Modeling and Assessing Young Children Abilities and Development in Ambient Intelligence

  • Emmanouil Zidianakis
  • Danai Ioannidi
  • Margherita AntonaEmail author
  • Constantine Stephanidis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9425)


This paper presents a novel framework, called Bean, which aims to monitor, evaluate and enhance pre-school children’s skills and abilities through playing in Ambient Intelligence environments. The framework includes: (i) a model of children development based on the ICF-CY model and the Denver - II assessment tool, aiming at early detection of children’s potential developmental issues to be further investigated and addressed if necessary; (ii) a reasoning mechanism for the automated extraction of child development knowledge, based on interaction monitoring, targeted to model relevant aspects of child’s developmental stage, maturity level and skills; (iii) content editing tools and reporting facilities for parents and therapists. The framework has been implemented in the context of an AmI environment for supporting children play in AmI, deploying a collection of augmented artifacts, as well as a collection of digital reproductions of popular games.


Child play Development Ambient intelligence Evaluation process and/or assessment 



This work is supported by the FORTH-ICS internal RTD Programme ‘Ambient Intelligence and Smart Environments’.


  1. 1.
    Adamson, L.B., Bakeman, R.: Viewing variations in language development: the communication play protocol. Augmentative Altern. Commun. 8, 2–4 (1999) (Newsletter for ASHA Division 12)Google Scholar
  2. 2.
    Baranek, G.T., Barnett, C., Adams, E., Wolcott, N., Watson, L., Crais, E.: Object play in infants with autism: methodological issues in retrospective video analysis. Am. J. Occup. Ther. 59(1), 20–30 (2005)CrossRefGoogle Scholar
  3. 3.
    Bosse, T., Both, F., Gerritsen, C., Hoogendoorn, M., Treur, J.: Methods for model-based reasoning within agent-based ambient intelligence applications. Knowl. Based Syst. 27, 190–210 (2012)CrossRefGoogle Scholar
  4. 4.
    Bricker, D.D., Squires, J., Potter, L.W., Twombly, R.E.: Ages and Stages Questionnaires (ASQ): A Parent-Completed, Child-Monitoring System. Paul H. Brookes Publishing CO, Baltimore (1999)Google Scholar
  5. 5.
    Casas, R., Blasco Maríın, R., Robinet, A., Delgado, A.R., Yarza, A.R., McGinn, J., Picking, R., Grout, V.: User modelling in ambient intelligence for elderly and disabled people. In: Miesenberger, K., Klaus, J., Zagler, W.L., Karshmer, A.I. (eds.) ICCHP 2008. LNCS, vol. 5105, pp. 114–122. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  6. 6.
    Clarke, A.M.: Young children and ICT-current issues in the provision of ICT technologies and services for young children. ETSI White Paper, No. 2 (2006)Google Scholar
  7. 7.
    Cooper, B., Brna, P.: Hidden curriculum, hidden feelings: emotions, relationships and learning with ICT and the whole child. Paper presented at the BERA conference, Exeter, September 2002Google Scholar
  8. 8.
    Costello, J., Ali, F.: Reliability and validity of peabody picture vocabulary test scores of disadvantaged preschool children. Psychol. Rep. 28(3), 755–760 (1971)CrossRefGoogle Scholar
  9. 9.
    Czyzewski, A., Odya, P., Grabkowska, A., Grabkowski, M., Kostek, B.: Smart Pen– New multimodal Computer Control Tool for Dyslexia Therapy. Gdansk University of Technology, Multimedia Systems Department, Poland (2010)Google Scholar
  10. 10.
    De Carolis, B., Pizzutilo, S., Palmisano, I.: D-Me: personal interaction in smart environments. In: Brusilovsky, P., Corbett, A.T., de Rosis, F. (eds.) UM 2003. LNCS, vol. 2702, pp. 388–392. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  11. 11.
    Fisher, K., Hirsh-Pasek, K., Golinkoff, R.M., Singer, D.G., Berk, L.: Playing around in school: implications for learning and educational policy. In: Pellegrini, A.D. (ed.) Oxford Handbook of the Development of Play. Oxford University Press, Oxford (2011)Google Scholar
  12. 12.
    Frankenburg, W.K., Dodds, J.B.: The denver developmental screening test. J. Pediatr. 71(2), 181–191 (1967)CrossRefGoogle Scholar
  13. 13.
    Frankenburg, W.K., Dodds, J., Archer, P., Shapiro, H., Bresnick, B.: The denver II: a major revision and restandardization of the denver developmental screening test. Pediatrics 89(1), 91–97 (1992)Google Scholar
  14. 14.
    Frankenburg, W.K.: Developmental surveillance and screening of infants and young children. Pediatrics 109(109), 144–145 (2002)CrossRefGoogle Scholar
  15. 15.
    Granlund, M., Eriksson, L., Ylven, R.: Utility of the international classification of functioning, disability and health participation dimension in assigning ICF codes to items for extant rating instruments. J. Rehabil. Med. 36(3), 130–137 (2004)CrossRefGoogle Scholar
  16. 16.
    Hayes, G.R., Gardere, L.M., Abowd, G.D., Truong, K.N.: CareLog: a selective archiving tool for behavior management in schools. In: Conference on Human Factors in Computing Systems (CHI 2008), pp. 685–694. ACM Press, Florence, Italy (2008)Google Scholar
  17. 17.
    Heckmann, D., Schwartz, T., Brandherm, B., Schmitz, M., von Wilamowitz-Moellendorff, M.: Gumo – the general user model ontology. In: Ardissono, L., Brna, P., Mitrović, A. (eds.) UM 2005. LNCS (LNAI), vol. 3538, pp. 428–432. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  18. 18.
    Hewes, J.: Let the children play:nature’s answer to early learning. Ph.D. Chair of the Early Childhood Education Program, Grant MacEwan College, Alberta, Canada (2006)Google Scholar
  19. 19.
    Hurlock, E.B.: Child Growth and Development. Tata McGraw-Hill Education, New Delhi (1978)Google Scholar
  20. 20.
    Jameson, A., Krüger, A.: Preface to the special issue on user modelling in ubiquitous computing. User Model. User-Adap. Interact. 15(3–4), 193–195 (2005)CrossRefGoogle Scholar
  21. 21.
    Kalliala, M.: Play Culture in a Changing World. Open University Press, Berkshire (2006)Google Scholar
  22. 22.
    Kientz, J.A., Abowd, G.D.: KidCam: toward an effective technology for the capture of children’s moments of interest. In: Tokuda, H., Beigl, M., Friday, A., Brush, A.J.B., Tobe, Y. (eds.) Pervasive 2009. LNCS, vol. 5538, pp. 115–132. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  23. 23.
    Kientz, J.A.: Decision support for caregivers through embedded capture and access. Ph.D. thesis, College of Computing, School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, USA (2008)Google Scholar
  24. 24.
    Knobloch, H., Pasamanick, B., Sherard, E.S.: A developmental screening inventory. Department of Pediatrics and Department of Psychiatry, Ohio State University College of Medicine, Columbus, Ohio (1966)Google Scholar
  25. 25.
    Msall, M.E., Msall, E.R.: Functional assessment in neurodevelopmental disorders. In: Accardo, P.J. (ed.) Capute and Accardo’s Neurodevelopmental Disabilities in Infancy and Childhood, 3rd edn, pp. 419–443. Paul Brookes, Baltimore (2007)Google Scholar
  26. 26.
    Kaklanis, N., Moschonas, P., Moustakas, K., Tzovaras, D.: Virtual user models for the elderly and disabled for automatic simulated accessibility and ergonomy evaluation of designs. Univ. Access Inf. Soc. 12(4), 403–425 (2013)Google Scholar
  27. 27.
    O’Hara, M.: Young children, learning and ICT: a case study in the UK maintained sector. Technol. Pedagogy Educ. 17(1), 29–40 (2008)Google Scholar
  28. 28.
    Piaget, J.: Main Trends in Psychology. George Allen & Unwin, London (1973)Google Scholar
  29. 29.
    Reynolds, P.C.: Play, language and human evolution. In: Bruner, J.S., Jolly, A., Sylva, K. (eds.) Play: Its Role in Development and Evolution, pp. 621–635. Basic Books, New York (1976)Google Scholar
  30. 30.
    Riva, S., Antonietti, A.: The application of the ICF CY model in specific learning difficulties: a case study. Psychol. Lang. Commun. 14(2), 37–58 (2010)CrossRefGoogle Scholar
  31. 31.
    Salah, A.A., Schouten, B.A., Göbel, S., Arnrich, B.: Playful interactions and serious games. J. Ambient Intell. Smart Environ. 6(3), 259–262 (2014)Google Scholar
  32. 32.
    Salkind, N.J.: An Introduction to Theories of Human Development. SAGE Publications Inc, California (2004)CrossRefGoogle Scholar
  33. 33.
    Sarama, J.: Technology in early childhood mathematics: Building Blocks as an innovative technology-based curriculum. State University of New York, Buffalo (2003)Google Scholar
  34. 34.
    Mulligan, S.E.: Occupational Therapy Evaluation for Children. Lippincott Williams & Wilkins. Philadelphia, Pennsylvania, USA (2003)Google Scholar
  35. 35.
    Stuberg, W.A., White, P.J., Miedaner, J.A., Dehne, P.R.: Item reliability of the Milani-Comparetti motor development screening test. Phys. Ther. 69(5), 328–335 (1989)Google Scholar
  36. 36.
    Sylva, K., Bruner, J.S., Genova, P.: The role of play in the problem-solving of children 3–5 years old. In: Bruner, J.S., Jolly, A., Sylva, K. (eds.) Play: Its Role in Development and Evolution, pp. 244–261. Basic Books, New York (1976)Google Scholar
  37. 37.
    Turbill, J.: A researcher goes to school: using technology in the kindergarten literacy curriculum. J. Early Child. Literacy 1(3), 255–278 (2001)CrossRefGoogle Scholar
  38. 38.
    Westeyn, T.L., Abowd, G.D., Starner, T.E., Johnson, J.M., Presti, P.W., Weaver, K.A.: Monitoring children’s developmental progress using augmented toys and activity recognition. Pers. Ubiquit. Comput. 16(2), 169–191 (2012)CrossRefGoogle Scholar
  39. 39.
    Westeyn, T.L., Kientz, J.A., Starner, T.E., Abowd, G.D.: Designing Toys with Automatic Play Characterization for Supporting the Assessment of a Child’s Development. College of Computing, Georgia Institute of Technology, Atlanta (2008)Google Scholar
  40. 40.
    World Health Organization: ICF CY the International Classification of Functioning, Disability and Health for Children and Adolescents. CH, WHO Ed, Geneva (2007)Google Scholar
  41. 41.
    Zidianakis, E.: Supporting young children in ambient intelligence environments. Ph.D. Thesis, University of Crete (2015)Google Scholar
  42. 42.
    Zidianakis, E., Antona, M., Paparoulis, G., Stephanidis, C.: An augmented interactive table supporting preschool children development through playing. In: The Proceedings of the 2012 AHFE International Conference (4th International Conference on Applied Human Factors and Ergonomics), San Francisco, California, USA, pp. 744–753, 21–25 July 2012. [CD-ROM]. USA Publishing (ISBN 978-0-9796435-5-2)Google Scholar
  43. 43.
    Zidianakis, E., Partarakis, N., Antona, M., Stephanidis, C.: Building a sensory infrastructure to support interaction and monitoring in ambient intelligence environments. In: Streitz, N., Markopoulos, P. (eds.) DAPI 2014. LNCS, vol. 8530, pp. 519–529. Springer, Heidelberg (2014)CrossRefGoogle Scholar
  44. 44.
    Zidianakis, E., Zidianaki, I., Ioannidi, D., Partarakis, N., Antona, M., Paparoulis, G., Stephanidis, C.: Employing ambient intelligence technologies to adapt games to children’s playing maturity. In: Antona, M., Stephanidis, C. (eds.) UAHCI 2015. LNCS, vol. 9177, pp. 577–589. Springer, Heidelberg (2015)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Emmanouil Zidianakis
    • 1
  • Danai Ioannidi
    • 1
  • Margherita Antona
    • 1
    Email author
  • Constantine Stephanidis
    • 1
    • 2
  1. 1.Foundation for Research and Technology – Hellas (FORTH) - Institute of Computer ScienceHeraklion, CreteGreece
  2. 2.Department of Computer ScienceUniversity of CreteHeraklion, CreteGreece

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