Model tulisan tangan berbantukan teknologi untuk memudahcara penulisan murid Disgrafia
Dysgraphia is a student learning problem related to handwriting skills, which is not inline according to their age. To overcome the problem, various handwriting skills intervention methods to dysgrapbic students have been conducted. However, past research on the intervention methods have not covered...
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Main Author: | |
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Format: | Thesis |
Language: | eng eng |
Published: |
2022
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Subjects: | |
Online Access: | https://etd.uum.edu.my/10241/1/s95862_01.pdf https://etd.uum.edu.my/10241/2/s95862_02.pdf |
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Summary: | Dysgraphia is a student learning problem related to handwriting skills, which is not inline according to their age. To overcome the problem, various handwriting skills intervention methods to dysgrapbic students have been conducted. However, past research on the intervention methods have not covered all levels of handwriting skills from the basic levels to automaticity. This embodies a research gap especially the absence of a comprehensive technology-assisted support model. The function of the dysgraphic student writing support application will be more effective with the presence of interaction design guidelines (IxD). Thus, this study proposes a technology-assisted handwriting model of dysgraphic students (DCHM) to improve their writing proficiency at the level of visualization, imagination and automation. The model involves a combination of letter formation components (transcription, visualization, imagination, text generation and cognitive) and ICT support (letter formation animation, control, tracing, arrow animation, feedback and repetition). To achieve the objective, three phases of research methods are involved namely 1) categorising and analysing handwriting patterns, model design and verifying the model; 2) developing the prototype; and 3) evaluating the prototype. The reliability of the model was tested through user's evaluation using handwriting legibility scale (HLS). Comparisons were made based on handwriting samples before and after the intervention with the assistance of the prototype. The findings demonstrated that, HLS is able to identify the sensitivity of each parameter in DCHM. To be more specific, the score achieved for global legibility and effort to read the script is 92 percent, layout on the page and letter fonnation attained 96 percent; while alterations to writing scored 100 percent. The overall evaluation of the model showed positive scores from the aspects of legibility, memory, correct letter formation, and ultimately automaticity achievement in handwriting. In conclusion, these findings confirmed that the implementation of DCHM in the prototype can significantly enhance the mastery of handwriting among dysgraphic students. More importantly, this study has contributed substantially to the field of interaction design by providing a novel understanding of the design model. |
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