get students interested in what matters most—the learning.

Emphasizing Learning Over Grades

Why students focus on grades—and how to reverse the trend.

Carl Rogers, a psychologist and one of the founders of the humanistic psychology movement, offers some insight into why students focus so much on grades as opposed to learning in his book On Becoming a Person . Rogers suggests that a person focuses on that which is important to the maintenance of the “Self.” Students focus on grades and degrees because they think that will help them get a good job and advance their careers—maintaining the Self. It appears they don’t relate acquired knowledge and skillsets with getting a good job.

The irony is that what was acquired and developed during their formal education is what is imperative to retaining employment. After a few years in a career, a person is rarely asked about GPA. What is learned, not the grades earned, is more important to keeping a job and advancing a career.

According to Rogers, we are born with a desire to learn and reach our human potential. Students need to be placed in the proper environment to nurture this desire. Yet, as educators, we continue to reward student behavior with grades while putting less emphasis on developing this innate desire to develop and grow. Instead, learning should be the goal of education.

Let’s imagine a fully engaged classroom where, instead of learning and education being viewed as a chore, our students follow their innate tendency to explore their environment, i.e., their intrinsic desire to grow and learn. A key ingredient in this vision is autonomy—which is a principle of Montessori education. It puts emphasis on students’ freedom, within limits, to control their own educational process and goal setting, which links both success and failure with their actions and the consequences of their decisions. In other words, students are encouraged to be creative, imaginative, and free to make mistakes. Learning from those mistakes and failures is normalized as part of the process.

As such, Montessori teachers are viewed as guides, rather than people who impart knowledge. One important focus for these teachers is to design, organize, and prepare an appropriate learning environment for students, where they can freely take responsibility and self-direction for the ways they choose to learn.

Following the intrinsic motivation model, Montessori principles believe that students will be guided by their interests. They are led to those things that are valuable and meaningful to them personally. The result of this process is the development of competence, self-confidence, and mastery. Competence fosters confidence, which in turn inspires students to tackle subsequent challenges. This cycle builds on itself and leads to a lifelong quest for learning.

Rethinking the Grading Paradigm

From my experience in the classroom, our current paradigm based on grades creates an environment in which students fear the possibility of failure rather than focusing on the possibility of learning. Students are afraid to speak up, ask questions, and make mistakes for fear that it will impact their grade.

But when classes are structured as learning laboratories—like they are at Montessori schools—and students aren’t penalized for exploring new methods, making mistakes, asking questions, or admitting failure, they become more creative and self-directed. They seem to open up and thrive when asked to write one-page reflections and implication papers about what the concepts or materials mean to them. In many such classes, students appear to be having fun while they are working on class exercises and engaging in active discussions related to the topic presented.

DO EMPLOYERS REALLY CARE ABOUT GRADES?

Many people think that without grades and grade point averages (GPAs), employers would have no way of evaluating students for potential employment. But smart employers have already put less emphasis on GPAs and have instituted their own internal tests and simulations to figure out what a potential job applicant knows or is interested in knowing.

Asking students what they know about a particular subject or topic is a great way to find out about a student’s knowledge in a given area. Some employers will even look at the courses a student has taken and ask questions about what they learned in a particular class. These are all great ways to assess knowledge and may be better indicators of what a student knows than relying on a GPA or an individual grade.

I believe that if more educators used this grading structure, student cheating would be diminished, grade inflation would be eliminated, and students would be much more inclined to discuss what they are learning because the classroom would become more creative, self-directed, and meaningful to them. By becoming learning labs, these classrooms would nurture a love of learning. What’s more, perhaps implementing these changes would make achieving excellence more attainable for all student groups.

Restoring Students’ Love of Learning

Why do we educators hang on to the current extrinsically motivated grading paradigm? I think at a gut level many of us feel that it is not working well, yet the whole educational system is built around it. And trying to imagine how the whole educational system would function without grades can seem monumental.

Reimagining how this would change our roles as educators can be threatening to both individuals and their institutions. Yet, if there is one thing that we have all learned from the COVID-19 pandemic, it’s that both people and organizations can adapt to change very quickly and creatively when necessity dictates.

It is time for the entire educational system to start re-examining our current grading paradigm. With the help of other educators, students, parents, and interested groups, we can take steps to improve this grading system and restore students’ love of learning. Change starts with conversation, and I hope that all of you will join me in this one.

Gerald E. Knesek , EdD, MBA, is a senior lecturer in the School of Management at the University of Michigan–Flint. He’s a retired human resources professional who spent his entire career of over 30 years in the automotive industry at General Motors Corporation. Since his retirement, he has held positions in educational administration and teaching. Knesek is known as a student-oriented teacher.

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Which Is More Important: Creativity or Knowledge?

Which is more important: creativity or knowledge? Find here the answer! This creativity vs. knowledge essay explains the relationship between imagination and intelligence and gives examples.

Introduction

Creativity vs. Knowledge

Works Cited

Schools are institutions that are set up with the aim of impacting students with knowledge. This being the primary focus of most education systems, generating new knowledge through creativity becomes secondary to most scholars. This leads to the question of which, between knowledge and creativity, is more important? This question is more relevant to students in higher institutions of learning since this level of learning is developed enough to generate creative thinking, in addition to impacting students with knowledge.

Creativity Is More Important than Knowledge

As such, a college student should ponder on this question, considering that such a student is almost ready for the job market. As a college student, creativity is more important than knowledge since creativity allows one to explore ideas with no boundaries, it gives birth to innovation, and it provides room for developing practical solutions to real life challenges, unlike knowledge which is limited to one’s expertise and experience.

While knowledge is limited to one’s skills, creativity has no boundaries since it goes as far as one’s imagination can reach. Knowledge hardly goes beyond one’s training or experience in a certain field, whereas creativity/imagination follows intuition and transcends one’s acquired skills (Ox and van der Elst 84).

Creative minds do not necessarily focus on achieving good grades in school. This is because good grades do not always imply creativity; instead, good grades are usually a reflection of one’s knowledge in a given subject since schooling systems are more oriented on impacting knowledge than creating an environment that enhances creativity.

Knowledge is determined by set standards and systems, but creativity transcends these systems since a creative mind is more flexible and imaginative. With specific focus on great people like Albert Einstein, who came up with the laws of relativity, it is very clear that Einstein exercised more creativity than knowledge in coming up with the laws (Gardner 108).

Although it is acknowledgeable that his prior knowledge in the field of physical science created an environment for developing the laws of relativity, his sense of imagination was far much important than the acquired knowledge. It is for such a reason that college students should be more creative, other than just acquiring knowledge in their course of learning.

Creativity births innovation since it is not bound by experience, unlike knowledge that is limited to acquired skills and experience. Creativity encompasses the intrinsic motivation to pursue a certain interest, and this gives birth to innovation. Creativity allows college students to think in a flexible and imaginative way such that when a motivating environment is provided, students can end up creating very impressive solutions to problems. Global success is pegged on innovation.

Virtually every sphere of life in the current world is competitive in its own way. This calls for innovative minds in order to emerge successful (HR Focus 8). On the other hand, new ideas cannot be generated by relying on knowledge alone since knowledge is limited to the skills that are acquired through a formal or informal process of learning.

As such, creative thinking remains to be the solution to innovation in the current world. It is said that contemporary organizations are encouraging creative thinking as a way of remaining competitive. College students can supplement the existing gap in innovation by being more creative, in addition to being knowledgeable in their fields of study. To a college student, divergent and convergent thinking are a recipe for success, even outside college (HR Focus 8).

Creativity holds promise to providing solutions to the numerous challenges in the work environment and the larger society. Combining expertise with imagination, which encompasses flexible thinking, would help explore problems beyond the limited human understanding and develop effective solutions.

Colleges, among other institutions of higher learning, should offer the best platform for developing individual creativity. College students have the right environment to develop creativity since university-level education encourages individual learning more than pedagogical structured learning.

The wide access to information and elaborate interaction and networking available in colleges should ignite students to be more creative and become problem solvers. Moreover, college students should realize that they are under preparation for the great roles they will later play in the society, especially in their places of work (Livingston 60). For this reason, creativity is far much important than knowledge to a college student.

Combined knowledge and creativity can generate greater achievement, thus the importance of both cannot be underestimated. For instance, while someone like Einstein used imagination to come up with the laws of relativity, he also relied heavily on his immense knowledge of physical science to draft these laws (Gardner 104). Thus, while it is right to argue that creativity is more important than knowledge to a college student, it does not mean that knowledge has no place in fostering creativity.

In fact, it is right to argue that creativity is boosted by one’s knowledge, thus a very thin line exists between knowledge and creativity. Creativity comprises of expertise, flexible thinking and imagination, and motivation. Hope (39) acknowledges that creative potential is build over time and calls for consistent study with a particular goal in mind. The study must be focused on a specific field for creativity in that field to be developed.

This implies that knowledge must be acquired under certain structures, such as schooling structures, to develop creative potential. An environment that does not foster creative thinking kills creativity. In addition, creativity is developed by acknowledging knowledge in a particular field (Ox and van der Elst 84). As such, college students cannot afford to ignore the need for structured learning and pursue creativity solely. Such an approach may not give birth to creativity since creativity is built on knowledge.

The world today is need of creative and innovative minds for global success to be achieved, and creative college minds can meet this need. To a college student, creativity will help in thinking and developing solutions beyond one’s acquired knowledge and skills.

Moreover, creative college students will find relevance in the present work environment since they will be able to come up with innovations. This notwithstanding, it is important for college student to acquire knowledge since creativity in any field is catalyzed by accumulated knowledge in the field of study.

As a college student, imagination should be given a priority in the course of acquiring knowledge if one wants to be creative. Moreover, college education should foster flexible thinking and provide a motivating environment that will give birth to creativity. Creativity among college students should be encouraged than the sole pursuit for knowledge in order to develop solutions that are so much needed in the working world and the society at large.

Gardner, Howard. Creating Minds: An Anatomy of Creativity Seen Through the Lives of Freud, Einstein, Picasso, Stravinsky, Eliot, Graham, and Gandhi . New York, NY: Basic Books, 2011. Print.

Hope, Samuel. “Creativity, Content, and Policy.” Arts Education Policy Review 111.2 (2010): 39-47. Print.

HR Focus. “Creativity and Innovation: Must-Haves for Global Success.” HR Focus News Briefs (2007): 8. Print.

Livingston, Larry. “Teaching Creativity in Higher Education.” Arts Education Policy Review 111.2 (2010): 59-62. Print.

Ox, Jack, and van der Elst Judith. “How Metaphor Functions as a Vehicle of Thought: Creativity as a Necessity for Knowledge Building and Communication.” Journal of Visual Art Practice 10.1 (2011): 83-102. Print.

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IvyPanda . 2018. "Which Is More Important: Creativity or Knowledge?" December 11, 2018. https://ivypanda.com/essays/as-a-college-student-creativity-is-more-important-than-knowledge/.

1. IvyPanda . "Which Is More Important: Creativity or Knowledge?" December 11, 2018. https://ivypanda.com/essays/as-a-college-student-creativity-is-more-important-than-knowledge/.

Bibliography

IvyPanda . "Which Is More Important: Creativity or Knowledge?" December 11, 2018. https://ivypanda.com/essays/as-a-college-student-creativity-is-more-important-than-knowledge/.

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Is a Long Essay Always a Good Essay? The Effect of Text Length on Writing Assessment

Johanna fleckenstein.

1 Department of Educational Research and Educational Psychology, Leibniz Institute for Science and Mathematics Education, Kiel, Germany

Jennifer Meyer

Thorben jansen.

2 Institute for Psychology of Learning and Instruction, Kiel University, Kiel, Germany

Stefan Keller

3 School of Education, Institute of Secondary Education, University of Applied Sciences and Arts Northwestern Switzerland, Brugg, Switzerland

Olaf Köller

Associated data.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher.

The assessment of text quality is a transdisciplinary issue concerning the research areas of educational assessment, language technology, and classroom instruction. Text length has been found to strongly influence human judgment of text quality. The question of whether text length is a construct-relevant aspect of writing competence or a source of judgment bias has been discussed controversially. This paper used both a correlational and an experimental approach to investigate this question. Secondary analyses were performed on a large-scale dataset with highly trained raters, showing an effect of text length beyond language proficiency. Furthermore, an experimental study found that pre-service teachers tended to undervalue text length when compared to professional ratings. The findings are discussed with respect to the role of training and context in writing assessment.

Introduction

Judgments of students’ writing are influenced by a variety of text characteristics, including text length. The relationship between such (superficial) aspects of written responses and the assessment of text quality has been a controversial issue in different areas of educational research. Both in the area of educational measurement and of language technology, text length has been shown to strongly influence text ratings by trained human raters as well as computer algorithms used to score texts automatically ( Chodorow and Burstein, 2004 ; Powers, 2005 ; Kobrin et al., 2011 ; Guo et al., 2013 ). In the context of classroom language learning and instruction, studies have found effects of text length on teachers’ diagnostic judgments (e.g., grades; Marshall, 1967 ; Osnes, 1995 ; Birkel and Birkel, 2002 ; Pohlmann-Rother et al., 2016 ). In all these contexts, the underlying question is a similar one: Should text length be considered when judging students’ writing – or is it a source of judgment bias? The objective of this paper is to investigate to what degree text length is a construct-relevant aspect of writing competence, or to what extent it erroneously influences judgments.

Powers (2005) recommends both correlational and experimental approaches for establishing the relevance of response length in the evaluation of written responses: “the former for ruling out response length (and various other factors) as causes of response quality (by virtue of their lack of relationship) and the latter for establishing more definitive causal links” (p. 7). This paper draws on data from both recommended approaches: A correlational analysis of a large-scale dataset [MEWS; funded by the German Research Foundation (Grant Nr. CO 1513/12-1) and the Swiss National Science Foundation (Grant Nr. 100019L_162675)] based on expert text quality ratings on the one hand, and an experimental study with untrained pre-service teachers on the other. It thereby incorporates the measurement perspective with the classroom perspective. In the past, (language) assessment research has been conducted within different disciplines that rarely acknowledged each other. While some assessment issues are relevant for standardized testing in large-scale contexts only, others pertain to research on teaching and classroom instruction as well. Even though their assessments may serve different functions (e.g., formative vs. summative or low vs. high stakes), teachers need to be able to assess students’ performance accurately, just as well as professional raters in standardized texts. Thus, combining these different disciplinary angles and looking at the issue of text length from a transdisciplinary perspective can be an advantage for all the disciplines involved. Overall, this paper aims to present a comprehensive picture of the role of essay length in human and automated essay scoring, which ultimately amounts to a discussion of the elusive “gold standard” in writing assessment.

Theoretical Background

Writing assessment is about identifying and evaluating features of a written response that indicate writing quality. Overall, previous research has demonstrated clear and consistent associations between linguistic features on the one hand, and writing quality and development on the other. In a recent literature review, Crossley (2020) showed that higher rated essays typically include more sophisticated lexical items, more complex syntactic features, and greater cohesion. Developing writers also show movements toward using more sophisticated words and more complex syntactic structures. The studies presented by Crossley (2020) provide strong indications that linguistic features in texts can afford important insights into writing quality and development. Whereas linguistic features are generally considered to be construct-relevant when it comes to assessing writing quality, there are other textual features whose relevance to the construct is debatable. The validity of the assessment of students’ competences is negatively affected by construct-irrelevant factors that influence judgments ( Rezaei and Lovorn, 2010 ). This holds true for professional raters in the context of large-scale standardized writing assessment as well as for teacher judgments in classroom writing assessment (both formative or summative). Assigning scores to students’ written responses is a challenging task as different text-inherent factors influence the accuracy of the raters’ or teachers’ judgments (e.g., handwriting, spelling: Graham et al., 2011 ; length, lexical diversity: Wolfe et al., 2016 ). Depending on the construct to be assessed, the influence of these aspects can be considered judgment bias. One of the most relevant and well-researched text-inherent factors influencing human judgments is text length. Crossley (2020) points out that his review does “not consider text length as a linguistic feature while acknowledging that text length is likely the strongest predictor of writing development and quality.” Multiple studies have found a positive relationship between text length and human ratings of text quality, even when controlling for language proficiency ( Chenoweth and Hayes, 2001 ; McCutchen et al., 2008 ; McNamara et al., 2015 ). It is still unclear, however, whether the relation between text length and human scores reflects a true relation between text length and text quality (appropriate heuristic assumption) or whether it stems from a bias in human judgments (judgment bias assumption). The former suggests that text length is a construct-relevant factor and that a certain length is needed to effectively develop a point of view on the issue presented in the essay prompt, and this is one of the aspects taken into account in the scoring ( Kobrin et al., 2007 ; Quinlan et al., 2009 ). The latter claims that text length is either completely or partly irrelevant to the construct of writing proficiency and that the strong effect it has on human judgment can be considered a bias ( Powers, 2005 ). In the context of large-scale writing assessment, prompt-based essay tasks are often used to measure students’ writing competence ( Guo et al., 2013 ). These essays are typically scored by professionally trained raters. These human ratings have been shown to be strongly correlated with essay length, even if this criterion is not represented in the assessment rubric ( Chodorow and Burstein, 2004 ; Kobrin et al., 2011 ). In a review of selected studies addressing the relation between length and quality of constructed responses, Powers (2005) showed that most studies found correlations within the range of r = 0.50 to r = 0.70. For example, he criticized the SAT essay for encouraging wordiness as longer essays tend to score higher. Kobrin et al. (2007) found the number of words to explain 39% of the variance in the SAT essay score. The authors argue that essay length is one of the aspects taken into account in the scoring as it takes a certain length to develop an argument. Similarly, Deane (2013) argues in favor of regarding writing fluency a construct-relevant factor (also see Shermis, 2014 ; McNamara et al., 2015 ). In an analytical rating of text quality, Hachmeister (2019) could showed that longer texts typically contain more cohesive devices, which has a positive impact on ratings of text quality. In the context of writing assessment in primary school, Pohlmann-Rother et al. (2016) found strong correlations between text length and holistic ratings of text quality ( r = 0.62) as well as the semantic-pragmatic analytical dimension ( r = 0.62). However, they found no meaningful relationship between text length and language mechanics (i.e., grammatical and orthographical correctness; r = 0.09).

Text length may be considered especially construct-relevant when it comes to writing in a foreign language. Because of the constraints of limited language knowledge, writing in a foreign language may be hampered because of the need to focus on language rather than content ( Weigle, 2003 ). Silva (1993) , in a review of differences between writing in a first and second language, found that writing in a second language tends to be “more constrained, more difficult, and less effective” (p. 668) than writing in a first language. The necessity of devoting cognitive resources to issues of language may mean that not as much attention can be given to higher order issues such as content or organization (for details of this debate, see Weigle, 2003 , p. 36 f.). In that context, the ability of writing longer texts may be legitimately considered as indicative of higher competence in a foreign language, making text length a viable factor of assessment. For example, Ruegg and Sugiyama (2010) showed that the main predictors of the content score in English foreign language essays were first, organization and second, essay length.

The relevance of this issue has further increased as systems of automated essay scoring (AES) have become more widely used in writing assessment. These systems offer a promising way to complement human ratings in judging text quality ( Deane, 2013 ). However, as the automated scoring algorithms are typically modeled after human ratings, they are also affected by human judgment bias. Moreover, it has been criticized that, at this point, automated scoring systems mainly count words when computing writing scores ( Perelman, 2014 ). Chodorow and Burstein (2004) , for example, showed that 53% of the variance in human ratings can be explained by automated scoring models that use only the number of words and the number of words squared as predictors. Ben-Simon and Bennett (2007) provided evidence from National Assessment of Educational Progress (NAEP) writing test data that standard, statistically created e-rater models weighed essay length even more strongly than human raters (also see Perelman, 2014 ).

Bejar (2011) suggests that a possible tendency to reward longer texts could be minimized through the training of raters with responses at each score level that vary in length. However, Barkaoui (2010) and Attali (2016) both compared the holistic scoring of experienced vs. novice raters and – contrary to expectations – found that the correlation between essay length and scores was slightly stronger for the experienced group. Thus, the question of whether professional experience and training counteract or even reinforce the tendency to overvalue text length in scoring remains open.

Compared to the amount of research on the role of essay length in human and automated scoring in large-scale high-stakes contexts, little attention has been paid to the relation of text length and quality in formative or summative assessment by teachers. This is surprising considering the relevance of the issue for teachers’ professional competence: In order to assess the quality of students’ writing, teachers must either configure various aspects of text quality in a holistic assessment or hold them apart in an analytic assessment. Thus, they need to have a concept of writing quality appropriate for the task and they need to be aware of the construct-relevant and -irrelevant criteria (cf. the lens model; Brunswik, 1955 ). To our knowledge, only two studies have investigated the effect of text length on holistic teacher judgments, both of which found that longer texts receive higher grades. Birkel and Birkel (2002) found significant main effects of text length (long, medium, short) and spelling errors (many, few) on holistic teacher judgments. Osnes (1995) reported effects of handwriting quality and text length on grades.

Whereas research on the text length effect on classroom writing assessment is scarce, a considerable body of research has investigated how other text characteristics influence teachers’ assessment of student texts. It is well-demonstrated, for example, that pre-service and experienced teachers assign lower grades to essays containing mechanical errors ( Scannell and Marshall, 1966 ; Marshall, 1967 ; Cumming et al., 2002 ; Rezaei and Lovorn, 2010 ). Scannell and Marshall (1966) found that pre-service teachers’ judgments were affected by errors in punctuation, grammar and spelling, even though they were explicitly instructed to grade on content alone. More recently, Rezaei and Lovorn (2010) showed that high quality essays containing more structural, mechanical, spelling, and grammatical errors were assigned lower scores than texts without errors even in criteria relating solely to content. Teachers failed to distinguish between formal errors and the independent quality of content in a student essay. Similarly, Vögelin et al. (2018 , 2019) found that lexical features and spelling influenced not only holistic teacher judgments of students’ writing in English as a second or foreign language, but also their assessment of other analytical criteria (e.g., grammar). Even though these studies do not consider text length as a potential source of bias, they do show that construct-irrelevant aspects influence judgments of teachers.

This Research

Against this research background, it remains essential to investigate whether the relation between essay length and text quality represents a true relationship or a bias on the part of the rater or teacher ( Wolfe et al., 2016 ). First, findings of correlational studies can give us an indication of the effect of text length on human ratings above and beyond language proficiency variables. Second, going beyond correlational findings, there is a need for experimental research that examines essay responses on the same topic differing only in length in order to establish causal relationships ( Kobrin et al., 2007 ). The present research brings together both of these approaches.

This paper comprises two studies investigating the role of essay length in foreign language assessment using an interdisciplinary perspective including the fields of foreign language education, computer linguistics, educational research, and psychometrics. Study 1 presents a secondary analysis of a large-scale dataset with N = 2,722 upper secondary school students in Germany and Switzerland who wrote essays in response to “independent writing” prompts of the internet-based Test of English as a Foreign Language (TOEFL iBT). It investigates the question of how several indicators of students’ English proficiency (English grade, reading and listening comprehension, self-concept) are related to the length of their essays (word count). It further investigates whether or not essay length accounts for variance in text quality scores (expert ratings) even when controlling for English language proficiency and other variables (e.g., country, gender, cognitive ability). A weak relationship of proficiency and length as well as a large proportion of variance in text quality explained by length beyond proficiency would be in favor of the judgment bias assumption.

Study 2 focused on possible essay length bias in an experimental setting, investigating the effect of essay length on text quality ratings when there was (per design) no relation between essay length and text quality score. Essays from Study 1 were rated by N = 84 untrained pre-service teachers, using the same TOEFL iBT rubric as the expert raters. As text quality scores were held constant within all essay length conditions, any significant effect of essay length would indicate a judgment bias. Both studies are described in more detail in the following sections.

This study investigates the question of judgment bias assumption vs. appropriate heuristic assumption in a large-scale context with professional human raters. A weak relationship between text length and language proficiency would be indicative of the former assumption, whereas a strong relationship would support the latter. Moreover, if the impact of text length on human ratings was significant and substantial beyond language proficiency, this might indicate a bias on the part of the rater rather than an appropriate heuristic. Thus, Study 1 aims to answer the following research questions:

(1) How is essay length related to language proficiency?
(2) Does text length still account for variance in text quality when English language proficiency is statistically controlled for?

Materials and Methods

Sample and procedure.

The sample consisted of N = 2,722 upper secondary students (11th grade; 58.1% female) in Germany ( n = 894) and Switzerland ( n = 1828) from the interdisciplinary and international research project Measuring English Writing at Secondary Level (MEWS; for an overview see Keller et al., 2020 ). The target population were students attending the academic track of general education grammar schools (ISCED level 3a) in the German federal state Schleswig-Holstein as well as in seven Swiss cantons (Aargau, Basel Stadt, Basel Land, Luzern, St. Gallen, Schwyz, Zurich). In a repeated-measures design, students were assessed at the beginning (T1: August/September 2016; M age = 17.34; SD age = 0.87) and at the end of the school year (T2: May/June 2017; M age = 18.04; SD age = 0.87). The students completed computer-based tests on writing, reading and listening skills, as well as general cognitive ability. Furthermore, they completed a questionnaire measuring background variables and individual characteristics.

Writing prompt

All students answered two independent and two integrated essay writing prompts of the internet-based Test of English as a Foreign Language (TOEFL iBT ® ) that is administered by the Educational Testing Service (ETS) in Princeton. The task instruction was as follows: “In the writing task below you will find a question on a controversial topic. Answer the question in an essay in English. List arguments and counter-arguments, explain them and finally make it clear what your own opinion on the topic is. Your text will be judged on different qualities. These include the presentation of your ideas, the organization of the essay and the linguistic quality and accuracy. You have 30 min to do this. Try to use all of this time as much as possible.” This task instruction was followed by the essay prompt. The maximum writing time was 30 min according to the official TOEFL iBT ® assessment procedure. The essays were scored by trained human raters on the TOEFL 6-point rating scale at ETS. In addition to two human ratings per essay, ETS also provided scores from their automated essay scoring system (e-rater ® ; Burstein et al., 2013 ). For a more detailed description of the scoring procedure and the writing prompts see Rupp et al. (2019) and Keller et al. (2020) . For the purpose of this study, we selected the student responses to the TOEFL iBT independent writing prompt “Teachers,” which showed good measurement qualities (see Rupp et al., 2019 ). Taken together, data collections at T1 and T2 yielded N = 2,389 valid written responses to the following prompt: “A teacher’s ability to relate well with students is more important than excellent knowledge of the subject being taught.”

Text quality and length

The rating of text quality via human and machine scoring was done by ETS. All essays were scored by highly experienced human raters on the operational holistic TOEFL iBT rubric from 0 to 5 ( Chodorow and Burstein, 2004 ). Essays were scored high if they were well-organized and individual ideas were well-developed, if they used specific examples and support to express learners’ opinion on the subject, and if the English language was used accurately to express learners’ ideas. Essays were assigned a score of 0 if they were written in another language, were generally incomprehensible, or if no text was entered.

Each essay received independent ratings by two trained human raters. If the two ratings showed a deviation of 1, the mean of the two scores was used; if they showed a deviation of 2 or more, a third rater (adjudicator) was consulted. Inter-rater agreement, as measured by quadratic weighted kappa (QWK), was satisfying for the prompt “Teachers” at both time points (QWK = 0.67; Hayes and Hatch, 1999 ; see Rupp et al., 2019 for further details). The mean text quality score was M = 3.35 ( SD = 0.72).

Word count was used to measure the length of the essays. The number of words was calculated by the e-Rater scoring engine. The mean word count was M = 311.19 ( SD = 81.91) and the number of words ranged from 41 to 727. We used the number of words rather than other measures of text length (e.g., number of letters) as it is the measure which is most frequently used in the literature: 9 out of 10 studies in the research review by Powers (2005) used word count as the criterion (also see Kobrin et al., 2007 , 2011 ; Crossley and McNamara, 2009 ; Barkaoui, 2010 ; Attali, 2016 ; Wolfe et al., 2016 ; Wind et al., 2017 ). This approach ensures that our analyses can be compared with previous research.

English language proficiency and control variables

Proficiency was operationalized by a combination of different variables: English grade, English writing self-concept, reading and listening comprehension in English. The listening and reading skills were measured with a subset of items from the German National Assessment ( Köller et al., 2010 ). The tasks require a detailed understanding of long, complex reading and listening texts including idiomatic expressions and different linguistic registers. The tests consisted of a total of 133 items for reading, and 118 items for listening that were administered in a multi-matrix-design. Each student was assessed with two rotated 15-min blocks per domain. Item parameters were estimated using longitudinal multidimensional two-parameter item response models in M plus version 8 ( Muthén and Muthén, 1998–2012 ). Student abilities were estimated using 15 plausible values (PVs) per person. The PV reliabilities were 0.92 (T1) and 0.76 (T2) for reading comprehension, and 0.85 (T1) and 0.72 (T2) for listening comprehension. For a more detailed description of the scaling procedure see Köller et al. (2019) .

General cognitive ability was assessed at T1 using the subtests on figural reasoning (N2; 25 items) and on verbal reasoning (V3; 20 items) of the Cognitive Ability Test (KFT 4–12 + R; Heller and Perleth, 2000 ). For each scale 15 PVs were drawn in a two-dimensional item response model. For the purpose of this study, the two PVs were combined to 15 overall PV scores with a reliability of 0.86.

The English writing self-concept was measured with a scale consisting of five items (e.g., “I have always been good at writing in English”; Eccles and Wigfield, 2002 ; Trautwein et al., 2012 ; α = 0.90). Furthermore, country (Germany = 0/Switzerland = 1), gender (male = 0/female = 1) and time of measurement (T1 = 0; T2 = 1) were used as control variables.

Statistical Analyses

All analyses were conducted in M plus version 8 ( Muthén and Muthén, 1998–2012 ) based on the 15PV data sets using robust maximum likelihood estimation to account for a hierarchical data structure (i.e., students clustered in classes; type = complex). Full-information maximum likelihood was used to estimate missing values in background variables. Due to the use of 15PVs, all analyses were run 15 times and then averaged (see Rubin, 1987 ).

Confirmatory factor analysis was used to specify a latent proficiency factor. All four proficiency variables showed substantial loadings in a single-factor measurement model (English grade: 0.67; writing self-concept: 0.73; reading comprehension: 0.42; listening comprehension: 0.51). As reading and listening comprehension were measured within the same assessment framework and could thus be expected to share mutual variance beyond the latent factor, their residuals were allowed to correlate. The analyses yielded an acceptable model fit: χ 2 (1) = 3.65, p = 0.06; CFI = 0.998, RMSEA = 0.031, SRMR = 0.006.

The relationship between text length and other independent variables was explored with correlational analysis. Multiple regression analysis with latent and manifest predictors was used to investigate the relations between text length, proficiency, and text quality.

The correlation of the latent proficiency factor and text length (word count) was moderately positive: r = 0.36, p < 0.01. This indicates that more proficient students tended to write longer texts. Significant correlations with other variables showed that students tended to write longer texts at T1 ( r = -0.08, p < 0.01), girls wrote longer texts than boys ( r = 0.11, p < 0.01), and higher cognitive ability was associated with longer texts ( r = 0.07, p < 0.01). However, all of these correlations were very weak as a general rule. The association of country and text length was not statistically significant ( r = -0.06, p = 0.10).

Table 1 presents the results of the multiple linear regression of text quality on text length, proficiency and control variables. The analysis showed that proficiency and the covariates alone explained 38 percent of the variance in text quality ratings, with the latent proficiency factor being by far the strongest predictor (Model 1). The effect of text length on the text quality score was equally strong when including the control variables but not proficiency in the model (Model 2). When both the latent proficiency factor and text length were entered into the regression model (Model 3), the coefficient of text length was reduced but remained significant and substantial, explaining an additional 24% of the variance (ΔR 2 = 0.24 from Model 1 to Model 3). Thus, text length had an incremental effect on text quality beyond a latent English language proficiency factor.

Linear regression of text quality on text length, English language proficiency, and control variables: standardized regression coefficients (β) and standard errors (SE).

Study 1 approached the issue of text length by operationalizing the construct of English language proficiency and investigating how it affects the relationship of text length and text quality. This can give us an idea of how text length may influence human judgments even though it is not considered relevant to the construct of writing competence. These secondary analyses of an existing large-scale dataset yielded two central findings: First, text length was only moderately associated with language proficiency. Second, text length strongly influenced writing performance beyond proficiency. Thus, it had an impact on the assigned score that was not captured by the construct of proficiency. These findings could be interpreted in favor of the judgment bias assumption as text length may include both construct-irrelevant and construct-relevant information.

The strengths of this study were the large sample of essays on the same topic and the vast amount of background information that was collected on the student writers (proficiency and control variables). However, there were three major limitations: First, the proficiency construct captured different aspects of English language competence (reading and listening comprehension, writing self-concept, grade), but that operationalization was not comprehensive. Thus, the additional variance explained by text length may still have been due to other aspects that could not be included in the analyses as they were not in the data. Further research with a similar design (primary or secondary analyses) should use additional variables such as grammar/vocabulary knowledge or writing performance in the first language.

The second limitation was the correlational design, which does not allow a causal investigation of the effect of text length on text quality ratings. Drawing inferences which are causal in nature would require an experimental environment in which, for example, text quality is kept constant for texts of different lengths. For that reason, Study 2 was conducted exactly in such a research design.

Last but not least, the question of transferability of these findings remains open. Going beyond standardized large-scale assessment, interdisciplinary research requires us to look at the issue from different perspectives. Findings pertaining to professional raters may not be transferable to teachers, who are required to assess students’ writing in a classroom context. Thus, Study 2 drew on a sample of preservice English teachers and took a closer look at how their ratings were impacted by text length.

Research Questions

In Study 2, we investigated the judgment bias assumption vs. the appropriate heuristic assumption of preservice teachers. As recommended by Powers (2005) , we conducted an experimental study in addition to the correlational design used in Study 1. As text quality scores were held constant within all essay length conditions, any significant effect of essay length would be in favor of the judgment bias assumption. The objective of this study was to answer the following research questions:

(1) How do ratings of pre-service teachers correspond to expert ratings?
(2) Is there an effect of text length on the text quality ratings of preservice English teachers, when there is (per design) no relation between text length and text quality (main effect)?
(3) Does the effect differ for different levels of writing performance (interaction effect)?

Participants and Procedure

The experiment was conducted with N = 84 pre-service teachers ( M Age = 23 years; 80% female), currently enrolled in a higher education teacher training program at a university in Northern Germany. They had no prior rating experience of this type of learner texts. The experiment was administered with the Student Inventory ASSET ( Jansen et al., 2019 ), an online tool to assess students’ texts within an experimental environment. Participants were asked to rate essays from the MEWS project (see Study 1) on the holistic rubric used by the human raters at ETS (0–5; https://www.ets.org/s/toefl/pdf/toefl_writing_rubrics.pdf ). Every participant had to rate 9 out of 45 essays in randomized order, representing all possible combinations of text quality and text length. Before the rating process began, participants were given information about essay writing in the context of the MEWS study (school type; school year; students’ average age; instructional text) and they were presented the TOEFL writing rubric as the basis for their judgments. They had 15 min to get an overview of all nine texts before they were asked to rate each text on the rubric. Throughout the rating process, they were allowed to highlight parts of the texts.

The operationalization of text quality and text length as categorical variables as well as the procedure of selecting an appropriate essay sample for the study is explained in the following.

Text Length and Text Quality

The essays used in the experiment were selected on the basis of the following procedure, which took both text quality and text length as independent variables into account. The first independent variable of the essay (overall text quality) was operationalized via scores assigned by two trained human raters from ETS on a holistic six-point scale (0–5; see Study 1 and Appendix A). In order to measure the variable as precisely as possible, we only included essays for which both human raters had assigned the same score, resulting in a sample of N = 1,333 essays. As a result, three gradations of text quality were considered in the current study: lower quality (score 2), medium quality (score 3) and higher quality (score 4). The corpus included only few texts (10.4%) with the extreme scores of 0, 1, and 5; these were therefore excluded from the essay pool. We thus realized a 3 × 3 factorial within-subjects design. The second independent variable text length was measured via the word count of the essays, calculated by the e-rater (c) scoring engine. As with text quality, this variable was subdivided in three levels: rather short texts (s), medium-length texts (m), and long texts (l). All available texts were analyzed regarding their word count distribution. Severe outliers were excluded. The remaining N = 1308 essays were split in three even groups: the lower (=261 words), middle (262–318 words) and upper third (=319 words). Table 2 shows the distribution of essays for the resulting combinations of text length and text score.

Distribution of essays in the sample contingent on text quality and text length groupings.

Selection of Essays

For each text length group (s, m, and l), the mean word count across all three score groups was calculated. Then, the score group (2, 3, or 4) with the smallest number of essays in a text length group was taken as reference (e.g., n = 22 short texts of high quality or n = 15 long texts of low quality). Within each text length group, the five essays being – word count-wise – closest to the mean of the reference were chosen for the study. This was possible with mostly no or only minor deviations. In case of multiple possible matches, the essay was selected at random. This selection procedure resulted in a total sample of 45 essays, with five essays for each combination of score group (2, 3, 4) and length group (s, m, l).

A repeated-measures ANOVA with two independent variables (text quality and text length) was conducted to test the two main effects and their interaction on participants’ ratings (see Table 3 ). Essay ratings were treated as a within-subject factor, accounting for dependencies of the ratings nested within raters. The main effect of text quality scores on participants’ ratings showed significant differences between the three text quality conditions ( low , medium , high ) that corresponded to expert ratings; F (2, 82) = 209.04, p < 0.001, d = 4.52. There was also a significant main effect for the three essay length conditions ( short , medium , long ); F (2, 82) = 9.14, p < 0.001, d = 0.94. Contrary to expectations, essay length was negatively related to participants’ ratings, meaning that shorter texts received higher scores than longer texts. The interaction of text quality and text length also had a significant effect; F (4, 80) = 3.93, p < 0.01, d = 0.89. Post-hoc tests revealed that texts of low quality were especially impacted by essay length in a negative way (see Figure 1 ).

Participants’ ratings of text quality: means (M) and standard deviations (SD).

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Visualization of the interaction between text length and text quality.

The experiment conducted in Study 2 found a very strong significant main effect for text quality, indicating a high correspondence of pre-service teachers’ ratings with the expert ratings of text quality. The main effect of text length was also significant, but was qualified by a significant interaction effect text quality x text length, indicating that low quality texts were rated even more negative the longer they were. This negative effect of text length was contrary to expectations: The pre-service teachers generally tended to assign higher scores to shorter texts. Thus, they seemed to value shorter texts over longer texts. However, this was mainly true for texts of low quality.

These findings were surprising against the research background that would suggest that longer texts are typically associated with higher scores of text quality, particularly in the context of second language writing. Therefore, it is even more important to discuss the limitations of the design before interpreting the results: First, the sample included relatively inexperienced pre-service teachers. Further research is needed to show whether these findings are transferable to in-service teachers with reasonable experience in judging students’ writing. Moreover, further studies could use assessment rubrics that teachers are more familiar with, such as the CEFR ( Council of Europe, 2001 ; also see Fleckenstein et al., 2020 ). Second, the selection process of essays may have reduced the ecological validity of the experiment. As there were only few long texts of low quality and few short texts of high quality in the actual sample (see Table 2 ), the selection of texts in the experimental design was – to some degree – artificial. This could also have influenced the frame of reference for the pre-service teachers as the distribution of the nine texts was different from what one would find naturally in an EFL classroom. Third, the most important limitation of this study is the question of the reference norm, a point which applies to studies of writing assessment in general. In our study, writing quality was operationalized using expert ratings, which have been shown to be influenced by text length in many investigations as well as in Study 1. If the expert ratings are biased themselves, the findings of this study may also be interpreted as pre-service teachers (unlike expert raters) not showing a text length bias at all: shorter texts should receive higher scores than longer ones if the quality assigned by the expert raters is held constant. We discuss these issues concerning the reference norm in more detail in the next section.

All three limitations may have affected ratings in a way that could have reinforced a negative effect of text length on text quality ratings. However, as research on the effect of text length on teachers’ judgments is scarce, we should consider the possibility that the effect is actually different from the (positive) one typically found for professional human raters. There are a number of reasons to assume differences in the rating processes that are discussed in more detail in the following section. Furthermore, we will discuss what this means in terms of the validity of the gold standard in writing assessment.

General Discussion

Combining the results of both studies, we have reason to assume that (a) text length induces judgment bias and (b) the effect of text length largely depends on the rater and/or the rating context. More specifically, the findings of the two studies can be summarized as follows: Professional human raters tend to reward longer texts beyond the relationship of text length and proficiency. Compared to this standard, inexperienced EFL teachers tend to undervalue text length, meaning that they sanction longer texts especially when text quality is low. This in turn may be based on an implicit expectation deeply ingrained in the minds of many EFL teachers: that writing in a foreign language is primarily about avoiding mistakes, and that longer texts typically contain more of them than shorter ones ( Keller, 2016 ). Preservice teachers might be particularly afflicted with this view of writing as they would have experienced it as learners up-close and personal, not too long ago. Both findings point toward the judgment bias assumption, but with opposite directions. These seemingly contradictory findings lead to interesting and novel research questions – both in the field of standardized writing assessment and in the field of teachers’ diagnostic competence.

Only if we take professional human ratings as reliable benchmark scores can we infer that teachers’ ratings are biased (in a negative way). If we consider professional human ratings to be biased themselves (in a positive way), then the preservice teachers’ judgments might appear to be unbiased. However, it would be implausible to assume that inexperienced teachers’ judgments are less biased than those of highly trained expert raters. Even if professional human ratings are flawed themselves, they are the best possible measure of writing quality, serving as a reference even for NLP tools ( Crossley, 2020 ). It thus makes much more sense to consider the positive impact of text length on professional human ratings – at least to a degree – an appropriate heuristic. This means that teachers’ judgments would generally benefit from applying the same heuristic when assessing students’ writing, as long as it does not become a bias.

In his literature review, Crossley (2020) sees the nature of the writing task to be among the central limitations when it comes to generalizing findings in the context of writing assessment. Written responses to standardized tests (such as the TOEFL) may produce linguistic features that differ from writing samples produced in the classroom or in other, more authentic writing environments. Moreover, linguistic differences may also occur depending on a writing sample being timed or untimed. Timed samples provide fewer opportunities for planning, revising, and development of ideas as compared to untimed samples, where students are more likely to plan, reflect, and revise their writing. These differences may surface in timed writing in such a way that it would be less cohesive and less complex both lexically and syntactically.

In the present research, such differences may account for the finding that pre-service teachers undervalue text length compared to professional raters. Even though the participants in Study 2 were informed about the context in which the writing samples were collected, they may have underestimated the challenges of a timed writing task in an unfamiliar format. In the context of their own classrooms, students rarely have strict time limitations when working on complex writing tasks. If they do, in an exam consisting of an argumentative essay, for example, it is usually closer to 90 min than to 30 min (at least in the case of the German pre-service teachers who participated in this study). Thus, text length may not be a good indicator of writing quality in the classroom. On the contrary, professional raters may value length as a construct-relevant feature of writing quality in a timed task, for example as an indicator of writing fluency (see Peng et al., 2020 ).

Furthermore, text length as a criterion of quality cannot be generalized over different text types at random. The genres which are taught in EFL courses, or assessed in EFL exams, differ considerably with respect to expected length. In five paragraph essays, for example, developing an argument requires a certain scope and attention to detail, so that text length is a highly salient feature for overall text quality. The same might not be true for e-mail writing, a genre frequently taught in EFL classrooms ( Fleckenstein et al., in press ). E-mails are usually expected to be concise and to the point, so that longer texts might seem prolix, or rambling. Such task-specific demands need to be taken into account when it comes to interpreting our findings. The professional raters employed in our study were schooled extensively for rating five-paragraph essays, which included a keen appreciation of text length as a salient criterion of text quality. The same might not be said of classroom teachers, who encounter a much wider range of genres in their everyday teaching and might therefore be less inclined to consider text length as a relevant feature. Further research should consider different writing tasks in order to investigate whether text length is particularly important to the genre of the argumentative essay.

Our results underscore the importance of considering whether or not text length should be taken into account for different contexts of writing assessment. This holds true for classroom assessment, where teachers should make their expectations regarding text length explicit, as well as future studies with professional raters. Crossley (2020) draws attention to the transdisciplinary perspective of the field as a source for complications: “The complications arise from the interdisciplinary nature of this type of research which often combines writing, linguistics, statistics, and computer science fields. With so many fields involved, it is often easy to overlook confounding factors” (p. 428). The present research shows how the answer to one and the same research question – How does text length influence human judgment? – can be very different from different perspectives and within different areas of educational research. Depending on the population (professional raters vs. pre-service teachers) and the methodology (correlational analysis vs. experimental design), our findings illustrate a broad range of possible investigations and outcomes. Thus, it is a paramount example of why interdisciplinary research in education is not only desirable but imperative. Without an interdisciplinary approach, our view of the text length effect would be uni-dimensional and fragmentary. Only the combination of different perspectives and methods can live up to the demands of a complex issue such as writing assessment, identify research gaps, and challenge research traditions. Further research is needed to investigate the determinants of the strength and the direction of the bias. It is necessary to take a closer look at the rating processes of (untrained) teachers and (trained) raters, respectively, in order to investigate similarities and differences. Research pertaining to judgment heuristics/biases can be relevant for both teacher and rater training. However, the individual concerns and characteristics of the two groups need to be taken into account. This could be done, for example, by directly comparing the two groups in an experimental study. Both in teacher education and in text assessment studies, we should have a vigorous discussion about how appropriate heuristics of expert raters can find their way into the training of novice teachers and inexperienced raters in an effort to reduce judgement bias.

Data Availability Statement

Ethics statement.

The studies involving human participants were reviewed and approved by the Ministry of Education, Science and Cultural Affairs of the German federal state Schleswig-Holstein. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.

Author Contributions

JF analyzed the data and wrote the manuscript. TJ and JM collected the experimental data for Study 2 and supported the data analysis. SK and OK provided the dataset for Study 1. TJ, JM, SK, and OK provided feedback on the manuscript. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Value of Knowledge by Erik J. Olsson LAST REVIEWED: 26 August 2013 LAST MODIFIED: 26 August 2013 DOI: 10.1093/obo/9780195396577-0008

The Psychology and Philosophy of Imagination

7.2 Knowledge

Plato and the Traditional Account of Knowledge

Problems with the Traditional Account of Knowledge

Dharmakīrti’s Mirage

Russell’s Case

Fake Barn Country

Fixing Plato’s Traditional Account of Knowledge

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Ruling Out Defeaters and Alternatives

The Problem with Justification

6 The Value and Importance of Knowledge

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Knowledge How

1.1 The Contemplation Argument

9.1 Skill Across Cultures

4. The Linguistic Argument

6. The Epistemology of Knowledge-How

7. The Argument from Cognitive Science

8. Varieties of Anti-Intellectualism

8.3 Radical Anti-Intellectualism: Practicalism

9. Knowledge-How and Skill

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Table of contents

What Are Skills?

Types Of Skills

1. Technical Skills

2. Interpersonal Skills

3. Cognitive Skills

4. Creative Skills

What Is Knowledge?

Types Of Knowledge

1. Explicit Knowledge

2. Tacit Knowledge

3. Procedural Knowledge

4. Declarative Knowledge

Skill Vs Knowledge: The Difference Between Skill And Knowledge

1. Definition And Nature

2. Acquisition

3. Application

4. Interplay And Importance

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