Computerized Assessment for Early Screening of Children with Handwriting Difficulty

Article Preview

Abstract:

This study aimed to investigate and identify the parameters that can be used in recognition of basic stroke patterns including straight lines, oblique lines, circles, and curves. The parameters determined are intended to be utilized in handwriting assessment system as a proposed method for screening of handwriting difficulty problem (HWD) among pupils. Seventeensubjects,agedbetween 7 and 8 years old, participated in this experiment. Each subject was requested to draw a series of principal graphic pattern (lines, circles and curves) using the computerized haptic system developed. Statistical analysis revealed that the threshold value used in identification of straight line patterns and angle difference range from-10.8963° ~ 54.4008°. The threshold value to identify a circle is-16.5435°< gap Angle < 64.2014°, and curve for 79.0398°< gap Angle < 187.7604°.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

392-397

Citation:

Online since:

September 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] V. W. Berninger and International Dyslexia Associaton (IDA): Understanding Dysgraphia, International Dyslexia Association (2008).

Google Scholar

[2] E. Chartrel and A. Vinter: The impact of spatio-temporal constraints on cursive letter handwriting in children, Learning and Instruction 18 (2008), pp.537-547.

DOI: 10.1016/j.learninstruc.2007.11.003

Google Scholar

[3] B. Engel-Yeger, L. Nagauker-Yanuv, and S. Rosenblum: Handwriting performance, self-reports, and perceived self-efficacy among children with dysgraphia, The American Journal of Occupational Therapy vol. 63 (2009), pp.182-192.

DOI: 10.5014/ajot.63.2.182

Google Scholar

[4] M. A. Rettig and J. Fischer: Dysgraphia: When Writing Hurts, Principal-Doing the Math-Web Exclusive, vol. 84 (2004), p.1–3.

Google Scholar

[5] C. D. Brina, R. Niels, A. Overvelde, and G. Levi: Dynamic time warping: A new method in the study of poor handwriting, Human movement, vol. 27 (2008), p.242–255.

DOI: 10.1016/j.humov.2008.02.012

Google Scholar

[6] T. Falk, C. Tam, and H. Schellnus: On the development of a computer-based handwriting assessment tool to objectively quantify handwriting proficiency in children, Computer Methods and Programs in Biomedicine (2011) p.1–10.

DOI: 10.1016/j.cmpb.2010.12.010

Google Scholar

[7] S. Rosenblum, S. Parush, and P. L. Weiss: Computerized temporal handwriting characteristics of proficient and non-proficient handwriters, The American Journal of Occupational Therapyvol. 57, no. 2 (2001), p.129–38.

DOI: 10.5014/ajot.57.2.129

Google Scholar

[8] L. Hen, N. Josman, and S. Rosenblum: Tele-evaluation and intervention among adolescents with handwriting difficulties–Computerized Penmanship Evaluation Tool (ComPET) implementation, Proceedings of the International Workshop on Educational Multimedia and Multimedia Education, (2008).

Google Scholar

[9] C.C. Neo, Eileen L.M. Su, P.I. Khalid, &C. F. Yeong: Algorithm for Identifying Writing Stroke and Direction, In Computational Intelligence, Modelling and Simulation (CIMSiM), (2012), pp.94-98.

Google Scholar

[10] C. C. Neo., Eileen L.M. Su, P. I. Khalid, &C. F. Yeong: Method to Determine Handwriting Stroke Types and Directions for Early Detection of Handwriting Difficulty, Procedia Engineering, 41, (2012), pp.1824-1829.

DOI: 10.1016/j.proeng.2012.08.110

Google Scholar