Skip to main content

Diagrams for Learning to Lead in Salsa Dancing

  • Conference paper
  • First Online:
Diagrammatic Representation and Inference (Diagrams 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13462))

Included in the following conference series:

Abstract

Diagrammatic and symbolic notations play a role in the performing arts, such as music, dance, and drama. Some notations for documenting movement of the human body in time have been developed for research and practice. However, contrary to music and drama, learning to dance does not require the mastery of dance notations. The goal of the paper is to examine the potential of diagrammatic notational schemes for learning to lead in salsa dancing. First, goals and functions of dance notation are considered and an existing diagrammatical system is examined as a representational system. Subsequently, a systematic analysis of moves between salsa position diagrams is undertaken and learning tasks are suggested for empirical study.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 44.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 59.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Crazy Lion Productions: Super Mario, Salsa on1 Partnerwork@HotSalsaWeekend, https://www.youtube.com/watch?v=oJpF7z5yWA4.

  2. 2.

    Dance Dojo: How to Remember Salsa Moves (the mistake that’s holding you back), https://www.youtube.com/watch?v=6W58JLb04AA.

References

  1. Adams, C., et al.: Encyclopedia of Knot Theory. CRC Press (2021)

    Google Scholar 

  2. Baillieul, J., Ozcimder, K.: The control theory of motion-based communication: Problems in teaching robots to dance. In: 2012 American Control Conference (ACC), pp. 4319–4326. IEEE, Montreal, QC (2012). https://doi.org/10.1109/ACC.2012.6315286

  3. Boucheix, J.-M., Forestier, C.: Reducing the transience effect of animations does not (always) lead to better performance in children learning a complex hand procedure. Comput. Hum. Behav. 69, 358–370 (2017). https://doi.org/10.1016/j.chb.2016.12.029

    Article  Google Scholar 

  4. Connors, M.H., et al.: Expertise in complex decision making: the role of search in chess 70 years after de Groot. Cogn. Sci. 35(8), 1567–1579 (2011). https://doi.org/10.1111/j.1551-6709.2011.01196.x

    Article  Google Scholar 

  5. Goodman, N.: Languages of art. An approach to a theory of symbols. Hackett, Indianapolis (1976)

    Google Scholar 

  6. Ozcimder, K.: Communication through motion in dance with topological constraints. In: 2014 American Control Conference, pp. 178–183 IEEE, Portland, OR, USA (2014). https://doi.org/10.1109/ACC.2014.6859167

  7. Ozcimder, K., et al.: Perceiving artistic expression: a formal exploration of performance art salsa. IEEE Access. 6, 61867–61875 (2018). https://doi.org/10.1109/ACCESS.2018.2871003

    Article  Google Scholar 

  8. Palmer, S.: Fundamental Aspects of Cognitive Representation. In: Rosch, E., Lloyd, B. (eds.) Cognition and Categorization. pp. 259–303. Lawrence Elbaum Associates, Hillsdale, NJ (1978)

    Google Scholar 

  9. von Renesse, C., Ecke, V.: Mathematics and Salsa dancing. J. Math. Arts 5(1), 17–28 (2011). https://doi.org/10.1080/17513472.2010.491781

    Article  MathSciNet  MATH  Google Scholar 

  10. Thorndyke, P.W., Hayes-Roth, B.: Differences in spatial knowledge acquired from maps and navigation. Cogn. Psychol. 14(4), 560–589 (1982). https://doi.org/10.1016/0010-0285(82)90019-6

    Article  Google Scholar 

  11. Zhang, J., Norman, D.A.: Representations in distributed cognitive tasks. Cogn. Sci. 18(1), 87–122 (1994)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Erica de Vries .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

de Vries, E. (2022). Diagrams for Learning to Lead in Salsa Dancing. In: Giardino, V., Linker, S., Burns, R., Bellucci, F., Boucheix, JM., Viana, P. (eds) Diagrammatic Representation and Inference. Diagrams 2022. Lecture Notes in Computer Science(), vol 13462. Springer, Cham. https://doi.org/10.1007/978-3-031-15146-0_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-15146-0_22

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-15145-3

  • Online ISBN: 978-3-031-15146-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics