Joel Chan

On the Benefits and Pitfalls of Analogies for Innovative Design: Ideation Performance Based on Analogical Distance, Commonness, and Modality of Examples

Drawing inspiration from examples by analogy can be a powerful tool for innovative design during conceptual ideation but also carries the risk of negative design outcomes (e.g., design fixation), depending on key properties of examples. Understanding these properties is critical for effectively harnessing the power of analogy. The current research explores how variations in analogical distance, commonness, and representation modality influence the effects of examples on conceptual ideation. Senior-level engineering students generated solution concepts for an engineering design problem with or without provided examples drawn from the U.S. Patent database. Examples were crossed by analogical distance (near-field vs. far-field), commonness (more vs. less-common), and modality (picture vs. text). A control group that received no examples was included for comparison. Effects were examined on a mixture of ideation process and product variables. Our results show positive effects of far-field and less-common examples on novelty and variability in quality of solution concepts. These effects are not modulated by modality. However, detailed analyses of process variables suggest divergent inspiration pathways for far-field vs. less-common examples. Additionally, the combination of far-field, less-common examples resulted in more novel concepts than in the control group. These findings suggest guidelines for the effective design and implementation of design-by-analogy methods, particularly a focus on far-field, less-common examples during the ideation process.

Analogy as a strategy for supporting complex problem solving under uncertainty

Complex problem solving in naturalistic environments is fraught with uncertainty, which has significant impacts on problem-solving behavior. Thus, theories of human problem solving should include accounts of the cognitive strategies people bring to bear to deal with uncertainty during problem solving. In this article, we present evidence that analogy is one such strategy. Using statistical analyses of the temporal dynamics between analogy and expressed uncertainty in the naturalistic problem-solving conversations among scientists on the Mars Rover Mission, we show that spikes in expressed uncertainty reliably predict analogy use (Study 1) and that expressed uncertainty reduces to baseline levels following analogy use (Study 2). In addition, in Study 3, we show with qualitative analyses that this relationship between uncertainty and analogy is not due to miscommunication-related uncertainty but, rather, is primarily concentrated on substantive problem-solving issues. Finally, we discuss a hypothesis about how analogy might serve as an uncertainty reduction strategy in naturalistic complex problem solving.

The impact of analogies on creative concept generation: lessons from an in vivo study in engineering design.

Research on innovation often highlights analogies from sources outside the current problem domain as a major source of novel concepts; however, the mechanisms underlying this relationship are not well understood. We analyzed the temporal interplay between far analogy use and creative concept generation in a professional design teams brainstorming conversations, investigating the hypothesis that far analogies lead directly to very novel concepts via large steps in conceptual spaces (jumps). Surprisingly, we found that concepts were more similar to their preceding concepts after far analogy use compared to baseline situations (i.e., without far analogy use). Yet far analogies increased the teams concept generation rate compared to baseline conditions. Overall, these results challenge the view that far analogies primarily lead to novel concepts via jumps in conceptual spaces and suggest alternative pathways from far analogies to novel concepts (e.g., iterative, deep exploration within a functional space).

Providing Timely Examples Improves the Quantity and Quality of Generated Ideas

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.

The importance of iteration in creative conceptual combination.

Theories of creative conceptual combination hypothesize that, to generate highly creative concepts, one should attempt to combine source concepts that are very different from each other. While lab studies show a robust link between far combinations and increased novelty of concepts, empirical evidence that far combinations lead to more creative concepts (i.e., both more novel and of higher quality) is mixed. Drawing on models of the creative process, we frame conceptual combination as a divergent process, and hypothesize that iteration is necessary to convert far combinations into creative concepts. We trace conceptual genealogies of many hundreds of concepts proposed for a dozen different problems on a large-scale Web-based innovation platform, and model the effects of combination distance on creative outcomes of concepts. The results are consistent with our predictions: (1) direct effects of far combinations have a mean zero effect, and (2) indirect effects of far combinations (i.e., building on concepts that themselves build on far combinations) have more consistently positive effects. This pattern of effects is robust across problems on the platform. These findings lend clarity to theories of creative conceptual combination, and highlight the importance of iteration for generating creative concepts.

Comparing Different Sensemaking Approaches for Large-Scale Ideation

Large-scale idea generation platforms often expose ideators to previous ideas. However, research suggests people generate better ideas if they see abstracted solution paths (e.g., descriptions of solution approaches generated through human sensemaking) rather than being inundated with all prior ideas. Automated and semi-automated methods can also offer interpretations of earlier ideas. To benefit from sensemaking in practice with limited resources, ideation platform developers need to weigh the cost-quality tradeoffs of different methods for surfacing solution paths. To explore this, we conducted an online study where 245 participants generated ideas for two problems in one of five conditions: 1) no stimuli, 2) exposure to all prior ideas, or solution paths extracted from prior ideas using 3) a fully automated workflow, 4) a hybrid human-machine approach, and 5) a fully manual approach. Contrary to expectations, human-generated paths did not improve ideation (as meas-ured by fluency and breadth of ideation) over simply showing all ideas. Machine-generated paths sometimes significantly improved fluency and breadth of ideation over no ideas (although at some cost to idea quality). These findings suggest that automated sensemaking can improve idea generation, but we need more research to understand the value of human sensemaking for crowd ideation.

The Meaning of “Near” and “Far”: The Impact of Structuring Design Databases and the Effect of Distance of Analogy on Design Output

This work lends insight into the meaning and impact of “near” and “far” analogies. A cognitive engineering design study is presented that examines the effect of the distance of analogical design stimuli on design solution generation, and places those findings in context of results from the literature. The work ultimately sheds new light on the impact of analogies in the design process and the significance of their distance from a design problem. In this work, the design repository from which analogical stimuli are chosen is the U.S. patent database, a natural choice, as it is one of the largest and easily accessed catalogued databases of inventions. The “near” and “far” analogical stimuli for this study were chosen based on a structure of patents, created using a combination of Latent Semantic Analysis and a Bayesian based algorithm for discovering structural form, resulting in clusters of patents connected by their relative similarity. The findings of this engineering design study are contextualized with the findings of recent work in design by analogy, by mapping the analogical stimuli used in the earlier work into similar structures along with the patents used in the current study. Doing so allows the discovery of a relationship between all of the stimuli and their relative distance from the design problem. The results confirm that “near” and “far” are relative terms, and depend on the characteristics of the potential stimuli. Further, although the literature has shown that “far” analogical stimuli are more likely to lead to the generation innovative solutions with novel characteristics, there is such a thing as too far. That is, if the stimuli are too distant, they then can become harmful to the design process. Importantly, as well, the data mapping approach to identify analogies works, and is able to impact the effectiveness of the design process. This work has implications not only in the area of finding inspirational designs to use for design by analogy processes in practice, but also for synthesis, or perhaps even unification, of future studies in the field of design by analogy.

Integrating laboratory paradigms and ethnographic field studies for advancing analyses of creative processes

This symposium responds to calls for an integration of in-vivo and in-vitro methods when studying how people tackle complex, open-ended issues in the areas of creativity, design, and innovation. Bringing together expertise from multiple perspectives and methodological backgrounds we explore fruitful ways towards integrative approaches to analyzing creative processes and practices. The theme is addressed from theoretical and practical viewpoints.

IdeaHound: Self-sustainable Idea Generation in Creative Online Communities

One main challenge in large creative online communities is helping their members find inspirational ideas from a large pool of ideas. A high-level approach to address this challenge is to create a synthesis of emerging solution space that can be used to provide participants with creative and diverse inspirational ideas of others. Existing approaches to generate the synthesis of solution space either require community members to engage in tasks that detract from the main activity of generating ideas or depend on external crowd workers to help organize the ideas. We built IDEAHOUND a collaborative idea generation system that demonstrates an alternative “organic” human computation approach, where community members (rather than external crowds) contribute feedback about ideas as a byproduct of an activity that naturally integrates into the ideation process. This feedback in turn helps the community identify diverse inspirational ideas that can prompt community members to generate more high-quality and diverse ideas.

Situative Creativity: Larger Physical Spaces Facilitate Thinking of Novel Uses for Everyday Objects.

People often use spatial metaphors (e.g., think “laterally,” “outside the box”) to describe exploration of the problem space during creative problem solving. In this paper, we probe the potential cognitive underpinnings of these spatial metaphors. Drawing on theories of situative cognition, semantic foraging theory, and environmental psychology, we formulate and test the hypothesis that larger physical spaces can facilitate divergent (but not convergent) processes in problem space exploration. Across two experiments, participants worked on a battery of problem solving tasks intended to represent divergent (alternative uses, shape invention) and convergent (remote associates, letter extrapolation) problem solving processes in either a large or a small room. In Experiment 1, participants in the larger room produced more novel alternative uses for everyday objects, and created more novel shape inventions, but generated less practical alternative uses, than participants in the smaller room. In Experiment 2, participants in the larger room (including a variant larger room) also produced more novel alternative uses for everyday objects, and less practical alternative uses, than participants in a small room, but did not create more novel shape inventions. These results suggest that spatial metaphors for problem space exploration may reflect meaningful cognitive phenomena: People may be able to search more broadly in a problem space if they are in an environment where broad physical search is a salient affordance; however, this effect appears to be relatively small and may depend on having sufficiently motivated participants. Correspondence: Correspondence concerning this article should be addressed to Joel Chan at the Human-Computer Interaction Institute, Carnegie Mellon University, 2504B Newell-Simon Hall, 5000 Forbes Ave, Pittsburgh, PA 15213, via email to joelchuc@cs.cmu.edu, or via telephone to (479) 647-0575.