Modeling semantic knowledge structures for creative problem solving: Studies on expressing concepts, categories, associations, goals and context

Doboli, Alex; Umbarkar, Anurag; Doboli, Simona; Betz, Joseph

doi:10.1016/j.knosys.2015.01.014

Cited by 20 publications

(8 citation statements)

References 53 publications

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“… Kim (2006) raised the use of creativity tests and suggested that creativity values could be adjusted for specific situations. Moreover, design mainly emphasizes the novelty of the product and its integration into a domain-specific context or field ( Doboli et al, 2015 ). Creativity is also considered as a key factor in the design advertising process ( Klebba and Tierney, 1995 ).…”

Section: Methodsmentioning

confidence: 99%

Intelligence Beliefs Predict Spatial Performance in Virtual Environments and Graphical Creativity Performance

Hong

Chen

et al. 2021

Front. Psychol.

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Although intelligence beliefs have been applied to explain the influence of cognition, behavior, and creativity, the research on creativity is still limited. Therefore, in order to effectively expand the understanding of the influence of intelligence beliefs on the creative performance of learners’ graphics, the implicit theories of intelligence were exploited as the basis of this study. Three hypothetical pathways were proposed to be explored, and a research model was validated. First- and second-year students from a technical high school in New Taipei City were invited to participate. There were 273 valid data (88.9% of complete data). Reliability and validity analyses were performed, as well as overall model fit analysis and research model validation, and descriptive statistical analysis of the learners’ performance in applying the operational virtual reality (VR). The results of this study showed that: (1) Incremental beliefs of aesthetic intelligence had a positive effect on spatial performance; (2) entity belief of spatial intelligence (EBSI) had a negative effect on spatial performance; and (3) spatial performance had a positive effect on graphical design performance. From the results, it is clear that design teachers can assess students’ implicit beliefs in the early stages of teaching to actively promote better spatial performance when students show high levels of entity beliefs.

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Section: Methodsmentioning

confidence: 99%

Intelligence Beliefs Predict Spatial Performance in Virtual Environments and Graphical Creativity Performance

Hong

Chen

et al. 2021

Front. Psychol.

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“…A concept might be connected to a goal meant for the outcome ( what frames), an implementation expressing a set of concepts connected through how frames (causal sequences), and a set of concepts in why frames (reasons for a goal or implementation). A mathematical description of the concept representation was presented in [ 10 , 77 , 78 ]. The novelty of a response is assessed using a weighted sum, in which goal and for who have the highest weights, features have middle weights, and the structure of the causal relations, their nature, and kinds of concepts used in the implementations have the lowest weights [ 25 , 79 ].…”

Section: Model Descriptionmentioning

confidence: 99%

“…We have previously used the presented solution space description for expressing the solution space for different open-ended and design problems, such as circuit design [ 10 , 77 , 78 , 80 ]. Our solution space representation includes elements similar to prototype schema [ 81 ], but emphasize the connection between concepts based on their roles in solutions.…”

Section: Model Descriptionmentioning

confidence: 99%

“…Figure 1 (b) shows the structure of the local knowledge of a group member. It includes concepts in responses grouped in categories similar to the models discussed in [ 10 , 77 , 78 , 80 ]. Categories can include sub-categories, which inherit the features of the more abstract category, but also have distinguishing parameters and constraints that separate it from other sub-categories pertaining to the same category.…”

Section: Model Descriptionmentioning

confidence: 99%

“…The variety associated to “mental illness” includes the similarities of the four latter instances and the typical exemplar. This level mainly implements associative learning, which identifies the invariant attributes of the concepts [ 37 , 78 ]. The next bottom level learns the main causal relations of the outcomes.…”

Section: Software Implementation Of the Computational Modelmentioning

confidence: 99%

See 2 more Smart Citations

A novel agent-based, evolutionary model for expressing the dynamics of creative open-problem solving in small groups

Doboli

2020

Appl Intell

Self Cite

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Understanding the process of producing creative responses to open-ended problems solved in small groups is important for many modern domains, like health care, manufacturing, education, banking, and investment. Some of the main theoretical challenges include characterizing and measuring the dynamics of responses, relating social and individual aspects in group problem solving, incorporating soft skills (e.g., experience, social aspects, and emotions) to the theory of decision making in groups, and understanding the evolution of processes guided by soft utilities (hard-to-quantify utilities), e.g., social interactions and emotional rewards. This paper presents a novel theoretical model (TM) that describes the process of solving open-ended problems in small groups. It mathematically presents the connection between group member characteristics, interactions in a group, group knowledge evolution, and overall novelty of the responses created by a group as a whole. Each member is modeled as an agent with local knowledge, a way of interpreting the knowledge, resources, social skills, and emotional levels associated to problem goals and concepts. Five solving strategies can be employed by an agent to generate new knowledge. Group responses form a solution space, in which responses are grouped into categories based on their similarity and organized in abstraction levels. The solution space includes concrete features and samples, as well as the causal sequences that logically connect concepts with each other. The model was used to explain how member characteristics, e.g., the degree to which their knowledge is similar, relate to the solution novelty of the group. Model validation compared model simulations against results obtained through behavioral experiments with teams of human subjects, and suggests that TMs are a useful tool in improving the effectiveness of small teams.

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A Formal Model for Robot to Understand Common Concepts

Liao

Luo

2019

Advances in Intelligent Systems and Computing

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Modeling semantic knowledge structures for creative problem solving: Studies on expressing concepts, categories, associations, goals and context

Cited by 20 publications

References 53 publications

Intelligence Beliefs Predict Spatial Performance in Virtual Environments and Graphical Creativity Performance

Intelligence Beliefs Predict Spatial Performance in Virtual Environments and Graphical Creativity Performance

A novel agent-based, evolutionary model for expressing the dynamics of creative open-problem solving in small groups

A Formal Model for Robot to Understand Common Concepts

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