Concept Validation during Collaborative Ideation and Its Effect on Ideation Outcome

ABSTRACT

A major goal of collaborative ideation is improving the creativity of the ideas generated. Recent approaches enhance creativity by showing users similar ideas during productive ideation and diverse ideas when they reach an impasse. However, related work either demands a higher mental effort from users to assess similarity or yields only a limited number of similarity values. Furthermore, idea relationship is only considered in one dimension (similarity). In our research in progress, we introduce a new approach called concept validation. It enables us to (1) capture the conceptualization of users' ideas and (2) assess multi-dimensional relationships between all ideas in near real-time. We conducted a study with 90 participants to validate the suitability of our approach. The results indicate that adding the extraction of semantic concepts to the ideation process has no negative impact on number and creativity of ideas generated. This signifies an important step towards our vision of an idea-based knowledge graph used by an interactive system to improve computer-supported human creativity.

References

1. Osvald M. Bjelland and Robert Chapman Wood. 2008. An Inside View of IBM's Innovation Jam. MIT Sloan Management Review 50, 1 (2008), 32--40.
2. Joel Chan, Steven Dang, and Steven P. Dow. 2016. Improving Crowd Innovation with Expert Facilitation. In Proc. of the 19th Conference on CSCW & Social Computing. ACM, 1223--1235.
3. Joel et al. Chan. 2017. Semantically Far Inspirations Considered Harmful? Accounting for Cognitive States in Collaborative Ideation. In Proc. of the ACM SIGCHI C & C. ACM, 93--105.
4. Victor Girotto, Erin Walker, and Winslow Burleson. 2017. The Effect of Peripheral Micro-tasks on Crowd Ideation. In Proc. of CHI. ACM, 1843--1854.
5. Abderrahmane Khiat, Maximilian Mackeprang, and Claudia Müller-Birn. 2017. Semantic Annotation for Enhancing Collaborative Ideation. In Proc. of the 13th Semantics. ACM, 173--176.
6. Bernard A. Nijstad, Carsten K. W. De Dreu, Eric F. Rietzschel, and Matthijs Baas. 2010. The dual pathway to creativity model: Creative ideation as a function of flexibility and persistence. European Review of Social Psychology 21, 1 (2010), 34--77.
7. Pao Siangliulue, Joel Chan, Steven P. Dow, and Krzysztof Z. Gajos. 2016. IdeaHound: Improving Large-scale Collaborative Ideation with Crowd-powered Real-time Semantic Modeling. In Proc. of UIST. ACM, 609--624.
8. Pao Siangliulue, Joel Chan, Krzysztof Z. Gajos, and Steven P. Dow. 2015. Providing timely examples improves the quantity and quality of generated ideas. In Proc. of the ACM SIGCHI C & C. ACM, 83--92.

Index Terms

• Human-centered computing

  • Collaborative and social computing