Problem Solving Styles in the Inventive Process
The Use of Mental and Visual Models
Donald R. Loftin
December 2, 2007
This paper provides a summary of the research that was completed [Loftin, 2006] in partial fulfillment of a Masters of Engineering in System Engineering at Penn State Great Valley (PSGV). The research explored the relationships between the problem solving styles of inventors, their inventive processes, and their inventions. In particular, the research attempted to link and build upon Kirton’s Adaption-Innovation (A-I) Theory [Kirton, 1994, 2000, 2003] and invention as a Cognitive Process [Gorman & Bernard, 1990]. Gorman and Carlson suggest that invention can be seen as a cognitive process in which mental, visual and mechanical models are aligned in order to solve some perceived problem. This process is illustrated in the Figure below. The research explored whether preferences were shown in the use of these models by inventors with different problem solving styles.
DEFINITION OF TERMS
Analogy – A form of logical inference, or an instance of it, based on the assumption that if two things are known to be alike in some respects, they may be alike in other respects. For this research: the use of a general pattern of a solution in one domain to create the general pattern of a solution in another domain.
Mental Model – The structures of inventions that are formed and manipulated mentally without the use of any external visual or mechanical representations. This includes the mental manipulation of proposed changes to an existing invention.
Visual Model – The structures of inventions that are formed and manipulated through the use of pictures, drawings, and other representations on paper. This term also refers to other 2-dimensional views of a structure that might be presented on a computer screen.
Mechanical Model – The structures of inventions that are formed and manipulated through the use of 3-dimensional physical structures, including samples, miniature representations, mock-ups, and prototypes. This term also refers to 3-dimensional modeling of an invention through the use of Computer-Aided-Design (CAD) applications.
Inventor – An individual who, individually or as part of a team, creates an item for which a patent is applied or for which a trade-secret is created.
Heuristics – This refers to techniques or rules of thumb that may be used within the inventive process.
Intuition – The apparent ability to acquire knowledge without a clear inference or reasoning process. (Within this research, the gathering of information about the problem followed by the appearance in the mind of the solution after “sleeping” on it.)
Top Down Problem Solving – A problem solving approach in which the system is first formulated, specifying but not detailing any first-level subsystems. Each subsystem is then refined in yet greater detail, sometimes in many additional subsystem levels, until the entire specification is reduced to base elements.
Bottom Up Problem Solving – A problem solving approach in which the individual base elements of the system are first specified in great detail. These elements are then linked together to form larger subsystems, which then in turn are linked, sometimes in many levels, until a complete top-level system is formed.
SUMMARY OF RESEARCH
The research was conducted by interviewing 12 different inventors. At the start of the interviews, each inventor was given the KAI. The KAI scores and sub-scores of each inventor are shown below in order of most innovative to most adaptive. Although none of the subscale scores are invalid, the ones highlighted in red below have some variation that is subject to interpretation. Note that in each case, the SO subscale score is higher and the E subscale score is lower. Since these individuals are inventors, this deviation is not completely unexpected, i.e., both the generation of ideas and the attention to detail are essential skills.
The interview process itself was conducted by asking each inventor to respond to 10 questions. Each session was recorded for further analysis. The questions consisted of both quantitative (3, 5, 7) questions and qualitative (1, 2, 4, 6, 8, 9, 10) questions. The questions that were used for the interview are provided below.
1. In your own words, please describe the typical process you follow when inventing.
2. What role do mental models play in your inventive process? What role do visual models play in your inventive process? What role do mechanical models play in your inventive process?
3. On a scale from zero to ten, please identify the level of importance of mental models, visual models, and mechanical models, respectively, in your inventive process.
4. Please describe your typical inventive process in terms of the sequence of use of the three types of models.
5. What percentage of the time do you typically spend during the inventive process with each of these models?
6. Are there specific triggers or criteria that indicate the need to move from one model to another? If so, please describe these and give examples.
7. Which of the models, i.e., mental, visual or mechanical, are most difficult for you to create and/or use? Which models are the least difficult for you to create and use?
8. Pick one of your inventions and describe the process you followed for that invention, with special attention to the role of mental, visual, and mechanical models in the process.
9. Do you have any heuristics that you use regularly to solve problems you encounter during the inventive process? If so, please describe them.
10. For which of your inventions was the inventive process the most difficult and why? For which of your inventions was the inventive process the least difficult and why?
SUMMARY OF RESULTS
The three quantitative results were recorded and used to perform statistical analysis. A brief explanation of each measure is provided below.
1. Relative Importance of Models – Each inventor was asked to provide the relative importance of each model in their inventive process using a number from zero to 10 with zero being of no importance and 10 being the most important. The inventors were not asked to make these numbers different. For example, one inventor rated all three models as 10.
2. Time Spent in Models – Each inventor was asked to provide the percentage of the inventive process that they spend in each model. The sum of the percentages for each model was expected to sum to 100%. In those cases in which it did not, a weighting factor was used to correct the values.
3. Difficulty of Use of Model – Each inventor was asked to order the models in terms of ease of use. A value of 1 was assigned to the easiest model and a value of 3 to the hardest model. When two models were seen to be equally easy or hard, an average between their positions was taken. For example, if the mental model was seen as easiest but the visual and mechanical models were seen as being equally difficult, the mental model was given a value of 1 and the visual and mechanical models were given the values of 2.5.
The results for each inventor interviewed are shown in the table below.
Most of the inventors interviewed did not participate significantly in the creation of the mechanical models. Instead, they often reported that they performed a consulting service or performed testing of the product. As a result, only limited inferences could be determined from these results. However, an examination of the relative importance of mechanical models for the 3 most innovative inventors show values of 6 or below while the 3 most adaptive individuals show values of 7 or above.
Statistical analysis of the data did show evidence for preferences in the way that mental and visual models are used. Details of this analysis are available in the original research paper [Loftin, 2005]. The table below shows an example of another way in which this data can be analyzed.
To analyze this data, the data was divided into three groups. Group 1 consists of the 3 most innovative inventors, Group 2 consists of the 6 inventors in the middle, and Group 3 consists of the 3 most adaptive inventors. The following observations can be made about each of these groups:
• Group 1 (Most Innovative) – 7 out of 9 measures show a preference for the use of the mental model vs. the visual models with 2 of 3 inventors indicating that mental models were more important, 2 of 3 inventors indicating that they spent more time with mental models and all 3 inventors Indicating that they find mental models easier to use.
• Group 2 (Middle) – 6 out of 18 measures show a preference for the use of mental models while 7 out of 18 measures show a preference for the use of visual models. There appears to be no preference within this group.
• Group 3 (Most Adaptive) – 6 out of 9 measures show a preference for the use of visual models vs. mental models with 2 of 3 inventors indicating that visual models were more important, 2 of 3 inventors indicating that they spent more time with visual models and 2 of 3 inventors Indicating that they find visual models easier to use.
The analysis of the data gathered from the interviews provides some additional interesting results. Apparent differences in preferred strategies for design were observed. Individuals with more innovative cognitive styles appear to start the invention process with a focus on more abstract patterns and templates that can be used to solve many problems. For example, the use of analogies to support the problem solving process was reported by three inventors, with KAI scores of 139, 120 and 119 while no other inventors mentioned this approach. Individuals with more adaptive cognitive styles appear to start the invention process with a focus on refinement and optimization of components of an overall solution. Inventors that fall between these two strategies appear to employ strategies that bring these two problem solving approaches together. They appear to accomplish this process by using intuition to bring the two strategies together into a synthesized solution in alignment with a particular problem. The use of this technique was mentioned by all inventors in the range of 100 to 120. Only one other inventor, inventor 12 with a KAI of 104, mentioned the use of this strategy.
There is existing follow on research that is attempting to extract more information from the recordings that were performed for the interviews. The recordings are being transcribed on a word-for-word basis in order to facilitate the use of data mining techniques to search for meaning that may not be easily apparent since what we hear is influenced by our problem solving styles.
The conclusion from the analysis of the data from these interviews indicates that there is evidence to support the following hypotheses which can be tested as a follow up project:
1. More innovative problem solvers have a preference for the use of mental models over visual models, spend more time with these models and find them easier to use; more adaptive problems solvers have a preference for the use of visual models over mental models, spend more time with these models and find them easier to use.
2. More adaptive problem solvers show a preference for solving problems bottom up while more innovative problem solvers show a preference for solving problems top down.
One of the interesting observations that were made during this research was the grouping of inventors that reported the use of intuition to solve problems. For this sample, all 5 inventors with KAI score in the range of 108 to 120 reported the use of intuition as a primary problem solving approach. Only one other inventor (KAI of 100) reported this preference. Additional investigations is needed in order to determine whether there is a segment of the KAI continuum in which there is a strong preference for intuition while other segments on the continuum show much less preference. If so, there are several implications that could be explored. For example, one could conclude that there exists a set of problems to be solved for which the preferred technique for solving them is intuition. What then is the nature of the problems for which intuition appears to be the best tool? In addition, the most innovative inventors showed a preference for the use of analogies to solve problems while the balance of the group did not. One possible answer to be researched is whether a series of segments of the KAI continuum can be identified in which one or two preferred techniques of problem solving appear.
The following references are contained within the original research paper:
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Clapp, R. G., 1991, The fate of ideas that aim to stimulate change in a large organization, PhD Thesis, University of Hertfordshire.
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Goldman, Robert and McKenzie, John D. Jr., 2005, The Student Guide to Minitab Release 14, Pearson Education, Inc.
Gorman, Michael E. and Carlson, W. Bernard, 1990, Interpreting Invention as a Cognitive Process: The Case of Alexander Graham Bell, Thomas Edison, and the Telephone, Science, Technology, & Human Values, Vol. 15, No. 2, Spring, 131-164.
Huber, John C., 1998. Invention and Inventivity Is a Random, Poisson Process: A Potential Guide to Analysis of General Creativity, Creativity Research Journal, Vol. 11, No. 3, 231-241, Lawrence Erlbaum Associates, Inc.
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Kirton, M. J., [1977, 1987] 1999, Kirton Adaption-Innovation Inventory Manual, Berkhamsted, UK: Occupational Research Centre.
Kirton, M. J.,  2000, Adaptors and Innovators – Styles of Creativity and Problem Solving; Hertfordshire, UK: KAI Distribution Center.
Kirton, M. J., 2003, Adaption-Innovation in the Context of Diversity and Change, New York: Routledge.
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The original research paper is identified below:
Loftin, D. R., 2006, Problem Solving Style and the Inventive Process, Penn State Great Valley