VIEW (Selby, Treffinger, & Isaksen, 2002) is a new instrument for assessing problem solving style, for use with individuals from ages 11 through adult. We describe the theoretical and research foundations for the instrument, emphasizing the interactions between work on the Creative Problem Solving (CPS) process and the psychology of the person (including personality and individual differences). We also describe three specific areas of theory and research that influenced the development of VIEW: learning style, psychological type, and cognitive style. We present definitions of VIEW’s three main dimensions, and we summarize the initial psychometric support for the measure. Finally, we describe ways that VIEW can be used by researchers and practitioners in relation to CPS and change management.
The purposes of this article are: to present a new instrument for assessing problem solving style, called VIEW (Selby, Treffinger, & Isaksen, 2002); to present its background and rationale; and, to identify its potential role and applications for research and practice. We begin by describing and summarizing the essential theoretical and research foundations underlying the development of this instrument: the important interactions between our work with the Creative Problem Solving (CPS) process (e.g., Isaksen, Dorval, & Treffinger, 2000; Treffinger, Isaksen, & Dorval, 2000) and the psychology of the person (with an emphasis on personality and individual differences). Those foundations evolved from a program of research called the Cognitive Styles Project, spanning more than two decades of inquiry, in which our major goal has been to improve our understanding of the connection of person and process in the study and practice of creativity.
We next describe the three important components or “building blocks” in the development of VIEW: learning style, psychological type, and cognitive style. We provide definitions of the three main dimensions of our new measure and a summary of the preliminary psychometric support for the measure. Figure 1 illustrates the theoretical and conceptual structure for our work on style: the foundations, the building blocks, and the three dimensions of our new instrument. To conclude the article, we discuss possible uses of the instrument by researchers and practitioners in the field of creative studies.
The Foundations: CPS and the Psychology of the Person
The core foundations for our work, at the bottom of Figure 1, are the expanding and dynamic CPS framework itself, an understanding of the psychology of the person, and their interactions.
Our work with the CPS process has its historical foundations in the early practical writings of Alex Osborn. He was an advertising executive who wrote about CPS with a very practical orientation, but he also provided clear indications of the theoretical foundation for his work. In Osborn’s book Your Creative Power (1948), a precursor to his more well-known book Applied Imagination (1953), he identified a few key references as sources that shaped his emphasis on using imagination in business as well as in education. CPS drew on the early theoretical work of Crawford (1937), Dewey (1910), Wallas (1926), and others, and was initially viewed by Osborn as an applied integration of these theories, concepts, and methods. Osborn’s work provided the early foundation for the development of numerous creativity development programs and courses and was guided by the available psychological knowledge of the time. One important outgrowth of Osborn’s work involved the development of an instructional program (Parnes, 1967; Parnes, Noller & Biondi, 1977) and the testing of its effectiveness (Noller & Parnes, 1972; Parnes, 1987; Parnes & Noller, 1972a, 1972b, 1973a, 1973b, 1974; Reese, Treffinger, Parnes, & Kaltsounis, 1976). Our current approach to CPS (Isaksen, Dorval, & Treffinger, 2000; Treffinger, Isaksen, & Dorval, 2000) is a multi-dimensional system; although it provides a variety of powerful, cognitive, rational tools and strategies for solving problems and managing change, it also involves explicit consideration of the person, the context, and the need, as well as process.
The literature indicates that the skills needed for creative thinking and creative problem solving can be taught and improved upon through practice (Basadur & Hausdorf, 1996; Isaksen & De Schryver, 2000; Isaksen & Treffinger, 2001; Torrance, 1987) The individual characteristics a person brings to the learning or problem-solving situation influence many aspects of behavior, including the ways that people learn and apply problem-solving skills and, their approach to problem-solving situations. Individual characteristics also influence how people select and use problem-solving tools and the results they obtain, or their level of creative productivity, whether they are working alone or in a group (Schoonover, 1996; Martinsen & Kaufmann, 1999). Dunn, Beaudry, and Klavas (1989) demonstrated that identifying a learner’s style preferences, and matching instruction to those preferences, is effective in promoting greater retention of curriculum content. Similarly, both Selby (1987) and Basadur and Head (2001) reported that an individual’s or a group’s creative productivity can be enhanced if there is an understanding of the individual creative styles involved.
Our on-going experience as educators and trainers in CPS and change management also contributed to our conclusion that individuals view problems and their solutions differently, based on their style. Individuals may approach the tasks of understanding challenges, generating ideas, and preparing for action in very different ways. Some individuals seek out originality; others respond to it. Some proliferate ideas; others produce just enough promising ideas to keep the process moving. While some individuals prefer a methodical, in-depth approach others look for immediate action. These differences can be beneficial or detrimental to the success of individuals and groups when solving problems. Gaining an understanding and appreciation of one’s style is an important first step in the development of the metacognitive skills needed to choose behaviors, tools, and techniques that contribute to productivity. These skills are important to the individual problem solver, and also when groups or teams are working together to solve problems or deal with change.
Several important areas of psychological theory and research contributed to our conceptual work, and most recently to the development of our measure of problem-solving style. These included contemporary work on personality, individual differences, the construction of meaning, and metacognition.
Numerous approaches and models focus on a psychological understanding of the person or personality (e.g., Cattell, Eber, & Tatsuoka, 1970; Costa & McCrae, 1985; Eysenck, 1947; Guilford, 1975; Guilford, Zimmerman & Guilford, 1976; Tellegen, 1982, 1985). Many of these suggest that personality traits can be viewed as hierarchically arranged, with narrow and specific traits at lower levels, and global or broader trait dimensions or domains above (e.g., Goldberg, 1993; Costa & McCrae, 1995).
Cattell, Eber, and Tatsuoka (1970) looked at personality variables related to style. These included, for example, preferences for the Expedient or Conscientious (Factor G). Those whose behavior indicates an Expedient preference disregard rules and feel few obligations, while those with a conscientious orientation behave in a preserving, moralistic, rule-bound manner. Another factor involved preferences along the Practical/Imaginative dimension, with the Practical being defined as careful, conventional, and regulated by external realities, while the Imaginative is defined as careless of practical matters, unconventional and absent-minded. The Conservative/Experimenting dimension is labeled “Factor Q1.” Conservatives have respect for established ideas and being tolerant of traditional difficulties, whereas Experimenters are liberal and analytical with preferences for innovation and radicalism. Other style-relevant factors from personality theory and assessment include: shy/venturesome, tough-minded or tender-minded, and reserved or warmhearted.
Goldsmith (1994) divided the broad concept of personality into three main types of individual difference variables: intellectual and spatial abilities, personality traits, and cognitive styles. According to Martinsen and Kaufmann (1999), cognitive style involves the overlap of the independent constructs of personality and cognition, and can be located where cognition and personality intersect. Several other studies support this view. Gryskiewicz (1982), Carne and Kirton (1982), Tefft (1990), Jacobson (1993), and Gryskiewicz and Tullar (1995) all noted significant correlations between assessments of cognitive style and psychological type, specifically the Kirton Adaption-Innovation Inventory (KAI; Kirton, 1976, 1999) and the Myers-Briggs Type Indicator (MBTI®; Myers, McCaulley, Quenk, & Hammer 1998). Of particular note, Adaptors, as identified by the KAI seemed to identify strongly with Sensing and Judging types, as identified by the MBTI, while Innovators identified more strongly with Intuition and Perception (Isaksen, Lauer, & Wilson, in press). We approach cognitive style as a natural outgrowth and integration of personality and cognitive psychology.
Scholarly interest in individual differences has also been well established (Dillon, 1985; Dillon & Schmeck, 1983; Willerman, 1979) as a fundamental concern in psychological studies of the person. Creativity researchers have used two main approaches to investigate such differences. Researchers interested in creative abilities, competence, and degree of performance focused primarily on level of creativity (e.g., Albert, 1983; Spearman, 1927, 1931; Terman, 1925; Thurstone, 1927; Guilford, 1986; Torrance, 1979). Others have been more concerned with the mode, manner, preference or style of creativity (e.g., Kirton, 1987; Kogan, 1973, Messick, 1976).
That students bring a wide breadth of abilities, potentials, and style preferences to learning and to the application of what is learned, is now widely accepted by educational professionals (e.g., Armstrong, 1987, 1994, 1998; Brooks & Brooks, 1993; Harmin, 1994). The ability to be self-managing and self-motivating is recognized as vital to the success of an actively involved learner (Harmin, 1994). How one manifests these abilities is a function of style. Research has also provided us with a neurological understanding of cognitive style and the emotional consequences when the problem solving or change management context is in conflict with an individual’s style (Sylwester, 1995; Wolfe, 2001). In discussing why otherwise “intelligent” people fail, Sternberg (1986) cites 20 impediments such as: lack of motivation, lack of impulse control, the inability to complete tasks and to follow through, the failure to initiate, procrastination, excessive dependency, and distractibility. Each of these 20 impediments can be viewed as resulting from manifestations of style preferences or psychological type where strengths are not understood and employed in the service of productivity.
Treffinger, Young, Selby, and Shepardson (2001) reviewed and synthesized an extensive body of theory and research on the key characteristics associated with creativity. They summarized the important characteristics in four areas: generating ideas, digging deeper into ideas, exploring ideas with openness and courage, and listening to one’s inner voice. The characteristics involving generating lead to the production of promising options, while those involving focusing lead to workable solutions and action plans. The reviewers concluded that personality, style, type, and cognitive skills all play important roles in the specific behavior of every individual problem solver.
Based on our review of theory and research on the psychology of the person, we concluded that:
1. Although personality is a complex construct, several important clusters of characteristics have been affirmed by many theorists and researchers.
2. The variables in many style theories and measures also reflect several fundamental elements of personality differences.
3. Individual differences in personal characteristics need investigation and clarification specifically in relation to problem solving and change management.
Our interest in the linkages between person and process led us to a key question that had significant impact on our research. It is a question that still influences our inquiry into the effective and efficient presentation and application of CPS. The question was: “What CPS approaches work best, for whom, and under what circumstances?” Posing this question led to a series of studies regarding the impact of learning CPS (Isaksen & De Schryver, 2000), as well as to the development of an extended research initiative, the Cognitive Styles Project.
The Cognitive Styles Project, initiated by Isaksen and Treffinger (1985), is a program of research that investigates the conceptual and practical relationships between aspects and characteristics of the creative person, and the operations of the creative process. The research is described in more detail in Isaksen (1987) and Isaksen and Dorval (1993). The Cognitive Styles Project included investigations of the effects of certain stylistic preferences on learning and applying CPS.
Studies conducted as part of the Cognitive Styles Project used a variety of measures of learning style (Corbett-Whittier, 1986; McEwen, 1986; Wittig, 1985), cognitive style (Hurley, 1993; Selby, 1991; Selby, Treffinger, Isaksen & Powers, 1993; Puccio, 1987; Wheeler, 1995; Zilewicz, 1986), and psychological type (Tefft, 1990). Other studies examined the relationships between and among various stylistic measures (e.g., Joniak & Isaksen, 1988), between measures of style and level of creativity (e.g., Dorval, 1990; Isaksen, Dorval & Kaufmann, 1992; Isaksen & Puccio, 1988), and between measures of style and various manifestations of creative behavior (Franklin, 1997; Holmes, 1995; Isaksen & Pershyn, 1994; Pershyn, 1992; Puccio, Treffinger & Talbot, 1995). Finally, other studies investigated the relationship between cognitive style and psychological climate (Isaksen & Kaufmann, 1990; Isaksen & Lauer, 1999) and the impact of these relationships upon organizational behavior (Dutcher, 1997; Kaufmann, Isaksen & Lauer, 1996).
In summary, considering the important linkages between person and process contributed significantly to the development of VIEW, in the following ways:
1. We needed information about the person’s style in several specific areas or dimensions that could be linked explicitly to preferences and performance when solving problems and managing change.
2. Various theories and measures assessed certain dimensions of style that are relevant to CPS, but no single theory or measure addressed the specific linkages to CPS in a concise, comprehensive, and dynamic manner.
3. In order to enhance and extend an individual’s understanding of style and ability to apply that understanding in real-life situations, beyond providing general typologies or labels, it is important to demonstrate specific and meaningful interactions of person and process that could be linked to behavior across all CPS components and stages.
4. Although style differences can be beneficial or detrimental to problem-solving success, it is important to emphasize positive or constructive uses of differences.
Problem Solving Style: An Emerging VIEW
We define problem solving styles as consistent individual differences in the ways people prefer to plan and carry out generating and focusing activities, in order to gain clarity, produce ideas, and prepare for action. An individual’s disposition towards change management and problem solving is influenced in part by mindset, willingness to engage in and respond to a situation as presented, and the attitudinal dimensions of one’s personality. Preferences are natural leanings that support productivity.
Through our work on this project, and our reviews of literature on style, we realized that a variety of major theoretical approaches would yield valuable insights into problem solving style. Therefore, VIEW builds specifically on the theoretical constructs from many models, and draws from three areas in particular (represented in the center row of Figure 1); these are: learning style, cognitive style, and psychological type.
Gregorc (1979) described learning styles as “mind-qualities that serve as mediators as we learn from and act upon our environment” (p. 19). Vital to our survival, these mind-qualities persist even as goals and content change. Hilgersom-Volk (1987) defined learning styles simply as the “unique internal processes that guide how we take in information from our environment” (p. 9). While many approaches to learning style are limited to specific categories, psychological, sociological, or emotional for instance, Dunn and Dunn (1978; Dunn, 1984) considered style as multi-faceted. Their model includes 21 elements of style distributed in the categories of environmental, emotional, sociological, physical, and psychological. Of special interest in the development of VIEW were the elements involving the need for structure, the need for proximity to authority, persistence, working alone or in groups, and the psychological elements of analytic/global and reflective/impulsive.
The Dunns noted that some individuals learn well in well-structured environments following a well-structured plan, while others find that their ability to absorb new and difficult information is limited by structure. Likewise, working close to authority figures enables some individuals, while others find the proximity of an authority figure disabling. The importance of the need for authority and structure in providing a picture of an individual’s problem solving and change management style were reinforced by the findings of Houtz, Selby, Esquivel, Okoye, Peters, and Treffinger (in press), and Alter (2000). We also anticipated learning-style differences to be related to manner of processing during problem solving (in relation to preferences for sound or quiet, learning with peers or learning alone, and learning away from authorities or with them present). Learning styles might also be expected to link to ways of deciding when solving problems, in relation to persistence, environmental preferences (such as light and design), and mobility.
Dunn and Dunn (1978) proposed that each learning style element might impact learners at one of three levels. First, a given element may have no impact on the learner at all. In this case the presence or absence of the element plays no part in the individual’s ability to learn new and difficult material. For others, the fact that a certain element of style is present or absent may enhance or constrain learning, although the student’s performance will be better when the element is addressed appropriately than when it is not. The Dunns referred to this as a preference. For some individuals, in the third case, certain elements of style must be addressed appropriately if the student is to be successful in learning new and difficult material. The Dunns refer to this as an element that is a factor for the person. Similarly, we hypothesize that various elements of problem solving and change management style may also have varying levels of impact on an individual’s productivity. For some, the presence or absence of a certain element will have no impact, for others productivity will be enhanced when the preference is addressed appropriately, and for some, failing to address the element appropriately will seriously impair creative productivity and effective problem solving.
Work in the area of cognitive style is often traced to a symposium at the 1949 American Psychological Association conference on “Personal and Social Factors in Perception” (Witkin & Goodenough, 1981). Areas of investigation were: constricted-flexible control, leveling-sharpening, equivalence range, tolerance of unrealistic experiences, and field dependence-independence. Guilford (1980) also discussed field dependence-independence. Field independence has value to creativity in as much as it involves a preference for transformation seeking. Guilford also noted (1986) that when dealing with different kinds of operations some individuals prefer divergent thinking while others prefer convergent thinking.
In developing his inventory, Kolb (1981) looked at preferences along two intersecting continua Converger/Diverger, and Accommodator/Assimilator. These are reflective of how people perceive and process information. Convergers perceive through thinking or abstract conceptualization and process through active experimentation or doing. Divergers perceive through concrete experience and process through reflective observation. Accommodators are individuals who also prefer to take in information through concrete experience but who process using active experimentation. Lastly, Assimilators have preferences for reflective observation and abstract conceptualization. Gregorc (1985) also viewed style as being influenced by preferences along two intersecting continua: concrete sequential to abstract random, and concrete random to abstract sequential. These “stylistic characteristics are powerful indictors of deep underlying psychological forces that help guide a person’s interactions with existential realities” (1985, p. 54).
Efforts to understand initiatives in management led Kirton (1961) to study cognitive style in the development of Adaption-Innovation (AI) theory. He posited two types of managers. One type initiated change that generally remained within the framework of the current paradigm. These individuals understand the system. They are able to use the system and current structure to get things done. He referred to this type of manager as an Adaptor. Adaptors are seen as resourceful, efficient, organized, and dependable; but are sometimes viewed as closed-minded and dogmatic. In groups they supply stability, order, and continuity. On the other hand, Innovators (Kirton’s second broad type of manager) initiate change that is often considered radical by others. They often view the current paradigm as the source of the problem. They are original, energetic, individualistic, spontaneous, and insightful, but are sometimes viewed as impractical, abrasive, and the source of confusion. Innovators offer many varied and unusual ideas and suggestions, but are often not strong in selecting the most promising idea and having it implemented.
Martinsen and Kaufmann (1999) proposed two preferred approaches to creativity along a single continuum. Their Assimilator-Explorer (A-E) theory is an expansion of the work of Piaget. The Martinsen and Kaufmann approach is based on the observation that some subjects “spontaneously vary their solution strategies without any prompting by task requirements or instructions. These subjects were labeled Explorers. Those who followed the pre-specified algorithm throughout were labeled Assimilators” (p. 227.) Martinsen and Kaufmann ‘s theory differs from Kirton’s in that, while Kirton sets the distinction between adaptors and innovators in the context of problem solving in general and based his theory on observations of change processes in organizations, A-E theory lies, according to its authors, within the more specific domain of creativity.
The concept of type can be traced back to the Ancient Greeks and Romans (Vernon, 1973). Jung’s (1923, 1971) typology may have been influenced by the classical division of the temperaments, but was certainly supported by his psychoanalytic practice and empirical research. He developed his theory of psychological type over many years and focused initially on preferences for introversion and extraversion (which Myers, et al.  described as complementary attitudes and orientations of energy or the direction in which a person’s interest flows). Is the individual’s focus on the outer world of actions, objects and people, or the inner world of concepts and ideas? These preferences influence when, during the process of problem solving, an individual will choose to engage others and the environment, and the preference for verbal vs. non-verbal interaction. Extraverts tend to engage others and the environment verbally and actively from the outset, modifying ideas as information is received and exchanged. Introverts tend to engage the world actively after reflection on non-verbal input, after ideas have been carefully and quietly considered.
Jung (1923, 1971) extended this initial interest by defining two opposing perceptual functions: sensation and intuition, referring to information gathering processes. These functions addressed the question: does the individual base perception on the immediate, real facts of experience and life, or the possibilities, relationships, and meanings of experience? Those with a well-developed preference for sensing tend to focus on details and what is practical. They seem to be careful and specific, preferring to begin with the concrete facts of the case and then move to the formation of more abstract ideas. Those with a well-developed preference for intuition tend to focus on inspiration and meaning. They look for insight, patterns and general concepts, beginning with abstract ideas from which will emerge concrete plans.
Jung (1923, 1971) also theorized two opposing judging functions: thinking and feeling. These referred to the ways in which individuals make decisions and reach conclusions. Are an individual’s decisions made objectively, impersonally, considering causes and logical outcomes, or subjectively and personally, weighing values of each choice and how it will affect others? People with a thinking orientation prefer to stay detached from emotion during problem solving while they search for well-reasoned conclusions or solutions. They tend to stress logical principles, order, standards, and rigor. They prefer to begin by offering a critique, finding the flaws in a plan or idea, and mastering the material. Those with a feeling orientation prefer to stay tuned to emotions. They attend to personal relationships, seeking harmony in their outcomes. Their judgments are based on their appreciation of people and things.
Type theory was expanded (Myers & McCaulley, 1985; Myers, et. al., 1998) with the addition of two attitudes to the outer world: judging and perceiving. These orientations influence how one approaches the other three dimensions described by the theory. Does the individual prefer a decisive, planned, and orderly way of life, aimed at regulating and controlling events, or a spontaneous, flexible way of life, aimed at understanding life and adapting to it? Those with a judging orientation prefer to begin the problem-solving process with a clear structure and to work with an orderly, consistent, predictable plan until they reach closure. Those with a perceiving orientation seem to prefer dynamic structure and planning, marked by open exploration through which structure emerges, but is ever fluid, stimulated by new and different ideas, and experience.
Lawrence (1993, 1997) looked at the connections between type and learning styles. He went beyond an emphasis on the behaviors, representing strengths and possible blind spots associated with each type, and added an emphasis on the values and priorities that provide the motivating energy that supports behavior. He proposed that individuals of a particular type exhibit very clear learning preferences. If those preferences are not respected and addressed appropriately during instruction or training, students may well be unable “to bring their best energies and effort to the learning tasks (1996, p. 15)”. Understanding type enables a learner to choose the learning tools and techniques that will provide the best results. Teachers and trainers who develop instructional approaches with type and learning preferences in mind may be expected to offer learners varied opportunities to maximize their energies.
Through our work in the Cognitive Styles Project and our review and analysis of a number of theories, models, and approaches to style, we synthesized the important concepts that helped us to define and construct the essential elements of a new measure directed specifically to problem solving and change management styles.
VIEW consists of three independent dimensions of problem solving style. As in all discussions of type and style, most people share some preferences associated with each style. No single score or set of scores is more or less socially valued than any other, and no approach is more (or less) creative than others. Individuals emphasize these style preferences through their typical behavior across varying contexts and over sustained periods of time. The consistency or clarity of one’s preferences locate one’s preference score along a continuum for each dimension. Those whose behavior and preferences are more clear, certain, and consistent have scores farther from the mean. The scores yielded by the first dimension provide an overall indication of the person’s perceived preferences along a continuum that we describe as Orientation to Change (OC), with two general styles: the Explorer and the Developer. The second dimension involves one’s preferred manner of Processing (P), with two styles: External and Internal. The third dimension of VIEW deals with one’s preferred ways of Deciding (D), in which we define two styles: People-focused and Task-focused. Let us consider each of the three dimensions in greater detail.
The items comprising the OC dimension represent cognitive aspects of problem solving style. This scale addresses the questions: “How do I prefer to deal with boundaries and parameters?” “How do I feel about and react to structure?” and “How do I prefer to respond to novel challenges?” Figure 2 summarizes the major descriptors for both Explorer and Developer styles.
The Explorer style is indicated by scores below the mean. In ordinary use, an “explorer” is an individual who thrives on venturing in uncharted directions, seeks to break new ground, and follow adventurous possibilities or promising new possibilities wherever they may lead. Explores enjoy initiating a broad range of tasks, and thrive on new, ill-defined, and ambiguous situations and challenges. Explorers seek to create many unusual and original options that, if developed and refined, might provide the foundation for productive new directions. They enjoy seeing unusual possibilities, patterns, and relationships. Other people may find their highly novel ideas difficult to understand or initially to “buy into.” Explorers tend to embrace new experience and to “plunge” right into novel situations. They do not fear (and may seem to thrive upon) risk and uncertainty, and often improvise their planning as the situation unfolds, becoming so involved in the excitement of new, leading edge ideas that concerns about efficiency and practicality are, at times, forgotten. Explorers may continue to consider new ideas about a project, even after closure has been reached, or they may abandon a project before reaching any closure, so they can pursue new challenges. They often find plans, procedures, and structures that are imposed on them to be confining and limiting.
The Developer style is indicated by scores above the mean on the OC scale. In ordinary use, a “developer” is an individual who brings tasks to fulfillment, who begins with the basic elements or ingredients and then organizes, synthesizes, refines, and enhances them, forming or shaping them into a more complete, functional, useful condition or outcome. Developers are concerned with practical applications and the reality of the task, and they use their creative and critical thinking in ways that are clearly recognized by others as being helpful and valuable. They prefer problems and solutions that are within the framework of their present experience, seeking change that is incremental, practical, and easily assimilated by the current reality. Developers prefer finding a small number of workable possibilities and guiding them to successful implementation. They tend to focus on bringing one task to closure before taking on a new challenge. Others often see Developers as persistent, careful, practical, methodical, well-organized, and as seeking to minimize risk and uncertainty. They are comfortable with plans, details, structure, and the guidance of authority figures. They find structure and the guidance of authority helpful, or even enabling, in moving tasks or projects forward in an efficient, deliberate manner.
A second dimension of VIEW describes one’s preferred manner of Processing (P) information during problem solving. This scale addresses the questions: “How do I prefer to manage information and its flow when problem solving?” “When do I share my thinking?” and “Does interacting with others build or spend energy?” Figure 3 presents a summary of some typical attributes associated with Processing preferences.
Scores below the mean indicate a preference for an “External” style of processing. Individuals who exhibit a well-developed preference for this style draw their energy from interaction with others, discussing possibilities, and building from the ideas of others. They prefer physical engagement with the environment. When learning new and difficult material those with an External style preference clarify their ideas and understandings through discussion. They find the input of authorities helpful as part of their active discussion. They are not bothered by noise in the study area, approach learning in several ways, and often find that physical mobility enhances their learning, thinking, and problem solving. When solving problems, they seek a great deal of input from others before reaching closure. “Externals” tend to be seen by others as good team members and often appear full of energy. Preferring action to reflection, they may appear to rush into things before others are ready to proceed.
Scores above the mean reflect a preference for an “Internal” style of processing. Those with a well-developed Internal style look first reflectively to their own inner resources and draw energy from their reflection. They prefer to consider ideas on their own before sharing them with others. They embark on action only after giving it careful consideration. People with an Internal preference emphasize quiet reflection and processing information at their own pace. They tend to become engrossed in inner events, ideas, and concepts. They prefer learning privately, working at least initially without the help of peers or authority figures. They may seem quiet and might be perceived by others as pensive or withdrawn.
The third dimension of VIEW involves preferences for Deciding (D) about options or possibilities. This scale addresses such questions as: “What factors get first priority when I focus or decide?” “Where do I start?” and “How do I make trade-offs?” Scores on this scale indicate whether one’s primary focus in decision-making is on “People” or “Task.” Figure 4 presents several key descriptors for the two styles in this dimension.
Individuals with scores below the mean tend to focus on the People style as their primary emphasis when deciding. They consider first the impact of choices and decisions on people’s feelings and support, and on the need for harmony and positive relationships. They prefer to be emotionally involved when setting priorities. They are often seen as warm, friendly and caring. They are often quick to become aware of, and to respond to, the needs of others. They seek solutions or decisions that all concerned can “buy into.”
Scores above the mean indicate a focus on the Task style. Those with this focus tend to look first at choices and decisions that are logical, sensible and can be justified objectively. They prefer making judgments that are impersonal, based on well-reasoned conclusions. Individuals with a Task style of decision making seek mastery of content or information to help them arrive at the “best solution” or response, or at a solution they can readily defend or justify. They may stress the need for staying cool and free from emotion, while seeking clarity, precision, and logical order.
Thinking aloud about ideas _ _ _ _ _ _ _ Thinking quietly about ideas
Ideas that are original _ _ _ _ _ _ _ Ideas that are workable
The respondents place a mark between each pair of statements closer to the left or right, so their choice will be nearer to the statement that best describes their personal preference, or usual way of doing things when solving problems. We ask them to think about the way of working that is most comfortable and natural for them, not the way they might wish they could be, or the way others want them to be. If both statements seem accurate but at different times, and to different degrees, respondents may place their mark on or near the center, in a position that best describes how they prefer to balance the two. Subjects with an sixth-grade level of English language reading proficiency can readily respond to VIEW in approximately 10 to 15 minutes. Items are scored from 1 to 7, so the possible scores on the OC dimension range from 18 to 126, with a theoretical mean of 72, and the P and D dimension scores can each range from 8 to 56, with a theoretical mean of 32.
The current edition of VIEW is the outgrowth of three rounds of development and revision based on data collected from more than 3,000 subjects, from 34 states and several foreign countries, ranging in age from 11 to 84. The initial studies included more than 200 subjects, and an extensive second round of study (with a revised and improved item set) involved more than 2,000 subjects. The subjects included: middle school, senior high school, community college, and university students; classroom teachers; educational administrators; church leaders; and, business managers from within the United States and from international settings. The third stage of research studies involved 743 subjects, and the most recent set of studies included 467 new subjects. Although we did not code data specifically to categorize socio-economic or ethnic distribution, those who participated represented a broad spectrum of demographic groups. Selby, Treffinger, Isaksen, and Lauer (2002) present more detailed information about the psychometric data supporting VIEW’s technical adequacy.
This section presents data on the stability and internal consistency of VIEW. The data from our developmental studies indicated that VIEW meets the customary expectations regarding reliability to support use in research and training contexts, in relation to both stability and internal consistency.
A reliability study involving stability, as reflected in test-retest results over a one-month interval, was carried out with 48 middle school students and nine adults. The correlations were .90, .60, and .65 for the OC, D, and P dimensions respectively. In another study of stability involving 23 adults over a one month period, the correlations were .85, .80, and .77 respectively.
Nineteen subjects from the VIEW-MBTI study completed the VIEW again after two months. The two-month stability correlations were .93 for the OC dimension, .93 for P, and .84 for the D dimension.
Demonstrating that an instrument is valid, or measures what it purports to measure, is an on-going process, not an “event” that can be established definitively in a single study or a specific set of results. Therefore, validation of VIEW, like any other new instrument, will require an on-going program of research by the developers and the active contributions of many other researchers over a period of years. We are committed to establishing and maintaining that research in our own work, and to encouraging research with VIEW by other investigators.
Our initial work included several preliminary validation efforts that we consider promising, including both quantitative and qualitative procedures.
We have conducted factor analytic studies of the instrument during the most recent two rounds of development (with 2,000 subjects in one round, and more than 700 in the second round). Although the results and interpretation of factor analysis are more complex than warranted for the purposes of this paper, we did find that the hypothesized factor structure was confirmed in accord with customary statistical procedures and criteria. The analyses did support the predicted factor structure of the item set.
Throughout our three rounds of development, reviewing all of the data we have collected there have been no significant correlations of the scores on the three VIEW dimensions with age or gender, with two exceptions. We found a greater preference for the Person style on the D dimension among female respondents, and a greater preference for the Task style among male respondents. Based on psychological type theory and research (Myers et al. 1998), this was not a surprising finding.
We have studied correlations between scores on the VIEW instrument and several other measures that represent the theories and models that influenced us in designing and developing our instrument.
Dunn and Dunn Learning Style. We conducted a correlational study in our first round of development, with 191 subjects who completed our instrument and the Productivity Environmental Preference Survey (PEPS; Dunn, Dunn and Price, 1991). The results indicated, as expected, that subjects with an Explorer preference tended to prefer Informal Design, while subjects with a Developer preference scored higher on Motivation and Persistence.
A second study involving 28 adults who were administered our instrument and PEPS also yielded several significant correlations in the expected direction. While studying new and difficult material, Developers preferred Quiet, Formal Design, and Structure, while Explorers preferred Sound, an Informal Design, and little or no imposed Structure. Those with an External processing style also preferred Mobility, working with Peers, and working in the presence of Authority figures. Subjects with an Internal processing style preferred to work Alone and had no preference for Mobility.
The most recent study involved the responses of 118 North Carolina Senior High School Students, whose VIEW results were correlated with scores on the Dunn and Dunn Learning Style Inventory (Dunn, Dunn and Price 1993). These data yielded significant correlations (p≤.05 or beyond) in the expected directions. Developers preferred Quiet, were high in Motivation and Persistence, preferred Structure and were motivated by Authority figures. Explorers had a preference for Sound, preferred low external Structure, and were not motivated by Authority figures. Students who preferred Internal processing also preferred Quiet, Learning Alone, learning in a set manner, and learning Visually. Those with an External style of processing preferred learning with Peers, in the presence of an Authority figure, and learning in Several Ways, often with Sound in the background.
Kirton’s KAI. Twenty-three educators were administered our instrument and the KAI (Kirton, 1987). The correlation between the OC scores and the KAI total score was .89 (p<.05). Since, in the early stages of our work, the OC scale was reversed (so that low scores represented the Developer style), this result was in the expected direction. These results were obtained before we developed the Processing and Deciding scales.
In another study with 48 adult professionals who responded to our instrument and the KAI, the correlation with the total KAI score and the OC dimension was .73 (p<.01). The D and P dimensions correlated -.14 and .24 respectively.
Myers-Briggs Type Indicator. A study involving 20 graduate and undergraduate students at an urban university in New York City examined the correlations of VIEW scores with scores on the Myers-Briggs Type Indicator (Myers et. al., 1998). The results were significant and in the expected direction. The OC dimension correlated .67 with Sensing/Intuition and .61 with Judging/Perception, and lower with Thinking/Feeling (.44) or Extraversion/Introversion (-.27). The Developer style was more strongly indicative of a Sensing and Judging MBTI® preference. The Processing (P) dimension correlated .59 with the MBTI Extraversion/Introversion scale, in the expected direction, and only minimally with other MBTI® scales (-.17 with S/N, -.15 with J/P, and .02 with T/F). The Deciding (D) dimension of VIEW correlated .49 with the Thinking/Feeling scale of the MBTI, also in the expected direction, and minimally with the other MBTI scales (.24 with S/N, .20 with J/P, and .11 with E/I).
In two stages of the development process, we also gathered qualitative data. In one study, we asked a group of 23 adults in a CPS training program to complete a questionnaire at the conclusion of the program, in which we posed the question, “Did your overall score [on VIEW] agree with your own personal assessment of your style preference?” In this group, 18 responded “yes,” three answered “only partly,” no one answered “no,” and two participants did not respond. As part of a middle school study, 10 parents voluntarily returned a survey asking how well the measure described their perception of their child’s typical behavior when solving problems. Four responded “very much so,” six responded “mostly,” while none responded “somewhat’ or “not at all.”
Based on the data we have collected in our initial studies of VIEW, involving more than 3,500 subjects, we conclude that VIEW is a promising measure for use with individuals or groups with a sixth grade or better level of English proficiency when seeking to identify and describe individual problem solving style preferences. VIEW has demonstrated acceptable levels of reliability, and the initial validation studies have been supportive. Through the publication of a Research Edition of VIEW and the development of a well-qualified user base that includes researchers as well as practitioners, we intend to continue studying the instrument’s reliability, validity, and usefulness.
The results offered by VIEW can help individuals to recognize, describe, and appreciate their own problem solving style preferences. The data provided by VIEW can be used to guide individuals in formulating their own creative strengths profiles, and to develop and apply their personal talents as fully as possible. Individuals can use their scores to test their reported or perceived preferences against their typical behavior or performance on a daily basis in varied situations, in order to affirm or modify an understanding of their strengths or weaknesses in terms of problem solving style. Their VIEW results can help them to grow in understanding of their unique style preferences. With this knowledge, individuals can identify ways to be at their personal best, and they can determine how, or under what conditions, they may benefit from the strengths of others. Through training they can use that knowledge and awareness to support and enhance their creative problem-solving behavior, and to use their knowledge to customize or personalize their selection and use of creative problem-solving methods and tools, either working on their own or working with a group or team.
VIEW also has implications for people who are working in, studying, or facilitating problem solving or change management with groups. It offers practitioners a common language or vocabulary for people to use constructively to understand and appreciate style similarities and differences among group members with whom they are working, and their contributions for Creative Problem Solving.
The ease of administration and scoring of the instrument makes VIEW an appropriate tool for use with young people and adults who wish to understand their own approach to change and problem solving. As such it has applicability in an effective team-building experience for adult leadership and management groups. As part of a training program, the data provided by VIEW can be very useful in helping teams and individuals develop more effective problem solving and change management strategies. When feedback is offered to students in school settings, the data provided by VIEW can be useful in helping teachers in creativity instruction, and in developing Creative Problem Solving teams.
In that it draws widely from the literature on learning and cognitive style, psychological type, and Creative Problem Solving, VIEW also offers many opportunities for researchers. These include correlational studies with instruments representing the theories that formed the foundation for VIEW’s development. In addition, data useful to practitioners could be provided through studies as to the efficacy of VIEW in enhancing creative productivity for both teams and individuals.
We are also especially interested in conducting and encouraging research and development in the following areas (although these are illustrations, and should not be considered an exhaustive list).
• Studies of VIEW with various age groups
• Experimental studies contributing to the validation of VIEW
• Cross-cultural research
• Predictive and longitudinal studies
• Comparisons of paper-pencil and web-based (on-line) assessments
• Studies of applications of VIEW in relation to leadership, inventiveness, or
tangible creative productivity (individual or team).
We believe that the use of a reliable assessment of problem solving style, accompanied by carefully prepared feedback, can enable teachers, trainers, group leaders, and individual problem solvers to be more effective in applying or facilitating many problem solving and change management approaches. We believe that the evidence supports our conclusion that VIEW: An assessment of Problem Solving Style is a promising instrument to enable people to understand and appreciate their unique, personal problem solving style preferences and to support them in using their preferences to solve problems and to manage change more effectively. We are continuing to gather data on the current research edition, and we invite researchers who wish to conduct additional studies to communicate with us.
Basadur, M., & Head, M. (2001). Team performance and satisfaction: a link to cognitive style within a process framework. Journal of Creative Behavior, 35, 227-248.
Brooks, J., & Brooks, M. (1993). The case for constructivist classrooms. Alexandria, VA: Association for Supervision and Curriculum Development.
Carne, G. C., & Kirton, M. J. (1982). Styles of creativity. Test-score correlations between the Kirton Adaption-Innovation Inventory and the Myers-Briggs Type Indicator. Psychological Reports, 50, 31-36.
Cattell, R. B., Eber, H. W., & Tatsuoka, M. M. (1970). The handbook for the Sixteen Personality Factor Questionnaire. Champaign, IL: Institute for Personality and Ability Testing.
Corbett-Whittier, C. (1986). The relationship of learning style preferences by high school gifted students on the Torrance Tests of Creative Learning. Unpublished master's thesis, Buffalo State College, Buffalo, NY.
Costa, P. T., & McCrae, R. R. (1985). Concurrent validation after 20 years: Implications of personality stability for its assessment. In J. N. Butcher & C. D. Spielberger (Eds.), Advances in personality assessment (Vol. 4, pp. 31-54). Hillsdale, NJ: Lawrence Erlbaum.
Costa, P. T., & McCrae, R. R. (1995). Primary traits of Eysenck’s P-E-N system: Three and five factor solutions. Journal of Personality and Social Psychology, 69, 308-317.
Crawford, R. (1937). Think for yourself. Wells, Vermont: Fraser.
Dewey, J. (1910). How we think. Boston: D. C. Heath.
Dillon, R. (Ed.). (1985). Individual differences in cognition (Vol. 2). Orlando, FL: Academic Press.
Dillon, R., & Schmeck, R. (Eds.). (1983). Individual differences in cognition (Vol. 1). Orlando, FL: Academic Press.
Dorval, K. (1990). The relationships between level and style of creativity and imagery. Unpublished master's thesis, Buffalo State College, Buffalo, NY.
Dutcher, A. J. (1997). Understanding the relationship of vision to creative climate and leadership practices. Unpublished master’s thesis, Buffalo State College, Buffalo, NY.
Dunn, R. (1984). How should students do their homework? Research vs. opinion. Early Years/k-8, 15, 4, 43-45.
Dunn, R., & Dunn, K. (1978). Teaching students through their individual learning styles: A practical approach. Englewood Cliffs, NJ, Prentice-Hall.
Dunn, R., Dunn, K., & Price, G. (1993) Learning Style Inventory. Lawrence, KS: Price Systems.
Dunn, R., Dunn, K., & Price, G. (1991) Productivity Environmental Preference Survey. Lawrence, KS: Price Systems.
Dunn, R., Beaudry, J., & Klavas, A. (1989). Survey of research on learning styles. Educational Leadership, 46, 6, 50-58.
Eysenck, H. J. (1947). Dimensions of personality. London: Routledge & Kegan Paul.
Franklin, J. (1997). A study of the relationship between cognitive style of creativity and the characteristics of creative products. Unpublished master’s thesis, Buffalo State College, Buffalo, NY.
Goldberg, L. R. (1993). The structure of phenotypic personality traits. American Psychologist, 48, 26-34.
Goldsmith, R. E. (1994). Creative style and personality theory. In M. J. Kirton (Ed.), Adaptors and Innovators: Styles of creativity and problem solving (pp. 34-50). London: Routledge.
Gregorc, A. (1979). Matching teaching and learning styles. Theory Into Practice, 23, 1, 51-55.
Gregorc, A. (1985). Gregorc Style Delineator: A self-assessment instrument for adults. Columbia, CT: Gregorc Associates, Inc.
Gryskiewicz, N., & Tullar, W. L. (1995). The relationship between personality type and creativity style among managers. Journal of Psychological Type, 32, 30-35.
Gryskiewicz, S. S. (1982). Creative leadership development and the Kirton Adaption-Innovation Inventory. Paper presented at the British Psychological Society Conference.
Guilford, J. P. (1975). Factors and factors of personality. Psychological Bulletin, 82, 802-814.
Guilford, J. P. (1980). Cognitive styles: what are they? Educational and psychological Measurement, 40, 715-735.
Guilford, J. P. (1986). Creative talents: Their nature, uses and development. Buffalo, NY: Bearly Limited.
Guilford, J. S., Zimmerman, W. S., & Guilford, J. P. (1976). The Guilford-Zimmerman Temperament Survey Handbook: Twenty-five years of research and application. Orange, CA: Sheridan Psychological Services.
Harmin, M. (1994). Inspiring active learning: A handbook for teachers. Alexandria, VA: Association for Supervision and Curriculum Development.
Hilgersom-Volk, K. (1987). Celebrating students’ diversity through learning styles. OSSC Bulletin, 30, 9.
Holmes, K. (1995). Profiling creativity: An innovator’s pathway. Unpublished master’s project, Buffalo State College, Buffalo, NY.
Houtz, J., Selby, E. Esquivel, G., Okoye, R., Peters, K., and Treffinger, D. (in press). Creativity styles and personal type. Creativity Research Journal.
Hurley, C. (1993). The relationship between Kirton Adaption-Innovation style and the use of Creative Problem Solving. Unpublished master's thesis, Buffalo State College, Buffalo, NY.
Isaksen, S. G. (Ed.). (1987). Frontiers of creativity research: Beyond the basics. Buffalo, NY: Bearly Limited.
Isaksen, S. G., & De Schryver, L. (2000). Making a difference with CPS: A summary of the evidence. In: S. G. Isaksen (Ed.). Facilitative leadership: Making a difference with CPS (pp. 187-248). Dubuque, IA: Kendall/Hunt.
Isaksen, S. G., & Dorval, K. B. (1993). Toward an improved understanding of creativity within people: The level-style distinction. In S. G. Isaksen, M. C. Murdock, R. L. Firestien, and D. J. Treffinger (Eds.), Understanding and recognizing creativity: The emergence of a discipline. (pp. 299-330). Norwood, NJ: Ablex.
Isaksen, S. G., Dorval, K. B., & Kaufmann, G. (1992). Mode of symbolic representation and cognitive style. Imagination, Cognition and Personality, 11, 271-277.
Isaksen, S. G., Dorval, K. B., & Treffinger, D. J. (2000). Creative approaches to problem solving. Dubuque, IA: Kendall/Hunt.
Isaksen, S. G., & Kaufmann, G. (1990). Adaptors and innovators: A discriminant analysis of the perceptions of the psychological climate for creativity. Studia Psychologica, 32, 129-141.
Isaksen, S. G., & Lauer, K. J. (1999). Relationship between cognitive style and individual psychological climate: Reflections on a previous study. Studia Psychologica, 41, 177-191.
Isaksen, S. G., Lauer, K. J., & Wilson, G. (in press). An examination of the relationship between personality type and cognitive style. Creativity Research Journal.
Isaksen, S. G., & Pershyn, G. (1994). Understanding Natural Creative Process using the KAI. KAI International, 3, 5.
Isaksen, S. G, & Puccio, G. (1988). Adaption-innovation and the Torrance Tests of Creative Thinking: The level-style issue revisited. Psychological Reports, 63, 659-670.
Isaksen, S. G., & Treffinger, D. J. (1985). Creative problem solving: The basic course. Buffalo, NY: Bearly Limited.
Jacobson, C. M. (1993) Cognitive styles of creativity: Relations of scores on the Kirton Adaption-Innovation Inventory and the Myers-Briggs Type Indicator among managers in USA. Psychological Reports, 72. 1131-1138
Joniak, A. J., & Isaksen, S. G. (1988). The Gregorc Style Delineator: Internal consistency and its relationship to Kirton’s Adaptive-Innovative Distinction. Educational and Psychological Measurement, 48, 1043-1049.
Jung, C. (1923). Psychological types. (H. B. Baynes, Trans.). New York: Harcourt, Brace.
Jung, C. G. (1971). The portable Jung. (R. F. C. Hull, Trans.). NY: Viking.
Kaufmann, G., Isaksen, S. G., & Lauer, K. J. (1996). Testing the Glass Ceiling effect on gender differences in upper level management: The case of innovator orientation. European Journal of Work and Organizational Psychology, 5, 29-41.
Kirton, M. J. (1961). Management initiative. London: Action Society Trust.
Kirton, M. J. (1976). Adaptors and innovators: A description and measure. Journal of Applied Psychology, 61, 622-629.
Kirton, M. J. (1987). Cognitive styles and creativity. In S. G. Isaksen (Ed.), Frontiers in creativity research: Beyond the basics. (pp. 282-304). Buffalo, NY: Bearly Limited.
Kirton, M. J. (1999). Kirton Adaption-Innovation Inventory manual (3rd ed.). Berkhamsted, UK: Occupational Research Centre.
Kogan, N. (1973). Creativity and cognitive style: A life-span perspective. In P. B. Baltes & K. W. Schaie (Eds.), Life span development psychology: Personality and socialization (pp. 145-178). New York: Academic Press.
Kolb, D. (1981). Learning style inventory. “Disciplinary inquiry norms and student learning styles: Diverse pathways for growth.” In A. Chickering (Ed.), The Modern American College. San Francisco: Jossey Bass.
Lawrence, G. (1993). People types & tiger stripes. Gainesville, FL: Center for Applications of Psychological Type.
Lawrence, G. (1997). Looking at Type and Learning Styles. Gainesville, FL: Center for Applications of Psychological Type.
Martinsen, O., & Kaufmann, G. (1999). Cognitive style and creativity. In M. A. Runco, & S. R. Pritzker (Eds.), Encyclopedia of creativity (Vol. I , pp. 273-282). New York: Academic Press.
McEwen, P. (1986). Learning styles: Ability and creativity. Unpublished master's thesis, Buffalo State College, Buffalo, NY.
Messick, S. (1976). Individuality in learning: Implications of cognitive styles and creativity for human development. San Francisco: Jossey-Bass.
Myers, I., & McCaulley, M. (1985). Manual: A guide to the development and use of the Myers-Briggs Type Indicator. Palo Alto, CA: Consulting Psychologists Press.
Myers, I., McCaulley, M., Quenk, N., & Hammer, A. (1998). MBTI manual: A guide to the development and use of the Myers-Briggs Type Indicator (3rd ed.). Palo Alto, CA: Consulting Psychologists Press, Inc.
Noller, R. B., & Parnes, S. J. (1972). Applied creativity: The creative studies project. Part III: The curriculum. Journal of Creative Behavior, 6, 275-294.
Osborn, A. F. (1948). Your creative power. New York: Scribners.
Osborn, A. F. (1953). Applied imagination: The principles and procedures of creative problem-solving .New York: Scribners.
Parnes, S. J. (1967). Creative behavior guidebook. NY: Scribers.
Parnes, S. J. (1987). The creative studies project. In S. G. Isaksen (Ed.), Frontiers in creativity research: Beyond the basics. (pp. 165-188). Buffalo, NY: Bearly Limited.
Parnes, S. J., & Noller, R. B. (1972a). Applied creativity: The creative studies project. Part I– The development. Journal of Creative Behavior, 6, (1), 11-22.
Parnes, S. J., & Noller, R. B. (1972b). Applied creativity: The creative studies project. Part II– Results of the two-year program. Journal of Creative Behavior, 6, 164-186.
Parnes, S. J., & Noller, R. B. (1973a). Applied creativity: The creative studies project. Part IV– Personality findings and conclusions. Journal of Creative Behavior, 7, 15-36.
Parnes, S. J., & Noller, R. B. (1973b). Toward supersanity: Channeled freedom. Buffalo, NY: DOK.
Parnes, S. J., & Noller, R. B. (1974). Toward supersanity: Channeled freedom. (Research Supplement.) Buffalo, NY: DOK.
Parnes, S. J., Noller, R. B., & Biondi, A. M. (1977). Guide to creative action. NY: Scribners.
Pershyn, G. (1992). An investigation into the graphic depictions of natural creative problem-solving processes. Unpublished master’s project, Buffalo State College, Buffalo, NY.
Puccio, G. J. (1987). The effects of cognitive style on problem-defining behavior. Unpublished master's thesis, Buffalo State College, Buffalo, NY.
Puccio, G. J., Treffinger, D. J., & Talbot, R. J. (1995). Exploratory examination of relationships between creativity styles and creative products. Creativity Research Journal 8, 157-172.
Reese, H. W., Treffinger, D. J., Parnes, S. J., & Kaltsounis, G. (1976). Effects of a creative studies program on structure of intellect factors. Journal of Educational Psychology, 68, 401-410.
Schoonover, P. (1996). The preference for and use of Creative Problem Solving tools among adaptors and innovators. Creative Learning Today: Center for Creative Learning Newsletter, 6 (3), 10-11.
Selby, E. (1997). Lucy and Michael: Case studies of creative styles in teenagers. Creative Learning Today: Center for Creative Learning Newsletter, 7 (2), 4-6.
Selby, E. C. (1991). The Kirton Adaption-Innovation Inventory as a tool for assessing problem solving styles in eighth grade students. Unpublished doctoral dissertation, Walden University, Minneapolis, MN.
Selby, E. C., Treffinger, D. J., & Isaksen, S. G. (2002). VIEW: An assessment of problem solving style. Sarasota, FL: Center for Creative Learning.
Selby, E. C., Treffinger, D. J., Isaksen, S. G., & Lauer, K. J. (2002). Technical manual and user’s guide: VIEW—an assessment of problem solving style. Sarasota, FL: Center for Creative Learning.
Selby, E., C. Treffinger, D. J., Isaksen, S. G., & Powers, S. (1993). Use of the Kirton Adaption-Innovation Inventory with middle schools students. Journal of Creative Behavior, 27 (4), 223-235.
Spearman, C. (1927). Abilities of man. New York: MacMillan.
Spearman, C. (1931). Creative mind. New York: D. Appleton.
Sternberg, R. J. (1986). Intelligence applied. New York: Harcourt, Jovanovich, & Brace.
Sylwester, R. (1995). A celebration of neurons: An educator’s guide to the human brain. Alexandria, VA: Association for Supervision and Curriculum Development.
Tefft, M. (1990). A factor analysis of the TTCT, MBTI, and KAI: The creative level style issue re-examined. Unpublished master's thesis, Buffalo State College, Buffalo, NY.
Tellegen, A. (1982). Brief manual for the differential personality questionnaire. Unpublished manuscript, University of Minnesota, Minneapolis.
Tellegen, A. (1985). Structures of mood and personality and their relevance to assessing anxiety with an emphasis on self-report. In A. H. Tuma & J. D. Maser (Eds.), Anxiety and the anxiety disorders (pp. 681-706). Hillsdale, NJ: Erlbaum.
Terman, L. (1925). Genetic studies of genius: Mental and physical traits of a thousand gifted children. Palo Alto, CA: Stanford University Press.
Thurstone, L. (1927). The nature of intelligence. New York: Harcourt, Brace.
Torrance, E. P. (1987). Teaching for creativity. In: S. G. Isaksen (Ed.), Frontiers of creativity research: Beyond the basics (pp. 204-215). Buffalo, NY, Bearly Limited.
Torrance, E. P. (1979). The search for satori and creativity. Buffalo, NY: Creative Education Foundation.
Treffinger, D. J., & Isaksen, S. G. (2001). Creative learning and problem solving. In: A. Costa (Ed.), Developing minds: A sourcebook for teaching thinking (3rd ed., pp. 442-445). Alexandria, VA: Association for Supervision and Curriculum Development.
Treffinger, D. J., Isaksen, S. G., & Dorval, K. B. (2000). Creative problem solving: An introduction. (3rd ed.). Waco, TX: Prufrock.
Treffinger, D. J., Young, G. C., Selby, E. C., & Shepardson, C. A. (2001). Assessing creativity: A technical assistance guide. Sarasota, FL: Center for Creative Learning.
Vernon, P. E. (1973). Multivariate approaches to the study of cognitive styles. In: J. R. Royce (Ed.), Multivariate analysis and psychological theory (pp. 125-141). London: Academic Press.
Wallas, G. (1926). The art of thought. London: Watts.
Wheeler, J. (1995). Exploratory study of preferences associated with creative problem solving. Unpublished master’s project. Buffalo State College, Buffalo, NY.
Willerman, L. (1979). The psychology of individual and group differences. San Francisco: W. H. Freeman.
Witkin, H. A., & Goodenough, D. R. (1981). Cognitive styles: Essence and origins. Madison, WI: International University Press.
Wittig, C. (1985). Learning style preferences among third graders high or low on divergent thinking and feeling variables. Unpublished master's thesis, Buffalo State College, Buffalo, NY.
Wolfe, P. (2001). Brain matters: Translating research into classroom practice. Alexandria, VA: Association for Supervision and Curriculum Development.
Zilewicz, E. (1986). Cognitive styles: Strengths and weaknesses when using CPS. Unpublished master's project, Buffalo State College, Buffalo, NY.
Figure 1. Foundations of problem solving style
Figure 2. The Orientation to Change dimension
Figure 3. The Processing dimension
Figure 4. The Deciding dimension