Skip to main content
Book cover

International Conference on - Design Computing and Cognition

DCC 2018: Design Computing and Cognition '18 pp 155–173Cite as

Side-by-Side Human–Computer Design Using a Tangible User Interface

Abstract

We present a digital–physical system to support human–computer collaborative design. The system consists of a sensor-instrumented “sand table” functioning as a tangible space for exploring early-stage design decisions.

This is a preview of subscription content, access via your institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-030-05363-5_9
  • Chapter length: 19 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   299.00
Price excludes VAT (USA)
  • ISBN: 978-3-030-05363-5
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Hardcover Book
USD   379.99
Price excludes VAT (USA)
Learn about institutional subscriptions
Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Notes

  1. 1.

    We initially intended to explore a third hypothesis addressing learning outcomes but were unable to do so due to an error in data collection.

  2. 2.

    In the case that user-generated designs dominated any configurations on the reference frontier, they were assigned the negation of this distance. Overall, we acknowledge that this choice of reference may limit the validity of our finding to a small time or a small number of function evaluations

References

  1. Allen JF, Guinn CI, Horvtz E (1999) Mixed-initiative interaction. IEEE Intel Syst Appl 14(5):14–23

    CrossRef  Google Scholar 

  2. Arias E, Eden H, Fischer G, Gorman A, Scharff E (2000) Transcending the individual human mind–creating shared understanding through collaborative design. ACM Trans Computer-Human Int (TOCHI) 7(1):84–113

    CrossRef  Google Scholar 

  3. Arrow KJ (2012) Social choice and individual values, vol 12. Yale University Press

    Google Scholar 

  4. Babbar-Sebens M, Minsker BS (2012) Interactive genetic algorithm with mixed initiative interaction for multi-criteria ground water monitoring design. Appl Soft Comput J 12(1):182–195

    CrossRef  Google Scholar 

  5. Balling R (1999) Design by shopping: a new paradigm? In: Proceedings of the third world congress of structural and multidisciplinary optimization (WCSMO-3), vol 1, pp 295–297

    Google Scholar 

  6. Chen R, Wang X (2008) An empirical study on tangible augmented reality learning space for design skill transfer. Tsinghua Science and Technology 13 Supple (October):13–18

    Google Scholar 

  7. Cho SB (2002) Towards creative evolutionary systems with interactive genetic algorithm. Appl Intel 16(2):129–138

    CrossRef  Google Scholar 

  8. Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: Nsga-ii. IEEE Trans Evol Comput 6(2):182–197

    CrossRef  Google Scholar 

  9. Deb K, Karthik S et al (2007) Dynamic multi-objective optimization and decision-making using modified nsga-ii: a case study on hydro-thermal power scheduling. In: International conference on evolutionary multi-criterion optimization. Springer, pp 803–817

    Google Scholar 

  10. Dhanalakshmi S, Kannan S, Mahadevan K, Baskar S (2011) Application of modified nsga-ii algorithm to combined economic and emission dispatch problem. Int J Electr Power Energy Syst 33(4):992–1002

    CrossRef  Google Scholar 

  11. Do-Lenh S, Jermann P, Cuendet S, Zufferey G, Dillenbourg P (2010) Task performance versus learning outcomes: a study of a tangible user interface in the classroom. In: European conference on technology enhanced learning. Springer, pp 78–92

    Google Scholar 

  12. Durillo JJ, Nebro AJ (2011) jmetal: A java framework for multi-objective optimization. Adv Eng Softw 42(10):760–771

    CrossRef  Google Scholar 

  13. Egan P, Cagan J (2016) Human and computational approaches for design problem-solving. In: Experimental design research. Springer, pp 187–205

    Google Scholar 

  14. Ferguson G, Allen JF et al (1998) Trips: an integrated intelligent problem-solving assistant. In: AAAI/IAAI, pp 567–572

    Google Scholar 

  15. Fischer G (2004) Social creativity: turning barriers into opportunities for collaborative design. In: Proceedings of the eighth conference on participatory design: Artful integration: interweaving media, materials and practices-Volume 1, ACM, pp 152–161

    Google Scholar 

  16. Gero JS (1998) Conceptual designing as a sequence of situated acts. In: Artificial intelligence in structural engineering. Springer, pp 165–177

    Google Scholar 

  17. Grosz BJ (1996) Collaborative systems (aaai-94 presidential address). AI Mag 17(2):67

    MathSciNet  Google Scholar 

  18. Hay L, Duffy AHB, McTeague C, Pidgeon LM, Vuletic T, Grealy M (2017) A systematic review of protocol studies on conceptual design cognition: design as search andexploration. Des Sci 3:e10. arXiv:1011.1669v3

    Google Scholar 

  19. Hitomi N, Bang H, Selva D (2017) Extracting and applying knowledge with adaptive knowledge-driven optimization to architect an earth observing satellite system. AIAA Information Systems-AIAA Infotech@ Aerospace, p 0794

    Google Scholar 

  20. Ishibuchi H, Masuda H, Tanigaki Y, Nojima Y (2015) Modified distance calculation in generational distance and inverted generational distance. EMO 2:110–125

    Google Scholar 

  21. Ishii H, Ratti C, Piper B, Wang Y, Biderman A, Ben-Joseph E (2004) Bringing clay and sand into digital design—continuous tangible user interfaces. BT Technol J 22(4):287–299

    CrossRef  Google Scholar 

  22. Jeyadevi S, Baskar S, Babulal C, Iruthayarajan MW (2011) Solving multiobjective optimal reactive power dispatch using modified nsga-ii. Int J Electr Power Energy Syst 33(2):219–228

    CrossRef  Google Scholar 

  23. Jordà S, Geiger G, Alonso M, Kaltenbrunner M (2007) The reactable: exploring the synergy between live music performance and tabletop tangible interfaces. In: Proceedings of the 1st international conference on Tangible and embedded interaction, ACM, pp 139–146

    Google Scholar 

  24. Kaltenbrunner M (2009) Reactivision and tuio: a tangible tabletop toolkit. In: Proceedings of the ACM international conference on interactive tabletops and surfaces, ACM, pp 9–16

    Google Scholar 

  25. Kicinger R, Arciszewski T, De Jong K (2005) Evolutionary computation and structural design: A survey of the state-of-the-art. Comput Struct 83(23):1943–1978

    CrossRef  Google Scholar 

  26. Kim HS, Cho SB (2000) Application of interactive genetic algorithm to fashion design. Eng Appl Artif Intell 13(6):635–644

    CrossRef  Google Scholar 

  27. Kim M, Maher M (2005) Comparison of designers using a tangible user interface and graphical user interface and impact on spatial cognition. Proc Human Behav Des 5

    Google Scholar 

  28. Kim MJ, Maher ML (2008) The impact of tangible user interfaces on spatial cognition during collaborative design. Des Stud 29(3):222–253

    CrossRef  Google Scholar 

  29. Laugwitz B, Held T, Schrepp M (2008) Construction and evaluation of a user experience questionnaire. In: Symposium of the Austrian HCI and usability engineering group. Springer, pp 63–76

    Google Scholar 

  30. Laumanns M, Thiele L, Deb K, Zitzler E (2002) Combining convergence and diversity in evolutionary multiobjective optimization. Evol Comput 10(3):263–282

    CrossRef  Google Scholar 

  31. Liu H, Tang M (2006) Evolutionary design in a multi-agent design environment. Appl Soft Comput J 6(2):207–220

    CrossRef  MathSciNet  Google Scholar 

  32. Maher ML, Lee L (2017) Designing for gesture and tangible interaction. Synth Lect Human-Centered Interact 10(2):i–111

    Google Scholar 

  33. McCarthy J (2007) What is artificial intelligence. URL: http://www-formal.stanford.edu/jmc/whatisai.html

  34. Ozgur A, Johal W, Mondada F, Dillenbourg P (2017) Windfield: learning wind meteorology with handheld haptic robots. In: HRI’17: ACM/IEEE international conference on human-robot interaction proceedings, ACM, EPFL-CONF-224130, pp 156–165

    Google Scholar 

  35. Patten J, Ishii H (2000) A comparison of spatial organization strategies in graphical and tangible user interfaces. In: Proceedings of DARE 2000 on designing augmented reality environments, ACM, pp 41–50

    Google Scholar 

  36. Petersson K, Kyroudi A, Bourhis J, Ceberg C, Knöös T, Bochud F, Moeckli R (2017) A clinical distance measure for evaluating treatment plan quality difference with pareto fronts in radiotherapy. Phys Imaging Radiat Oncol 3:53–56

    CrossRef  Google Scholar 

  37. Ramchurn SD, Wu F, Jiang W, Fischer JE, Reece S, Roberts S, Rodden T, Greenhalgh C, Jennings NR (2016) Human-agent collaboration for disaster response. Auton Agent Multi-Agent Syst 30(1):82–111

    CrossRef  Google Scholar 

  38. Reed P, Minsker BS, Goldberg DE (2003) Simplifying multiobjective optimization: an automated design methodology for the nondominated sorted genetic algorithm-ii. Water Resour Res 39(7)

    Google Scholar 

  39. Selva D (2014a) Experiments in knowledge-intensive system architecting: interactive architecture optimization. In: Aerospace conference, 2014 IEEE, IEEE, pp 1–12

    Google Scholar 

  40. Selva D (2014b) Knowledge-intensive global optimization of earth observing system architectures: a climate-centric case study. In: Sensors, systems, and next-generation satellites XVIII, international society for optics and photonics, vol 9241, p 92411S

    Google Scholar 

  41. Selva D, Cameron BG, Crawley EF (2014) Rule-based system architecting of earth observing systems: earth science decadal survey. J Spacecraft Rockets

    Google Scholar 

  42. Shen W, Hao Q, Li W (2008) Computer supported collaborative design: retrospective and perspective. Comput Ind 59(9):855–862

    CrossRef  Google Scholar 

  43. Shirado H, Christakis NA (2017) Locally noisy autonomous agents improve global human coordination in network experiments. Nature 545(7654):370–374

    CrossRef  Google Scholar 

  44. Simon HA (1996) The sciences of the artificial. MIT press

    Google Scholar 

  45. Smithers T, Conkie A, Doheny J, Logan B, Millington K (1989) Design as intelligent behavior: an ai in design research program. In: Gero JS (ed) Artificial intelligence in design

    Google Scholar 

  46. Smithwick D, Kirsh D, Sass L (2017) Designerly pick and place: coding physical model making to inform material-based robotic interaction. In: Design computing and cognition’16. Springer, pp 419–436

    Google Scholar 

  47. Starcic AI, Zajc M (2011) An interactive tangible user interface application for learning addition concepts_1217 131. 135. Br J Edu Technol 42(6):E131–E135

    CrossRef  Google Scholar 

  48. Thornton C, Du Boulay B (2012) Artificial intelligence through search. Springer Science and Business Media

    Google Scholar 

  49. Ullmer B, Ishii H (1997) The metadesk: models and prototypes for tangible user interfaces. In: Proceedings of the 10th annual ACM symposium on user interface software and technology, ACM, pp 223–232

    Google Scholar 

  50. Van Veldhuizen DA, Lamont GB (1998) Evolutionary computation and convergence to a pareto front. In: Late breaking papers at the genetic programming 1998 conference, pp 221–228

    Google Scholar 

  51. Watson D, Clark LA, Tellegen A (1988) Development and validation of brief measures of positive and negative affect: the panas scales. J Pers Soc Psychol 54(6):1063

    CrossRef  Google Scholar 

  52. Xie L, Antle AN, Motamedi N (2008) Are tangibles more fun? comparing children’s enjoyment and engagement using physical, graphical and tangible user interfaces. In: Proceedings of the 2nd international conference on tangible and embedded interaction, ACM, pp 191–198

    Google Scholar 

  53. Zitzler E, Brockhoff D, Thiele L (2007) The hypervolume indicator revisited: on the design of pareto-compliant indicators via weighted integration. In: Evolutionary multi-criterion optimization. Springer, pp 862–876

    Google Scholar 

Download references

Acknowledgements

This work was supported primarily by the Civil, Mechanical and Manufacturing Innovation Program of the National Science Foundation under NSF Award No. 1635253.

Author information

Authors and Affiliations

  1. Cornell University, Ithaca, NY, USA

    Matthew V. Law, Nikhil Dhawan, Hyunseung Bang, So-Yeon Yoon, Daniel Selva & Guy Hoffman

Authors
  1. Matthew V. Law
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nikhil Dhawan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hyunseung Bang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. So-Yeon Yoon
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Daniel Selva
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Guy Hoffman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Matthew V. Law .

Editor information

Editors and Affiliations

  1. Department of Computer Science and School of Architecture, University of North Carolina at Charlotte, Charlotte, NC, USA

    Prof. John S. Gero

Rights and permissions

Reprints and Permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Law, M.V., Dhawan, N., Bang, H., Yoon, SY., Selva, D., Hoffman, G. (2019). Side-by-Side Human–Computer Design Using a Tangible User Interface. In: Gero, J. (eds) Design Computing and Cognition '18. DCC 2018. Springer, Cham. https://doi.org/10.1007/978-3-030-05363-5_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-05363-5_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05362-8

  • Online ISBN: 978-3-030-05363-5

  • eBook Packages: EngineeringEngineering (R0)