THE IMPACT OF THE IMPLEMENTATION OF MOBILE APPLICATION FOR CHILDREN WITH DYSGRAPHIA
Keywords:
Dysgraphia, Handwriting, Learning Disabilities, Mobile Application
Abstract
This study investigates the utilization of mobile applications to provide assistance to
children with dysgraphia, a cognitive impairment that impacts their ability to write by
hand. The objective of the study is to determine current patterns of research,
benefits, and difficulties associated with the utilization of mobile applications for
children diagnosed with dysgraphia. The research methodology employed a
systematic examination of studies published from 2014 to 2024, adhering to the
Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)
guidelines. The study findings indicate that the majority of research was carried out
in Asia, with a particular focus on the Middle East and South East Asia. The
participants consisted of students, teachers, and professionals or experts. Mixedmethods was the predominant research approach. The study also found benefits
and difficulties linked to the utilization of mobile applications for children with
dysgraphia, such as the requirement for interfaces that are easy to use,
customization options, and techniques to enhance engagement. The study highlights
the significance of aligning technology initiatives with established instructional goals
and safeguarding sensitive data collected by mobile applications.
References
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interests, and barriers. Journal of Special Education Technology, 35(4), 236–248.
Barnett, A. L., Connelly, V., & Miller, B. (2020). The Interaction of Reading, Spelling,
and Handwriting Difficulties With Writing Development. In Journal of learning
disabilities (Vol. 53, Issue 2, pp. 92–95).
https://doi.org/10.1177/0022219419894565
Bhatt, P. (2020). Mobile application for dysgraphia, surface dyslexia, semantic
dyslexia and dyscalculia. Journal of Emerging Technologies and Innovative
Research (JETIR), 7(12), 813–815.
https://api.semanticscholar.org/CorpusID:235483939
Choi Lean, E. K. (2019). Intensive remedial program for pupils at risk of dysgraphia:
A single case study. Jurnal Pendidikan Bitara UPSI, 12, 65–71.
https://doi.org/https://doi.org/10.37134/bitara.vol12.sp.7.2019 Published
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Adolescent Health, 8(1), 27.
Chung, P., Patel, D. R., & Nizami, I. (2020). Disorder of written expression and
dysgraphia: definition, diagnosis, and management. Translational Pediatrics,
9(Suppl 1), S46–S54. https://doi.org/10.21037/tp.2019.11.01
Criollo-C, S., Guerrero-Arias, A., Jaramillo-Alcázar, Á., & Luján-Mora, S. (2021).
Mobile Learning Technologies for Education: Benefits and Pending Issues.
Applied Sciences, 11(9), 4111.
https://doi.org/https://doi.org/10.3390/app11094111
Drigas, A., & Angelidakis, P. (2017). Mobile Applications within Education: An
Overview of Application Paradigms in Specific Categories. Int. J. Interact. Mob.
Technol., 11, 17–29. https://doi.org/https://doi.org/10.3991/ijim.v11i4.6589
Athanasios
Feder, K. P., & Majnemer, A. (2007). Handwriting development, competency, and
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Hopcan, S., & Tokel, S. T. (2022). The views of special education teachers about a
mobile writing application. Research on Education and Psychology, 6(1), 84–
100.
Ikermane, M., & El Mouatasim, A. (2023). Digital handwriting characteristics for
dysgraphia detection using artificial neural network. Bulletin of Electrical
Engineering and Informatics, 12(3), 1693–1699. https://doi.org/DOI:
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dysgraphia students. Journal of Basic & Applied Sciences, 13, 500–507.
https://doi.org/https://doi.org/10.6000/1927-5129.2017.13.82 Accepted
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(2023). Deep learning and procrustes analysis for early dysgraphia risk
detection with a tablet application. Life, 13(3), 598.
https://doi.org/10.3390/life13030598
Madeiraa, J., Silvaa, C., Marcelinoa, L. A., & Ferreiraa, P. (2015). Assistive Mobile
Applications for Dyslexia. ScienceDirect Conference on ENTERprise
Information Systems / International Conference on Project MANagement /
Conference on Health and Social Care Information Systems and Technologies
, CENTERIS / ProjMAN / HCist 2015 October 7-9 , 2015, 8.
https://doi.org/10.1016/j.procs.2015.08.535
Molina-Vargas, G., Arias-Flores, H., & Jadán-Guerrero, J. (2021). Benefit of
Developing Assistive Technology for Writing. In D. Russo, T. Ahram, W.
Karwowski, G. Di Bucchianico, & R. Taiar (Eds.), Intelligent Human Systems
Integration 2021 (pp. 586–590). Springer International Publishing.
https://doi.org/10.1007/978-3-030-68017-6_86
Muthumal, S. A. D. M., Neranga, K. T., Harshanath, S. M. B., Sandeepa, V. D. R. P.,
Lihinikaduwa, D. N. R., & Rajapaksha, U. U. S. K. (2022). Mobile and
Simulation-based Approach to reduce the Dyslexia with children Learning
Disabilities. 2022 IEEE 10th Region 10 Humanitarian Technology Conference
(R10-HTC), 311–317. https://api.semanticscholar.org/CorpusID:253271120
Nabhan, R., & Kamel, N. (2021). Technologically enhanced art therapy: Introducing
a new synergistic model to enhance morphological awareness in students with
dysgraphia. LingLit Journal Scientific Journal for Linguistics and Literature,
2(1), 1–8. https://doi.org/https://doi.org/10.33258/linglit.v2i1.416 1
Nurchaerani, M., Hartadhi, S. H. R., Alfian, A., & Sadikin, I. S. (2022). How is
perseveration in dysgraphia students? A research at yayasan pantara jakarta.
Pedagonal : Jurnal Ilmiah Pendidikan, 6(2), 283–291.
https://doi.org/10.55215/pedagonal.v6i2.5644 ?
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow,
C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., & Brennan, S. E. (2021). The
prisma 2020 statement: an updated guideline for reporting systematic reviews.
International Journal of Surgery, 88, 105906.
https://doi.org/https://doi.org/10.1016/j.ijsu.2021.105906 Available
Polat, E., Albayrak, E., Hopcan, S., Baştuğ, Y. E., SIBIÇ, S. C., Örs, E., Ayaşli, H.,
& Başkurt, İ. (2023). Are existing mobile writing applications for writing
difficulties sufficient? Participatory Educational Research, 10(5), 21–40.
https://doi.org/http://dx.doi.org/10.17275/per.23.73.10.5 Id:
Sihwi, S. W., Fikri, K., & Aziz, A. (2019). Dysgraphia identification from handwriting
with support vector machine method. Journal of Physics: Conference Series,
1201(1), 12050. https://doi.org/10.1088/1742-6596/1201/1/012050
Vignoli, M., Kraker, P., & Schramm, M. (2022). Open Knowledge Maps: A visual
interface to the world‘s scientific knowledge. Blogs.Iadb.Org.
https://blogs.iadb.org/conocimiento-abierto/en/open-knowledge-maps/
Williams, P., Jamali, H. R., & Nicholas, D. (2006). Using ICT with people with special
education needs: what the literature tells us. Perspectives, 58(4), 330–345.
https://doi.org/10.1108/00012530610687704
Zablotska, L., Chernii, L. V., & Meleshchenko, V. O. (2021). Mobile Technologies in
Education. Intellectual Archive. https://doi.org/10.32370/IA_2021_12_12
Mobile application for dysgraphia children in Malaysia. International Journal of
Engineering and Technology(UAE), 7, 440–443.
https://doi.org/10.14419/ijet.v7i4.36.23912
Atanga, C., Jones, B. A., Krueger, L. E., & Lu, S. (2020). Teachers of students with
learning disabilities: Assistive technology knowledge, perceptions,
interests, and barriers. Journal of Special Education Technology, 35(4), 236–248.
Barnett, A. L., Connelly, V., & Miller, B. (2020). The Interaction of Reading, Spelling,
and Handwriting Difficulties With Writing Development. In Journal of learning
disabilities (Vol. 53, Issue 2, pp. 92–95).
https://doi.org/10.1177/0022219419894565
Bhatt, P. (2020). Mobile application for dysgraphia, surface dyslexia, semantic
dyslexia and dyscalculia. Journal of Emerging Technologies and Innovative
Research (JETIR), 7(12), 813–815.
https://api.semanticscholar.org/CorpusID:235483939
Choi Lean, E. K. (2019). Intensive remedial program for pupils at risk of dysgraphia:
A single case study. Jurnal Pendidikan Bitara UPSI, 12, 65–71.
https://doi.org/https://doi.org/10.37134/bitara.vol12.sp.7.2019 Published
Chung, P., & Patel, D. R. (2015). Dysgraphia. International Journal of Child and
Adolescent Health, 8(1), 27.
Chung, P., Patel, D. R., & Nizami, I. (2020). Disorder of written expression and
dysgraphia: definition, diagnosis, and management. Translational Pediatrics,
9(Suppl 1), S46–S54. https://doi.org/10.21037/tp.2019.11.01
Criollo-C, S., Guerrero-Arias, A., Jaramillo-Alcázar, Á., & Luján-Mora, S. (2021).
Mobile Learning Technologies for Education: Benefits and Pending Issues.
Applied Sciences, 11(9), 4111.
https://doi.org/https://doi.org/10.3390/app11094111
Drigas, A., & Angelidakis, P. (2017). Mobile Applications within Education: An
Overview of Application Paradigms in Specific Categories. Int. J. Interact. Mob.
Technol., 11, 17–29. https://doi.org/https://doi.org/10.3991/ijim.v11i4.6589
Athanasios
Feder, K. P., & Majnemer, A. (2007). Handwriting development, competency, and
intervention. Developmental Medicine & Child Neurology, 49(4), 312–317.
https://doi.org/https://doi.org/10.1111/j.1469-8749.2007.00312.x
Gkeka, E., & Drigas, A. (2022). Ict’s and dysgraphia. Technium Social Sciences
Journal, 31, 228–240.
https://techniumscience.com/index.php/socialsciences/article/view/6423
Gouraguine, S., Riad, M., Qbadou, M., & Mansouri, K. (2023). Dysgraphia detection
based on convolutional neural networks and child-robot interaction.
International Journal of Electrical and Computer Engineering (IJECE), 13(3),
2999–3009. https://doi.org/10.11591/ijece.v13i3
Hopcan, S., & Tokel, S. T. (2021). Exploring the effectiveness of a mobile writing
application for supporting handwriting acquisition of students with dysgraphia.
In Education and Information Technologies (Vol. 26). Springer.
Hopcan, S., & Tokel, S. T. (2022). The views of special education teachers about a
mobile writing application. Research on Education and Psychology, 6(1), 84–
100.
Ikermane, M., & El Mouatasim, A. (2023). Digital handwriting characteristics for
dysgraphia detection using artificial neural network. Bulletin of Electrical
Engineering and Informatics, 12(3), 1693–1699. https://doi.org/DOI:
10.11591/eei.v12i3.4571
John, S., & Renumol, V. G. (2022). Design and development of an android app
(handex) to enhance hand dexterity in children with poor handwriting. IEEE
Access, PP, 1. https://doi.org/10.1109/ACCESS.2022.3172330
Khan, M. F., Hussain, M. A., Ahsan, K., Saeed, M., Nadeem, A., Ali, S. A., Mahmood,
N., & Rizwan, K. (2017). Augmented reality based spelling assistance to
dysgraphia students. Journal of Basic & Applied Sciences, 13, 500–507.
https://doi.org/https://doi.org/10.6000/1927-5129.2017.13.82 Accepted
Kraker, P., Schramm, M., & Kittel, C. (2017). Open knowledge maps: A visual
interface to the world’s scientific knowledge. Open Science Conference.
https://www.open-science-conference.eu/wpcontent/uploads/2017/03/18_Abstract.pdf
Lomurno, E., Dui, L. G., Gatto, M., Bollettino, M., Matteucci, M., & Ferrante, S.
(2023). Deep learning and procrustes analysis for early dysgraphia risk
detection with a tablet application. Life, 13(3), 598.
https://doi.org/10.3390/life13030598
Madeiraa, J., Silvaa, C., Marcelinoa, L. A., & Ferreiraa, P. (2015). Assistive Mobile
Applications for Dyslexia. ScienceDirect Conference on ENTERprise
Information Systems / International Conference on Project MANagement /
Conference on Health and Social Care Information Systems and Technologies
, CENTERIS / ProjMAN / HCist 2015 October 7-9 , 2015, 8.
https://doi.org/10.1016/j.procs.2015.08.535
Molina-Vargas, G., Arias-Flores, H., & Jadán-Guerrero, J. (2021). Benefit of
Developing Assistive Technology for Writing. In D. Russo, T. Ahram, W.
Karwowski, G. Di Bucchianico, & R. Taiar (Eds.), Intelligent Human Systems
Integration 2021 (pp. 586–590). Springer International Publishing.
https://doi.org/10.1007/978-3-030-68017-6_86
Muthumal, S. A. D. M., Neranga, K. T., Harshanath, S. M. B., Sandeepa, V. D. R. P.,
Lihinikaduwa, D. N. R., & Rajapaksha, U. U. S. K. (2022). Mobile and
Simulation-based Approach to reduce the Dyslexia with children Learning
Disabilities. 2022 IEEE 10th Region 10 Humanitarian Technology Conference
(R10-HTC), 311–317. https://api.semanticscholar.org/CorpusID:253271120
Nabhan, R., & Kamel, N. (2021). Technologically enhanced art therapy: Introducing
a new synergistic model to enhance morphological awareness in students with
dysgraphia. LingLit Journal Scientific Journal for Linguistics and Literature,
2(1), 1–8. https://doi.org/https://doi.org/10.33258/linglit.v2i1.416 1
Nurchaerani, M., Hartadhi, S. H. R., Alfian, A., & Sadikin, I. S. (2022). How is
perseveration in dysgraphia students? A research at yayasan pantara jakarta.
Pedagonal : Jurnal Ilmiah Pendidikan, 6(2), 283–291.
https://doi.org/10.55215/pedagonal.v6i2.5644 ?
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow,
C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., & Brennan, S. E. (2021). The
prisma 2020 statement: an updated guideline for reporting systematic reviews.
International Journal of Surgery, 88, 105906.
https://doi.org/https://doi.org/10.1016/j.ijsu.2021.105906 Available
Polat, E., Albayrak, E., Hopcan, S., Baştuğ, Y. E., SIBIÇ, S. C., Örs, E., Ayaşli, H.,
& Başkurt, İ. (2023). Are existing mobile writing applications for writing
difficulties sufficient? Participatory Educational Research, 10(5), 21–40.
https://doi.org/http://dx.doi.org/10.17275/per.23.73.10.5 Id:
Sihwi, S. W., Fikri, K., & Aziz, A. (2019). Dysgraphia identification from handwriting
with support vector machine method. Journal of Physics: Conference Series,
1201(1), 12050. https://doi.org/10.1088/1742-6596/1201/1/012050
Vignoli, M., Kraker, P., & Schramm, M. (2022). Open Knowledge Maps: A visual
interface to the world‘s scientific knowledge. Blogs.Iadb.Org.
https://blogs.iadb.org/conocimiento-abierto/en/open-knowledge-maps/
Williams, P., Jamali, H. R., & Nicholas, D. (2006). Using ICT with people with special
education needs: what the literature tells us. Perspectives, 58(4), 330–345.
https://doi.org/10.1108/00012530610687704
Zablotska, L., Chernii, L. V., & Meleshchenko, V. O. (2021). Mobile Technologies in
Education. Intellectual Archive. https://doi.org/10.32370/IA_2021_12_12
Published
2024-04-27
