Problem Map: An Ontological Framework for a Computational Study of Problem Formulation in Engineering Design

Studies of design cognition often face two challenges. One is a lack of formal cognitive models of design processes that have the appropriate granularity: fine enough to distinguish differences among individuals and coarse enough to detect patterns of similar actions. The other is the inadequacies in automating the recourse-intensive analyses of data collected from large samples of designers. To overcome these barriers, we have developed the problem map (P-maps) ontological framework. It can be used to explain design thinking through changes in state models that are represented in terms of requirements, functions, artifacts, behaviors, and issues. The different ways these entities can be combined, in addition to disjunctive relations and hierarchies, support detailed modeling and analysis of design problem formulation. A node‐link representation of P-maps enables one to visualize how a designer formulates a problem or to compare how different designers formulate the same problem. Descriptive statistics and time series of entities provide more detailed comparisons. Answer set programming (ASP), a predicate logic formalism, is used to formalize and trace strategies that designers adopt. Data mining techniques (association rule and sequence mining) are used to search for patterns among large number of designers. Potential uses of P-maps are computer-assisted collection of large data sets for design research, development of a test for the problem formulation skill, and a tutoring system. [DOI: 10.1115/1.4030076]

[1]  Nigel Cross,et al.  Expertise in engineering design , 1998 .

[2]  J. Fleiss.  Measuring nominal scale agreement among many raters. , 1971 .

[3]  Jami J. Shah,et al.  A Computational Aid for Problem Formulation in Early Conceptual Design , 2013, J. Comput. Inf. Sci. Eng..

[4]  John C. Thomas,et al.  The psychological study of design , 1979 .

[5]  Nigel Cross,et al.  Solution driven versus problem driven design: strategies and outcomes , 2006 .

[6]  M. Boden.  The creative mind : myths & mechanisms , 1991 .

[7]  Simon Szykman,et al.  A functional basis for engineering design: Reconciling and evolving previous efforts , 2002 .

[8]  Cynthia J. Atman,et al.  A comparison of freshman and senior engineering design processes , 1999 .

[9]  Crispin Hales,et al.  Engineering design: a systematic approach , 1989 .

[10]  Nigel Cross,et al.  Research in design Thinking , 1992 .

[11]  Joseph D. Novak,et al.  Learning How to Learn , 1984 .

[12]  John S. Gero,et al.  Locating Creativity in a Framework of Designing for Innovation , 2007, IFIP CAI.

[13]  Jami J. Shah,et al.  Applied Tests of Design Skills—Part 1: Divergent Thinking , 2012 .

[14]  John A. Barnden,et al.  Semantic Networks , 1998, Encyclopedia of Social Network Analysis and Mining.

[15]  Mary Lou Maher,et al.  Formalising Design Exploration as Co-Evolution , 1996 .

[16]  Nigel Cross,et al.  Analysing design activity , 1996 .

[17]  Daniel T. Larose,et al.  Discovering Knowledge in Data: An Introduction to Data Mining , 2005 .

[18]  J. Fleiss,et al.  Statistical methods for rates and proportions , 1973 .

[19]  K. A. Ericsson,et al.  Protocol Analysis: Verbal Reports as Data , 1984 .

[20]  Kristina Shea,et al.  A Computational Product Model for Conceptual Design Using SysML , 2009 .

[21]  Cynthia M. Sifonis,et al.  The Role of Specificity and Abstraction in Creative Idea Generation , 2004 .

[22]  K. Gwet,et al.  Variance Estimation of Nominal-Scale Inter-Rater Reliability with Random Selection of Raters , 2008 .

[23]  G. Goldschmidt,et al.  How good are good ideas? Correlates of design creativity , 2005 .

[24]  Richard Coyne,et al.  Wicked problems revisited , 2005 .

[25]  Ashok K. Goel,et al.  Structure, behavior, and function of complex systems: The structure, behavior, and function modeling language , 2008, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[26]  Terri Gullickson.  The Creative Mind: Myths and Mechanisms. , 1995 .

[27]  B. Everitt,et al.  Statistical methods for rates and proportions , 1973 .

[28]  John S. Gero,et al.  The Situated Function - Behaviour - Structure Framework , 2002, AID.

[29]  Chun-Heng Ho,et al.  Some phenomena of problem decomposition strategy for design thinking: differences between novices and experts , 2001 .

[30]  Jami J. Shah,et al.  The Structure of Creative Design: What Problem Maps Can Tell Us About Problem Formulation and Creative Designers , 2012 .

[31]  Gabriela Goldschmidt,et al.  Capturing indeterminism: representation in the design problem space , 1997 .

[32]  Nigel Cross,et al.  Creativity in the design process: co-evolution of problem–solution , 2001 .

[33]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[34]  Renate Eisentraut.  Styles of problem solving and their influence on the design process , 1999 .

[35]  Santiago V. Lombeyda,et al.  An Approach to Capturing Structure, Behavior, and Function of Artifacts in Computer-Aided Design , 2001, J. Comput. Inf. Sci. Eng..

[36]  Vinod Goel,et al.  The Structure of Design Problem Spaces , 1992, Cogn. Sci..

[37]  Ac Rianne Valkenburg,et al.  The reflective practice of design teams , 1998 .

[38]  Allen Newell,et al.  Human Problem Solving. , 1973 .

[39]  Jacob Cohen.  A Coefficient of Agreement for Nominal Scales , 1960 .

[40]  John S. Gero,et al.  Design Prototypes: A Knowledge Representation Schema for Design , 1990, AI Mag..

[41]  Mary Lou Maher,et al.  Formalising Design Exploration as Co-Evolution , 1996 .

[42]  Linden J. Ball,et al.  Spontaneous analogising in engineering design: a comparative analysis of experts and novices , 2004 .

[43]  M. Ross Quillian,et al.  4 – Semantic Memory , 1988 .

[44]  H. Kundel,et al.  Measurement of observer agreement. , 2003, Radiology.

[45]  S Harfield,et al.  On design ‘problematization’: Theorising differences in designed outcomes , 2007 .

[46]  John S. Gero,et al.  An approach to the analysis of design protocols , 1998 .

[47]  Michael Gelfond,et al.  Answer Sets , 2008, Handbook of Knowledge Representation.

[48]  J. Bradshaw,et al.  Institute for Human and Machine Cognition , 2022 .

[49]  Kurt VanLehn,et al.  The Behavior of Tutoring Systems , 2006, Int. J. Artif. Intell. Educ..

[50]  Jami J. Shah,et al.  TOWARDS A FORMAL REPRESENTATION MODEL OF PROBLEM FORMULATION IN DESIGN , 2011 .

[51]  J. Novak,et al.  The theory underlying concept maps , 2016 .

[52]  Morteza Pourmohamadi,et al.  LINKOGRAPHER: AN ANALYSIS TOOL TO STUDY DESIGN PROTOCOLS BASED ON FBS CODING SCHEME , 2011 .