Personal and Ubiquitous Computing

, Volume 21, Issue 2, pp 253–265 | Cite as

Innovative technologies for intangible cultural heritage education and preservation: the case of i-Treasures

  • G. CozzaniEmail author
  • F. Pozzi
  • F. M. Dagnino
  • A. V. Katos
  • E. F. Katsouli
Original Article


The recent technological development has opened up innovative scenarios in the field of intangible cultural heritage (ICH) education and preservation. Main aim of this paper is to present a study, whose objective was to investigate whether and to what extent technologies can play a role in the ICH preservation and education. The study was conducted in the context of i-Treasures, a project funded by the European Community. During the project, a platform has been created, which provides different types of services that can meet the demands of different types of users in the ICH education domain. In the paper, the process followed for the implementation of such platform is described, starting from the analysis of the user needs, down to the development of the various innovative features. These encompass not only informative functionalities but—even more importantly—features allowing sensorimotor learning experiences for the user, who—by wearing innovative sensors—can practice rare forms of dancing or singing and get feedback about the correctness of the performance. The paper presents the methodology and findings of the user evaluation and then points out the main strong points and weaknesses of using innovative technologies in the ICH preservation and education.


Intangible cultural heritage (ICH) Education Preservation Platform User requirements Motor learning Sensors 


  1. 1.
    Severo M, Venturini T (2015) Intangible cultural heritage webs: comparing national networks with digital methods. New Media Soc 18(8):1–20Google Scholar
  2. 2.
    Chianese A, Piccialli F, Valente I (2015) Smart environments and cultural heritage: a novel approach to create intelligent cultural spaces. J Locat Based Serv 9(3):209–234CrossRefGoogle Scholar
  3. 3.
    Chianese A, Piccialli F (2015) Improving user experience of cultural environment through IoT: the beauty or the truth case stud. Smart Innov Syst Technol 40(2015):11–20CrossRefGoogle Scholar
  4. 4.
    Mortara M, Catalano CE, Bellotti F, Fiucci G, Houry-Panchetti M, Petridis P (2014) Learning cultural heritage by serious games. J Cult Herit 15(3):318–325CrossRefGoogle Scholar
  5. 5.
    Aspasia D, Hatziharistos D, Koutsouba M, Tyrovola V (2011) The use of technology in movement and dance education: recent practices and future perspectives. Proc Soc Behav Sci 15:3355–3361CrossRefGoogle Scholar
  6. 6.
    Bauer WI (2014) Music learning and technology. New Dir: A J Scholarsh Creat Leadersh Music Educ 1. Accessed 27 Sept 2016
  7. 7.
    Leijen Ä, Admiraal W, Wildschut L, Simons PR-J (2008) Students’ perspectives on e-learning and the use of a virtual learning environment in dance education. Res Dance Educ 9(2):147–162CrossRefGoogle Scholar
  8. 8.
    Ho Wai-Chung (2004) Use of information technology and music learning in the search for quality education. Br J Educ Technol 35(1):57–67CrossRefMathSciNetGoogle Scholar
  9. 9.
    Pozzi F, Alivizatou M, Dagnino FM, Ott M (2015) Going beyond preservation: how to support technology-enhanced learning in ICH education. Int J Herit Digit Era 4:21–40. doi: 10.1260/2047-4970.4.1.21 CrossRefGoogle Scholar
  10. 10.
    Glushkova A, Katsouli E, Kourvoulis G, Manitsaris A, Volioti C (2015) A hybrid content-learning management system for education and access to intangible cultural heritage. In: Proceeding of the 17th international conference on computer supported education (CSEDU 2015)Google Scholar
  11. 11.
    Pozzi F, Antonaci A, Dagnino FM, Ott M, Tavella M (2014) A participatory approach to define user requirements of a platform for intangible cultural heritage education. In: Proceeding of the 9th international conference on computer vision theory and applications (VISAPP2014), vol 2, pp 782–788Google Scholar
  12. 12.
    Dias BD, Diniz JA, Hadjileontiadis LJ (2014) Towards an intelligent learning management system under blended learning. Springer, Berlin, p 235CrossRefGoogle Scholar
  13. 13.
    Pozzi F, Cozzani G, Dagnino FM, Ott M, Tavella M (2015) Deliverable no: D2.3 second report on user requirements identification and analysis. Accessed 28 July 2016
  14. 14.
    Wiegers KE (1996) Creating a software engineering culture. Dorset House Publishing, NewYorkGoogle Scholar
  15. 15.
    Pozzi F, Alivizatou M, Antonaci A, Dagnino FM, Ott M (2013)i-Treasures project—deliverable no: D2.1 First report on user requirements identification and analysis. Accessed 28 July 2016
  16. 16.
    Manitsaris A, Katsouli E, Katos A, Hadjileontiadis L, Charisis V, Hadjidimitriou S (2015), i-Treasures project—deliverable no: D7.2 first evaluation report. Accessed 28 July 2016
  17. 17.
    Manitsaris A, Kourvoulis G, Nikolopoulos S, Chantas G, Grammalidis N, Yilmaz E, Pozzi F, Dagnino FM, Cotescu M (2015) i-Treasures project—deliverable no: D5.4 first version of the integrated platform. Accessed 27 Sept 2016
  18. 18.
    Dagnino FM, Hadjileontiadis L, Ott M, Pozzi F (2014) An integrated platform for intangible cultural heritage education: discussing around the definition of requirements and evaluation criteria. J Comput Inf Technol (CIT) 22(4):277–292CrossRefGoogle Scholar
  19. 19.
    Kitsikidis A, Dimitropoulos K, Uğurca D, Bayçay C, Yilmaz E, Tsalakanidou F, Douka S, Grammalidis N (2015) A game-like application for dance learning using a natural human computer interface. In: Proceedings of the HCI international 2015. Los Angeles, pp 2–7Google Scholar
  20. 20.
    Al Kork SK, Denby B, Roussel P, Chawah P, Buchman L, Adda-Decker M, Xu K, Tsalakanidou F, Kitsikidis A, Dagnino FM, Ott M, Pozzi F, Stone M, Yilmaz E, Uğurca D, Şahin C (2015) A novel human interaction game-like application to learn, perform and evaluate modern contemporary singing: “human beat box”. In: Proceedings of the 10th international conference on computer vision theory and applications (VISAPP2015)Google Scholar
  21. 21.
    Al Kork SK, Jaumard-Hakoun A, Adda-Decker M, Amelot A, Buchman L, Chawah P, Dreyfus G, Fux T, Pillot-Loiseau C, Roussel P, Stone M, Xu K, Denby B (2014) A multi-sensor helmet to capture rare singing, an intangible cultural heritage study. In: 10th international seminar on speech production (ISSP 2014), vol 1, pp 5–8Google Scholar
  22. 22.
    Hair F, Anderson R, Tatham R, Black W (2008) Multivariate data analysis with readings. Prentice-Hall, LondonGoogle Scholar
  23. 23.
    Byrne BM (2010) Structural equation modeling with AMOS: basic concepts, applications, and programming, 2nd edn. Routledge, LondonGoogle Scholar
  24. 24.
    Bollen KA (1989) Structural equations with latent variables. Wiley, New YorkCrossRefzbMATHGoogle Scholar
  25. 25.
    Delery J, Doty DH (1996) Modes of theorizing in strategic human resource management: test of universalistic, contingency and configurational performance predictions. Acad Manag J 39:802–835CrossRefGoogle Scholar
  26. 26.
    Kline RB (1998) Principles and practice of structural equation modeling. Guilford Press, New YorkzbMATHGoogle Scholar
  27. 27.
    Volioti C, Manitsaris S, Katsoul E, Manitsaris A (2016) x2 Gesture: how the machine learns the expressive gesture variations of expert musicians. In: Proceedings of the new interfaces for musical expression NIME2016, Brisbane, pp 11–15Google Scholar

Copyright information

© Springer-Verlag London 2016

Authors and Affiliations

  • G. Cozzani
    • 1
    Email author
  • F. Pozzi
    • 1
  • F. M. Dagnino
    • 1
  • A. V. Katos
    • 2
  • E. F. Katsouli
    • 2
  1. 1.Institute for Educational Technologies (ITD-CNR)GenoaItaly
  2. 2.University of MacedoniaThessaloníkiGreece

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