Skip to main content
Springer Nature Link
Log in

Realizing the Potential Effect of Interactable Concept Network for Idea Generation

  • Conference paper
  • First Online:
Cross-Cultural Design. Applications in Business, Communication, Health, Well-being, and Inclusiveness (HCII 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13313))

Included in the following conference series:

  • 1230 Accesses

Abstract

Idea generation is the foundation of creativity and innovation, and learning various ideation methods, such as mind-map, scamper, etc. is a critical capability in a design-thinking course. With emerging technologies, many data-driven conceptual design tools exist to provide designers with external inspirational stimuli for ideation. Compared to traditional ideation methods, the data-driven conceptual tools are time-saving for gathering information, and labor-saving for generating numerous, various and creative ideas. Moreover, designers are able to avoid individually experiential limitation, which may cause the fixation of ideation. However, most data-driven conceptual tools are biased towards the industrial engineering field, and are too complicated to intuitively use for novice designers. Hence, this study established the user-friendly ideation tool named Interactable Concept Network (ICN) by integrating the mind-mapping method, semantic network database, and human cognitive process, additionally investigated its effects on novice designers learning of design-thinking courses. We assume that there is a potential effectiveness to assist and inspire novice designers to develop more creative concepts by applying ICN tool. With a pre–post-test design, a brief design course-long experiment as pre-test was then conducted with the mind-map method to evaluate the initial learning motivation and creativity. At this current study stage, the pre-test results revealed that the recognition and delivery errors caused by the handwritten and inaccurate description influenced the score of creativity.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Amabile, T.M.: Creativity in Context. Westview Press, Boulder (1996). https://doi.org/10.4324/9780429501234

  2. Baer, J.: Commentary: divergent thinking tests have problems, but this is not the solution. Psychol. Aesthet. Creat. Arts 2(2) 89–92 (2008)

    Google Scholar 

  3. Chan, J., Fu, K., Schunn, C., Cagan, J., Wood, K., Kotovsky, K.: On the bene- fits and pitfalls of analogies for innovative design: Ideation performance based on analogical distance, commonness, and modality of examples. J. Mech. Des. 133 (2011)

    Google Scholar 

  4. Chen, L., et al.: An artificial intelligence based data-driven approach for design ideation. J. Vis. Commun. Image Represent 61, 10–22 (2019)

    Article  Google Scholar 

  5. Gero, J.S., Kannengiesser, U.: The situated function–behaviour–structure framework. Design Studies 25(4), 373–391 (2004). https://doi.org/10.1016/j.destud.2003.10.010. https://www.sciencedirect.com/science/article/pii/S0142694X03000735

  6. Han, J., Forbes, H., Shi, F., Hao, J., Schaefer, D.: A data-driven approach for creative concept generation and evaluation. In: Proceedings of the Design Society: DESIGN Conference, vol. 1, pp. 167–176 (2020). https://doi.org/10.1017/dsd.2020.5

  7. Han, J., Hua, M., Shi, F., Childs, P.R.N.: A further exploration of the three driven approaches to combinational creativity. In: Proceedings of the Design Society: International Conference on Engineering Design, vol. 1, pp. 2735–2744 (2019). https://doi.org/10.1017/dsi.2019.280

  8. Han, J., Park, D., Forbes, H., Schaefer, D.: A computational approach for using social networking platforms to support creative idea generation. Procedia CIRP 91, 382–387 (2020)

    Article  Google Scholar 

  9. Han, J., Shi, F., Chen, L., Childs, P.R.: The combinator–a computer-based tool for creative idea generation based on a simulation approach. Des. Sci. 4 (2018). https://doi.org/10.1017/dsj.2018.7

  10. Han, J., Shi, F., Park, D., Chen, L., Childs, P., et al.: The conceptual distances between ideas in combinational creativity. In: DS 92: Proceedings of the DESIGN 2018 15th International Design Conference, pp. 1857–1866 (2018)

    Google Scholar 

  11. Koronis, G., Silva, A., Kang, J.K.S., Yogiaman, C.: How to best frame a design brief to maximize novelty and usefulness in idea generation. In: Proceedings of the Design Society: DESIGN Conference, vol. 1, pp. 1745–1754 (2020). https://doi.org/10.1017/dsd.2020.77. https://www.cambridge.org/core/article/how-to-best-frame-a-design-brief-to-maximize-novelty-and-usefulness-in-idea-generation/BF14ECC7199C206E6B9A757AE4C09E1B

  12. Lee, S., Yoon, B., Park, Y.: An approach to discovering new technology opportunities: keyword-based patent map approach. Technovation 29(6–7), 481–497 (2009). https://doi.org/10.1016/j.technovation.2008.10.006

    Article  Google Scholar 

  13. Luo, J., Sarica, S., Wood, K.L.: Guiding data-driven design ideation by knowledge distance. Knowl.-Based Syst. 218, 106873 (2021)

    Article  Google Scholar 

  14. Miller, G.A.: WordNet: An Electronic Lexical Database. MIT Press, Cambridge (1998)

    Google Scholar 

  15. Ozer, M., Cebeci, U.: Affective design using big data within the context of online shopping. J. Eng. Des. 30(8–9), 368–384 (2019). https://doi.org/10.1080/09544828.2019.1656803

  16. Pintrich, P.R., De Groot, E.V.: Motivational and self-regulated learning components of classroom academic performance. J. Educ. Psychol. 82(1), 33 (1990)

    Article  Google Scholar 

  17. Sarica, S., Luo, J.: Design knowledge representation with technology semantic network. Proc. Des. Soc. 1, 1043–1052 (2021)

    Article  Google Scholar 

  18. Sarica, S., Luo, J., Wood, K.L.: TechNet: technology semantic network based on patent data. Exp. Syst. Appl. 142, 112995 (2020)

    Google Scholar 

  19. Song, B., Luo, J.: Mining patent precedents for data-driven design: the case of spherical rolling robots. J. Mech. Des. 139(11) (2017)

    Google Scholar 

  20. Song, B., Luo, J., Wood, K.: Data-driven platform design: patent data and function network analysis. J. Mech. Des. 144(2), 021101 (2019)

    Google Scholar 

  21. Srinivasan, V., et al.: Does analogical distance affect performance of ideation? J. Mech. Des. 140(7) (2018)

    Google Scholar 

  22. Wodehouse, A., Vasantha, G., Corney, J., Jagadeesan, A., MacLachlan, R.: Realising the affective potential of patents: a new model of database interpretation for user-centred design. J. Eng. Des. 29(8–9), 484–511 (2018)

    Google Scholar 

  23. You, W.T., Sun, L.Y., Yang, Z.Y., Yang, C.Y.: Automatic advertising image color design incorporating a visual color analyzer. J. Comput. Lang. 55, 100910 (2019)

    Google Scholar 

  24. Zhao, Y., et al.: Mining affective words to capture customer’s affective response to apparel products. Text. Res. J. 88(12), 1426–1436 (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. The Graduate Institute of Design Science, Tatung University, Taipei, Taiwan

    Yi-Jing Lin & Yen Hsu

Authors
  1. Yi-Jing Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yen Hsu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yi-Jing Lin .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Pei-Luen Patrick Rau

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Lin, YJ., Hsu, Y. (2022). Realizing the Potential Effect of Interactable Concept Network for Idea Generation. In: Rau, PL.P. (eds) Cross-Cultural Design. Applications in Business, Communication, Health, Well-being, and Inclusiveness. HCII 2022. Lecture Notes in Computer Science, vol 13313. Springer, Cham. https://doi.org/10.1007/978-3-031-06050-2_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-06050-2_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06049-6

  • Online ISBN: 978-3-031-06050-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics