Two experimental studies on creative concept combinations in modular design of electronic embedded systems

Doboli, Alex; Umbarkar, Anurag; Subramanian, Varun; Doboli, Simona

doi:10.1016/j.destud.2013.10.002

Cited by 29 publications

(19 citation statements)

References 47 publications

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“…For example, research has considered how the semantic relevance [8,9,13], novelty [9,1], and diversity [15,51,5,45] of examples influence ideation. However, one important question has received less attention: when should innovators look at examples?…”

Section: Introductionmentioning

confidence: 99%

Providing Timely Examples Improves the Quantity and Quality of Generated Ideas

Siangliulue

Chan

Gajos

et al. 2015

Proceedings of the 2015 ACM SIGCHI Conference on Creativity and Cognition

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Emerging online ideation platforms with thousands of example ideas provide an important resource for creative production. But how can ideators best use these examples to create new innovations? Recent work has suggested that not just the choice of examples, but also the timing of their delivery can impact creative outcomes. Building on existing cognitive theories of creative insight, we hypothesize that people are likely to benefit from examples when they run out of ideas. We explore two example delivery mechanisms that test this hypothesis: 1) a system that proactively provides examples when a user appears to have run out of ideas, and 2) a system that provides examples when a user explicitly requests them. Our online experiment (N=97) compared these two mechanisms against two baselines: providing no examples and automatically showing examples at a regular interval. Participants who requested examples themselves generated ideas that were rated the most novel by external evaluators. Participants who received ideas automatically when they appeared to be stuck produced the most ideas. Importantly, participants who received examples at a regular interval generated fewer ideas than participants who received no examples, suggesting that mere access to examples is not sufficient for creative inspiration. These results emphasize the importance of the timing of example delivery. Insights from this study can inform the design of collective ideation support systems that help people generate many high quality ideas.

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Section: Introductionmentioning

confidence: 99%

Providing Timely Examples Improves the Quantity and Quality of Generated Ideas

Siangliulue

Chan

Gajos

et al. 2015

Proceedings of the 2015 ACM SIGCHI Conference on Creativity and Cognition

View full text Add to dashboard Cite

show abstract

“…The semantic network properties in Subsection 2.4 highlight the importance of effective convergent and divergent reasoning for creative problem solving (Doboli, Subramanian, Umbarkar & Doboli, 2014). Expressions (3)-(6) describe the time efficiency of the process, in which the observed features rapidly converge to correct identification of the involved concepts.…”

Section: Discussionmentioning

confidence: 99%

“…Creativity is defined by the novelty, usefulness, and feasibility of the solutions (Amabile, 1982;Doboli, Subramanian, Umbarkar & Doboli, 2014): · Novelty relates to the network part presenting features, concepts, and categories as this part characterizes the variety of the concepts that are reached starting from a certain concept. The higher the variety, the higher the likelihood of reaching concepts that were rarely utilized before in problem solving, and hence the novelty of the solution is higher.…”

Section: Discussionmentioning

confidence: 99%

“…Problem solving involves ideation and implementation, like (i) identifying the concept features that are used in the solution and (ii) devising new association sequences between concepts and their features as expressed by a semantic network. · Open-ended problems require identifying new goals and rewards starting from an extensible set of building blocks and related rules (Doboli, Subramanian, Umbarkar & Doboli, 2014). Such examples include the problems of game design and embedded system design in Section III.…”

Section: Figure 2: Connection Between Semantic Network Organization Amentioning

confidence: 99%

“…sensors, actuators, computing and storage elements, and networking modules (Doboli, Umbarkar, Subramanian & Doboli, 2014). Problem solving involves problem framing, ideation, and implementation of the identified needs.…”

Section: Electronic Embedded System Designmentioning

confidence: 99%

See 2 more Smart Citations

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

Doboli

Umbarkar

Doboli

et al. 2015

Knowledge-Based Systems

Self Cite

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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.

show abstract

Two experimental studies on creative concept combinations in modular design of electronic embedded systems

Cited by 29 publications

References 47 publications

Providing Timely Examples Improves the Quantity and Quality of Generated Ideas

Providing Timely Examples Improves the Quantity and Quality of Generated Ideas

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

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

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