Influence of assistive technology applications on dyslexic students: The case of Saudi Arabia during the COVID-19 pandemic

Al-Dokhny, Amany Ahmed; Bukhamseen, Amani Mohammed; Drwish, Amr Mohammed

doi:10.1007/s10639-022-11090-9

Cited by 7 publications

(5 citation statements)

References 103 publications

(122 reference statements)

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“…Frame sizes between 20 ms and 45 ms have been employed with sampling rates between 8 and 10 kHz in conventional LPC-based speech analysis. The frame size of 10-50 ms has also been employed widely in applications for acoustic analysis 25 .…”

Section: Results and Experimental Analysismentioning

confidence: 99%

Detection and Diagnosis of Learning Disabilities in Children of Saudi Arabia with Artificial Intelligence

Alshehri,

Sharma,

Gupta

et al. 2023

Preprint

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Learning Disability (LD) is an umbrella term for various learning difficulties. It is a neurological disorder that affects the brain of children and hinders their capacity to do one or more specified activities. Youngsters with learning disabilities are neither sluggish nor mentally retarded. This paper utilizes Speech, as an acceptable motor activity to address the problem and its solution. In this work, Mel-Frequency Cepstral Coefficients (MFCC) and Linear Predictive Cepstral Coefficients (LPCC) are used to extract speech characteristics. For every speech sample, 205 characteristics are retrieved, consisting of 13 acoustical features from MFCC, 128 features from LPCC, and 64 features from power spectrum density. In addition, linear predictive coding-based parameterization is used to every speech sample to extract Weighted Linear Predictive Cepstral Coefficients (WLPCC) and Linear Predictive Coding features (LPC). The Extracted Features are identified using a Deep Convolutional Neural Network (DCNN), and their performance is analyzed. It is found that the correlation between speech characteristics and various classification models may be assessed to get the highest classification accuracy. These findings demonstrate that the suggested feature extraction approaches and classification models are highly successful in categorizing the speech of intellectually impaired and typically developing youngsters.

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Section: Results and Experimental Analysismentioning

confidence: 99%

Detection and Diagnosis of Learning Disabilities in Children of Saudi Arabia with Artificial Intelligence

Alshehri,

Sharma,

Gupta

et al. 2023

Preprint

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“…All of those things help pupils in strengthening the relationship between words and sounds that lead to a better understanding of phonology. Al-Dokhny et al (2022) in his study used graphic and visual learning materials in the delivery of teaching content to improve visual perception and phonological awareness of dyslexic pupils.…”

Section: The Use Of Technology In the Learning Of Dyslexic Childrenmentioning

confidence: 99%

Technology-based Interventions for Dyslexic Children: A Systematic Literature Review (SLR)

Yaacob,

Zakariya,

Mohd Rashid

2024

IJARBSS

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In modern society today, reading skills are increasingly important. Thus, any failure in mastering reading skills can limit an individual's potential to grow to an optimal level. The main importance of reading as a basic skill in modern life has prompted many studies to be carried out to implement more effective interventions in tandem with education that has changed dramatically in recent decades under the influence of the development of digital technology and the fourth industrial revolution (IR4.0). In this article, a review of the systematic literature (SLR) was conducted to identify current research on the use of technology in the implementation of reading skills teaching interventions to dyslexic pupils. The main objective of the study was to identify the use and effectiveness of the technologies used in meeting the learning needs of children with dyslexia. Three databases are used, namely Scopus, Web of Science and Google Scholar. Of the 318 articles that were screened, 46 relevant articles were accepted for analysis based on the appropriateness of the title and only 21 were included in the study after further screening. The results showed the use of different forms of technology such as audiobooks, text-to-speech (TTS), speech-to-text (STT); digital technologies such as computer software programs, gaming applications; haptic technologies such as virtual reality (VR) and augmented reality (AR); new technologies such as mulsemedia; robotic technologies in addition to the use of non-digital technologies. Studies have also found that the use of technology has a positive impact on the learning of dyslexic children, especially the mastery of reading skills. Studies have found that technology intergration in education provides a more enjoyable learning experience and increases children's motivation through a learning while playing approach. Therefore, the practice of Technological Pedagogical Content Knowledge (TPACK) should be enhanced among teachers. In addition, more studies are needed to identify the use of technology in the aspect of the diagnosis and management of dyslexic children in the future. This is because most individuals with disabilities such as dyslexia benefit from additional support that allows them to learn and function on their own.

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“…Furthermore, in early 2022, King Faisal University launched the first educational application, Kofu to support student learning both inside and outside classrooms. Apart from this, efforts have been made to achieve comprehensive educational management at the level of both faculty and staff members [11].…”

Section: Mobile Learning (Ml)mentioning

confidence: 99%

“…Furthermore, ML has become an important complementary tool for digital learning strategies in both K-12 and higher education because of its positive impact on all participants in these systems-it positively affects the attitudes of participants and works to enhance their perceptions toward this kind of learning [10]. It is worth noting that this role became more evident after the COVID-19 pandemic, during which mobile learning became a distinguishing feature of the time [11,12]. Moreover, the wide usage of mobile devices and the consequent adoption of ML in many learning systems [13] have enabled it to play a positive role in a learner-centered learning environment by negating the constraints of time and space [14].…”

Section: Introductionmentioning

confidence: 99%

A Sustainable Quality Model for Mobile Learning in Post-Pandemic Higher Education: A Structural Equation Modeling-Based Investigation

et al. 2023

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As an effect of the digital transformation encountered by higher education institutions in the post-pandemic phase, the current study aims to inspect the factors affecting the actual use of mobile learning among higher education students. A novel hybrid model based on the information system success and technology acceptance models was proposed and tested. The study included 400 undergraduate and postgraduate students from four Saudi universities who responded to a questionnaire consisting of two parts and seven dimensions, with a total of 26 items. For the analysis, a quantitative approach was applied using structural equation modeling. The results displayed that information quality had no impact on the actual use of mobile learning among higher education students. In contrast, other quality factors (system quality, service quality, and satisfaction) and perceived factors (perceived usefulness and perceived ease of use) had a positive effect. Accordingly, this study proposed an integrated framework to assist decision makers at higher education institutions in scaffolding students to develop their educational performance by depending on mobile applications comprising high-quality factors that address their real needs. This would also enable higher education institutions to enhance their digital transformation experience, thus contributing to achieving positive learning sustainability after the pandemic.

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Influence of assistive technology applications on dyslexic students: The case of Saudi Arabia during the COVID-19 pandemic

Cited by 7 publications

References 103 publications

Detection and Diagnosis of Learning Disabilities in Children of Saudi Arabia with Artificial Intelligence

Detection and Diagnosis of Learning Disabilities in Children of Saudi Arabia with Artificial Intelligence

Technology-based Interventions for Dyslexic Children: A Systematic Literature Review (SLR)

A Sustainable Quality Model for Mobile Learning in Post-Pandemic Higher Education: A Structural Equation Modeling-Based Investigation

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