Editor | On 12, Apr 2002

Dr. Rodney K. King
www.supersmartnetwork.com
r.k.king@supersmartnetwork.com
Copyright 2002. Dr. Rodney K. King.

Readers of The TRIZ Journal are authorized to download and make one copy of this article for personal study. No other reproduction is permitted without prior written permission from Dr. Rodney K. King.

Foreword
This article introduces the Theory of Ideal SuperSmart Learning and contains a set of tools for personal, business, product and institutional development.
The Theory of Ideal SuperSmart Learning is like a theory of everything and provides a framework for activities including the following:
• rapidly generating breakthrough ideas and gaining deep insights in diverse domains
• rapidly simplifying, learning, integrating, and applying methods of

– problem solving (including TRIZ and creative problem solving)
– creativity (the whole spectrum of creativity tools and techniques)
– ideas management (including mind mapping and concept mapping)
• rapidly solving problems involving conflicts, contradictions, or dilemmas in business as well as product development
• rapidly improving products in diverse domains
• conceptually designing or inventing products in diverse domains
• smarter, versatile, and accelerated learning in diverse domains
• rapidly create magic tricks and routines

The article on the Theory of Ideal SuperSmart Learning contains three parts.In part I, an overview of the philosophy and framework of the theory is presented. Part II presents applications of the theory. In particular, the theory is used to simplify and integrate tools of TRIZ as well as other problem solving methodologies. In part III, the main conclusions of the article are presented.

THE THEORY OF IDEAL SUPERSMART LEARNING:
A Versatile Holistic Framework for Rapidly Simplifying, Learning, and Applying TRIZ & Other Problem-Solving Methodologies Part I

PART I: OVERVIEW OF THE FRAMEWORK FOR IDEAL SUPERSMART LEARNING
1. INTRODUCTION
2. GOAL, OBJECTIVES, AND TOOLS OF IDEAL SUPERSMART LEARNING
3. THE IVY-PARADIGM AS THE MACRO-CONCEPTUAL FRAMEWORK FOR IDEAL SUPERSMART LEARNING
4. FURTHER DETAILS ON TOOLS OF IDEAL SUPERSMART LEARNING REFERENCES (Part I)

1. INTRODUCTION
Several years ago and in the course of my hobby, I encountered an impossible problem: How to systematically invent magic tricks? To this day, Im wrestling with the problem of automated invention.
It was my quest for a systematic method of inventing magic tricks that led me to TRIZ, which is a Russian acronym for the Theory of Inventive Problem Solving. Genrich Altshuller, a Russian scientist and naval patent officer, pioneered TRIZ in the 1940s. Information on the evolution of TRIZ could be found in Internet web sites1 and a few books in English. Initially, I was excited to discover TRIZ. Published comments on the background, development, and power of TRIZ led me to believe that I could use TRIZ to directly invent magic tricks. But, I was disappointed.

My serious reading on TRIZ began with Altshuller’s And Suddenly the Inventor Appeared. I later went on to read other publications, especially on the Internet. However, I found it difficult to thoroughly understand TRIZ, let alone apply it to solve my impossible problem of systematically and transparently inventing magic tricks. My basic academic and professional disciplines cover civil engineering,
infrastructure planning, and regional development planning. TRIZ, however, seems to be grounded in mechanical engineering and product development. Although there are claims that TRIZ is a generic methodology for problem solving and there are increasing attempts to generify TRIZ, TRIZ still appears to be limited in the context of openended or wicked problems, especially in non-physical systems.
The Theory of Ideal SuperSmart Learning (TISL) is the culmination of my efforts to find a framework that could be used for solving all types of problems: well-defined and ill-defined problems; close-ended and openended problems; “tame” and “wicked” problems; mathematical and non mathematical
problems; “soft” and “hard” problems. The framework of Ideal SuperSmart Learning is holistic and could be used for applying all methods of problem solving, creativity, and ideas management. In addition, principles and tools of Ideal SuperSmart Learning could be used to more systematically invent magic tricks as well as routines.

In the rest of this article, I shall present some results of my experience in using the framework of Ideal SuperSmart Learning. I shall outline a framework that could be used to not only simplify the learning and application of TRIZ but also integrate TRIZ with other methodologies of problem solving, creativity, and ideas management.

2. GOAL, OBJECTIVES, AND TOOLS OF IDEAL SUPERSMART LEARNING

In the Theory of Ideal SuperSmart Learning, smart and versatile learning are assumed to be at the centre of not only successful problem solving, creativity, and ideas management but also rapid product improvement, innovation, and invention. Ideal SuperSmart Learning could be defined in many ways. One approach is based on the concept of supersmartness . The focus in this article, however, is from the general perspective of ideality and in particular, an ideal object. An ideal object is defined as a system that either infinitely demonstrates its potential functions and properties or infinitely attains its objectives under (internal) conditions of ideality, e.g., using no external (additional)
resources or freely available resources, and without causing any disadvantage or negative harmful/undesirable) side effect. The aforementioned definition refers to an ideal object at a macro-level. At a meso-level, an ideal object could be regarded as a closed (self-contained), self-organising, self-informative, and self-regulating system that has infinite efficiency and versatility but may not materially exist. An ideal object could be a field, wave, or void that has ideal elements and attributes as well as belong to an ideal supersystem. Also, an ideal object is
assumed to be implicitly or explicitly purposeful. The goal of Ideal SuperSmart Learning subsumes this concept of an ideal object.

The crux of the Theory of Ideal SuperSmart Learning is that in an ideal world, one would deeply question, understand and know everything from nothing and in no time. This goal, together with objectives and tools of Ideal SuperSmart Learning, is presented in Fig. 1.

The goal of Ideal SuperSmart Learning is acknowledged to be impossible. For instance, it would be an impossible task for someone to know and understand everything (in the universe) from nothing and in no
time. The goal of Ideal SuperSmart Learning therefore reflects utopic ideality. This goal, like a normative mission statement for an organisation, provides a constant vision and an ideal orientation as well as a benchmark for determining deficits of the actual from the ideal. Utopic ideality is also useful for exploring unusual possibilities, especially when searching for creative (out-of-the-box) concepts.
In the real world, minimality often replaces nothingness or zeroness. For day-to-day activities, one would therefore speak of practical ideality and practically ideal objects rather than utopic ideality and utopic ideal objects. Many practically ideal objects may appear conceptually unusual but are highly effective and/or efficient with respect to their functions. Nature, through the process of evolution and natural selection, provides many examples of practically ideal objects and solutions, i.e., systems that are largely self-contained, self-organising, self-informative, self-regulating, and versatile (adaptive). In human learning environments, supersmart learners epitomise practical ideality. A supersmart learner would rapidly know as well as understand many and diverse subjects using an apparently small knowledge base.

Supersmart learners often display mastery of skills of versatile problem solving, creativity, and ideas management as well as self-directed learning. Supersmart learners in real life are often described as geniuses or polymaths. The key and rather ideal assumption of this article is that Ideal SuperSmart Learning is learnable, i.e., everyone has the potential to be a supersmart learner. Ideal SuperSmart Learning could be regarded as a language that anyone could learn and speak.

Objectives of Ideal SuperSmart Learning directly relate to the goal of utopic ideality but are nevertheless pragmatic. The objectives focus on general activities such as versatile thinking, problem solving, creativity, and ideas management as well as specific tasks such as improvement, invention, and identification/detection. One aim of Ideal SuperSmart Learning is to develop as well as make available a vocabulary and language for more fully understanding and quickly coping with uncertainties, dilemmas, and complexities in the Information Age. A hierarchy of tools has been devised to attain the objectives of Ideal SuperSmart Learning. At the highest level are macro-tools. These include paradigmatic tools such as Template theory, PAO thinking, and B.E.A.R. strategy as well as other macro-tools such as ideal metacognition, ideal meta-learning, ideal meta-ideas management, and structured intuition, analysis, and reflection. Meso- and micro-tools include the following: system of problem archetypes and anti-archetypes; solution archetypes; object mapping; the creative web; versatile map; IVY-template; SCAMPER-DUTION matrix; IVY-matrix of bipolar variables, dimensions, and criteria; objectBots, scenetransformation matrix; creaLogic, paoisms; object-templates.

3. THE IVY-PARADIGM AS THE MACRO-CONCEPTUAL FRAMEWORK FOR IDEAL SUPERSMART LEARNING
Although the concepts of ideality and an ideal object are mentioned during the discussion on the goal of Ideal SuperSmart Learning, the paradigm on which Ideal SuperSmart Learning rests is not described. This section focuses on that paradigm, which has the acronym IVY: Ideality, Versatility, and Ympossibility. IVY- could be broadly regarded as a prefix that means the following: self-contained, self-organised, self-informative, selfregulating, and versatile (multi-polar).

The IVY-paradigm is fundamental to deeply understanding and applying Ideal SuperSmart Learning. The IVY-paradigm directly relates to all objectives and nearly all tools of Ideal SuperSmart Learning. In Ideal SuperSmart Learning, a practically ideal object has multi-level properties and is synonymous with an IVY-object. Thus, an IVY-object not only performs its core, primary, or technical functions but also is self-contained and displays, at no (extra) cost, properties of self-organisation, self-informativeness, selfregulation, and versatility. The prefix, IVY-, could be applied to any artefact, organism, or idea. Consequently, we may have the following: IVY-final result; IVY-mobile phone; IVY-pen; IVY-air bag; IVY-student; IVY-spoon; IVY-effect; IVY-prop; IVY-gimmick; IVY-character; IVY-trick; IVY-screen; IVY-problem; IVY-method; IVY-solution; IVY-TRIZ; IVY-organisation; IVY-process; IVYmanagement; IVY-team.

As indicated in the acronym, IVY, the paradigm rests on the triangle of ideality, versatility, and impossibility. In a way, the concepts of versatility and impossibility could be derived from the concept of ideality. Nevertheless, I consider versatility and impossibility to be important enough to warrant separate treatment. Unlike in TRIZ, the ultimate output in Ideal SuperSmart Learning, i.e., the IVY-Final Scenario, is bipolar. There is a best (positive) IVY-Final Scenario at one end and a worst (negative) IVY-Final Scenario at the other end. The latter could be referred to as anti-IVY-Final Scenario. The notions of bipolarity and qualitatively different final scenarios indicate that the concept of ideality is not value-judgement free. In short, the IVY-Final Scenario is subjective.
Best ideality is often meant when people speak of ideality. However, the idea of worst ideality should not be ignored. Worst ideality is a provocative construct that is useful for creative (out of the box) thinking, failure analysis, recognition of pervasive constraints in systems, and (re)formulation of objectives that take into account unusual causal factors in situations. Also, the concept of worst ideality could be used for carrying out extreme sensitivity analysis and subsequently, devising extreme contingency scenarios (plans).
In this article, best IVY-Final Scenario is considered as the default output of Ideal SuperSmart Learning. Unless otherwise stated, best IVY-Final Scenario is synonymous with the term of IVY-Final Scenario.Selected conditions and criteria for the IVY-Final Scenario are contained in table 1.

The range of conditions and criteria indicates that there is no unique description of ideality.11 Many levels and dimensions of ideality exist. Although the majority of criteria reinforce each other and are positively correlated, a few criteria such as ideal nothingness and ideal infinity conflict with each other. Utopic criteria, which are often used in science and theoretical engineering, could be used to practise, reflect on, and facilitate improbable thinking.
Between the IVY-Final Result and anti-IVY Final Result lies the neutral (zero) or non-IVY-Final Result. The non-IVY-Final Result is regarded as transitory or on the edge of chaos. Consequently, an object on a bipolar spectrum of IVY-Final Scenario moves either towards or away from the best IVY-Final Scenario.
The IVY-Final Scenario could be purely descriptive or may be operationalised using rating scales. The most common rating scales are the ratio and ordinal scales. The concept of IVYality replaces the IVY-Final Scenario at an operational level. Thus, one may speak of levels and degrees of IVYality.
The basic measurement variables of IVYality are advantages and disadvantages. 14 Consequently, the level of IVYality could be expressed on an interval scale and defined as the difference between the advantages and disadvantages. The level of IVYality corresponds to the concept of net worth (benefit).

The degree of IVYality (or IVYality efficiency)15 refers to the ratio of advantages to disadvantages. In an ideal world, advantages would be infinite and disadvantages would be zero. Consequently, both the level and degree of IVYality would be infinite. In the real world, however, constraints exist and
a maxi-mini strategy, i.e., maximisation of advantages and minimisation of disadvantages, would be adopted in order to maximise the IVYality-efficiency or level of the IVY-Final Result. Versatility is an integral part of the IVY-paradigm as well as the concept of an ideal or IVY-object. In Ideal SuperSmart Learning, versatility is synonymous with the concepts of multi-level hierarchy and multiple
bipolarity. Versatility is encompassed in the principle of object equivalence, principle of multi-polarity, and B.E.A.R. strategy, each of which is an element of Versatile Thinking. B.E.A.R. is an acronym for Bring Every Available Resource. The B.E.A.R. strategy is a cognitive approach that
encourages versatile and improbable thinking; it is more an attitude towards thinking than an operational strategy in physical systems. Thus, the B.E.A.R. strategy implies that, to achieve an objective, a person should consider every available resource, especially resources in the span of a bipolar spectrum such as for creative and logical thinking. Also, multi-level resources, e.g.,
resources at level of a system, its elements, and supersystem, should be considered. A principal aim of the B.E.A.R. strategy is to overcome psychological inertia and facilitate improbable thinking during activities of problem solving, creativity, and ideas management.

Ympossibility or impossibility is the aspect of the IVY-paradigm that deals exclusively with overcoming psychological inertia, especially facilitating improbable thinking in problem solving, creativity, and ideas management as well as in performance delivery, i.e., theatrical communication or presentation. Magic is a metaphor for impossibility. Magic could be used to enhance improbable thinking. My main approach for confronting and being comfortable with the impossible is to analyse, improve, create, and present magic (conjuring) tricks as well as routines. A useful, constructivist maxim for rapid innovation, creativity, and design is to always start with at least two known(dis/similar) objects and operate on the object using improbable thinking and its tools.

At the core of every successful magic trick is bipolarity or what TRIZ calls a physical contradiction.18 In the language of TRIZ, principal props and gimmicks in magic tricks (apparently) perform their functions and do not perform their functions. For instance, in a magic trick involving the disappearance of a coin, the physical contradiction may be expressed as the coin exists and does not exist. The formulation of a magical disappearance effect as a physical contradiction suggests several dichotomous strategies or separation heuristics for resolving the (apparent) physical contradiction. TRIZs separation heuristics include the following solution-paths: separation
in space; separation in time; separation between part and whole; separation upon condition. Thus, magic or conjuring affords many opportunities not only for exploring, discovering, formulating, and resolving physical contradictions (dilemmas) but also for demonstrating them in an entertaining manner. Conjuring could facilitate the systematic development of sub-categories for each separation heuristic. Similar opportunities exist for dealing with technical contradictions (dilemmas) in the improvement or design of gimmicked apparatus and utility gimmicks.

An activity for developing versatile problem solving is trying to figure out – from technical, psychological, and presentational perspectives – the secrets of presented, recorded, and catalogued magical effects. I have dubbed this approach of scientifically studying magic tricks as conjurology. Conjurology is an essential component and enhancer of Ideal SuperSmart Learning.

4. FURTHER DETAILS ON TOOLS OF IDEAL SUPERSMART LEARNING
Some tools of Ideal SuperSmart Learning are listed in Fig. 1; an interaction matrix may be prepared to illustrate interrelationship between tools. Of the tools, only macro-tools are covered in this section. Macro-tools provide a conceptual framework for devising tools at the meso- and micro-levels. Also, macro-tools aim to facilitate a paradigm shift, eliminate psychological inertia and transform attitudes not only during problem solving, creativity, and ideas management but also thereafter. A qualitative but strong evidence of learning is positive transformation of behaviour towards dealing with (similar) problems.
Like macro-tools, meso- and micro-tools are generic. However in this article, meso- and micro-tools are presented within discussions on specific methodologies such as Creative Problem Solving (CPS), TRIZ, Advanced Systematic Inventive Thinking (ASIT), and Unified Structured Inventive Thinking (USIT). The reason behind this approach is to focus on practical applications rather than theoretical aspects of meso- and micro-tools. As the B.E.A.R. strategy and conjurology are highlighted in the previous section, this section presents an overview of the remaining macro-tools.

4.1 Paradigmatic Tools
Template Theory for Versatile Creativity
Templates play a central role in the application of Ideal SuperSmart Learning and in particular, Versatile thinking. A template, pattern, or (archetypal) plot could be defined as a deep (intrinsic) or surface (extrinsic) structure of a closed (self-contained) system. Like in language, templates
may be used to produce outputs that are qualitatively or quantitatively similar. Outputs that are to be regarded as novel at a particular level of observation, however, should be quantitatively and qualitatively dissimilar.
Many disciplines implicitly use templates in conceiving and solving problems as well as in generating creative (out-of-the-box) ideas. Methodologies that directly focus on a template approach include the following: TRIZ methodology; Christopher Alexander’s Pattern Language; Software Design
Patterns; Jennifer Kemeny’s Systems Archetypes; Adrian Slywotzky and David Morrison’s Profit Patterns; Joseph Campbell’s Hero’s Journey; Dariel

Fitzkee’s The Trick Brain. In my view, the template, pattern, or (archetypal) plot approach may be the most efficient means for rapidly acquiring creativity and problem solving skills across a wide variety of domains. Template approaches often focus on documenting existing best and worst (anti-) solutions such as in benchmarking and software design patterns. However, templates could have a normative orientation as in the case of archetypal (dramatic) plots, heuristics, algorithms, and patterns of evolution. Below is my summary of axioms of the Template Theory for Versatile Creativity.

(i) The occurrence and mutation of templates: Every object has one or more templates. And like memes, templates evolve and are passed from one generation to the next. Every solution to a problem constitutes a template. In general, templates that move towards IVYality survive and those that move away tend to suffer death.
(ii) Hierarchy and number of templates: Templates in a methodology could be presented as a hierarchy of at least three levels: macro,meso-, and micro-levels. Templates become more qualitatively different and specific as well as increase in number as one moves down the hierarchy from macro- through meso- to micro-levels. Macrotemplates are generic and based on heuristics.28 In contrast, micro- templates tend to be specific and algorithmic. Experiential or concrete knowledge is often required for the formulation and use of micro-templates. In every domain and at a particular time, there is a finite number of elemental templates that form an alphabet or higher-order templates. Similar higher-order templates may exist in different domains.
Myriad higher-level templates, patterns, concepts, meanings, and objects could be generated using combinations of the alphabet of basic templates. Schemas and scripts (Boden, 1996) are examples of
higher-order templates.
(iii) Types of structural templates: There are four basic structures for representing templates: stone-heap, linear, hierarchical, and network structures; see table for example of (object) structural templates. Templates could exist in physical reality and may be visual, verbal, kinaesthetic, olfactory, and/or gustatory. Also, templates may be rigid (algorithmic)31 or flexible (heuristic). Out-of-the-box thinking often uses flexible verbal templates. So-called uncreative people predominantly use rigid templates. Finally, templates could be means (tools) as well as ends.
(iv) Generative rules for templates: In every template are embedded many and varied rules for generating and/or representing the template.
(v) The occurrence of novelty: Basic creativity or novelty occurs when, from an observer’s point of view, generative rules for coherent templates especially those that are explicitly known – are violated to form “emergent” (unexpected but higher-level coherent) patterns and objects. Basic creativity involves bisociation (Koestler, 1971) and transformation (unification) of conceptual spaces.

(vi) Enhancing “basic creativity”: “Unusualness” or improbable thinking is at the epicentre of creativity. Creativity involves possessing, developing, and/or applying unusual but coherent perceptions to situations. “Basic creativity” could be enhanced by the following experiential activities:
• Unusually observing, recognising, discovering, and exploring templates (patterns)
• Unusually deconstructing and analysing templates (patterns)
• Unusually adapting and modifying templates (patterns)
• Unusually exploiting or exhausting existing multi-level resources, opportunities, and constraints33
• Unusually combining, synthesising, “sculpting”, or constructing templates (patterns)
• Unusually envisioning and transforming templates (patterns)
• Reflecting on each of the above activity

Pattern And Object (PAO) Thinking
Pattern And Object (PAO) Thinking™34 operationalises the Template Theory, especially its first axiom. The philosophy of PAO Thinking™ is encapsulated in the following three interrelated principles:
(i) Principle of Object Equivalence
“Everything is an object.”
This principle is derived from the concept of an object in Object-Oriented Programming.35 In PAO Thinking™, an “object” refers to both tangible and intangible items. Artefacts, nature, elements of nature (“naturfacts”), and ideas are examples of objects.36 This principle of object equivalence
facilitates analogical thinking, knowledge transfer, and the development of a “creative database.”
The definition of an “object”, in the format of a paoism, is as follows:
an object is Â…
the universe of
an object is
an object of
an object is Â…

The above definition indicates that an object is a nested (hierarchical) system. The format of the definition is an adaptation and extension of Gertrude Stein’s famous remark, “A rose is a rose is a rose is a rose.” The above definition of an object is open-ended as well as recursive. The meaning of an object is retained when the definition is read from bottom to top. The definition’s circularity could be illustrated by arranging the words to form a circle or loop.
Also, the format is a template in which an object could be replaced by a specific item (for example, the word “fractal”, “holon”, “resource”, “function”, or “attribute”) or successively different items.
An alternative format for representing an object is presented in table 2. Elemental parameters in table 2 could be obtained from TRIZs parameters. The cells of the matrix could contain verbal and/or graphic descriptions. The template for the properties of an object is particularly useful for deconstructing and documenting the unitary space of an object during problem solving, creativity, and ideas management especially when developing, improving, or inventing products. The object-matrix could also be used for identifying and illustrating technical contradictions in a given system. If the properties of several (similar) objects are recorded in the object-matrix, this matrix could be
used as a morphological box (matrix) for conceptually designing objects.
(ii) Principle of Interconnectedness
“Every object has an alphabet, a vocabulary and pattern.”
This principle reflects reductionist, holistic, and systemic thinking. The principle of interconnectedness implies that everything in the universe is connected. Every object has its own elements and the object is also part of a larger (super-)system. This pattern principle has been echoed by the physicist, David Bohm, who says, “Everything is enfolded into everything.”
And Leonardo da Vinci expresses the principle of interconnectedness when he says that “Everything comes from everything and everything is made out of everything, and everything returns into everything …”
(iii) Principle of Multi-polarity
“Every object is the same and different.”
This principle highlights the multi-level nature of objects. At the highest level of abstraction, all objects are the same. At the lowest level of abstraction, all objects are different. Nevertheless, the principle of multi-polarity may be metaphorically true in the case of HeisenbergÂ’s uncertainty principle. Using a poetic license within the framework of the principle of multi-polarity, one may
say: “The speed of an electron matches and does not match.”

Table 2: Object-matrix for defining the “unitary space” of a system (“object”)
Name of system (“object”): …………………………………….………………….
Main function(s)/objective(s): Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â…Â….Â…Â….

Bipolarity is embedded in the concept of multi-polarity. If “different” is interpreted as “opposite” in the original formulation of the principle of multipolarity, the expression becomes, “Every object is the same and opposite. This latter formulation is regarded as the principle of bipolarity, which is a special and normative interpretation of the principle of multi-polarity. An
example of the principle of bipolarity is the existence of light as a wave and particle. The concepts of unity of opposites (dialectical tension) and physical contradictions (dilemmas) are strongly related to the principle of bipolarity. All bipolar objects41 and consequently, all physical contradictions (dilemmas) may be expressed as a paoism in the basic format:
“[word] is [opposite word] is …”
The evaporating cloud or conflict resolution diagram in the Theory of Constraints provides another means of depicting physical contradictions (dilemmas) that are derived from an (organisationÂ’s) objective.
Hirshberg (1999) comments that living with ambiguity is essential for innovative thinking. The (normative) statements of the principles of bi- and multi-polarity are purposely ambiguous. They embody concepts of object equivalence, dialectical tension, uniqueness, oneness (unity of opposites),
and “infinity in all directions.”

4.2 Other Macro-Tools
It is being increasingly recognised that a personÂ’s ability to successfully deal with novel and complex tasks increases with the level of that personÂ’s engagement in thinking about thinking (meta-cognition) and learning about how to learn (meta-learning). From my experience, I would add meta-ideas
management (managing ideas about ideas management) to meta-cognition and meta-learning. At an institutional level, meta-ideas management encompasses knowledge management. However, the discussion in this article focuses on personal ideas management.
Ideal SuperSmart™ Learning assumes that personal knowledge maps and level of understanding are greatly enhanced by regular activities of metacognition, meta-learning, and meta-ideas management as well as structured intuition, analysis, and reflection. The latter approach recognises the role of
intuition in learning and especially draws on tools for meta-cognition and meta-learning. People have models and assumptions about meta-cognition, meta-learning, and meta-ideas management. In fact, people are bounded by such models and assumptions, particularly if they are implicit rather than explicit. Ideal SuperSmart™ Learning therefore focuses on making explicit our models so that we could reinforce, expand, and/or transform them. No doubt, how we think, learn, and manage ideas affect the quality of our cognitive and physical outputs.
Meta-cognition, meta-learning, and meta-ideas management are briefly discussed below from two perspectives: utopic and practical ideality on the one hand and an ideal object on the other hand. Due to the scope of this article, humans are considered to be the principal agents as well as recipients
of meta-cognition and meta-learning. Nevertheless, these cognitive processes and especially meta-ideas management could be enhanced using technology.
Ideal meta-cognition refers to a process that involves constantly thinking about thinking under (internal) conditions of ideality. All strategies and conditions of utopic ideality, which are listed in table 1, relate to ideal metacognition.
Criteria for practical ideality, however, could be selected with respect to the resources that are required for the domain- or subject-specific task, to which meta-cognition should be applied. My general strategies and criteria for moving towards ideal meta-cognition include the following:

• ideal (“functional”) nothingness: thinking about as well as observing “nothingness”43 and minimalism
• ideal “infinity”: using versatile thinking and B.E.A.R. strategy; trying to devise IVY-objects
• ideal efficiency and “automaticity”: trying to resolve physical as well as technical contradictions (dilemmas); regularly observing and trying to apply the following principles: self-regulation; self-appraisal or analysis; self-monitoring; reflection; self-critique
• ideal conflict resolution and unity: trying to use bipolar principles such as win-win and maxi-mini-strategies; unification of opposites; using improbable thinking and trying to invent magic tricks as well as routines; thinking about impossibilities
• ideal simplicity, variety, and beauty: searching for simpler and more elegant situations; adding variety, asymmetry, and “unusuality” to situations; practising structured and unstructured (organic) improbable thinking; “beautifying” situations

• ideal identification/detection: observing as well as classifying patterns, anomalies (“unusalities”), and causes in situations; trying to identify biand multi-polar objects as well as IVY-objects in real life For a specific task, the process of ideal meta-cognition involves a hierarchy
of reflection45 as follows:
• Level 1 – Occurrence of task: Reflection-in-action
• Level 2 – Reflection on action, i.e., reflection on reflection-in-action
• Level 3 – Reflection for action, i.e., reflection and planning for similar tasks in future
Like in ideal meta-cognition, ideal meta-learning involves constantly learning about how to learn under (internal) conditions of ideality. In ideal metalearning, learning becomes a way of life and a lifelong activity. In some cases, learning may become an obsession, albeit a positive one! Activities for ideal meta-learning include learning about how people learn to observe and solve problems, learn to create or design objects, and learn to manage ideas.
Criteria for ideal meta-learning include self-learning; self-monitoring and regulation; self-directed creativity; autonomous problem solving; holistic ideas management. In short, an ideal meta-learner is synonymous with an “IVYstudent ” (from the perspective of utopic ideality) or a highly motivated and
self-managed learner (from the perspective of practical ideality).
In Ideal SuperSmart™ Learning, the main models for enhancing metalearning are the Problem-Situated Learning and Transformative (PSLT) Game, Pyramid Model of Understanding, and Versatile Matrix of
Strategies for Problem Solving and Creativity. The PSLT game is shown in Fig. 2. This model emphasises problem-situated learning and synthesises ideas from Laurillard’s conversational framework46, Kolb’s learning cycle, Bigg’s SOLO taxonomy, and Schön’s reflective practitioner. The PSLT game could be used as a model for illustrating processes of learning, teaching, and reflection, for example in TRIZ and other problem solving methodologies.
A key assumption of the PSLT game is that practically ideal learning involves a learner recursively or “conversationally” experiencing a loop that consists of three modes of learning: expository learning, (theoretical) problem solving learning, and experiential learning. In addition, a facilitator – preferably, a more knowledgeable person (“expert”) – enhances learning. When a learner’s knowledge base is small, the preferred cycle or loop for a given task is from expository learning through (theoretical) problem solving learning to experiential learning and back to expository learning. As shown in Fig. 2, recursive relationships exist between the various modes of
learning.
A more knowledgeable learner may “short-circuit” the loop by directly proceeding from a given task to the experiential level. The learner could then focus on experiential and other modes of learning as the learner thinks appropriate. Facilitation for more knowledgeable learners could take place in
a team of peers and/or through an “expert.” Mastery of a subject occurs when a learner creates a dense network of knowledge maps and skills by repeatedly as well as recursively going through the loop of expository, problem solving, and experiential learning. It should be noted, however, that the PSLT game focuses on individual learning. The basic notions of the PSLT game could be applied to team (group) learning but a different order of interpersonal dynamics operates in environments of collaborative learning.

Any learning task could be structured according to the PSLT game. For example, learning creativity could be structured as follows: “expository creativity”; “problem solving creativity”; “experiential creativity”; “reflective creativity.” Similarly, the learning or teaching of TRIZ might be structured as “expository TRIZ”; “problem solving TRIZ”; “experiential TRIZ”; “reflective TRIZ.”
The pyramid model distinguishes four levels of understanding:
• Level 0 – Little or “no” understanding
• Level I – Low-order understanding (“novice” learner)
• Level II – Intermediate-order understanding
• Level III – High-order understanding (advanced learner or ”expert”)

The pyramid model describes the evolution of a learner’s understanding using the concepts of “knowledge deficit”, “potential higher-order knowledge map”, and “multiple-cycle learning49.” Also suggested in the pyramid model are pedagogy-based mechanisms50 for transforming a learner’s existing knowledge map, i.e., moving a learner’s understanding from one level of understanding to another.
A novice learner has loosely integrated or “stone-heap” knowledge maps. In contrast, an advanced learner or expert possesses tightly integrated or densely networked knowledge maps. The more loops a learner makes through the recursive cycle of expository, problem solving, and experiential
learning, the tighter is the knowledge map and the greater is the potential for ascending the pyramid of understanding. Together with the PSLT game, the pyramid model could be used for planning as well as devising learning strategies, especially for novel areas of study such as in TRIZ and conjuring.

The versatile matrix of strategies for problem solving and creativity is an integral part of the versatile map™, which is discussed in section 5.3. The versatile matrix is presented as table 4. This matrix may be used to identify deficits in strategies and techniques for meta-cognition as well as metalearning. The matrix may also be used to select alternative strategies and techniques for problem solving as well as creativity.
Ideal meta-ideas management deals with two main aspects of ideas management: managing physical records (records management) and managing the processing, storage, and retrieval of ideas (knowledge management). The focus of this article is the management and processing of ideas at a personal level.
One of the tools in Ideal SuperSmart™ Learning, which deals with personal ideas management, is object mapping. Object mapping is based on the principle of object equivalence and incorporates the B.E.A.R. strategy. On an object map, everything – an element, a system, or supersystem – is regarded
as an “object.” Object mapping integrates the tools of mind mapping, concept mapping, cluster mapping, and “natural language mapping.” Thus, all graphic and textual tools of ideas processing as well as principles of memory management are welcomed when using object mapping. Another useful tool
for constantly recording and managing ideas is an idea log or journal. Structured Intuition, Analysis, and Reflection (SIAR) is the operational philosophy for problem solving, creativity, and ideas management, especially when information is sparse. Tools for meta-cognition, meta-learning, and
meta-ideas management are strongly linked to the approach of SIAR. The SIAR approach assumes that intuition, analysis, and reflection should be carried out within a structured framework, especially using higher-level templates. The main tools for applying the SIAR approach include mindstorming (brainstorming) as well as the versatile map, creative web, IVYtemplate, and IVY-matrix of bipolar variables, dimensions, and criteria. These latter templates are discussed in more detail in part II of this article.
Next month, parts II and III of this article on the Theory of Ideal SuperSmart™ Learning will be presented.

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About the author
Dr. Rodney K. King
www.supersmartnetwork.com
r.k.king@supersmartnetwork.com
* Meta-inventor
* Inventor/Author of many items including the following:
Theory of Ideal SuperSmart™ Learning;
Versatile Thinking™ (including PAO Thinking™ and Versatile Map™);
Six Colored Eyes
* Developer/Teacher of “S-TRIZ”
* Conjurologist
* Civil Engineer; Infrastructure Planner; Regional Development Planner
* Problem Solving, Creativity, and Ideas Management Consultant/ Facilitator
Copyright 2002. Dr. Rodney K. King.
Readers of The TRIZ Journal are authorized to download and make one copy of this article for personal study. No other reproduction is permitted without prior written permission from Dr. Rodney K. King.