Importance of Educology for Improving Education Systems

Theodore W. Frick

doi:10.1007/978-3-319-17727-4_92-1

Learning, Design, and Technology pp 1-50 | Cite as

Importance of Educology for Improving Education Systems

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Theodore W. Frick

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First Online: 05 December 2019

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Abstract

Educology is “knowledge of education.” Since knowledge is “recorded signs of knowing” and education is “intended and guided learning,” educology is therefore “recorded signs of knowing about intended and guided learning.” Knowledge of education systems is also part of educology. Distinctions are made in educology among terms that include education, education system, learning, knowing, signs, and knowledge. Precisely defined terms are required for educology to advance, much as has been done in disciplines such as physics, biology, physiology, and anatomy. If we are to improve education systems, then we must create worthwhile education. Worthwhile education is defined in educology as “education that is both instrumentally good and intrinsically good.”

Note that italics font is specifically used in this chapter to identify terms that are defined precisely in educology. Formal definitions of terms in educology are enclosed in double quotation marks. Appendix A “Defined and Undefined Terms in Educology” includes a list of basic terms and their definitions.

Keywords

Educology Knowledge Education Education system Learning Knowing Signs Theory Universals Terminology Definitions Effective education Worthwhile education

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Appendix A: Defined and Undefined Terms in Educology

Definitions of Basic Terms

In order to explicate theory, it is necessary to define terms. Steiner (1988) states it this way:

… when one sets forth the terms of the theory and their definitions, descriptive metaphysics is presented…. Descriptive metaphysics is a division of the phenomena which are the object of theorizing—the system—so that a set of descriptors characterizing the systems properties emerges. To do this, the metaphysician must provide a set of class terms for characterizing each and every component of the system…. Therefore, classification is basic to descriptive metaphysics.
However, classification always involves definition. A class term denotes all the particulars to which the term is applicable (the extension of the term) and connotes the characteristics that a particular must have in order for the term to be applicable to it (the intension of the term). (Steiner, 1988, p. 64, italics added)

Steiner provides criteria for evaluating descriptive theory: exactness, exclusivity, exhaustiveness, external coherence, extendibility, equivalence, chaining, and substitution (pp. 64–74). Descriptive theory is necessary for building a foundation before explanatory theory can be explicated.

Fundamental to educology are the following defined terms (=_Df is read as is defined as):

Mental structures = _Df affect-relations which constitute intelligence.
Learning = _Df increasing of complexity of a person’s mental structure (for Types 1–12).
Learner = _Df person whose volition is learning.
Forgetting = _Df decreasing of complexity of a person’s mental structure.

These and other terms are defined at http://educology.indiana.edu. This website provides definitions of these terms and more. It is easier to follow the chains of definitions on the website by clicking on the hyperlinks. Words in this chapter which are italicized and underlined are defined elsewhere by Thompson (2019) and in the ATIS Glossary at https://aptac.sitehost.iu.edu/glossary/ (e.g., affect-relations, complexity, system).

I have been discussing mental structure above, and now I must be more precise. I take some definitions here from general system theory, and in particular, Axiomatic Theories of Intentional Systems (Thompson, 2006a, b, 2008, 2019). Affect-relations are the connections among components of a system, and complexity is the number of strong connections. Thus, learning is defined as increasing the number of connections in a one’s mental structure. This is consistent with what Kandel (1989) has concluded on a biological level, claiming that long-term memory is “associated with growth in synaptic connections [among neurons]” (p. 115) and that “learning produces enduring changes in structure and function of synapses” (p. 121, italics added). Mental structures can be formed for right and wrong opinions, for effective, ineffective, ethical and unethical conduct, and for true or false beliefs.

The biological explanation of changes in the human nervous system is not part of educology. Educology asserts that humans form mental structures as they learn. To use Steiner’s criterion, there is external coherence. This definition of learning in educology has external coherence with neurobiological knowledge.

Undefined Terms

Some terms in a theory must remain undefined (Steiner, 1988). Definitions could go on ad infinitum if there are no primitive terms. This is to avoid circularity in definitions, as well as infinite regress. Undefined terms follow: intelligence, think, feel, intend, believe, perceive, guide, person, good, object (thing), course of action (conduct), and end (goal).

More Definitions of Terms in Educology

The domain of human learning is shown as a Venn diagram in Fig. 1, which illustrates defined terms that include intended learning, guided learning, education, effective education, and worthwhile education. Figures 2 through 14 illustrate via shadings in the Venn diagram how these terms are related but yet distinct.

Accidental learning = _Df learning which is neither guided nor intended (see Fig. 2)
Discovery learning = _Df learning which is intended but unguided (see Fig. 9)
Compelled learning = _Df learning which is not intended but guided (see Fig. 11)
Conducive learning = _Df education = _Df learning which is both intended and guided (see Fig. 5)
Student = _Df a person who intends to learn content with a teacher
Teacher = _Df a person who intends to guide another person’s learning
Teaching = _Df a teacher guiding another person’s learning (see Fig. 3)
Sign = _Df representamen = _Df “something which stands to somebody for something in some respect or capacity…. every representamen being thus connected with three things, the ground, the object, and the interpretant” (see Peirce, 1932, 2.228)
- Interpretant = _Df a sign derived by a person as a mental construct that is a representamen of the equivalent external sign, which relates to an object
Content = _Df objects and signs of objects selected for student learning
Context = _Df system environment of teacher and student that contains content
Education system = _Df intentional system consisting of at least one teacher and one student in a context
Knowing = _Df mental structures which consist of warranted beliefs, right opinions, and capabilities for performance (see Fig. 17)
- Knowing that one: mental structures for right opinion about Q, the object of knowing.
  Recognitive: select the unique Q from not-Q and not-Q from Q.
  Acquaintive: identify relations determinate of the unique Q.
  Appreciative: identify relations appropriate of the unique Q.
- Knowing how: mental structures for effective performance.
  Protocolic: take one path to goal.
  Adaptive: take alternative paths to goal, choosing or combining paths based on specific conditions.
  Creative: innovate or invent a new way to reach an existing or new goal.
- Knowing that: mental structures for beliefs warranted by disciplined inquiry.
  Instantial: classification of objects of the same kind
  Relational: rational explanation of relationships between kinds of objects
  Criterial: rational judgment of kinds of objects and their relations according to a norm
Knowledge = _Df recorded knowing = _Df preservation of signs that represent what is known in some medium external to knower
Disciplined inquiry = _Df rigorous research = _Df learning which is regulated by criteria for creating scientific, praxiological, and philosophical knowledge. (See Fig. 10.
Instrumentally good = _Df means that are good for an end (goal)
- Means = _Df course of action, a way to reach an end (goal)
Intrinsically good = _Df means or ends that are good in themselves, not with respect to their instrumental goodness
Effective education =_Df education that is instrumentally good (Steiner, 1988, pp. 16–17) (see Fig. 6.)
Effective bad education = _Df education that is instrumentally good but not intrinsically good (see Fig. 13.)
Worthwhile education = _Df education that is both instrumentally and intrinsically good (Steiner, 1988, p. 17) (see Fig. 8.)
Totally integrated education = _Df education that results in student completely-connected knowing, intention and emotion. See Frick (2018)

Appendix B: Examples of Kinds of Knowing

Knowing That One

Let us use the symbol Q to represent an object and a subscript to index each unique object. For example, in Fig. 16, let us use Q₁ as a further sign for representing the screen-porch-built-by-Ted-in-1993, Q₂ represents the unique person Theodora, and Q₃ represents the unique person Miguel. How can we tell if someone can recognize Q₁, that is, knows-that-one-Q₁? According to Maccia (1987), the cognition is of “none other.” To recognize Q₁, requires that it be discerned from all else. To select Q₁ from not- Q₁, and to select not- Q₁ from Q₁, is to recognize Q₁.

Recognitive Knowing That One

Recognition is a fundamental cognitive act. It is required for identification of each unique object. It is the cognitive act that is required of a witness in a court of law who is asked to identify the defendant as the one the witness observed to commit the crime. The witness on the stand is asked by the lawyer to select Q_i from all else, where Q_i is that-one unique individual. When the selection is correct or accurate, we say that a person has right opinion.

Plato made this distinction between right opinion and true opinion in Theaetetus. According to Maccia (1987):

Right opinion was described [by Plato] as the direct apprehension of things. True opinion was described as conception which was justified by definition or classification. In leading Theaetetus to see that right opinion was not equivalent to true opinion, Socrates had him conclude that it was impossible to distinguish Socrates or Theodorus from any other snub-nosed person by means of definition or classification. He brought Theaetetus to agree that he and Theaetetus would recognize each other when they met next at the Agora (p. 213).

True opinion is knowing that, whereas right opinion is knowing that one. True opinion requires description, whereas recognition does not. Maccia (1986) explains further:

Shared attributes enable comparisons of class membership of things, thereby enabling definitions. Through definitions we come to “know that” to have true beliefs about the relations of things. We have an explanation.
Characteristic attributes, on the other hand, are incomparable. Such attributes locate the betweenness of things. We come to know “that-one,” not an instance of a kind. One can argue about the adequacy of a definition, but one can only acknowledge a unique. If you know it, you have the right opinion of its identity as an existent (pp. 5–6).

Such acknowledgment depends on experience, which is affected by what Peirce (1932) called sinsigns.

A Sinsign (where the syllable sin is taken as meaning “being only once,” as in single, simple, Latin semel, etc.) is an actual existent thing or event which is a sign. It can only be so through its qualities… (2:245).

Sinsigns are the basis of experience. Peirce described experience this way (1931):

We perceive objects brought before us; but that which we especially experience—the kind of thing to which the word “experience” is more particularly applied—is an event…. It is the compulsion, the absolute constraint upon us to think otherwise than we have been thinking that constitutes experience (1:336, italics added).

Maccia (1986) further clarified Peirce’s category of “Secondness,” which distinguishes sinsigns from qualisigns:

Such compulsion is termed by Peirce, “Secondness.” Secondness is force by “brute action.” The brute action of secondness results in facts. Brute facts that is. Such facts are …. immediate. They are right now. Brute facts mark identity and existence. They characterize the single one (p. 6).

Dewey (1916) was referring to the same idea as experience and how it can affect our thinking, as discussed in section “Need for Systems Theory and Education Theory in Educology” above.

Peirce’s and Maccia’s notion of experience is less restrictive than Dewey’s, since events can happen that are not our doing – e.g., a strong gust of wind blows sand in our eyes. Nonetheless, it is the experience, the brute fact, that which compels us “to think otherwise than we have been thinking.”

In another report, Maccia (1987) further explicates knowing that one:

Recognition will be described as selection through marking the non-comparable features of a thing. Exemplification of recognition will be drawn from studies in perception and pattern recognition. Acquaintance will be described as mapping unique relations connecting components of an entity. I shall draw from studies in forensic art and topography. Appreciation will be described as a discernment of the fittingness of unique relations connecting constituents of an entity. In exemplifying appreciation, I shall employ modes of judgment for determining authenticity of objects or events (pp. 213–214, italics added).

Acquaintive Knowing That One

Experience, if it is to be grounded, requires immediate perception of the object. Returning to Fig. 16, if you the reader have never been physically inside or near Ted’s screened porch, then your experience lacks grounding. You may observe the symbolic signs of the unique persons represented in Fig. 16 (i.e., their names: Theodora and Miguel), but you would not know that one Q₂ or Q₃. Unless you had met them before, you would pass right by Theodora or Miguel on the street without recognizing either of them. Moreover, you would not be acquainted with them. You would not know that Miguel is a software engineer and appreciates listening to live performances of the Chicago Symphony Orchestra. You would not know that Theodora enjoys Cypriot and modern dancing and is a talented graphic artist.

Acquaintive knowing that one requires more than recognition. Acquaintance requires identification of relationships that determine the uniqueness of Q_i – relationships that set Q_i apart from all else, which makes it unique. For example, if you were acquainted with the unique screened porch represented in Fig. 16 and also depicted in photographs at https://tedfrick.sitehost.iu.edu/screenporch/, you might notice the particular picture window pattern of sections, and that it was built inside and under an existing awning with steel supports embellished with a leaf pattern. You might notice that wind chime hangs in the center section on the west side, but you would not know that it was a gift from friends who brought it back from a trip to South America and consisted of slices of a particular rock crystal from Uruguay. Nor would you know the way that particular wind chime sounded, as it twisted in the breeze. You might not have noticed in one of the photos the tall tulip tree behind the vegetable garden to the west silhouetted in the sunset. Nonetheless, this writer has been well-acquainted with that-one screened porch and its immediate surroundings. When you visit this location after July, 2011, you might notice that the screened porch which is now there is not that-one-screened-porch-built-by-Ted-in-1993. If you knew the unique original screened porch, you would recognize that the one now there is not that-one-originally-built-by-Ted that is shown in the photographs at https://tedfrick.sitehost.iu.edu/screenporch/.

Appreciative Knowing That One

Appreciation requires more than recognition and acquaintance. Appreciation requires qualitative judgment as did a colleague when initially sitting inside the screened porch. He had a spontaneous “aha moment” when looking out: “Now I get it! You designed it [the screen porch] this way so we can see the backyard and garden better.” His acknowledgment indicated his appreciation of the picture window design element of this particular screened porch. See Fig. 15.

Appreciative knowing that one means mental structures to identify relationships which are appropriate of Q_i – a valuation of what is special and fitting about Q_i. When a connoisseur identifies the special qualities of a particular wine after smelling its bouquet and tasting it, this is a further example. She might indicate this by saying, “Ah, this is a superb wine!” This would be a sign of appreciation of that-one-wine.

Another example of appreciation occurred during a usability test of a particular software product by a person who said, “This is awful! Do you expect students to use this?” Appreciation does not have to be positive. Clearly, from the frustrating experience of trying to use that product, this parent of a college student was literally disgusted with the poor quality of the product her son would have to use in school.

In summary, knowing that one requires right opinion of the unique object. To have right opinion requires at minimum recognition of that unique object. Recognition, in turn, is necessary for acquaintance; and acquaintance is necessary for appreciation. When the experience of the object is immediate, then such knowing is literally grounded. The relation between the sign and the object represented by the sign is clearly evident to the person who knows-that-one.

Knowing How

In considering knowing how, it is important to note here that no distinction is being made between mind and body. Knowing how is a kind of cognition as is knowing that one and knowing that. Knowing how consists of mental structures for effective conduct.

As with the other kinds of cognition, we cannot observe a mental structure for knowing how directly, but we must infer it by observing the person carry out successfully some task which requires the knowing how to do so. Thus, we must look for indicators or signs of such knowing how.

For example, we cannot tell if Miguel has the capability to write software in Java by somehow peering into his mind. We could ask him if he has this capability, and his response would be an indicator. We could design a task for him to do in Java and then observe how well he does it. Or we might use other indicators, such as examining Java source code he wrote on the job as a software engineer.

Protocolic Knowing How

For protocolic knowing how, a person follows one path to reach the goal, by duplicating or reproducing the way in which someone else has done it. Protocolic knowing how is inflexible. A person’s capability to follow a recipe in cook book to prepare food is an example of protocolic knowing how. Another example would be to carry out data analysis by mimicking the step-by-step procedure listed in a statistics textbook, such as performing an ANOVA (analysis of variance).

Estep (2006) refers to this kind of knowing how as rule-governed (see p. 226 and 263) in which single-pathed doings are contrasted with rule-bound ones which are multi-pathed. Maccia (1988) referred to the former as protocolic knowing how and the latter as conventional.

Adaptive Knowing How

In adaptive knowing how, a person can achieve a goal through alternative existing paths, not just one path as in protocolic knowing how. Because there are multiple paths, and more than one way to accomplish the goal, this is flexible knowing how. Moreover, one chooses paths based on the specific conditions encountered when the person does evidence it through performance. Thus, such knowing how is adaptive. Estep (2006) referred to this kind of knowing as rule-bound, and Maccia (1988) called it conventional knowing how.

From an educational perspective, an important criterion for assessing achievement of adaptive knowing how is sometimes described as transfer of learning. That is, if one has achieved adaptive knowing how, then she or he can transfer the knowing how to new situations and perform successfully. When this kind of knowing how is done at a very high level of complexity, it is exemplified by what surgeons, airline pilots, and chess players do as experts. They are able to adapt their doing, according to the specifics of a given situation. They are very good at reaching their goal across a wide range of conditions because they are flexible. Their knowing how is highly adaptive. It is clearly more than imitation of someone else’s doing. They may take a specific combination of pathways that no one else has ever done before. Such capability is not merely a reproduction of a fixed way of doing something, although at least one pathway will be a strict imitation. Protocolic knowing is necessary for adaptive knowing. But adaptive knowing now is more in that it is evidenced by multiple paths to a goal, and different paths are chosen based on specific conditions.

Creative Knowing How

Creative knowing how is evidenced by innovating or inventing a new way of doing – a new way to reach the same goal, or even a new goal itself – breaking new ground, so to speak. In medical surgery, for example, a new way of repairing injuries to knee joints via use of an arthroscopic device was developed. At one point, such a surgical method did not exist. Instead of making a large incision to get to the location of the injury, a small incision is made into which such a device is threaded. In contrast to open surgery, it is a remote method of performing the operation, which does less damage to surrounding tissue, results in faster patient recoveries, etc. This is evidence of creative knowing how – arthroscopic knee surgery.

As different example, the Wright brothers invented a new way for manned flight. Instead of trying to make a machine that flapped its wings in imitation of how birds fly, they employed the idea of propelling a plane through the air that had stationary airfoils as wings.

Clearly, creative knowing how is not protocolic, and it is more than adapting existing ways of doing. While the examples above are well recognized because of subsequent widespread adoption, such adoption or success is not a requirement for creative knowing how, rather it can be a by-product. The products of creative knowing how have often been important for the advancement of civilization and culture.

Creative knowing how is also evidenced by devising a new end or goal. It is not reproducing something that already exists, but what results is something new that did not exist before. When Einstein developed the special theory of relativity, this was a new theory. When Frank Lloyd Wright designed the Fallingwater house in Mill Run, Pennsylvania, this was a new architectural design. When the Diffusion Simulation Game was originally designed as a multiplayer board game, it was a new way of learning about Rogers’ theory of diffusion of innovations (Molenda & Rice, 1979). The invention of the first spreadsheet program, VisiCalc, by Dan Bricklin and Bob Frankston is a further example of creative knowing how. The theory of relativity, Fallingwater house, the Diffusion Simulation Game, and VisiCalc were new when they were created – they did not exist before.

Creative knowing how is not restricted to invention of new methods or things – it can also result in new theories and new knowledge. Nor is creative knowing how restricted to the fine arts – such as making a new sculpture or new music composition. Practical arts can be creative, such as design of new structures in architecture, or new machines such as the iPad or the Airbus A380.

Once a new way of doing has been created, and then afterward when others follow the new way, or they reproduce the same goal, for these others, it would be protocolic knowing how. They could be taught the new method. For example, many surgeons learned the new arthroscopic method after it was initially invented and demonstrated to be practical and safe. It then became one more technique in their surgical repertoire. As another example, the invention of symbol systems (that we call language) is also evidence of creative knowing how. At one time, writing itself was a new way to signify experience. Once this new method of communicating was invented, others could then be taught to write using those symbols.

One might wonder what mental structures for creative knowing how might be or whether such structures are possible. TIE theory (Frick, 2018) posits that this is a kind of knowing how that requires both protocolic and adaptive knowing how, and yet creative knowing how is something more. A new means or a new end is created. To list a few well-known cases: Thomas Edison invented the light bulb, Charles Goodyear the vulcanization of rubber, the Wright brothers the airplane, Henry Ford the assembly line for mass production, Charles Babbage the first programmable computer, etc. The evidence that humans have this capability is a matter of historical record, and some of these creations or inventions have had major impacts on civilization and culture.

However, the result of creative knowing how does not have to be well-known nor necessarily unique. For example, when I designed and built the screen porch that was discussed above, it did not exist before. I did not follow a blueprint that someone else had created, which would have been protocolic knowing how. For me, the design was original. Somewhere there may be some other screened porch like this one that someone else has designed, and for him or her it could have been likewise creative knowing how.

Knowing That

Knowing that involves cognition of similarity or commonality among objects or things. Such discrimination of commonality (i.e., similar vs. not similar) was important from an evolutionary perspective. Survival often depended on making such discriminations – e.g., those who learned to comprehend the pattern of hurt or die from falling from a high place survived longer than those who ignorantly stepped off cliffs or jumped from trees. Early humans may not have had the same concepts of mass, velocity, and acceleration that Newton later formalized into his laws of gravity, but survival favored those who could predict the consequences of falling from high places and who avoided such falling. Survival also favored those who could further discriminate kinds of plants or fruits that were poisonous and avoided eating them. These are generalizations or knowing that as a “kind of” – i.e., it is classificatory.

The relatively modern game of charades exemplifies the challenge of signing knowing that without symbols – without being able to use words – before symbolic human languages were invented. Knowing that one and knowing how can be achieved without use of symbols. Indeed, other living beings can come to knowing that one and knowing how without using symbols. A dog or cat can recognize its owner and the place where they live (knowing that one). These animals exhibit knowing how, such as being able to find their way home. When a dog barks at the approach of an unrecognized stranger, that is an indexical sign. Some dogs and cats can signal intent to leave a residence by pawing at a door to the outside.

Instantial Knowing That

When we have an idea (concept) that is associated with more than one unique object of the same kind, then we are instantiating. For example, consider the notion of female. This idea can be used to classify individuals who fit the kind that is being signified.

Instantial knowing that requires discrimination and classification, which is a sorting of things into one kind or another according to common properties or characteristics. We make the classifications that Theodora is a female, while Miguel is not. We logically distinguish that-kind and not-that-kind when we classify instances.

One the other hand, if one can recognize Theodora, clearly being able to separate her from all else (as none-other, who is unique), this is knowing that one. Yet, at the same time, we can state a fact about her, which is instantial knowing that: Theodora is female. When we state such a fact and it is warranted, then this is a sign of knowing that about the instance, Theodora.

Peirce (1932) referred to symbolic signs that are used to represent classifications (in contrast to indexes and icons). Symbolic signs are legisigns (e.g., female, screened porch), which are used to represent classes of objects. Legisigns may differ according to language, such as Spanish, Greek, or Macedonian. Nonetheless, the same concept can be symbolized as a class for which objects of the same kind can be classified, and the cultural legisign is used to represent the class.

When we classify objects as instances, we no longer are treating each as unique. We often use the article, a, not the article, the, in English, when we achieve knowing that. When we refer to the screened-porch-built-by-Ted represented by the photo in Fig. 16, we use the article, the, to indicate the unique or particular, just as we would indicate the person whose name is Theodora. Whereas, when we refer to a screened porch, then we are treating the object as an instance of a class of objects of the same kind.

Relational Knowing That

For relational knowing that, more than instantial knowing that is required. One must know a kind of relationship between two or more classes of objects. Consider the screened porch example once again in Fig. 16. Theory about visible light was relevant to the window design within each panel. Some kinds of objects will allow visible light to pass through and others will not. Light will be blocked from passing through solid wood, but it does pass through fine, aluminum screen mesh. The fine screen mesh will allow light, wind, rain, and snow to mostly pass through this filter, whereas it will prevent mosquitoes and other larger things from entering. These theoretical relationships were considered in the structural design of the window. Several concepts have been mentioned, including visible light, window, aluminum screen, solid, wood, filter, mosquitoes, passing through, wind, rain, and snow. Each of these is a class which can be instantiated by many objects that can be sorted into these classes.

But there are relationships between these kinds of objects. For example, wind (moving air) passes through aluminum screen. Here the kind of relationship is passes through, and one kind of object is wind, and the other kind is aluminum screen.

Furthermore, there can be classes of classes. Aluminum screen is one kind of filter. Plexiglas is another type of filter. Filter is the superclass. In fact, superordinate is itself a type of relationship.

Generalizable relationships constitute the content of science, praxiology, and philosophy (Steiner, 1988). Scientific signs of knowing that are important for explaining and predicting phenomena, such as Einstein’s famous equation that symbolizes the relationship between matter, energy, and light (E = mc²). Praxiological signs of knowing that symbolizes relationships between means and ends, which are instrumentally good, such as the process of tempering steel in order to strengthen it. Philosophical signs of knowing that symbolizes general relationships which are intrinsically good, such as the ethical principle that human beings ought to treat each other with benevolence and justice.

Criterial Knowing That

Criterial knowing that requires instantial and relational knowing that but involves a norm beyond them so that judgment (evaluation) of such concepts and relations is possible. Meta-theoretical is another term that could be used for criterial knowing that where meta- means “beyond” or “transcends.” The judgment requires a standard that transcends the theory itself and its terms.

For example, logical truth is a standard or criterion. Suppose there are two assertions: “Theodora is a female” and “Theodora is a male.” If the categories of gender (male, female) are mutually exclusive, then both of the assertions cannot be rationally held at the same time without violating the notion of logical truth (P and not-P is logically false – i.e., either P is true or not-P is true, but not both).

Consider the proposition from the screened-porch example: “Wind passes through aluminum screen mesh.” This is a different kind of proposition in that is it not a fact about an individual object but instead about all objects in the classes involved – anywhere, anytime, and anyplace. Even if it is the case that wind passes through the screen on the porch that Ted built, this does not mean that this relationship will hold for all instances of wind and all instances of aluminum screen mesh.

What kinds of evidence would be needed to warrant the assertion about the general relationship between wind and aluminum screen? What criteria are needed to make such a judgment? For example, if the criterion empirically holds without exception and just one counterexample is discovered to exist, then the assertion is not warranted according to that criterion. In various scholarly disciplines (e.g., chemistry, physics, biology, anthropology, philosophy, etc.), there is considerable discussion about research methods and criteria that are appropriate for warranting claims. Such a discussion about research methodologies in disciplined inquiry is beyond the scope of this report.

Appendix C: Lose Weight? Or Decrease Fat Mass?

The following example from biochemistry illustrates the importance of precise terminology to describe what we are talking about and how the chemical factories in our body operate so we have energy to stay alive and to move around. As it is, this is a somewhat oversimplified explanation, but is nonetheless consistent with biochemistry in our bodies and how our hormones and enzymes regulate metabolism (McKinley et al., 2016).

According to estimates by the National Center for Health Statistics (2015), about 1 out of every 3 Americans 20 years or older is obese, and 2 out of 3 are overweight (Taubes, 2016). This problem is significant because people who are obese are more likely to develop type 2 diabetes and subsequently are predicted to be more likely to die from heart disease, stroke, and cancer. What can we do about this situation?

First, the problem is not that most Americans are overweight. We could ship them all to the moon, and they would weigh about one-sixth of what they now do on earth. That would work immediately but would not address the underlying problem.

More to the point is that too many individuals have an excessive mass of fat stored in their bodies. The problem is not solved by losing weight; rather the problem is solved by reducing excess mass of fat stored in our bodies. I am using italics here to identify well-defined terms.

So what is human fat? Technically, body fat is stored in adipose cells largely as triglyceride molecules. When we consume carbohydrates, they are broken down into glucose molecules (and others). Our pancreas secretes the insulin hormone in order to lower our blood sugar level (amount of glucose). Some of the glucose is immediately taken in by cells in our bodies for energy via a metabolic process called glycolysis, but a further process called lipogenesis converts extra glucose into fatty acids, and, in the presence of insulin and lipoprotein lipase, those fatty acid molecules are combined with glycerol molecules in a three-to-one ratio to form triglyceride molecules stored as body fat (in adipose tissue cells).

Notice we are now using specific, well-defined terminology in physiology, anatomy, biochemistry, and physics to describe the problem. In order to address obesity, we need to reduce the mass of fat stored in adipose tissue. And to be even more specific, we normally do not want to reduce the mass of our skeletal muscle tissue, tendons, ligaments, organs, and bones. We do not want to end up as 98-pound weaklings. And we do not want to get rid of all fat stored in adipose tissue because fatty acids are needed as fuel for creating energy when insufficient glucose is currently available.

So how does our body extract the fat from adipose tissue? This is more complicated, because our bodies have multiple metabolic pathways (different ways our cells create needed energy, depending on conditions). Our bodies first use available glucose in our bloodstream for cells to metabolize for energy through a process called glycolysis. If our glucose level is too low (also low insulin level), then our pancreas secretes glucagon, a hormone which in combination with the enzyme hormone-sensitive lipase signals adipose cells through a process called lipolysis to break down triglycerides into free fatty acid and glycerol molecules that are released into the bloodstream. The free fatty acids are then metabolized by our cells to create energy. So the problem is not to consume fewer calories than we expend as energy, as is often misunderstood. The problem is to release more fat than we store. Therefore, solutions should address metabolic pathways that lead to fat storage and to fat release for use as energy.

One effective method is to stop eating. The starvation method works – note the appearance of people who are starving to death, literally ending up looking like “skin and bones” (little muscle and adipose tissue remains). But starving is unsustainable as a method when we have plenty of food around us.

A further method is to exercise excessively. But that is impractical, with respect to burning any significant amount of fat stored in adipose cells. There are much more effective methods. Some exercise is good for us, but for other reasons to maintain health.

Unfortunately, the often-recommended method of reducing caloric consumption and increasing exercise does not, in fact, work in the long run for 95 percent of us, and is unsustainable (Eades & Eades, 1996; Bailor, 2015). Furthermore, people who try this method often end up with a more fat mass and less lean body mass though homeostasis. When done repeatedly (a “yo-yo” dieting pattern), this in effect exacerbates the fat mass problem (e.g., see Taubes, 2016; Bailor, 2015).

What is needed is a solution that stimulates our bodies to extract fatty acids from adipose cells and burn them for needed energy. And to do this at a rate that is greater than the rate of storing fat in adipose tissue. Over time, this will reduce the mass of fat. Understanding of metabolic processes in the human body can help us identify strategies that can safely reduce the mass of fat stored in adipose tissue without losing muscle mass or eventually starving to death.

Dietary approaches that are effective typically recommend eating proportionally more proteins along with a sufficient amount of healthy fats and eating proportionally much less carbohydrates (that are converted to glucose and stimulate insulin secretion by the pancreas). When our pancreas spends more time secreting glucagon than it does insulin, our bodies will extract fatty acids stored in adipose cells for energy at a greater rate than it stores fatty acids as triglycerides. See Eades and Eades (1996, pp. 34–37). It is a problem of the rate of feedin of fatty acids and glycerol to adipose tissue cells when contrasted with the rate of feedout. Feedin and feedout are system properties (e.g., see Thompson, 2008; Maccia & Maccia, 1966). The daily quantity of total calories we consume is less significant than quality of macro-nutrients we proportionally consume, the rate of consumption of those macronutrients during the day, and the energy demands of muscles cells (to move our bodies) throughout the day.

It is a rate problem, not a weight problem, and it is specifically about rates of different metabolic pathways our bodies use to create energy to stay alive and to move about.

While this fat metabolism example is oversimplified (there are additional metabolic pathways not discussed here such as ketosis and gluconeogenesis), it nonetheless illustrates the value of well-defined terminology, so we all know precisely what we are talking about. It further clarifies how we frame a problem and potential solutions to the problem.

References

Bailor, J. (2015). The calorie myth. New York, NY: HarperWave.Google Scholar
Bateson, G. (1979). Mind and nature. New York, NY: E. P. Dutton.Google Scholar
Bloodletting. (n.d.). In Wikipedia. Retrieved from: http://en.wikipedia.org/wiki/Bloodletting
Brown, D. G. (1970). Knowing how and knowing that, what. In G. Pitcher & O. Wood (Eds.), Ryle: A collection of critical essays (pp. 213–248). Garden City, NY: Doubleday.CrossRefGoogle Scholar
Cornford, F. M. (translator, 1945). The republic of Plato. New York, NY: Oxford University Press.Google Scholar
Dewey, J. (1916). Democracy and education. New York, NY: The Free Press.Google Scholar
Duffy, F. (2009). The scarecrow education series on leading school improvement. Retrieved from: http://www.thefmduffygroup.com/publications/series.html
Eades, M. R., & Eades, M. D. (1996). Protein power. New York, NY: Bantam Books.Google Scholar
Eagleman, D. (2015). The brain. New York, NY: Pantheon Books.Google Scholar
Estep, M. (2003). A theory of immediate awareness: Self-organization and adaptation in natural intelligence. Boston, MA: Kluwer Academic Publishers.CrossRefGoogle Scholar
Estep, M. (2006). Self-organizing natural intelligence: Issues of knowing, meaning and complexity. Dordrecht, The Netherlands: Springer.Google Scholar
Federative Committee on Anatomical Terminology. (1998). Terminologia anatomica: International anatomical terminology. Stuttgart, Germany: Thieme.Google Scholar
Frick, T. W. (1997). Artificially intelligent tutoring systems: What computers can and can’t know. Journal of Educational Computing Research, 16(2), 107–124.CrossRefGoogle Scholar
Frick, T. W. (2018). The theory of totally integrated education: TIE. In J. M. Spector, B. B. Lockee, and M. D. Childress (Oversight Eds.), Learning, design, and technology: An international compendium of theory, research, practice and policy (Vol. 1: Learning theory and the learning sciences (J. Elen, Vol. ed.)). Springer International Publishing AG 2018 J.M. Spector et al. (eds.), Learning, Design, and Technology, https://doi.org/10.1007/978-3-319-17727-4_69-2Google Scholar
Frick, T., Thompson, K., & Koh, J. (2006). Predicting education system outcomes: A scientific approach. In: M. Simonson (Ed.), Proceedings of the Association for Educational Communication and Technology, Dallas, TX.Google Scholar
Geach, P. (1964). Mental acts. New York, NY: The Humanistic Press.Google Scholar
Goleman, D. (2011). The brain and emotional intelligence: New insights (Kindle ed.). Northhampton, MA: More Than Sound LLC.Google Scholar
Greenspan, S. I., & Benderly, B. L. (1997). The growth of the mind and the endangered origins of intelligence. Reading, MA: Addison-Wesley.Google Scholar
Greenspan, S. I., & Shanker, S. G. (2004). The first idea: How symbols, language, and intelligence evolved from our primate ancestors to modern humans (Kindle ed.). Cambridge, MA: Da Capo Press.Google Scholar
Henneberg, M. (1998). Evolution of the human brain: Is bigger better? Clinical and Experimental Pharmacology and Physiology, 25(9), 745–749.CrossRefGoogle Scholar
Husserl, E. (1965). Phenomenology and the crisis of philosophy (Q. Lauer, Trans.). New York, NY: HarperCollins Torchbook.Google Scholar
Kandel, E. R. (1989). Genes, nerve cells, and the remembrance of things past. Journal of Neuropsychiatry, 1(2), 103–125.CrossRefGoogle Scholar
Kandel, E. R. (2001). The molecular biology of memory storage: A dialogue between genes and synapses. Science, 294, 1030–1038.CrossRefGoogle Scholar
Kant, I. (1785). Grounding for the metaphysics of morals (3rd ed., J. W. Ellington, 1993, Trans.). Indianapolis, IN: Hackett Publishing.Google Scholar
Lustig, R. (2009). Sugar: The bitter truth. University of California TV. Retrieved from http://www.uctv.tv/shows/Sugar-The-Bitter-Truth-16717
Maccia, G. S. (1973). Epistemological considerations of educational objectives. Paper presented at the XVth Word Congress of Philosophy, Varna, Bulgaria. Retrieved from: http://educology.iu.edu/Maccia/Maccia1973EpistemologyOfEdObjectives.pdf
Maccia, G. S. (1986). Right opinion and Peirce’s theory of signs. In: Paper Presented at the Semiotic Studies Faculty Seminar. Retrieved from: http://educology.indiana.edu/Maccia/RightOpinionAndPeircesTheoryOfSigns_GSMaccia1987.pdf
Maccia, G. S. (1987). Genetic epistemology of intelligent natural systems. Systems Research, 4(3), 213–218. Retrieved from: http://educology.indiana.edu/Maccia/Correspondence_GeneticEpistemologyOfIntelligentNaturalSystems1987.pdfCrossRefGoogle Scholar
Maccia, G. S. (1988). Genetic epistemology of intelligent natural systems: Propositional, procedural and performative intelligence. Paper Presented at Hangzhou University, China. Retrieved from: http://educology.indiana.edu/Maccia/GeneticEpistemologyOfIntelligentSystems_propositionalProceduralPerformativeIntelligence1988.pdf
Maccia, E. S., & Maccia, G. S. (1966). Development of educational theory derived from three educational theory models (final report, project no. 5–0638). Washington, DC: U.S. Department of Health, Education, and Welfare.Google Scholar
McKinley, M. P., O’Loughlin, V. D., & Bidle, T. S. (2016). Anatomy & physiology: An integrative approach (2nd ed.). New York, NY: McGraw-Hill Education.Google Scholar
Molenda, M., & Rice, J. M. (1979). Simulation review: The diffusion simulation game. Produced and distributed by the university consortium for instructional development and technology (UCIDT). Simulations and Games, 10(4), 459–467.CrossRefGoogle Scholar
Mourshed, M., Chijioke, C., & Barber, M. (2010). How the world’s most improved school systems keep getting better. London: McKinsey & Co. Retrieved from: https://www.mckinsey.com/industries/social-sector/our-insights/how-the-worlds-most-improved-school-systems-keep-getting-better
National Center for Health Statistics. (2015). Prevalence of obesity among adults and youth: United States, 2011–2014. Centers for Disease Control and Prevention. Retrieved from: https://www.cdc.gov/nchs/products/databriefs/db219.htm
Peirce, C. S. (1877). The fixation of belief. In J. Buchler (Ed.), The philosophic writings of Peirce. New York: Dover Publications, 1955, 5–22.Google Scholar
Peirce, C. S. (1931). Collected papers, Vol. I, Principles of philosophy (C. Hartshorne & P. Weiss, Eds.). Cambridge, MA: Harvard University Press.Google Scholar
Peirce, C. S. (1932). Collected papers, Vol. II, Elements of logic, (C. Hartshorne & P. Weiss, Eds.). Cambridge, MA: Harvard University Press.Google Scholar
Peirce, C. S. (1934). Collected papers, Vol. V, Pragmatism and pragmaticism (C. Hartshorne & P. Weiss, Eds.). Cambridge, MA: Harvard University Press.Google Scholar
Polyani, M. (1962). Personal knowledge: Towards a post-critical philosophy. Chicago, IL: University of Chicago Press.Google Scholar
Reigeluth, C. M., & Karnopp, J. R. (2013). Reinventing schools: It’s time to break the mold. Lanham, MD: Roman and Littlefield Education.Google Scholar
Ryle, G. (1959). The concept of mind. New York, NY: Barnes and Noble.Google Scholar
Scheffler, I. (1965). Conditions of knowledge. Glenview, IL: Scott-Foresman.Google Scholar
Semmelweis, I. P. (2008). In Encyclopædia Britannica. Retrieved from Encyclopædia Britannica Online: http://search.eb.com/eb/article-9066723
Short, T. L. (2007). Peirce’s theory of signs. New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Squire, L. R., & Kandel, E. R. (1999). Memory: From mind to molecules. New York, NY: Henry Holt and Co.Google Scholar
Stedman, T. L. (2006). Stedman’s medical dictionary (28th ed.). Baltimore, MD: Lippincott, Williams & Wilkins.Google Scholar
Steiner, E. (1977). Educology: Its origin and future. ERIC document No. ED141201.Google Scholar
Steiner, E. (1986). Crisis in educology. In J. E. Christensen (Ed.), Educology 86. Proceedings of a Conference on Educational Research and Development with an Educational Perspective, at Australian National University, Canberra, 10–12 July (pp. 221–227). Sydney, NSW: Educology Research Associates.Google Scholar
Steiner, E. (1988). Methodology of theory building. Sydney, NSW: Educology Research Associates.Google Scholar
Taubes, G. (2016). The case against sugar. New York, NY: Alfred A. Knopf.Google Scholar
Thompson, K. R. (2006a). “General system” defined for predictive technologies of A-GSBT (axiomatic general systems behavioral theory). Scientific Inquiry Journal, 7(1), 1–11.Google Scholar
Thompson, K. R. (2006b). Axiomatic theories of intentional systems: Methodology of theory construction. Scientific Inquiry Journal, 7(1), 13–24.Google Scholar
Thompson, K. R. (2008). ATIS graph theory. Columbus, OH: Systems Predictive Technologies. Retrieved from: https://mapsat.iu.edu/overview/reports/11ATISgraphtheory.pdf
Thompson, K. R. (2019). ATIS glossary. Retrieved from https://aptac.sitehost.iu.edu/glossary/
van Merriënboer, J. J., & Kirschner, P. A. (2013). Ten steps to complex learning: A systematic approach to four-component instructional design. New York, NY: Routledge.Google Scholar
von Bertalanffy, L. (1950). An outline of general systems theory. British Journal for the Philosophy of Science, 1(2), 134–165.CrossRefGoogle Scholar
von Bertalanffy, L. (1972). The history and status of general systems theory. In G. J. Klir (Ed.), Trends in general systems theory (pp. 21–41). London: Wiley.Google Scholar
Vreeman, R., & Greene, G. (2007). Medical myths even doctors believe. British Medical Journal, 335(7633), 1288–1289.CrossRefGoogle Scholar
Yazzie-Mintz, E. (2007). Voices of students on engagement: A report on the 2006 high school survey of student engagement. Retrieved from http://www.eric.ed.gov/PDFS/ED495758.pdf

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Theodore W. Frick
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1.Department of Instructional Systems TechnologySchool of Education, Indiana University BloomingtonBloomingtonUSA

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Eugene Kowch
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1.Werklund School of EducationUniversity of CalgaryCalgaryCanada

Importance of Educology for Improving Education Systems

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