Justified True Belief - an overview | ScienceDirect Topics

Justified True Belief
The Gettier problem is a special case in philosophy in which an agent ends up having a justified true belief about a given situation (e.g., they believe an object to be where it actually is) despite lacking information relevant to actually knowing about what they believe (e.g., they were unaware that the object was moved several times beforehand).
3.3 The Gettier challenge
Gettier [1963] pointed out examples that effectively jettisoned the justified true belief analysis of knowledge. The ensuing discussions are central to modern epistemology. For an overview of the area, see, e.g., Steup [Spring 2006].
Perhaps the easiest related example in epistemic logic is the following. Consider a muddy children scenario with two children, say A and B. A is muddy and B clean. A parent announces that at least one is muddy, asks if the two know their state. Usually, A would announce affirmatively and B negatively, but this time let A lie and say that she does not; B of course truthfully replies that he doesn't know. Then on second round, both announce that they do know. The point is, that B's announcement is truthful: taking knowledge to be justifiable true belief, he will have some knowledge of his state after hearing A once, no matter what she says. B's announcement is also justified, being based on A's first declaration. At that point, B has a justified true belief that he knows his state. But we would not judge B to actually know whether he is dirty or not. This would mean either knowing that he is dirty, or knowing that he is clean: he thinks he knows the former and denies he knows the latter.
Philosophy
Epistemic-doxastic logic is a somewhat austere account of qualitative information. But ever since its birth, it has triggered discussions in philosophical epistemology. It was soon found that the universal quantifier in information as range provides a rather poor analysis of knowledge in the philosopher's demanding sense, where the quest for a satisfactory definition of knowing that P involves finding the right sort of ‘robustness’ in addition to the obvious features of truth of P and belief in P. Plato famously proposed ‘justified true belief, but sophisticated new definitions have kept appearing until today, such as Dretske's ‘true belief grounded in correct information’, or Nozick's ‘true belief with counterfactual tracking: if P had been false, we would have believed that ¬P'. Even though epistemic logic has never offered a definition of knowledge of comparable sophistication, the very mismatch with the richer philosophical tradition has been much more exciting than many happy marriages, leading to clarification and fruitful debate. For instance, the distribution axiom K(ϕ → ψ) → (Kϕ → Kψ) has sparked debates about Logical Omniscience, and the axiom Kϕ → KKϕ about Positive Introspection. We refer the reader to [Hendricks, 2006; Williamson, 2000; van Benthem, 2006a; Baltag et al., 2007] for a wide array of interface topics, such as definitions of knowledge, skeptical arguments (see also Dretske's chapter in this Handbook), different sources of information (language, senses, etc.), omniscience, bounded rationality, and reflection.11
Framing the question
Many analyses of the scholarly communication system focus on the what and the how of communication but rarely the why. Understanding the why is locked up in the sociology and psychology of human discovery: how can I establish that I discovered something first, how sure can I be that my claims will be accepted, and how do I prevent others stealing my ideas and passing them off as their own? These issues lie at the heart of answering our first question. But aspects of this sit even deeper, embedded in the DNA of what it means to say something is knowledge.
In Plato’s epistemological formulation, knowledge is justified true belief, that is to say, I can only assert that a belief (an observation if you will) is knowledge if it can be justified and it turns out to be true. In philosophy of science, experimental results are observed (the collection of beliefs), they are put together to create theories that might explain them (justification) and are subsequently tested by further observation to see if they are true. In this context the scientific method is an epistemological engine generating knowledge out of observation.
This philosophical structure is also embedded in the evolved system of scholarly communication. An investigator reports on his or her observations (beliefs), relates them to the existing literature and the tests he or she conducts (the justification) and has them tested by external critical comment by peer reviewers (the test of truth). Of course this is only partially correct as the truth of the hypothesis is rarely contained or proved by a single experiment or paper reporting it. For the whole body of work in a field, however, the analogy is apt and I believe goes some way to explaining the essential conservatism of how academic work is reported. Albeit dimly, investigators know they have to demonstrate that what they saw once in their apparatus on a wet Wednesday is true everywhere for everyone for all time. For science, the status of knowledge is insufficient: that knowledge must be objective, seen by all. In Ziman’s phrase, science is public knowledge (Ziman, 1968).
6.2 Misadventures of the Classical View
Philosophical analysis has fallen on hard times. The “Classical View” of concepts on which it was based, according to which concepts have necessary and sufficient “defining” conditions discoverable by a priori reflection alone is widely thought to have been refuted simply by the failure to provide any convincing examples. Socrates and Plato famously sought to extract some from a method of dialectical exchange with fellow Athenians, and occasionally some plausible examples emerged, most famously, an analysis of knowledge as “justified true belief,”2 and then the famous definitions of arithmetic and geometric notions that emerged with Euclid.
In the modern era, traditional empiricists like Locke and Hume took up a suggestion already in Plato whereby ideas were claimed to be derived from sense impressions, a suggestion that the Logical Positivists of the first half of the 20th century combined with the then newly developed formal logic to undertake precise “reductions” of concepts to sensorimotor ones. Such reductions were linked to the Positivists’ strong “verificationist theory of meaning,” which Quine (1953b) and Putnam (1962/1975) subsequently pointed out was seriously at odds with good scientific practice. Quine notoriously pressed the point even further, arguing that there was no basis in any empirically establishable fact for any distinction between “analytic” claims, true somehow solely by “analysis,” and “synthetic” ones, that depended also upon facts about the world. This skepticism coincided with Wittgenstein’s (1953/2009:§66ff) independent observations of the fact that people don’t seem to have available to them analyses of most of the ordinary concepts they are competent to use, but seem to know merely about ordinary usage and “family resemblances” among exemplars, a proposal that spawned several decades of research by psychologists on “prototype” and “exemplar” theories of concepts that came to be regarded as alternatives to the Classical View.3
Things seemed to take an even more surprising turn when Putnam (1965, 1975) and Kripke (1972/80) pointed to how the analyses of “kind” terms and concepts, like [water] or [polio], seemed not to be of the a priori “conceptual” kind philosophers might provide, but might emerge from empirical research in the relevant domain.2 Even if there were something like classical definitions, they might not always be found by traditional “armchair” analyses alone.
Most recently, Fodor (1998, 2003) has argued that belief in any kind of analytic, conceptual connections sought in the Classical View is where cognitive science—and indeed the whole of the 20th century—“went wrong,” and he joined particularly Putnam, Burge, and others in advocating an “externalist” theory, whereby the content of a concept is constituted not by any role internal to a thinker, but by the worldly phenomenon to which it bears some real causal relation (Section 6.4 below).
That’s a lot of opposition to the Classical View that I’ll be undertaking to oppose. Despite all this misery for the Classical View, the theme I want to pursue here is that much of it is unwarranted, arising from confusions about what the proper role of conceptual analyses were supposed to be, and from burdening that role with conceptions of the project of analysis that were not only needless, but independently bad ideas. I think there are still good reasons to believe in something like classical analyses, even if philosophy may have to turn to cognitive science to discover them—as will cognitive science should have to turn to some of that traditional philosophy to benefit from at least some of the strategies it employed.
One thing that should be stressed from the start is a feature central to philosophy, but often disregarded in cognitive science, and that is the crucial role in the Classical View of a thinker’s competence to make modal judgments with the concept: what she thinks would satisfy a concept in various actual and counterfactual circumstances, and related facts about what she finds intelligible. These may not always easy facts to ascertain,4 but, where there are such facts, the existence of “analytic” connections that might explain them is not in the least undermined by the failure of verificationism, the superficial unavailability of analyses, or people’s exploitation of prototypes. Whether or not someone reasons prototypically, if on reflection she didn’t find the possibility of, say, a female doctor in a black coat even intelligible, but as unintelligible as “married bachelor” or “round square,” that would be a reason to think she didn’t really have the concept [doctor]—that “doctor” for her meant may be [typical American TV doctor]. This role for concepts in people’s thought seems to me to be related to one of the main advantages of conceptual ascription in the first place: it identifies what agents can understand, and how their attitudes might in principle be modifiable by evidence and argument, abstracting semantic issues from the epistemic ones with which they are too often conflated. More colloquially: it factors out the “merely verbal” issues from the genuinely substantive ones.
An Externalist like Fodor, however, might argue that questions of modality and intelligibility are questions a person settles not by consulting meaning-constituting analyses, but simply by learning a good theory of the actual phenomenon in the world to which a concept refers. Although, for reasons we will explore in Sections 6.3 and 6.4, this option can seem plausible in the case of concepts that do genuinely refer, it is obviously problematic for empty concepts, or concepts that don’t refer to any real, or even genuinely possible phenomenon in the world, e.g., [ghost], [demon], [bogeyman], [triangle], [phlogiston], and the like. And, as we shall see in Section 6.4, empty concepts are by no means confined to fairy tales and bad science: they may be a crucial part of our normal, successful interaction with the world. Brentano (1874/1973) went so far as to argue that they were a distinctive mark of the mental! I’ll argue in Section 6.5 that a psychology of such concepts, and of the rich mental and behavioral processes to which they give rise, requires something at least very like the analyses that the Classical View sought.
On the other hand, there is no question that many philosophers and psychologists have underestimated the difficulty of producing these analyses. For all my belief in analyses, I take quite seriously the skeptical challenges that have been raised against them. Consequently, in my remarks here I want to engage in a rather delicate dialectical balancing act: on the one hand, urging the need for philosophical analysis in any cognitive psychology, particularly one treating empty concepts; but, on the other hand, drawing attention to the formidable problems of providing any—but also, in this update, a proposal about some recent work offers a promising strategy as to how to proceed. All this, at any rate, ought to provide some idea of how the topic presently stands in philosophy.
6 Technological Knowledge as Tacit
Using ideas and notions developed by Michael Polanyi [1958; 1966], some authors have emphasized the importance of tacit knowledge in engineering and technol-ogy.19 They have argued, or stated, that part of the knowledge produced by technological practice is hard or even impossible to make fully explicit in declarative statements, but can only be acquired through personal experience. Some make tacitness part of their characterization of technological knowledge, e.g.: “(…) the knowledge of techniques, methods and designs that work in certain ways and with certain consequences, even when one cannot explain exactly why.” [Rosenberg, 1982, p. 143] Others use technological practice to characterize tacit knowledge, e.g.: “(…) the implicit, wordless, pictureless knowledge essential to engineering judgement and workers’, skills.” [Vincenti, 1990, p. 198]
This emphasis on tacit knowledge is not exclusive to the philosophy of technology. In fact, most work on tacit knowledge and technology is done outside of philosophy. One field where this relation is especially prominent is that of knowledge management, where the communication and sharing of knowledge is a central concern (e.g., [Nonaka and Takeuchi, 1995; Choo, 1998; Baumard, 1999; Firestone and McElroy, 2003]). Other fields where tacit knowledge is an important point of concern are the design of expert systems (e.g., [Berry, 1987]) and studies of technological innovations and technology transfer (e.g., [Nooteboom et al., 1992; Senker, 1993; Howells, 1996; Leonard & Sensiper, 1998; Nightingale, 1998; Wong and Radcliffe, 2000; Salter & Gann, 2003]). Here, the appeal to tacit knowledge is typically used to indicate the firm-specificity and person-dependence of knowledge. It is stressed, for instance, that successful implementation of new technologies requires detailed and specific knowledge about a particular situation, which is — at least at first — only available through personal experience and rules of thumb (e.g., [Arora, 1996]). Other authors point out that, although codified and explicit knowledge is available for more established technologies, effective use still relies on skilled operators and maintenance personnel, arguably showing that there is an irreducibly tacit component in technological knowledge (e.g., [Noble, 1978]).
That many contributions to the literature on technological knowledge appeal to tacitness is beyond question; moreover, most do so by pointing out that it has been generally overlooked, because of an exclusive focus on codified knowledge, and that it is essential to a full account of knowledge. Thus, the existing literature seems based on the idea that there is something distinctive about tacit knowledge, and perhaps also something distinctively tacit about technological knowledge. This makes the appeal to tacit knowledge potentially interesting for the epistemic-emancipation project. Yet to see how and to what extent the appeal to tacit knowledge could improve our understanding of the nature of technological knowledge, and emancipate it from scientific knowledge, two questions need to be answered. Firstly: what is the relation between tacit and technological knowledge? Secondly: is the tacitness of technological knowledge more prominent or encompassing than that of other types of knowledge?
Insofar as these questions have (implicitly) been answered in the literature, the answer to the crucial second question appears to be negative. Let us tackle them each in turn.
Virtually everyone who writes on tacit knowledge, even those who do not ultimately use the term, agrees about one conceptual issue — that there is something about human knowledge that standard, justified-true-belief or propositional, accounts do not capture. Beyond this stage, however, there is considerable disunity about the appropriate concepts, concerning both the phenomenon of “tacitness” and the standard view(s) with which it supposedly contrasts. At least three distinctions are at issue in the literature. These distinctions are related, but different, and they are seldom distinguished as carefully as they should be. Firstly, there is, what might be called, the psychological distinction between implicit and explicit knowledge (e.g., [Dienes and Perner, 1999]; see also [Reber, 1993]).20 One way to phrase this distinction is as follows: when we know a fact, we have an accurate representation of it. On the basis of its functioning and its accuracy, this representation may be identified as “knowledge” (rather than a desire). If we are not aware of this representation, and its accuracy, the knowledge is implicit. By contrast, our knowledge concerning this representation is fully explicit. Phrased in this way, the psychological distinction is gradual, and all distinguished states involve representations. Secondly, there is a grammatical or linguistic distinction between two types of statements involving ‘knowing’: knowing that something is the case, and knowing how something can be done. This distinction is, of course, primarily associated with work by Gilbert Ryle [1949], and it is clearly language-relative. In some languages, like German and Dutch, this distinction is expressed by means of similar-sounding words (“kennen’, as in ‘Ich kenne Der Zauberberg nicht‘; and ‘können’, as in ‘Ich kann Schlittschuhlaufen’, respectively) rather than one word; other languages may even use completely different words. Thirdly, types of knowledge may be distinguished social-epistemically, with regard to their communicability: knowledge that can be transferred exclusively through verbal communication, and knowledge that is not or cannot be so transferred — for instance, because it can only be acquired through personal experience. I will call the first type ‘verbal’, knowledge, and the second ‘non-verbal’.
When introduced, the term “tacit knowledge” is typically used in the latter sense. However, the interconnections with Ryle's primarily grammatical distinction are particularly strong in the philosophical literature, so that the actual use of “tacit knowledge” is at least ambiguous in this respect. Even authors who do not explicitly refer to Ryle often use terminology reminiscent of his, and refer to the same stock examples, e.g., of riding a bicycle. Furthermore, connections are forged with the (folk-) psychological distinction between knowledge and skills. This is frequently equated with Ryle's distinction, and “tacit knowledge” is taken to refer to skills and “know-how”. Much more may be said about this, but I will cut some corners in calling this distinction a red herring. The reason is that, as soon as the unicity and autonomy of technological knowledge is sought by assimilating it to skills, the epistemic-emancipation project becomes open to the objection that it is based on a category mistake. After all, if skills are contrasted with knowledge, and the difference between technology and science is based on this contrast, the sought (and perhaps found) difference cannot be epistemological: it is not a distinction between types of knowledge, but between knowledge and something else, e.g., action.
Thus, the frequent appeals to tacitness, and discussions of this phenomenon with regard to technology, suffer from multiple ambiguities in the very notion of “tacit knowledge”, which affect its usefulness for the epistemic-emancipation project.
One may think that, while these ambiguities are being sorted out, a preliminary epistemological distinction may be made between fully explicit, propositional, verbal knowledge on the one hand, and the overlooked “tacitness” phenomenon on the other hand. This would, however, be naive, since a major epistemological distinction is concealed beneath the conceptual distinctions.21
One possible understanding of tacit knowledge is as a supplement of the traditionally analyzed body of propositional knowledge. The associations with Ryle's sharp grammatical distinction, and with the knowledge-skill distinction facilitate this understanding. From a psychological perspective, this understanding is highly problematic: one may think up all kinds of cognitive processes that share characteristics of both types of knowledge, undermining the idea of supplementary, but autonomous bodies of knowledge. The internalization of calculation rules is, for instance, a process that shows how explicit, and highly verbalized procedures can turn into implicit routines through frequent exercise. This does not mean that the distinction is conceptually indefensible, but it does not have the immediate plausibility of Polanyi's original appeal to tacitness. Moreover, this understanding has the disadvantage of inviting the category-mistake objection mentioned above: if tacit knowledge is this skill-based supplement to propositional knowledge, why call it “knowledge” at all?
Therefore, some psychologists — and researchers in other disciplines who take psychological studies into account — prefer another understanding of the appeal to tacitness (e.g., [Wagner, 1987]). On it, our body of knowledge contains a tacit element, in all senses distinguished above: explicit knowledge must be based on implicit knowledge, which is at least conceptually prior; knowledge-that always involves knowing-how, since it involves, among other things, competence in reasoning; and verbal knowledge presupposes non-verbal knowledge, if only in the trivial sense that we cannot make fully explicit our speech patterns, including rules for appropriate utterances and other pragmatic aspects of language. Some passages in the writings of both Ryle and Polanyi suggest this understanding of tacitness — as a general aspect, component or ‘dimension’, of knowledge. And although this view requires substantial elaboration, it does not have the above-mentioned disadvantages of the first understanding. Gradualism can be captured by analyzing knowledge as having a more or less prominent tacit component; and since tacitness is an integral part of all knowledge, it is an appropriate subject for epistemology.
This understanding of tacit knowledge answers the two questions posed earlier. Firstly, technological knowledge may be said to have a strong relation to tacit-ness. Both the knowledge possessed by designers and that possessed by users, and even the more theoretical models of engineering sciences involve a tacit component. Indeed, some examples in the general literature on tacit knowledge, such as Ryle's bicycle riding, are derived from the technological domain broadly conceived (albeit mainly from the user's perspective); and both design and use are clearly competence-based activities, easily described in terms of knowing-how. That they also involve knowing-that, and can in various degrees be verbalized does not run counter to the appeal to tacitness in this sense.22
However, on this understanding of tacitness, there is almost by definition no special relation between it and technological knowledge. If the arguments of Ryle and Polanyi are sound, they would show that all knowledge contains a tacit component. And their general arguments have been supported by a host of more specific studies in cognitive psychology (e.g., [Reber, 1993]) and the epistemology of science. Like engineers, scientists are said to rely on rules of thumb in designing experiments and interpreting data, and to require personal experience in addition to theoretical education (e.g., [Collins, 1973, 1982; Senker, 1993; Sternberg and Horvath, 1999]). The works of Donald Schön [1983; 1988] also illustrate this generality. Some of Schön's examples are drawn from domains that might be called technological; and he often phrases his general claims by referring to “technical” problems or “design” contexts.23 Yet Schön's claims regarding the importance of personal experience and improvisation concern professional practice in general, not engineering design in particular.
In sum, the literature on tacitness in technological knowledge shows a lack of conceptual clarity. Furthermore, insofar as clarity can be obtained, appealing to tacitness does not further the end of epistemic emancipation. Instead, it increases the burden of proof resting on those who want to establish emancipation through pointing out the role of tacit knowledge in technology: rather than showing that such knowledge plays a role, they should show that it plays a distinctive role.
5.2 The analytic data
The analogy with grammar seems to me quite close. As with grammar, we are confronted by regularities that need to be explained. In the kinds of cases that the analytic is supposed to explain, these include, inter alia, a non-negligible convergence in people's judgments with regard to particular concepts and/or lexical items, e.g., about synonymies, ambiguities, antinomies, entailments13. Ask speakers whether “bank,” or “pride” are ambiguous; whether “killings” necessarily involve “dyings;” whether “open” and “closed” are antonyms; whether “Jim boiled the water” implies “The water boiled;” whether “The square-root of a shadow is red” is anomalous. Ask people what things qualify as a bachelor, knowledge, coercion, a voluntary act, perception, water, and brisket; elicit their considered judgments about hypothetical cases; ask them what they think constitutes being one of these things: I submit that one finds what philosophers have found since Socrates, that there is great deal of convergence about what clearly does and what clearly does not satisfy a concept, and that, although people cannot readily provide adequate rules or definitions to capture these patterns, they soon realize they cannot, and, despite disagreement, are quick to acknowledge at least the cogency of each others' cases and considerations. Whether or not they call them “analytic,” or are even justified in thinking in these ways, people do seem to have analytic intuitions, which I call “the analytic data,” leaving it open whether it is to be explained by an actual analytic.
Alas, however these analytic intuitions are a lot more slippery and elusive than the lovely examples of bad grammar. The history of philosophy is filled with purported analyses by one generation that have been refuted with counterexamples from the next: there is an entire sub-industry that has been devoted for some time to analyzing “x knows that p,” still without success [see, e.g., Morton (1997)].
Many of the difficulties in providing analyses, however, could be taken as actually an argument for, not against, the project of trying to find them, or something like them (it is a little like the combination of success and failure in science that argues for realism about its objects: we get enough success to think we are on to something, and enough failure to think that it is not all wishful thinking either). For what is it that leads us to reject proposed analyses? Why do we tend to agree about plausible candidates and also about their inadequacies? What do many of us know about “know” that leads us to fall for “justified true belief” and then to appreciate Gettier's (1963) counterexamples14? Or, what do we know about gods and ghosts to know that they had better have minds? Or, what do we know about [MURDER] and [PERSON] such that we understand why, for example, abortion and euthanasia are difficult cases? That is to say, we should ask here exactly the question that Chomsky (2000) asked about syntax: What explains the patterns and projections in peoples' judgments?
An interesting case in point is Fodor's (1981) rejection of any analysis of “painttr” (the transitive verb). He proposes and rejects a number of plausible proposed analyses, ending with:
(P) x painttr y iff x is an agent and x intentionally covers the surface of y with paintn and x's primary intention in covering the surface of y with paint is that the surface of y should be covered with paintn in consequence of x's having so acted upon it.
—Fodor (1981, p. 287)
Fodor (1981, p. 288) then raises still a further counterexample of Michelangelo dipping his brush into the paint, and so satisfying (P), but presumably not thereby “painting his brush.” At this point, Fodor concludes:
I don't know where we go from here. For all I know – for all anybody knows – 'painttr' is undefinable; for all I know, you can't eliminate it even in terms of such a closely related term as 'paintn'. Or perhaps it is definable, but only in a reduction base that includes 'dinosaur' and 'Chlorodent'. Either way, the present point is that [standard examples] don't work. That's not surprising; when it comes to definitions, the examples always don't work.
—Fodor (1981, p. 288, emphasis his)
Now, first of all, it seems to me odd that Fodor breaks things off at this point -just when things are getting interesting! Several lines of continuation suggest themselves – specifying a still more detailed intention, restricting the scope of an analysis and allowing for pragmatic variation in how “painttr” is understood in a context, perhaps understanding analyses as constitutive default rules, to be overridden in certain circumstances15. But this is not the place to take up any of these suggestions. My points are methodological:
(i)
How and why do we so readily see the plausibility of (P) and the cogency of Fodor's further example? Is it really because (à la Quine) we have such a good empirical theory of the activity of painting? Could this be refuted by discovering that 6 out of 10 painters do paint their brushes? Does anyone care whether Michelangelo was painting his brush – apart from their grasp of the meaning of painttr? and
(ii)
Why do we think uncovering the analysis of an item – determining either the primitives or the analysis – ought to be easy? Why do we not presume it will be at least as difficult as uncovering the principles of grammar?
In any case, being undefinable is hardly the natural conclusion to draw from the series of increasingly plausible analyses Fodor considered. We do seem to be converging on something, but, unsurprisingly, are maybe missing some subtle resources.16
Principle #7—Motivational evidence can only answer certain questions
Although the famous philosopher Karl Popper (1963) proclaimed that “there are no ultimate sources of knowledge” (p. 54), some sources of knowledge are, indeed, more reliable than others. First, knowledge can originate through individual experience; nevertheless, this type of knowledge is usually biased and limited in scope. Personal knowledge is filtered through the mind of the beholder, is frequently subjective, and cannot be duplicated by others under similar circumstances. Second, knowledge can be based upon cultural tradition; however, traditional knowledge is potentially flawed, as it is largely based upon collective experience and, in essence, resembles personal knowledge in that it lacks veracity of origin or replication. Third, knowledge can be authority based and predicated upon the power of the knowledge originator. Dictated knowledge is typically transient and self-serving to meet the needs of the entity initiating the knowledge, as evidenced by the goal of race annihilation at the whims of ruthless dictators throughout history. Fourth, the source of knowledge most relevant for the scientific study of motivation is described as “justified” knowledge. Justification implies that the knowledge will survive empirical scrutiny, it can be replicated under controlled conditions, and, if true, the knowledge can be analyzed and applied without bias or subjectivity.
Most definitions of knowledge include three important components: truth, belief, and evidence (Southerland, Sinatra, & Matthews, 2001). A prerequisite to verify truth is the ability to evaluate a belief rationally against an external and objective evidentiary standard. A personal belief, sometimes called a proposition, is the conviction that a set of rules, evaluations, or circumstances are assumed to be true (Southerland et al., 2001). Evidence is information gathered and evaluated objectively and systematically. The evidence can be replicated and verified while ruling out other plausible interpretations. If the evidence is subjective or cannot be externally verified, we describe the belief as unjustified (Sinatra & Seyranian, in press), lacking sufficient substance to classify the evidence as knowledge. If sufficient evidence is gathered, and other plausible explanations can be ruled out, we warrant the evidence as knowledge with explanatory power, otherwise known as a justified true belief (Gettier, 1963).
Sometimes providing learners with concrete evidence helps clarify the distinction between knowledge and beliefs. One important principle of cognition is the realization that humans have information processing limitations. Students usually acknowledge that there are restrictions to the amount of information they can hold in their heads at any one time; this restriction is known as working memory capacity. If you have ever tried to remember someone’s phone number while also being asked directions, you will quickly realize the limitations of your working memory. When I teach, I ask students to turn off their cell phones and refrain from texting during class. Invariably, some learners do not heed my warning and text anyway. Fortunately, my warning has sinister intentions and results in a fantastic teaching opportunity when someone texts in class. Typically, when caught texting, learners quickly affirm, contrary to most scientific evidence, that they have the unique ability to multi-task and usually swear they can text and pay attention simultaneously. The first question I ask after students make this resounding proclamation about multi-tasking is, “How do you know?” Typically, learners proceed to recount various examples of personal experience, indicating how they believe they can complete multiple tasks simultaneously. Multi-tasking, however, is one of many “urban legends” in education (Kirschner & van Merrienboer, 2013, p. 169) that is quickly dispelled by evidence. To make my point, I merely ask the student to recite the alphabet using a normal speaking pace and write the letters of the alphabet simultaneously. The outcome is usually unintelligible writing, or an alphabet recital that resembles a geriatric moose signaling its mate. This strategy usually does the trick and changes their beliefs about multi-tasking because learners fail at the task (go ahead, try it yourself, and then see if you can lick your elbow). Typically, the results from these amusing scenarios show that working memory is limited and that personal experience has limited explanatory power. This teaching scenario easily launches a discussion of what questions can be answered by scientific inquiry, while driving home the distinction between justified knowledge and beliefs.
Once future MDs realize the power of belief-bias, they are then able to successfully address the need for scientific inquiry as the source of knowledge. Although there is little consensus on the perfect process to conduct scientific inquiry (Shermer, 2002), most experimental regimens include making predictions, gathering evidence, analyzing data, and reaching plausible inferences about what the data means, while ruling out plausible rival hypotheses. By using systematic data collection and interpretation, knowledge is warranted, or certified, and defensible on methodological grounds, avoiding conclusions based upon perception, opinion, or conjecture. In other words, how knowledge is attained and disseminated will, in part, determine the validity of the knowledge.
The premise of fallibility dictates that knowledge is transient and always subject to revision (Phillips & Burbules, 2000). Justified knowledge must have the ability to be falsified by disconfirming evidence. Knowledge without contradiction has little explanatory power because it is stagnant. A stagnant theory cannot evolve by experimentation, nor can it be debunked. The pink elephant dilemma may convince you of the necessity of my fallibility contention. Most justified knowledge about elephants universally describes the animals as large, gray, sometimes tusked mammals with big floppy ears, equipped with a long proboscis designed to extract peanuts from small children, tourists, and the palms of zoologists. My elephant hypothesis suggests that pink polka dot elephants may exist but have yet to be discovered. My hypothesis is contrary to the justified knowledge that elephants only come in 50 shades of gray. Today, my outlandish idea is only an unjustified belief because no pink polka dot elephants have ever been observed. But is my hypothesis false? Does this mean no polka dot elephants exist? Surely, it is possible that one day we will discover pink polka dot elephants. Perhaps, our visually acuity is insufficient for us to see the polka dots that are already there. Thus, the theory of gray elephants can potentially be falsified and subsequently evolve. Today, we can rule out other plausible interpretations of the elephant data and reasonably infer that all elephants are, indeed, shades of gray, until an alternative hue of pachyderm is unearthed. Knowing that my theory is viable and testable, all the knowledge from the theory is warranted with explanatory power.
Now, we have illuminated the three foundational premises necessary to evaluate scientific inferences. Recapping, we should first verify the source of the knowledge; next, we must determine if the knowledge is justified or not; and finally, we should closely examine whether or not our inquiry can meet the falsification test. If these three criteria are met, we can confidently proceed and determine what questions can or cannot be answered by motivational science. Table 2.1 describes actual inquiries meeting the three principles of inquiry, along with some provocative situations that we shall encounter as we elaborate on the scientific evidence that explains motivation for learning and performance throughout the remainder of the book.
Table 2.1. Examples of what questions motivational science can and cannot answer
Inquiries motivational science CAN answer
Source
Inquiries motivational science CANNOT answer
Can we predict if mentally preoccupied people prefer cake or fruit?
Shiv and Fedorikhin (2002)
Does cake taste better than fruit?
Do monetary rewards lead to less effective work performance?
Ariely, Gneezy, Loewenstein, and Mazar (2005)
Do professional athletes prefer higher earnings or fame?
Can biological evidence substantiate evolution?
Geary (2008)
Were our distant relatives apes?
Do future teachers believe in zombies and ghosts?
Losh and Nzekwe (2010)
Are zombies and ghosts real?
Do people make better decisions when angry or calm?
Moons and Mackie (2007)
Are angry people more likely to commit suicide?
Can certain written words promote happiness in others?
Kloumann, Danforth, Harris, Bliss, and Dodds (2012)
Is this the best book about motivation ever written?
The answer to every question in the left-hand column of Table 2.1 is “yes.” Although you may debate the veracity of these findings based upon your own personal beliefs, each finding is supported by objective evidence warranting a justified knowledge conclusion. The studies cited all used rigorous scientific methods to rule out alternative explanations before reaching conclusions. Although the answers to all of the questions are affirmative, we should be cautious not to generalize these findings beyond the scope of the research question. The answers are warranted only for the specific situation described. The questions in the right-hand column of the table represent questions that cannot be answered through scientific inquiry. Answers to these questions are largely subjective (cake or fruit), unethical to investigate (anger and suicide), or impossible to measure using existing research methods (ancestry). Cognizant of the unique evaluation criteria needed to evaluate motivational research, we turn to the evidence and see precisely what practical inferences can be confidently made.