dmTEA: Mobile Learning to Aid in the Diagnosis of Autism Spectrum Disorders

  • David Cabielles-Hernández
  • Juan Ramón Pérez-Pérez
  • MPuerto Paule-Ruiz
  • Víctor M. Álvarez-García
  • Samuel Fernández-Fernández
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8719)

Abstract

Mobile Learning is a teaching-learning methodology which has been developed successfully both inside and outside the classroom. Thanks to the several possibilities of mobile devices, it has been possible to use them with students with special educational needs thus giving rise to software applications focussed on competence acquisition on the students’ part and offering such a high level of interaction that it could not be possible by using a PC. Advances in the development of mobile devices have made it feasible to go a step forward and help the teacher with the modelling and evaluation of this type of students. dmTEA is a mobile technology which allows both behaviour evaluation and modelling of students on the autism spectrum. It implements 12 activities – duly verified by experts – which are adapted to interaction with the mobile device within a specific context, the aim of which is to deal with student’s disorders by observing learning processes and modelling his or her behaviour during task performance. dmTEA implementation in two studies, i.e. a student with severe autism and another student with moderate autism, has helped the teacher at the time of evaluating by offering him or her the necessary information to carry out any possible intervention.

Keywords

mobile learning users with special needs autism 

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References

  1. 1.
    Afyouni, I., Ilarri, S., Ray, C., Claramunt, C.: Context-aware modelling of continuous location-dependent queries in indoor environments. J. Ambient Intell. Smart Environ. 5, 65–88 (2013)Google Scholar
  2. 2.
    Sharples, M.: The design of personal mobile technologies for lifelong learning. Comput. Educ. 34, 177–193 (2000)CrossRefGoogle Scholar
  3. 3.
    Elias, T.: 71. Universal instructional design principles for mobile learning. Int. Rev. Res. Open Distance Learn. 12, 143–156 (2011)Google Scholar
  4. 4.
    Park, Y.: A pedagogical framework for mobile learning: Categorizing educational applications of mobile technologies into four types. Int. Rev. Res. Open Distance Learn. 12, 78–102 (2011)Google Scholar
  5. 5.
    Traxler, J., Kukulska-Julme, A.: Mobile Learning in Developing Countries. Commonwealth of Learning (2005)Google Scholar
  6. 6.
    Ally, M.: Mobile learning: Transforming the delivery of education and training. Athabasca University Press (2009)Google Scholar
  7. 7.
    Wing, L., Gould, J.: Severe impairments of social interaction and associated abnormalities in children: Epidemiology and classification. J. Autism Dev. Disord. 9, 11–29 (1979)CrossRefGoogle Scholar
  8. 8.
    Rivière, Á., Martos, J.: Tratamiento del autismo. Nuevas perspectivas. Instituto de Migraciones y Servicios Sociales, Madrid (1998)Google Scholar
  9. 9.
    Rose, D.H., Meyer, A.: Teaching every student in the digital age: Universal design for learning. ERIC (2002)Google Scholar
  10. 10.
    Gea-Megías, M., Medina-Medina, N., Rodríguez-Almendros, M.L., Rodríguez-Fórtiz, M.J.: Sc@ut: Platform for Communication in Ubiquitous and Adaptive Environments Applied for Children with Autism. In: Stary, C., Stephanidis, C. (eds.) UI4ALL 2004. LNCS, vol. 3196, pp. 50–67. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  11. 11.
    Fernández-López, Á., Rodríguez-Fórtiz, M.J., Rodríguez-Almendros, M.L., Martínez-Segura, M.J.: Mobile learning technology based on iOS devices to sup-port students with special education needs. Comput. Educ. 61, 77–90 (2013)CrossRefGoogle Scholar
  12. 12.
    Leijdekkers, P., Gay, V., Wong, F.: CaptureMyEmotion: A mobile app to improve emotion learning for autistic children using sensors. In: Proceedings of CBMS 2013 - 26th IEEE International Symposium on Computer-Based Medical Systems, pp. 381–384 (2013)Google Scholar
  13. 13.
    Nicolás, F.T.: Tecnologías de ayuda en personas con trastornos del espectro autis-ta: guía para docentes. CPR Murcia I (2004)Google Scholar
  14. 14.
    Linstone, H.A., Turoff, M.: The Delphi method: Techniques and applications (1975)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • David Cabielles-Hernández
    • 1
  • Juan Ramón Pérez-Pérez
    • 1
  • MPuerto Paule-Ruiz
    • 1
  • Víctor M. Álvarez-García
    • 2
  • Samuel Fernández-Fernández
    • 3
  1. 1.Departament of Computer ScienceUniversity of OviedoSpain
  2. 2.Katholieke Universiteit LeuvenBelgium
  3. 3.Departament of Education ScienceUniversity of OviedoSpain

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