Assistive e-Learning Software Modules to Aid Education Process of Students with Visual and Hearing Impairment: A Case Study in North Macedonia
Date Issued
2022
Author(s)
Karovska Ristovska, Aleksandra
Rashikj-Canevska, Olivera
Simjanoska, Monika
Abstract
This paper presents a technology4good initiative that integrates multiple breakthrough software modules with the aim to build
a generic framework to aid the educational process for students with
disabilities, such as, hearing and vision impairments, as well as various
types of dyslexia. The purpose of the study is to apply various distinct
researches among which the highlight is on the text-to-speech engine for
the first time developed to support Macedonian language. Additionally,
the framework integrates Macedonian sign language to guide the hearing impaired students through the contents of the educational framework.
Also, there is a specially developed font (typeface) and color environment
for students with specific reading difficulties (dyslexia). The methods
that support the educational framework are developed by mix of social,
special education and computer science experts. The methodology for
developing the text-to-speech engine relies on the newest and most efficient principles in Machine Learning for Natural Language Processing
- a Deep Learning approach. The framework has been tested on target
group of students and the satisfaction has been measured by using the
standard Likert scale.
a generic framework to aid the educational process for students with
disabilities, such as, hearing and vision impairments, as well as various
types of dyslexia. The purpose of the study is to apply various distinct
researches among which the highlight is on the text-to-speech engine for
the first time developed to support Macedonian language. Additionally,
the framework integrates Macedonian sign language to guide the hearing impaired students through the contents of the educational framework.
Also, there is a specially developed font (typeface) and color environment
for students with specific reading difficulties (dyslexia). The methods
that support the educational framework are developed by mix of social,
special education and computer science experts. The methodology for
developing the text-to-speech engine relies on the newest and most efficient principles in Machine Learning for Natural Language Processing
- a Deep Learning approach. The framework has been tested on target
group of students and the satisfaction has been measured by using the
standard Likert scale.
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