Advertisement

Detection and Behavioral Analysis of Preschoolers with Dyscalculia

  • Sheffali SuriEmail author
  • Annu Tirkey
  • J. Delphy
  • Sagaya Aurelia
Chapter
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 6)

Abstract

Human behaviours are influenced by various factors that might impact their thought process. The way human beings response in situations have a strong connection with genetic makeup, cultural values and experiences from the past. Behaviour Analysis discusses the effect of human response to external/internal stimuli. This study helps in understanding behaviour changes among individuals suffering from various psychological disorders. Dyscalculia is one similar type of learning disorder [LD] which is commonly found among individuals and goes undetected for years. It is a lifelong condition which causes difficulty for people to perform mathematics-related tasks. Dyscalculia is quite eminent at every age. Since the symptoms are prominent from a young age, it can be detected at the earliest. Dyscalculia has no medical treatment but can be minimized by getting involved in some brain exercises especially created for children with Learning Disabilities. The chapter deals with minor research and the behaviour analysis for the above-mentioned disorder among pre-schoolers. In this chapter, a study of the behavioural patterns of pre-schoolers with dyscalculia is performed. This chapter also attempts to propose a model that can detect and predict the possibility of a child suffering from dyscalculia. It also includes a number of brain training activities that can help them to improve and enhance their confidence in mathematics.

Keywords

Behaviour analysis Behaviour Dyscalculia Analysis Brain training 

References

  1. 1.
    Anxiety in Children, www.anxietyinchildren.com
  2. 2.
    B.N. Verdine, C.M. Irwin, R.M. Golinkoff, K. Hirshpasek, NIH public access. J. Exp. Child Psychol. 126, 37–51 (2014)CrossRefGoogle Scholar
  3. 3.
    B. Butterworth, S. Varma, D. Laurillard, Dyscalculia: from brain to education. Science 332 (2011)MathSciNetCrossRefGoogle Scholar
  4. 4.
    ‘Shalev et al. (1997)’, ‘Butterworth (1999)’, ‘Gross-Tsur and Manor (1996)’, ‘Ostad (1998)’ and ‘Dickson et al. (1984)’Google Scholar
  5. 5.
    I. Rapin, Dyscalculia and the calculating brain. Pediatr. Neurol. 61, 11–20 (2016)CrossRefGoogle Scholar
  6. 6.
    P.J. Dinkel, K. Willmes, H. Krinzinger, K. Konrad, J.W. Koten, Jr., Diagnosing developmental dyscalculia on the basis of reliable single case FMRI methods: promises and limitations. PLOS ONE 8(12), e83722 (2013)CrossRefGoogle Scholar
  7. 7.
    O. Simsek, Use of a game-based app as a learning tool for students with mathematics learning disabilities to increase fraction knowledge/skill, June 2016Google Scholar
  8. 8.
    Understood for learning and attention issues, https://www.understood.org/en
  9. 9.
    A. Plerou, Dealing with dyscalculia over time, in ICICTE, no. 2008, pp. 1–12 (2014)Google Scholar
  10. 10.
    T. Käser et al., Modelling and optimizing mathematics learning in children. Int. J. Artif. Intell. Educ. 23(1–4), 115–135 (2013)CrossRefGoogle Scholar
  11. 11.
    G. Karagiannakis, A. Baccaglini-Frank, Y. Papadatos, Mathematical learning difficulties subtypes classification. Front. Hum. Neurosci. 8, 57 (2014)Google Scholar
  12. 12.
    J. Borg, A. Lantz, J. Gulliksen, Accessibility to electronic communication for people with cognitive disabilities: a systematic search and review of empirical evidence. Univers. Access Inf. Soc. 14(4), 547–562 (2014)CrossRefGoogle Scholar
  13. 13.
    N. Sachdeva, A.M. Tuikka, K.K. Kimppa, R. Suomi, Digital disability divide in information society: literature review. J. Inf. Commun. Ethics Soc. 13(3), 283–298 (2015)CrossRefGoogle Scholar
  14. 14.
    F. Ferraz, H. Vicente, A. Costa, J. Neves, Analysis of dyscalculia evidences through artificial intelligence systems. J. Softw. Netw. 53–78 (2016)CrossRefGoogle Scholar
  15. 15.
    R.K. Vukovic, N.K. Lesaux, The relationship between linguistic skills and arithmetic knowledge. Learn. Individ. Differ. 23(1), 87–91 (2013)CrossRefGoogle Scholar
  16. 16.
    M.M. Ariffin, F.A. Abd Halim, N. Abd Aziz, Mobile application for dyscalculia children in Malaysia, in Proceedings of the 6th International Conference on Computing and Informatics, Paper No. 099, 27 Apr 2017Google Scholar
  17. 17.
    S. Pieters, H. Roeyers, Y. Rosseel, H. Van Waelvelde, A. Desoete, Identifying subtypes among children with developmental coordination disorder and mathematical learning disabilities, using model-based clustering. J. Learn. Disabil. (2013).  https://doi.org/10.1177/0022219413491288CrossRefGoogle Scholar
  18. 18.
    J. Ismaili, E.H.O. Ibrahimi, Mobile learning as alternative to assistive technology devices for special needs students. Educ. Inf. Technol. (2016)Google Scholar
  19. 19.
    K.L. Luxy, Learning difficulties and attention deficit hyperactivity disorder. J. Psychiatry 20(2), 1000404 (2017)Google Scholar
  20. 20.
    T. Nagavalli, P. Juliet, Technology for Dyscalculic Children (Salem, 2015)Google Scholar
  21. 21.
    I.C. Mammarella, S. Caviola, C. Cornoldi, D. Lucangeli, Mental additions and verbal-domain interference in children with developmental dyscalculia. Res. Dev. Disabil. (2013)Google Scholar
  22. 22.
    F.A. Aziz, H. Husni, Z. Jamaludin, Translating interaction design guidelines for dyslexic children’s reading application, in Proceedings of the World Congress on Engineering, vol. II (2013)Google Scholar
  23. 23.
    A.M. Hakkarainen, L.K. Holopainen, H.K. Savolainen, The impact of learning difficulties and socioemotional and behavioural problems on transition to postsecondary education or work life in Finland: a five-year follow-up study. Eur. J. Spec. Needs Educ. 31(2), 171–186 (2016)CrossRefGoogle Scholar
  24. 24.
    Cognitive Learning-Breaking Barriers to Learning, http://www.cognitivelearning.co.za/
  25. 25.
    S.Z. Ahmad, A. Abdul Mutalib, Exploring computer assisted learning for low achieving children: a comparative analysis study. J. Teknol. 77(29), 1–7 (2015)Google Scholar
  26. 26.
    A.C.G.C. Duijzer, S. Shayan, A. Bakker, M.F. Van der Schaaf, D. Abrahamson, Touchscreen tablets: coordinating action and perception for mathematical cognition. Front. Psychol. 8, 1–19 (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Sheffali Suri
    • 1
    Email author
  • Annu Tirkey
    • 1
  • J. Delphy
    • 1
  • Sagaya Aurelia
    • 1
  1. 1.Department of Computer ScienceCHRIST (Deemed to be University)BangaloreIndia

Personalised recommendations