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Melioration as a Higher Thinking Skill of Future Intelligence

by David Passig - 2007

This paper examines the characteristics of the thinking skill we call “melioration” i.e., the competence to borrow a concept from a field of knowledge supposedly far removed from his or her domain, and adapt it to a pressing challenge in an area of personal knowledge or interest. The skill has its source in conscious personal meaning-making, not in the process of deduction. In the unplanned operation of connection and association, one creates a new concept generating a new insight into a phenomenon, which hitherto had not been described in such a way. This paper relates melioration to existing theories of intelligence, taking the position that human cognitive/intellectual functioning is in part the ability to learn or think in the framework of familiar systemic concepts, and in part the ability to learn or think with new systemic concepts that are then available for future application.


In previous publications (Passig, 2000, 2001, 2003), we suggested a taxonomy of thinking and learning skills (see Table 1) that future generations will need to master if they are to successfully manage the continuation of society. References were also made to the challenges likely to be faced by succeeding generations. The taxonomy we proposed used the six categories of Bloom’s taxonomy (1956, a, b) as a basis for our broadening of the definitions.

Before redefining Bloom’s categories, we reviewed approximately 300 books from the literary catalog of the international organization for the study of the future (World Future Society - www.wfs.org) considered important to society’s future in a number of areas. This catalog is organized according to fields of interest. We selected best sellers from each field and organized them under eight clusters: Technological, social, organizational, economic, scientific, medical, educational, and sociological. We employed the technique of content analysis to extract behavioral terms and keywords that might supplement the definitions in Bloom’s categories. Our intent was to better understand whether future environments will challenge Bloom’s definitions of skills. We sought additional definitions, keywords, or behavioral objectives to update Bloom’s taxonomy and better reflect future thinking necessities for the next generation of learners.

Table 1: Bloom’s Taxonomy and Broadened Definitions, Additional Behavioral Objectives and Keywords (Passig, 2000, 2001, 2003)


Bloom’s Definition

Broadened Definition

Behavioral Objectives

Key Words


Any teaching purpose that just needs memorization.

To achieve successful application of information in real time.

To know where to find details; to master search strategies; to develop new symbols in a super-symbolic society; to develop conventions.

To locate; to know where to search; to filter; to be updated; to leave out; to develop.


A thinking process in which a message is changing form.

Multi-faceted comprehension of certain information; setting up fragments of information in various ways, when each composition has a different meaning.

To expand existing models of thinking; to set the ways of thinking in a wider framework; to invent symbols for concrete elements and to trade in these symbols; to create inferences & analogies in various ways.

To expand; to set up wider frameworks; to invent symbols; to connect things relatively.


The ability to implement rules, principles, information, assumptions, theories, or other abstractions for new and real situations.

The ability to produce new ideas out of old, in order to implement relevant information in real time and with variations. To create meaning for new symbols, new meaning for existing symbols, and to create a new symbol for an existing meaning.

Use of codes and symbols—new and old; modification of old codes and symbols.

To initiate change; to be flexible; to decide; to reorganize.


A thorough study to comprehend the structure of the learned content, its formal and logical way of organization, in order to detect the elements, outlooks, and methods this content is based upon.

Dividing a unit of information into its components, and structuring varied and different relationships, even when opposed to the unit’s components. To choose from the ocean of dynamic information of personal/cultural/ ethnic judgmental values. To set fragments of information up in a multi-dimensional spatial structure. To simulate various implications to various relations, and simulation of various perspectives in multi-dimensional space.

To create relations; to distinguish between relations; to analyze pieces of information in various ways; to evaluate reliability of information and set up fragments of information in different relationships, keeping in mind that the relations will be subject to the influences of time, space and personal intuition.

Relevant choice, subtlety in a personal prism, disassembling and structuring relations between fragments of information.



Establishing a whole new creation by combination of ideas from different sources, in a way that formats and molds will be created, and will stand at the basis of the new creation.

Creating various combinations with different meanings out of given units of information.

To locate separate elements out of pieces of earlier information, in order to grant it a new meaning.

To identify; to connect.


Judging the values in the ideas through use of standards of estimations, that will determine the accuracy level, purposefulness, and practicality of the details.

To know how to choose suitable criteria and develop new criteria in order to develop an evaluation that will be useful for the continuation of the learning process. Evaluating the concealed as well as the obvious.

To evaluate qualitatively and quantitatively; to focus and connect between overall relevant items.

Disqualifies; processes; checks; confronts.

Experience has suggested that revolutionary ideas as well as tools are actually the infusion of two or more concepts from quite different realms. People, for example, can take an electric appliance that exists in one context, transfer it to another context in a completely new way, and find unexpected potential uses for it. The skill, through personal and cultural connotations, of being able to merge realms of thought that are quite different from one another, and then generate new concepts or technology, is what we call melioration. In the course of our current search of future-oriented literature for the purpose of reevaluating Bloom’s six categories of skills, we found a new, seventh category. We “stumbled” upon a skill that we could not easily integrate into other skills. We suggest that this construct might stand by itself and seek to “meliorate” as expanded upon in Table 2.

Table 2: Melioration and its Behavioral Objectives



Behavioral Objectives

Key Words


The skill of selecting an appropriate amalgam of information, meliorating that current amalgam, and applying it to the solution of problems in new situations which arise at different times and places.

1. Consonance: To create an innovative product by making a personal cognitive connection between two areas, which appear to be distant one from the other.

2. Connotation: The personal significance which a particular person attaches to a particular piece of information of which he is aware.

3. The courage to forget.

Adaptation; connotation; simultaneity

We argue that melioration is a form of cognitive/intellectual skill which, to the best of our knowledge, is only mildly addressed in today’s school curriculum. According to the literature we have reviewed, however, the skill of melioration is becoming important to future learning and thinking as well as to research and development, marketing, and production processes in the real world beyond classrooms.


To put melioration skill into perspective, we briefly note some recent theories of intelligence, and how their ideas relate to the construct. Three theories dealing with the structure of intelligence in particular are relevant because they address the factors that comprise intelligence:

a. Howard Gardner’s theory of “multiple intelligences” (Gardner, 1983) offered the claim that human intelligence is not a single, intellectual entity, but a bundle of several separate intelligences, including, for example, mathematical-logical, musical, visual-spatial, kinesthetic, personal, interpersonal, and verbal.

b. From his early writing on intelligence, Sternberg (1982, 1985, 2003) argued for a “triarchy model of intelligence,” maintaining that intelligence can be observed and measured on three dimensions and on the relations between them which he defined as inner cognition, external world, and experience, as follows:

A person’s inner cognitive world includes the acquisition of knowledge, the processing of that knowledge, and those component aspects of meta-cognition that deal with the planning and coordination of the stages of knowledge, acquisition, and organization.

Thinking in contact with a person’s external world includes the ability to adapt to the environment, to change it, or to exchange it for a different environment.

A person’s thinking and entire arc of experience includes the ability to cope with new situations, and turn talents into automatic actions  in the repertoire of behavior.

c. Perkins (1995) developed the idea that people have a special reflective thinking, or “thinking landscape,” which is capable of development and bound together with cognitive inclinations. These “inclinations,” in part, determine the progress of thinking, no less than the cognitive elements by which intelligence is characterized.

Melioration, thus, could be considered a sub-skill of one of Gardner’s intelligences, or it could cut across the forms of intelligence as defined by either Gardner, Sternberg, or Perkins.

As this short list suggests, researchers have pondered the subject of thinking and intelligence for many years. Some scholars have noted the troubling fact that there exist an abundance of overlapping concepts and definitions of intelligence in the literature (e.g., Sheppard, 1997). Others have suggested adopting a general concept of “higher thinking skills” not specific to one or another kind of thinking, but which would emphasize in a general way the contrast between lower thinking skills (repetition, memorization, etc.) and other thinking skills that require higher intellectual activity.

In our view, it is less productive to suggest a different direction for the theoretical understanding of human intelligence than to advocate considering “intelligence as a tool” relevant to the improvement of human conditions in the future. A similar metaphor and approach has been suggested by Bereiter and Scardamalia (1996) in their “knowledge building theory” (Scardamalia, Bereiter, & Lamon, 1994; Bereiter & Scardamalia, 1996;  Scardamalia, 2001). Bereiter and Scardamalia claim that knowledge building is a tool of a social nature. Their analysis of the history and sociology of science provides evidence that problems that are researched, methods of inquiry that are used, and findings that are considered advances in science, are all socially determined. Constructs such as race, gender, and status are seen by Bereiter and Scardamalia as associated with knowledge building. To make the case for knowledge building, Bereiter and Scardamalia base themselves upon Popper’s (1972) philosophical approach to theories, hypotheses, inquiry methods, and similar intellectual artifacts as objects of inquiry. These objects are most profitably scrutinized, improved, and put to new uses, according to Bereiter and Scardamalia, as a result of discourse by the community of learners.

It is our contention that a step in this direction provides a proactive approach to identifying the skills ensuing generations will need to function productively. Human intelligence should be viewed, therefore, as evolutionary. It demands constant renewal. Similarly, goals of education need to be constantly renewed if they are to remain relevant to the needs of future generations.


In order to distinguish melioration from other allegedly similar skills, we discuss leading theories of innovation, synthesis, and creativity.

Melioration and innovation

The qualitative advantage and level of innovation that characterizes the results or products of melioration can be demonstrated by comparison with Henderson and Clark’s (1990) Model of Innovation. They claimed that any intellectual product can be perceived in two ways: As a collection of components with separate distinctions, or as a system with distinctive characteristics—different from the specific characteristics of its components. When viewed from this point of view, innovation contains two dimensions: a horizontal dimension that measures the impact components have on the level of innovation, and a vertical dimension that calculates the impact of the system as a whole on the quality of the innovation. Reflecting this analysis, Henderson and Clark (1990) defined four types of thematic innovations (incremental, modular, architectural, and radical) corresponding to the components of the system and the direction of interaction among them.

Incremental innovation can be perceived of as mild changes in the components and architecture.

Modular innovation can be seen as drastic change in the components and mild change in the architecture.

Architectural innovation can be seen as mild change in the components and drastic change in the architecture.

Radical innovation can be evident as drastic change in the components and drastic change in the architecture.

It seems evident that Bloom’s skill of synthesis may be seen as able to generate incremental and architectural innovations. Innovations that are architectural as well as radical, however, seem to require melioration. Figure 1 demonstrates visually the differences in the quality of innovations that can be generated by both incremental and architectural skills.

Figure 1: Melioration as a radical and architectural innovation (figure adopted from Henderson and Clark (1990)

Change in the


Change in the Architecture




Modular innovation

Incremental innovation


Radical innovation

Architectural innovation


Architectural innovation

We will site several examples of architectural innovation based upon Bloom’s skills. The “literature-review” chapter of a dissertation is an example of a product of synthesis that can be considered incremental innovation. Such a chapter, generally, reports on existing resources. The format of the review makes no changes in the components (or source material being reviewed), nor does it add new components or source material. It does, however, frequently introduce a mild change in the architecture of the information, in order to convey a theoretically new meaning appropriate to the research question.

Furthermore, a product of synthesis that can be considered architectural is a proposed new model or theory. When the model is based upon other models from the same field, typically only minor change is introduced in any one model. If drastic change, however, is made to the architecture of the components of the pre-existing models, then the thematic innovation is architectural.

Now contrast these with an example for a product of melioration that can be considered architectural innovation—namely, the idea behind a new construct such as Emotional Intelligence. In this instance, the proponents of the construct do not alter the two original concepts (emotion and intelligence) significantly. They did not so much change the basic components of either construct as they aggregated the two constructs together to interrelate separate fields of research, thus leading to a new field of research.

Finally, the idea of the sociological meme can serve as an example of a product of melioration that can be considered as a radical innovation. The “meme idea came from Dawkins (1989), who borrowed it from genetic engineering in order to develop a sociological concept that described the development of information in human culture. The meme describes a unit of wisdom in the development of human culture. Memes develop in the human mind, and are reproduced by mimicking, in the process of being transferred from one mind to another. At the time a person is registering an idea heard at a lecture, conversation, or mentioned in a book, s/he is reproducing the human information database, and is causing it to produce new mutations that ultimately serve to advance humanity’s level of wisdom. The innovation of this idea is based upon drastic change that was introduced to the components and architecture of the original concepts.

Melioration and synthesis

There are similarities and differences between melioration and other thinking skills such as synectics or creative idea generation (Gordon, 1961) and lateral thinking or thinking divergently (DeBono, 1992). We assume, however, that most similar to melioration is the thinking skill synthesis. Table 3 is presented to clarify differences between melioration and synthesis as we see them.

Table 3: A Comparison Between the Skills of Melioration and Synthesis








The skill of establishing a whole new creation by combining ideas from different sources, in a way that formats and molds will be created, and will stand at the basis of the new creation.

With the help of the thinking strategy of constructivism, combining parts from the same or close fields into a new format.

Reorganization, integration, unification, fusion, combination, assembling.

Productive thinking,

Innovative thinking

Synthesis leads innovation to new insight while reorganizing and integrating different sources. There is no need for invention.

The resources need to remain unchanged in order to synthesize the new creation that stands as their basis.

The procedure needs to be objectively replicable by others and reach the same outcome.

Environment, timing, personal background, and constraints should not affect the process and outcome.


The skill of selecting the appropriate amalgam of information and applying it to a solution of problems in situations, which arise at different times and places, thereby meliorating the amalgam.

With the help of the thinking strategy of creativity, aggregating parts from very far and opposing fields into a totally new and striking format.

Adaptation, connotation, simultaneity

Productive thinking,

Innovative thinking

Melioration leads innovation to the level of invention while adapting different sources through personal, ethnic religious, etc., connotations.

The courage to forget parts of the sources leads to new forms of connotations.

The outcome is purely subjective and cannot be fully reproduced by others.

Environment, timing, personal background, and constraints mold and shape the outcome.

Generally speaking, melioration leads innovation to the level of invention while adapting different sources through personal, ethnic and religious connotations, while synthesis leads innovation to new insight merely by reorganizing and integrating different sources.

Melioration and creativity

Critics might consider melioration skill as part of the vast array of definitions of creativity. Arieti (1976) catalogued eight models of the creative thinking processes that were proposed during the period 1908 to 1964. The variety of definitions for creativity leads to a variety of possible explanations for its foundation, and scholars have had difficulty grasping a definition for creativity. For example, Farrell (2001) proposes: “Creativity involves combining two or more ideas so as to produce something new and useful or beautiful.” Schmitt (1994) offers a simplistic but eloquent definition: “Creativity is the art of causing original ideas or objects to exist.”

For this paper, we analyzed and compared a large number of definitions of creativity with melioration. Table 4 shows a sampling of a few definitions of creativity we found—and how they differ from melioration.

Table 4: A Comparison Between Melioration and a Sample of Definitions of Creativity


according to:

Characteristics of creativity

Characteristics of Melioration



Wallas (1926)

The implied theory behind Wallas' definition of creativity is that creative thinking is a subconscious process that cannot be directed, and that creative and analytical thinking are complementary. The Wallas process of creativity is based upon 4 stages:


Defining the issue. Starts with a failure.

Identification of a problem or a need.

Deciding upon the field of inquiry. The need is an ill-defined problem.



Laying the issue aside for a time. There is no intention to solve it. The process continues unconsciously.

Collecting data. Laying near and far relevant fields. Personal connotations are reflected.

Intensive processes of thinking to discover unconventional and unexpected thoughts.

Wallas assumes that the incubation stage is unconscious.

In melioration, this stage is conscious in order to locate intersections that can trigger connotations.


The moment when a new idea finally emerges.

The new idea emerges from the adaptation of two separate and opposite fields glued with personal, ethnical, local, etc., connotations.

Sometimes the new idea is perceived as illumination.

Wallas assumes that the illumination stage is one single occasion that is not replicable.

In melioration, this stage can be reproduced with different connotations and in different timings to achieve various ideas.


Checking it out for presentation in public.

The product is verified by others checking whether it solves the problem.

Productive thinking. The standard for verification is the quality of its solution of the problem.


Mednick (1962)

Proposed that creativity often depends on finding new connections among ideas.

The measure of creativity is designed to evaluate how readily a person finds these connections.

The measure of melioration is designed to evaluate how far a person can go to stretch these connections.

Both processes strive for innovation by breaking common thinking frameworks.

Mednick emphasizes far fetched associations without asking whether they can be consciously triggered.

Melioration emphasizes far fetched conscious associations triggered by personal adaptations and connotations.

Guilford (1968)

Divergent thinking is seen by Guilford to be important in producing new, original, and "creative" ideas. The Guilford Model for the Process of Creativity is based upon 4 stages:


The number of raw responses.

A meaning which connects in personal awareness to a certain bit of information.

Idea flow can be a concept from a deep reservoir of connotations which makes it possible to select ideas for melioration.

Guilford doesn’t address the question of how to create flow. In meliorative thinking, there is a productive action for the creation of flow.


A number of different categories of answers.

A cognitive tie between two content areas that seem far apart from one another.

In both cases, the learner is expected to show flexible thinking in order to make a connection between new and existing data.

Guilford didn’t discuss the development of creativity. He concentrated on its measurement. In meliorative thinking, the learner is expected to apply cognitive behaviors.


Statistical rarity.

The readiness to do without and to set aside existing paradigms.

The aspiration of identifying an idea characterized as original guides both definitions of skills.

Guilford measures creativity.  He doesn’t ask how it is acquired. Meliorative thinking advances the behaviors needed to acquire originality.


The degree of richness of the described content.

Cognitive connection between two content areas that are distant from one another.

In both Guilford's definition of creativity and melioration, there is sufficient rich content for the identification of worthy ideas.

In melioration, the richness of the content stems from the ability to carry out fruitful matching between two content areas that are far removed from one another.  Guilford doesn’t say how rich content is obtained.

DeBono (1992)

Coined the term “lateral thinking” to describe going outside the usual channels of thinking. DeBono suggests the use of provocation in order to encourage creative thinking.

The role of provocation is to bump thinking out of its usual course into other venues.

The readiness to abandon existing paradigms.

The courage to forget supports the abandoning of familiar furrows of thought, and the identification of new, groundbreaking lines of thinking.

Unlike in melioration, DeBono doesn’t say if there are cognitive behaviors that are essential for provocative thinking.

Weisberg (1993)

Creativity as nothing special: The creative process is nothing more than an expression of an ideal solution of problems. Creative thinking begins with content that is familiar to us, but which goes backward in time, as it bases itself on new information that comes from the situation.

Expertise in a relevant content coupled with support from the surroundings provides the opportunity, the motivation, and the commitment to find a solution.

The meliorative thinking is processed through 6 stages: Initial intention, retrospective intention, continual integrations, result, evaluation, and proved validity.

Support, opportunity, motivation, and commitment are necessary for nurturing creative thinking.

The meliorative thinking process is aimed at creating those conditions by giving the same opportunities to all those who are learning to pinpoint new, authentic, and contextual ideas.

Weisberg maintains that creative thinking demands an expertise in a specific content area.

In the process of melioration, the assumption is that the necessary knowledge can be acquired, and is not the exclusive property of a chosen few.

Boden (1994)

Creativity as the study and transfer of conceptual space. Creative ideas are those that could not be created by an organized system of laws. Unique ideas are those that can be described by the same system of laws in which familiar ideas are located.

Going outside the existing system of laws by changing basic values in the system of laws.

Readiness to abandon the existing paradigm.

The kind of thinking that Boden seeks to encourage can be promoted via the Courage to Forget behavior.

Getting out of the existing system of laws in order to return and join it at another place changes the point of view.

Boden speaks of getting out of the space in order to return and rejoin it.

In melioration there is no such demand.  On the contrary, the aspiration is to get out of the existing space and to attain new spaces.

Perkins (1995)

The creative process is a search via a broad range of possibilities in order to arrive at a final destination, which is called "the solution."  Perkins identifies four areas in which creative ideas are found:

Rarity of the problem: This appears in the part of the search in which there are rare solutions.

Four different spaces of wonderment enables the generation of a solution that is considered creative.

Six stages enables one to meliorate an idea: initial intention, retrospective intention, continual integrations, result, evaluation, and proved validity.

In order to overcome the obstacles on the way to meliorating ideas, one should be assisted by a working process such as a computerized search, a change in the rules of the game, teamwork, openness to new information, a change in the point of entry to the problem, or by identifying the limits of the blockage.

Perkins listed a number of obstacles on the path to finding a creative idea. The ability to orient oneself in a situation where one is blocked is vital on the way to formulating insights.

Perkins defined the places in which the process is stuck. Meliorative thinking encourages being alert to these situations, and nurtures the ability to remain in them for an extended period of time.

Isolation of the problem: This appears if the solution isn’t accessible to the search mechanism.

Whirlpool of the problem: This appears if the search is nearing success, but doesn’t get there.

Blockage of the problem: This appears when there is no apparent direction in which to go for a solution.

It is important to note that some experts dismiss the notion that creativity can be described as a sequence of steps in a model. For example, Vinacke (1953) is adamant that creative thinking in the arts does not follow a model. In a similar vein, Gestalt philosophers like Wertheimer (1945) assert that the process of creative thinking is an integrated line of thought that does not lend itself to the segmentation implied by the steps of a model. But while such views are strongly held, they are in the minority. The table clearly shows that, while creativity is a non-conscious process that leads to innovation and can be achieved through different venues or stages, melioration is a conscious process that leads to innovation by being aware of and using the most sub-conscious elements of personal thinking, such as connotations and inner beliefs.


In our research, we have distinguished two kinds of melioration. Within each kind of melioration, we hypothesize six progressive stages of skill development. The two principle kinds of melioration are the melioration of information, concepts, ideas, and insights, and the melioration of tools and technologies.

The six hypothetical stages of development we propose around the core process of meliorating concepts and tools include: Initial intention, retrospective intention, continual integrations, result, evaluation, and proved validity. Table 5 summarizes the six cognitive steps that we see accompanying the core process of meliorating an idea or a tool. These stages are conscious or unconscious steps one normally should cross in order to engage in meliorating a concept or a tool. We do not expect that it is necessary to pass through all of the stages, and we assume that an agile learner could readily skip a stage or two.

Table 5: Six Cognitive Stages in the Melioration of Concepts and Tools


Melioration of Concepts and Tools


Initial intention

The melioration of concepts or  tools is planned in advance


Retrospective intention

Occasionally, intentions appear only after the melioration, i.e., the melioration wasn't planned in advance. The process creates the intention.


Continual integrations

Combinations of very far aparta ideas that are being continually tested to respond to a challenging dilemma, issue, product, etc.



A new and very unconventional concept, product, or feature for an existing or new tool emerges.



One is able to evaluate the outcome and recognize its uniqueness and significance.


Proved validity

The new concept turns out to be a viable solution to a known or unknown problem and is so recognized by the immediate community. The community further examines its meanings and applications.


In the remainder of this paper, we illustrate both kinds of melioration with educationally relevant examples. These include illustrations from technology, economics, medicine, and business. Our examples should help clarify how authors throughout history have meliorated ideas. As noted above, our definition of melioration as a skill is derived from the structure of the development of ideas. From the literature we learned how processes are perfected, and from that we elaborated the characteristics, keywords, and behavioral terms of the required skill i.e., melioration. Our examples are organized according to the two kinds of melioration.

Melioration of concepts, ideas, and insights

The following examples, a representative sample from the literature we reviewed, illustrate how thinkers and researchers can borrow a concept from a field of knowledge, supposedly far removed from their realm, and adapt it to their area of interest. This borrowing seems frequently to have its source in what may be called the personal connotation, rather than in some logical process of deduction. That is, it is the unexpected connections and associations of the thinker lead to a new concept in a given area of knowledge, and these concepts, in turn, generate new insights into a phenomenon. The addition of new depth and breadth of knowledge is the essence of the researcher’s contribution. There are those who would maintain that this process may be nothing but transference. As we understand it, however, transference is based on logical rules (e.g., induction), whereas the connections in the following examples are principally associative, and not predictable, logically speaking.

To our surprise, evidence of melioration as we have defined it appears again and again in many best-selling books. We would hypothesize that the thinking structure of best-selling authors is an important element in their success.

Melioration of a sociological concept

One of the pivotal ideas in genetic engineering is that half of the genes present in the body are involved in the creation of every new generation. Those carefully selected genes are transferred and make up the DNA of the next generation, only if they increase the chances of the next generation’s survival. This process is known as MEME.

According to Dawkins (1989), who borrowed this idea from genetic engineering, a MEME can describe the unit of wisdom (on an infinite scale) in the development of human culture. The MEME develops in the person’s mind through conscious or unconscious blending with other existing ideas, and is reproduced by mimicking itself in the process of being transferred from one mind to another. When a person is registering an idea heard at a lecture, a conversation, or a concept mentioned in a book, and so forth, he is reproducing the human information pool and is infusing it with personal connotations. He is causing it to produce new mutations that in turn advance humanity’s level of wisdom. In this respect, the concept of MEME is parallel to that of the GENE. Dawkins claims that in an infinite number of variations of processes of this sort, the MEME creates an independent life for itself, and becomes essentially free within the mimetic pool of human culture.

The MEME can also be an idea generated in a person’s mind, which comes to be replicated in the minds of many others via lectures, conversations, and so forth. The purpose of the MEME is to survive in human culture by constant adaptation to changing situations and changing minds with personal preferences and cultural connotations. The ability to constantly adapt to demands can be described as a melioration process. Its results are expressed in the continuing adaptation of MEMES to the changing conditions of life and environment.

This example has demonstrated the melioration skill. It demonstrated how Dawkins created a new idea—a social meme—combining two far removed fields into a new and different concept. By meliorating the genetic concept of MEMEs, Dawkins was able to show how conceptual MEMEs unfold through a process of connotations into new and meliorated ideas suited to a human mimetic pool.

Melioration of science with the help of populism

Another example describes how personal style in science solves a scientific problem with political and economic implications for an organization such as NASA. Carl Sagan (1994) claimed that the results of stupidity in science are much more dangerous in our era than they were at any previous period in human history. His contention was that this danger is doubled and quadrupled especially at a time when scientific thinking has become obligatory for the existence of democratic organizations, and essentially of civilization itself. Sagan maintains, to our regret, that precisely the period of time when science has reached such impressive levels of achievement, the number of people who are suspicious of science and who distance themselves from it is growing in leaps and bounds. This is happening mainly for three reasons: The technological risks that science assumes, the challenge that science is likely to make to accepted wisdom, and the difficulty involved in understanding science.

Sagan devoted the final years of his life to an appeal to scientists to make science more popular. He became world famous as a result of his scientific series “Cosmos,” in which he succeeded (in a much too populist style, so far as many scientists were concerned) in interesting a great many people in space research. He felt that it would be possible to overcome the popular suspicion of science only through scientific populism, and by making science more available and closer to people, by describing it in the day-to-day language of as many people as possible.

In short, Sagan was suggesting the melioration of science. He maintained that it was possible to use science to simplify its concepts, to make science understandable for the man in the street, and, thereby, meliorate its uses. Thus, a personal style that brings together opposite cultural paradigms—science and populism—is able to meliorate a leading-edge science such as space exploration. The new idea that emerged from that unique integration of opposite values is summarized in the term “spin-off.” The concept of spin-off was born in the space industry, and one of its originators was Carl Sagan. The goal of the spin-off that began at NASA was to pass along to the private and public sector technologies and ideas that were developed for the space industry in a new format. A special department, established in NASA, has since been involved in the commercial development of spin-off ideas from NASA projects. Subsequently, NASA spin-offs with new social and scientific values in mind have led to important breakthroughs in medicine, transportation, computers, environmental projects, and home products. Without the popularism that Sagan gave to science, it is hard to imagine how the many life-saving technologies (e.g., ultrasound) taken for granted today could have been generated.

Melioration of artificial intelligence

The method of nerve imaging, which is mentioned by Copeland (1993) in the book Artificial Intelligence provides another example of how thinkers overcome a difficult scientific problem by presenting a new construct (neurology) to an existing idea (artificial intelligence). The result of this new approach to research in artificial intelligence, led to the creation of what today is known as nerve imaging, a process by which one attempts to construct a model for simulating the activity of the neurons in the brain.

Copeland (1993) further maintains that if we relate what is known from research in brain activity with the field of artificial intelligence, then research in artificial intelligence will be likely to find ways around some of its current dead ends. This connection now takes rules from the discipline of neurology and adapts them to the paradigms of computer science. In this example, five stages of melioration have become apparent, as follows:


Intention—to perform nerve imaging in a way intended and planned from the outset by bundles of knowledge accumulated in both brain research and artificial intelligence.


Continual integrations—neural networks reconstruct processes identified as belonging to a specific field of knowledge with ongoing activity in a different area.


Result—in this case the product may be found at the focus of the innovation—by bundling together knowledge from a number of areas, one arrives at a new product; an artificial brain, for example.


Evaluation—additional insights occasionally arise during the stage of evaluation. These may be about the product or, sometimes, also about the original intentions—in our case the possibility of creating and connecting more artificial neurons.


Validity—the concept or tool as examined and studied now in laboratories, and perhaps in the future, may lead to creating continuity independent of outside factors. While only a small number of the innovations reach this stage, we posit a kind of autonomic, evolutionary development of the innovation or invention from the outset.

Melioration of interfaces

Gershenfeld (1999), in his book When Things Start to Think, presents the studies he and his colleagues have been conducting in the Media Lab at MIT. They have been involved in an effort to introduce the computer into every area of human life, from computers woven into our clothing, built into our kitchen appliances, molded into the soles of our shoes, and so on. Gershenfeld describes the digital revolution and its influence on our lives, and on our expectations from computers. He argues that the interfaces of men and machines must undergo a conceptual revolution so that people will want to use many smart appliances. Here again we have an example of personal meaning-making or connotation bringing about breakthroughs in basic concepts in technological interfaces.

Gershenfeld adopted some standards of measurement for “good” and “efficient” interfaces from the field of biology and others from the area of technology. In doing so he created a new concept of computer interfaces that can be adapted to anyone in many aspects of life. Bites in technology become like atoms in biology. Atoms tend to react in different ways to different people, therefore, Gershenfeld claims, bits should react to different people in different ways. Thus, the examples of what is being developed at MIT are both surprising and entertaining.

In one such example, the computer can be fitted into a shoe to enable the wearer to know where he is located, (i.e., in a dangerous neighborhood, going in the wrong direction, and so forth). The shoe will also be able to turn the heat caused by walking-generated friction into electricity, which will be used to run computers and refill batteries. The sound system by recognizing a touch of your shoe will play your favorite station or music genre.

Furthermore, though early-21st-century computers are unable to track people’s sensations, Gershenfeld’s lab has proven that it is not unreasonable to expect that future computers will even be able to calm a person under stress, as sensors will report information on his body temperature, his perspiration rate, his muscle tension, and will assess his state of mind.

This example demonstrates how meaningful connections made by an individual between diverse building blocks in biology and electronics can generate a new concept of technological interface. This may provide the drive for the development of unusual tools able to infuse biological standards within mechanical ones. This opens the door to a new realm of very different tools that were designed, originally, from a biological mindset.

Melioration of tools and technologies

Recall, we divided melioration into two main categories: The melioration of ideas and the melioration of tools. We found that the melioration of ideas and concepts leads to more advanced and sophisticated tools, and these often engender additional new ideas. We now focus on the melioration of tools, which are formed from within bits of knowledge and applications appropriate for the solution of problems in different situations of time and space.

The examples here also emphasize thinking skills, but as they are expressed in the assembling of different tools and technological systems. Our purpose is to point out, with the aid of these examples, some of the skills that our children will be expected to demonstrate when their turn comes to continue the human journey through the ages.

Tool paradigm

Freeman Dyson (1998), in his book “Imagined Worlds,” coins a new term which he calls “Tool Paradigm.” This term, as opposed to the familiar term “Scientific Paradigm” (Kuhn, 1962), relates to the way technology develops and endures. Dyson made a new distinction dividing paradigms into two groups, a Tool Paradigm and a Concept Paradigm. Until the time of his writing, Dyson noted that accepted wisdom had been that the development of a paradigm leads to the invention of new and better tools. The moment, however, that we accept the distinction between these two kinds of paradigms, it is possible to assume that the development of tools could also lead to the development of concepts, and not just vice versa, as was previously thought. Evidently, Dyson claims, that what we have here is a complete spiral of the development of human culture.

Dyson presents different examples to support his claim that tools generate concepts, just as concepts generate tools. The telescope is the classic example. The telescope is a tool that motivated biology and chemistry scientists of astrophysics to explore and generate theories regarding the source of the universe and the life cycle of the stars. Indeed, the personal computer (PC), today, is taking an increasingly greater role in the fashioning of most important theories of humankind, in mathematics, physics, and biology. The Human Genome Project and the Proteome Project would never have been possible without the personal computer.

Dyson also gives examples of tools that in the future will give shape and direction to paradigms, which will be of the most crucial importance to humanity. In the 21st century, he claims, we will be able to see interesting and efficient tools that will be a product of the synthesis of computers and genetic engineering. These tools will break new paths to scientific theories that are unreachable without them. Today, we already have technologies that break scientific paradigms. An example is the combining of computer technologies with the applications from research in tele-sensation. This promises the development of intelligent cars that can travel to a desired destination without a driver.

Another tool of the future will be a technology, undoubtedly controversial: Ectogenesis, or extra-uterine birth. It will be possible to grow fetuses in the laboratory for the full term of pregnancy. If ectogenesis is permitted, it would very likely bring about a qualitative change in our conception of the creation of life. It would be possible to choose the sex of the child to be born, as well as several other human traits. This technology would require rethinking of the most basic assumptions of our existence as human beings. It will force us to redefine what it is to be human in our age, to redefine the psychology and legal characteristics of family ties, and evidently redefine our purpose and place in the larger universe.

This example raises the need for the distinctive skill of melioration of tools. As tools lead to new paradigms, our children will also have to demonstrate their ability to meliorate ideas with the help of tools. “The Tool Paradigm” is itself a melioration of the paradigm, which views the development of science as a continuing revolution of paradigms.

In the past, most scientists thought that scientific revolutions happen because of shifts in perception. Revolutions of that sort, however, have been quite rare. In the last 500 years, there have only been six such revolutions, and they have been connected with personalities such as Copernicus, Newton, Darwin, Maxwell, Freud, and Einstein. More of the revolutions that have influenced humanity have stemmed from new tools such as the computer, the telephone, the television, the railroad, the automobile, and other technological breakthroughs.

Revolutions connected with tools are, in many cases, meliorations, because people take an appliance that exists in one context, and transfer it to another context in a completely new way, sometimes leading to illogical and unexpected discoveries.


Neurophysiology is a branch of science focused on the understanding of the organizing principles of the central nervous system. To conduct research in this field, scientists borrow sophisticated tools from areas such as physics so that they will be able to observe nerve signals at high levels of resolution. Similarly, they borrow tools from mathematics and computer science to “fish out” and understand significant signals from the midst of a sea of noise. Research in neurophysiology is able to progress because its focus involves joining the researcher’s efforts to the tools of various other disciplines.

Engines of Creation

The creation of molecular computers, as discussed by Regis (1995) in his book, Nano, is another example of the melioration of tools. According to Regis, the purpose of computers is to work with bytes of information. Since a byte of information has no size as such, we aspire to make the computer, which deals with it, as small as possible. On the other hand, the smallest component part of anything known to man is the molecule. Biology has introduced us to complex, organized systems of molecules. Regis predicts that the day is not far away when we will develop a molecular-sized computer that will become a tool at the disposal of our sciences. This molecular computer will certainly be different from the brain in that it will be mechanical and not biological. It will also be much smaller, more efficient, and capable as any small machine, when compared with the human mind, which is relatively massive, and which loses and/or adds cells every day.

Initiating this line of thought, Eric Drexler (1992), then a student at MIT and now the head of the Foresight Institute for the Study of Nanotechnology in California, had the idea of taking biological components and metaphorically “convincing” them to do things for us, as they do in nature. His idea was to put nature’s components together in a new way in order to get a different overall arrangement. What he is suggesting is not merely a laboratory arrangement of known biological structures, but an arrangement not seen in any natural serial structures of atoms and molecules.

The innovation in Drexler’s idea is that these tools could push the cells to produce something of a completely new kind, as opposed to creating merely artificial versions of things that already exist. The idea of arranging building blocks of nature in a different manner, is another example of the fusion of mechanical engineering and molecular biology to create a new science which meliorates both realms of science. This provides us with a new, meliorated tool with which we could work in ways previously unimaginable.


At the beginning of the 21st century it is clear, even to conservative authors such as Hernstein and Murray (1994), that only about ten percent of successful people would have been predicted to succeed on the basis of their performance on standardized tests. This issue is becoming more and more troubling to the training systems from elementary schools and universities to the employers who hire their graduates.

In his book Successful Intelligence, Sternberg (1997) claimed that day-to-day intelligence demands a broader range of talents than those measured by accepted tests. The skills valued most in our school curricula are precisely those of least value in life outside school walls. Intelligence is not a person’s ability to learn or think in the framework of familiar systemic concepts, but the ability to learn and think with new systemic concepts that are applied thereafter to the existing body of knowledge. As Sternberg (2003) suggested, scholars should search for a new approach to intelligence with whose aid it would be possible to develop different, more relevant measurement tools.

Sternberg’s theory of intelligence is expressed mainly in terms of the context in which intelligence functions. He suggests a contextual framework for understanding intelligence (see also Stanford Aptitude Seminar, 2002). The movement by modern psychology to contextualize concepts heretofore promoted as being “inside the head,” provides a way out of another dilemma that has confronted research on intelligence in the past. In the past, intelligence was too often defined circularly as that which is examined by intelligence tests. Our new contextual concept of intelligence can additionally provide a view of the quality of intelligence, something that has too often been neglected.

Most of the research carried out in the 1970s and 1980s on intelligence dealt with intelligence as part of the individual’s internal world (Resnick, 1976; Sternberg, 1985). These studies provided a means of understanding intelligence in terms of the cognitive structures and processes that contribute to it. They provided nothing, however, to support the understanding of the connection between the individual and the external world. If we conceive of intelligence, at least in part, as behavior adapted to the environment, then it is impossible to understand the quality of intelligence without also understanding how the actual world fashions that which is intelligent behavior in any given cultural and social context. Modern aptitude theories take this perspective.

It should perhaps be noted that Sternberg’s theory was initially considered too impractical to be easily accommodated by the educational system. This was because it didn’t give educators clear measuring instruments to work with in the framework of a curriculum for helping students progress across the triarchy of intelligence. Recently, more is being done to develop such measuring instruments that do reflect a contextual approach.

In the 1980s, Glasersfeld (1995) asked, “How is our knowledge created, and how valid is it?” He maintained that epistemology becomes a search for the ways and means that intelligence uses to construct an orderly world. We pluck the components of this world from a flood of experiences. The radical form of constructivism, Glasersfeld espoused, begins with the assumption that every cognitive action takes place within a world of practical experience, perceived through goal-oriented awareness. There does not necessarily have to be a tie between the “real” world and individual experience. We build our world of experience through cognitive processes such as comparison, the creation of things and permanence, and thereafter think of it as the independent world. What makes knowledge true is its ability to exist. What makes knowledge capable of existing is its suitability and use for different goals, especially those that enable us to explain, control, and predict our behavior. Later, Glasersfeld (1997) added the idea that knowledge is the result of creative activity, and therefore cannot be transferred to a passive receiver. Each person, he suggested, who purportedly “receives knowledge” actually builds it up, actively and individually. Even so, learners may be guided in a general direction, and may have conceptual structures that will help prevent poor decisions. Although this type of radical constructivism seems to have had some good days in the education system, it is far more difficult to measure achievements according to process rather than according to results. The system always seems to prefer shortcuts.

Gardner (1983) tried a more practical way when he described intelligence as including many kinds of intelligence. Gardner found himself adding to his list every year, one or two new kinds of intelligence. Perkins (1995) suggested focusing on “soft” intelligence, which may be learned easily. Goleman (1995), unlike Glasersfeld and Gardner, based human intelligence on one seemingly simple factor that he called emotional intelligence. Still another group of researchers went further and based their approach on the work of Jung (1971), suggesting development of a taxonomy of personality called MBTI (Myers-Briggs Type Indicator), which describes 16 kinds of personalities (Myers, 1962; Myers & Myers, 1980; Myers & McCaulley, 1985; Ring, 1998). MBTI makes many distinctions: between personalities—Extrovert vs. Introvert; between perceptual functions—Intuition vs. Sensation; between judgmental functions—Thinking vs. Feeling; between ways of dealing with the external world—Judging vs. Perceiving; and other distinctions. Grigorenko and Sternberg (1997) added distinctive ways of treatment—Space and Time. She maintained that it is possible to categorize people as Abstract or Concrete in their relation to space, and as Continuous or Random in their relation to time. Finally, Miller (1997) suggested a slightly different taxonomy which distinguishes between Analytic vs. Holistic individuals, Objective vs. Subjective, and Emotionally-stable vs. Emotionally-unstable.

What is common to all of these thinkers is that they attacked the “empire of the person,” which flew the flag of IQ, let it rule, and then kept adding components as others failed to gain empirical support. All of these theorists seemed to maintain that the phenomenon known as human intelligence is elusive and suspect, and refuses to adapt itself to human concepts (Harpaz, 1998).


The broad and colorful cloth woven of many approaches, only a few of which we comment on in this paper, indicates that as the 21st century begins we have not yet learned to develop a simple scale of cognitive goals with whose help it will be possible to prepare the next generation for taking on the task of continuing to lead humankind.

If this is indeed a correct assessment of the current field of research on human characteristics, and since there is still no clearly accepted definition of intelligence and the changes in everything around us seem so deep and dynamic, it makes sense to try a different approach. The new approach has to be more relevant, at least, for the educational system. Our approach is not meant to be a new theory that explains what intelligence, cognition, or some other form of thinking is. Rather, it is meant to give us more concrete cognitive goals that will better prepare our children for the many challenges they will confront at every turn in the future. These goals are formulated in terms of thinking or learning skills. We used the language of thinking skills, behavioral terms, and keywords to lead us on the arduous journey of preparing our children better for the future. We suggested the addition of a new layer to the foundations and advantages of Bloom’s very practical taxonomy in the hope that it will advance schooling goals and make them more relevant to our children’s future. We have focused here on a new, seventh category of skill, which we offer to the educational and teacher-training systems of the coming decades (see also Passig, 2000, 2001, 2003).

The implications of this revamped Bloom’s taxonomy for primary, secondary, and higher education are important. Bloom’s original taxonomy affected curricular design and theories of assessment in many ways. A melioration skill is standing on the shoulders of these implications, supplements the educational system with a variety of pedagogical processes and alternative testing venues. We are engaged in studies that test computerized learning units in science for grades K-6 and 7 (Cohen, 2003), as well as for teachers in their professional development (Passig & Margaliot, 2003). The aim of these studies is to find evidence that the skill of melioration is developmental. We are also developing a tool that would measure the level of melioration that has been developed as a result of a specified course of study. Preliminary results suggest that melioration skills are learned, that melioration as a skill can be measured reliably, and that melioration skill correlates with other cognitive skills and processes. We hope to be able to report on these findings in the near future.

In an age in which knowledge has become the primary resource of advanced nations, it has also lost its metaphysical validity and its state of being concretely absolute. As Harpaz (1998) writes, knowledge has become “floating knowledge”. Therefore, in presenting taxonomy of future skills, we need not point to eternal skills. This approach demands that there be a regular examination of the skills our children will be expected to display, among other educational goals that are important components of the environment in which our children will live. We believe that every generation will need to return to the kind of thinking presented in this article over and over again, and examine the definitions and terms detailed in it. Each generation will have to bring the terms up-to-date, change them, and add to them. This is what our generation owes to our children and their children.

The skill of choosing the appropriate chunks of information, and applying them to the solution of problems in different time and space-dependent situations, thereby meliorating the chunks, may well be the skill demanded by anyone who wants to function successfully in the 21st century. Adaptation, connotation, and simulation are the behavioral terms and keywords that will then be constantly with them. We hope that understanding the skill of melioration will help those who develop school curricula prepare coming generations more effectively.


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Cite This Article as: Teachers College Record Volume 109 Number 1, 2007, p. 24-50
https://www.tcrecord.org ID Number: 12716, Date Accessed: 5/28/2022 6:23:14 AM

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About the Author
  • David Passig
    Bar-Ilan University
    E-mail Author
    DAVID PASSIG is heading the Graduate Program of Educational Technology at the School of Education, Bar Ilan University, Israel. He is teaching graduate courses on Educational Futures and is heading the Virtual Reality Lab.
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