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A Composite Methodology for Supporting Early-Detection of Handwriting Dysgraphia via Big Data Analysis Techniques

  • Pierluigi D’Antrassi
  • Iolanda Perrone
  • Alfredo CuzzocreaEmail author
  • Agostino Accardo
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 76)

Abstract

Handwriting difficulties represent a common cause of underachievement in children’s education and low self-esteem in daily life. Since proper handwriting teaching methods can reduce dysgraphia problems, the evaluation of these methods represents an important task. In this paper a methodology to compare visual and spatio-temporal teaching methods is proposed and applied in order to assess the influence of different teaching approaches on handwriting performance, via big data analysis techniques. Data was collected from children in their final years of primary school, when cursive writing skills have typically been mastered. Qualitative and kinematic parameters were considered: the former were calculated by means of quality checklists, whereas the latter were automatically extracted from digitizing tablet acquisitions. Results showed significant differences in pupils’ handwriting depending on the teaching method applied.

References

  1. 1.
    Sassoon, R.: Handwriting: A New Perspective. Stanley Thornes, Cheltenham (1990)Google Scholar
  2. 2.
    Maeland, A.E.: Handwriting and perceptual motor skills in clumsy, dysgraphic, and normal children. Percept. Mot. Skills 75, 1207–1217 (1992)Google Scholar
  3. 3.
    Rubin, N., Henderson, S.E.: Two sides of the same coin: variation in teaching methods and failure to learn to write. Spec. Educ. Forw. Trends 9, 17–24 (1982)Google Scholar
  4. 4.
    Smits-Engelsman, B.C., Niemeijer, A.S., Van Galen, G.P.: Fine motor deficiencies in children diagnosed as DCD on poor grapho-motor ability. Hum. Mov. Sci. 20, 161–182 (2001)CrossRefGoogle Scholar
  5. 5.
    Karlsdottir, R., Stefansson, T.: Problems in developing functional handwriting. Percept. Mot. Skills 94, 623–662 (2002)CrossRefGoogle Scholar
  6. 6.
    Dunford, C., Missiuna, C., Street, E., Sibert, J.: Children’s perceptions of the impact of developmental coordination disorder on activities of daily living. Br. J. Occup. Ther. 68, 207–214 (2005)CrossRefGoogle Scholar
  7. 7.
    Hetzroni, O.E., Shrieber, B.: Word processing as an assistive technology tool for enhancing academic outcomes of students with writing disabilities in the general classroom. J. Learn. Disabil. 37(2), 143–154 (2004)CrossRefGoogle Scholar
  8. 8.
    Graham, S., Harris, K.R., Fink, B.: Is handwriting causally related to learning to write? Treatment of handwriting problems in beginning writers. J. Educ. Psychol. 92(4), 620–633 (2000)CrossRefGoogle Scholar
  9. 9.
    Frith, U.: Beneath the surface of surface dyslexia. Surf. Dyslexia Surf. Dysgraphia 32, 301–330 (1985)Google Scholar
  10. 10.
    Forster, K.: Accessing the mental lexicon. In: New Approaches to Language Mechanisms. North-Holland, Amsterdam (1976)Google Scholar
  11. 11.
    Coltheart, M.: Lexical access in simple reading tasks (1978)Google Scholar
  12. 12.
    Morton, J., Patterson, K.: A new attempt at an interpretation, or, an attempt at a new interpretation. In: Deep Dyslexia. Routledge, London (1980)Google Scholar
  13. 13.
    Coltheart, M.: Disorders of reading and their implications for models of normal reading. Visible Lang. 15(3), 245–286 (1981)Google Scholar
  14. 14.
    Margolin, D.I.: The neuropsychology of writing and spelling: semantic, phonological, motor, and perceptual processes. Q. J. Exp. Psychol. 36(3), 459–489 (1984)CrossRefGoogle Scholar
  15. 15.
    Denes, G., Cipollotti, L.: Dislessie e disgrafie acquisite. In: Manuale di Neuropsicologia. Zanichelli, Bologna (1990)Google Scholar
  16. 16.
    Van Galen, G.P.: Handwriting: issues for a psychomotor theory. Hum. Move. Sci. 10(2–3), 165–191 (1991)CrossRefGoogle Scholar
  17. 17.
    Ellis, A.W.: Spelling and writing (and reading and speaking). In: Normality and Pathology in Cognitive Functions. Academic Press, London (1982)Google Scholar
  18. 18.
    Miceli, G., Silveri, M.C., Caramazza, A.: Cognitive analysis of a case of pure dysgraphia. Brain Lang. 25, 187–196 (1985)CrossRefGoogle Scholar
  19. 19.
    Hamstra-Bletz, L., Blote, A.: A longitudinal study on dysgraphic handwriting in primary school. J. Learn. Disabil. 26, 689–699 (1993)CrossRefGoogle Scholar
  20. 20.
    Rosenblum, S., Aloni, T., Josman, N.: Relationships between handwriting performance and organizational abilities among children with and without dysgraphia: a preliminary study. Res. Dev. Disabil. 31, 502–509 (2010)CrossRefGoogle Scholar
  21. 21.
    Smits-Engelsman, B., Van Galen, G.: Dysgraphia in children lasting psychomotor deficiency or transient developmental delay. J. Exp. Child Psychol. 67, 164–184 (1997)CrossRefGoogle Scholar
  22. 22.
    Feder, K., Majnemer, A.: Handwriting development, competency, and intervention. Dev. Med. Child Neurol. 49, 312–317 (2007)CrossRefGoogle Scholar
  23. 23.
    Tseng, M., Chow, S.: Perceptual-motor function of school-age children with slow handwriting speed. Am. J. Occup. Ther. 54, 83–88 (2000)CrossRefGoogle Scholar
  24. 24.
    Pollock, N., Lockhart, J., Blowes, B., Semple, K., Webster, M., Farhat, L., et al.: Handwriting Assessment Protocol. McMaster University, Hamilton (2009)Google Scholar
  25. 25.
    Schneck, C.M., et al.: Prewriting and handwriting skills. In: Occupational Therapy for Children, 6th edn., pp. 555–582 (2010)Google Scholar
  26. 26.
    Schwellnus, H., Carnahan, H., Kushki, A., Polatajko, H., Missiuna, C., Chau, T.: Effect of pencil grasp on the speed and legibility of handwriting in children. Am. J. Occup. Ther. 66(6), 718–726 (2012)CrossRefGoogle Scholar
  27. 27.
    Schwellnus, H., Carnahan, H., Kushki, A., Polatajko, H., Missiuna, C., Chau, T.: Writing forces associated with four pencil grasp patterns in grade 4 children. Am. J. Occup. Ther. 67(2), 218–227 (2013)CrossRefGoogle Scholar
  28. 28.
    Genna, M., D’Antrassi, P., Ajčević, M., Accardo, A.: A new approach for objective evaluation of writing quality. In: 16th Nordic-Baltic Conference on Biomedical Engineering, pp. 32–35. Springer International Publishing (2015)Google Scholar
  29. 29.
    Accardo, A., Chiap, A., Borean, M., Bravar, L., Zoia, S., Carrozzi, M., Scabar, A.: A device for quantitative kinematic analysis of children’s handwriting movements. In: 11th Mediterranean Conference on Medical and Biomedical Engineering and Computing, pp. 445–448. Springer, Berlin, Heidelberg (2007)Google Scholar
  30. 30.
    Terzi, I.: ll Metodo spazio-temporale, basi teoriche e guida agli esercizi. Ghedini, Milano (1995)Google Scholar
  31. 31.
    Thomassen, A.J., van Galen, G.P.: Handwriting as a motor task: experimentation, modelling, and simulation. In: Approches to the Study of Motor Control and Learning. Elsevier Science, Amsterdam (1992)Google Scholar
  32. 32.
    Thelen, E.: Time-scale dynamics and the development of an embodied cognition. In: Mind as Motion: Explorations in the Dynamics of Cognition, pp. 69–100 (1995)Google Scholar
  33. 33.
    Iverson, J.M., Thelen, E.: Hand, mouth and brain. The dynamic emergence of speech and gesture. J. Conscious. Stud. 6(11–12), 19–40 (1999)Google Scholar
  34. 34.
    Tucha, O., Tucha, L., Lange, K.W.: Graphonomics, automaticity and handwriting assessment. Literacy 42(3), 145–155 (2008)CrossRefGoogle Scholar
  35. 35.
    Kushki, A., Schwellnus, H., Ilyas, F., Chau, T.: Changes in kinetics and kinematics of handwriting during a prolonged writing task in children with and without dysgraphia. Res. Dev. Disabil. 32(3), 1058–1064 (2011)CrossRefGoogle Scholar
  36. 36.
    Van Galen, G.P., Weber, J.F.: On-line size control in handwriting demonstrates the continuous nature of motor programs. Acta Psychol. 100, 195–216 (1998). (Amst)CrossRefGoogle Scholar
  37. 37.
    Accardo, A., Genna, M., Borean, M.: Development, maturation and learning influence on handwriting kinematics. Hum. Move. Sci. 32, 136–146 (2013)CrossRefGoogle Scholar
  38. 38.
    Djioua, M., Plamondon, R.: A new algorithm and system for the characterization of handwriting strokes with delta-lognormal parameters. IEEE Trans. Pattern Anal. Mach. Intell. 31(11), 2060–2072 (2009)CrossRefGoogle Scholar
  39. 39.
    Mavrogiorgou, P., Mergl, R., Tigges, P., El Husseini, J., Schröter, A., Juckel, G., et al.: Kinematic analysis of handwriting movements in patients with obsessive-compulsive disorder. J. Neurol. Neurosurg. Psychiatry 70(5), 605–612 (2001)CrossRefGoogle Scholar
  40. 40.
    Alston, J., Taylor, J.: Handwriting: Theory, Research and Practice. Croom Helm, London (1987)Google Scholar
  41. 41.
    Favretto, G., Fiorentini, F.: Ergonomia della formazione. Carocci, Roma (1999)Google Scholar
  42. 42.
    Drew, S.: Movement for writing: practical consideration from an occupational therapist’s perspective. Handwriting Today 1, 55–61 (2000)Google Scholar
  43. 43.
    Guiard, Y.: Asymmetric division of labor in human skilled bimanual action: the kinematic chain as a model. J. Modern Behav. 19, 486–517 (1987)CrossRefGoogle Scholar
  44. 44.
    Thomas, S.: The grip characteristics of pre-schoolers. Handwriting Rev. 11, 48–56 (1997)Google Scholar
  45. 45.
    Saaty, T.L.: The Analytic Hierarchy Process. McGraw-Hill, New York (1980)zbMATHGoogle Scholar
  46. 46.
    Creative Decision Foundation. Super Decision Software for decision making (2012). http://www.superdecisions.com
  47. 47.
    MIUR, “Linee guida per il diritto allo studio degli alunni e degli studenti con disturbi specifici di apprendimento,” Ministerial Decree, prot.5669, July 12nd (2011)Google Scholar
  48. 48.
    Cuzzocrea, A.: Privacy and security of big data: current challenges and future research perspectives. In: ACM PSBD 2014, pp. 45–47 (2014)Google Scholar
  49. 49.
    Cuzzocrea, A., Matrangolo, U.: Analytical synopses for approximate query answering in OLAP environments. In: DEXA 2004, pp. 359–370 (2004)Google Scholar
  50. 50.
    Cannataro, M., Cuzzocrea, A., Pugliese, A.: A probabilistic approach to model adaptive hypermedia systems. In: WebDyn 2001 (2001)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Pierluigi D’Antrassi
    • 1
  • Iolanda Perrone
    • 2
  • Alfredo Cuzzocrea
    • 1
    • 3
    Email author
  • Agostino Accardo
    • 1
  1. 1.DIA DepartmentUniversity of TriesteTriesteItaly
  2. 2.DCD DepartmentULSS 7TrevisoItaly
  3. 3.ICAR-CNRRendeItaly

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