Benefit of Developing Assistive Technology for Writing

Molina-Vargas, Galo; Arias-Flores, Hugo; Jadán-Guerrero, Janio

doi:10.1007/978-3-030-68017-6_86

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…This result is consistent with those of Alhaythami (2022) and Qaraan (2021) in terms of the high level of teachers' techno-satisfaction. This finding also confirms previous results concerning the importance of technology in supporting the unique needs of special needs students (Ciampa, 2017;Nordström et al, 2018;Atanga et al, 2019;Olakanmi et al, 2020;Molina-Vargas et al, 2021;Starks and Reich, 2023). On the other hand, this finding is at odds with studies by Belabas and Bouhila (2021) and Aburayash (2022) regarding the levels of teachers' techno-satisfaction.…”

Section: Discussionsupporting

confidence: 89%

“…The use of technology in special education classrooms has the potential to greatly enhance the teaching and learning experience (Ciampa, 2017;Nordström et al, 2018;Olakanmi et al, 2020;Starks and Reich, 2023). It offers customized learning opportunities, accessibility features, and assistive technologies that cater to the diverse needs of students (Atanga et al, 2019;Olakanmi et al, 2020;Molina-Vargas et al, 2021). E-learning may offer certain advantages over traditional teaching methods for students with special needs as well (Beck et al, 2014;Basham et al, 2015).…”

Section: Techno-satisfaction Among Special Education Teachersmentioning

confidence: 99%

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Techno-anxiety and techno-satisfaction during the COVID-19 pandemic: the case of special education teachers

Al Mulhim,

Almulhem

2024

Front. Educ.

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The objective of this study was to assess the levels of techno-anxiety and techno-satisfaction that special education teachers in Saudi Arabia experienced during the COVID-19 pandemic. We used a survey to gather data from 286 teachers of students with special needs across from early intervention to secondary school (5–18 years) the Kingdom, and we interviewed 23 teachers (3 early intervention, 13 primary, 2 intermediate, 5 secondary). Quantitative analysis was employed to analyze the survey responses, while qualitative thematic analysis was used for the interview data. The findings showed that the teachers experienced moderate levels of anxiety (a mean of 2.33 out of 4). On the other hand, the teachers expressed satisfaction (a mean of 2.98 of 4) with the distance learning system they used. The study highlights the benefits and challenges associated with implementing distance learning for students with special needs. These findings could help inform the design of distance learning environments and identify the factors that influence teachers’ feelings of anxiety or satisfaction during the implementation of distance learning. Additionally, the study’s results could encourage parents of students with special needs to foster improved collaboration and cooperation with teachers.

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Section: Discussionsupporting

confidence: 89%

Section: Techno-satisfaction Among Special Education Teachersmentioning

confidence: 99%

Techno-anxiety and techno-satisfaction during the COVID-19 pandemic: the case of special education teachers

Al Mulhim,

Almulhem

2024

Front. Educ.

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“…Learning disabilities are a major problem for many students who suffer from them [1]. They face real challenges that are not limited to academic aspects, but also extend to behavioral and social aspects [2].…”

Section: Introductionmentioning

confidence: 99%

Dysgraphia detection based on convolutional neural networks and child-robot interaction

Gouraguine

Riad

Qbadou

et al. 2023

IJECE

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Dysgraphia is a disorder of expression with the writing of letters, words, and numbers. Dysgraphia is one of the learning disabilities attributed to the educational sector, which has a strong impact on the academic, motor, and emotional aspects of the individual. The purpose of this study is to identify dysgraphia in children by creating an engaging robot-mediated activity, to collect a new dataset of Latin digits written exclusively by children aged 6 to 12 years. An interactive scenario that explains and demonstrates the steps involved in handwriting digits is created using the verbal and non-verbal behaviors of the social humanoid robot Nao. Therefore, we have collected a dataset that contains 11,347 characters written by 174 participants with and without dysgraphia. And through the advent of deep learning technologies and their success in various fields, we have developed an approach based on these methods. The proposed approach was tested on the generated database. We performed a classification with a convolutional neural network (CNN) to identify dysgraphia in children. The results show that the performance of our model is promising, reaching an accuracy of 91%.

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A humanoid robot assistant for the classification of students according to their type of dysgraphia

Gouraguine

Riad

Rafik

et al. 2023

2023 3rd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)

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Benefit of Developing Assistive Technology for Writing

Cited by 3 publications

References 11 publications

Techno-anxiety and techno-satisfaction during the COVID-19 pandemic: the case of special education teachers

Techno-anxiety and techno-satisfaction during the COVID-19 pandemic: the case of special education teachers

Dysgraphia detection based on convolutional neural networks and child-robot interaction

A humanoid robot assistant for the classification of students according to their type of dysgraphia

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