Effects of New Supportive Technologies for Blind and Deaf Engineering Students in Online Learning

Batanero, Concha; de‐Marcos, Luis; Holvikivi, Jaana; Hilera, José Ramón; Otón, Salvador

doi:10.1109/te.2019.2899545

Cited by 47 publications

(37 citation statements)

References 13 publications

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“…In university classrooms, the presence of technological media, and more specifically the use of virtual environments, is shaping many of the teaching practices that are being considered inclusive. In fact, as is demonstrated in this investigation, numerous studies conclude that LMSs are one of the essential tools in teaching, thanks in part to the fact that their use has practical applications in various areas of learning for students with and without disabilities [48,61]. Along these lines, the main findings of this study emphasise the interest that faculty recognise they have in the possibilities offered by LMSs when used to support face-to-face university teaching in order to develop inclusive practices.…”

Section: Discussionmentioning

confidence: 55%

“…The first area defines the environment as an accessible space that contains the material and tools that support students with and without disabilities, allowing them to regulate the pace and intensity of their learning according to their interests [31,32]. The second area contemplates the environment as an inclusive space for the differentiated performance of face-to-face teaching activities, which facilitates the development of digital educational processes [48,50]. Lastly, the third area considers the environment as an adapted space that is used to store and provide adapted materials, with which learners improve significantly in their studies by being able to interact with learning objects [3].…”

Section: Discussionmentioning

confidence: 99%

“…Universal design can help provide greater accessibility in the virtual learning environment, not only for students with disabilities but for all students [47]. Studies have shown that the improvement of student learning increases significantly when the LMS is adapted [48]. However, studies focusing on accessibility do not seem to have consistently considered the design of learning materials in digital format [49], despite the fact that adapting LMSs improves their accessibility when learning objects are adapted [50].…”

Section: Accessibility In Virtual Environments As a Prelude To Digital Education For Allmentioning

confidence: 99%

“…For this reason, LMSs should incorporate materials adapted to the personal needs and preferences of all learners, although studies such as those by Brito and Dias [51] conclude that there is no single solution that can meet all individual needs, even when responding to the same type of disability. However, many of the materials that are shared are not adapted, thus the level of accessibility of information in LMSs is often quite low [48].…”

Section: Accessibility In Virtual Environments As a Prelude To Digital Education For Allmentioning

confidence: 99%

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Technological Platforms for Inclusive Practice at University: A Qualitative Analysis from the Perspective of Spanish Faculty Members

et al. 2021

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Currently, the development of new virtual environments as a complementary tool to face-to-face teaching and the increased presence of students with disabilities at university classrooms are changing the landscape of university teaching. This article analyses the actions of faculty members who carry out inclusive practices in the context of technological platforms. The research was based on the assumptions of the qualitative paradigm, using individual semi-structured interviews with 119 faculty members from 10 Spanish public universities. The results show the reasons for inclusive learning with technological platforms, the use that faculty members make of these platforms in their inclusive educational practices, and the influence of these on the learning of students, especially students with disabilities. The conclusions give a good account of the conditions that determine the pedagogical use that faculty members make of virtual environments to facilitate the inclusion of students.

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Section: Discussionmentioning

confidence: 55%

Section: Discussionmentioning

confidence: 99%

Section: Accessibility In Virtual Environments As a Prelude To Digital Education For Allmentioning

confidence: 99%

Section: Accessibility In Virtual Environments As a Prelude To Digital Education For Allmentioning

confidence: 99%

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Technological Platforms for Inclusive Practice at University: A Qualitative Analysis from the Perspective of Spanish Faculty Members

et al. 2021

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“…Learning analytics [1], [2] and supportive learning [3], [4] have become emerging research areas in today's era of big data and artificial intelligence to facilitate students' learning. Student education is vital to the sustainable development of society because students learn knowledge and abilities to contribute the community.…”

Section: Introductionmentioning

confidence: 99%

Predicting Students’ Performance With School and Family Tutoring Using Generative Adversarial Network-Based Deep Support Vector Machine

et al. 2020

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It has been witnessed that supportive learning has played a crucial role in educational quality enhancement. School and family tutoring offer personalized help and provide positive feedback on students' learning. Predicting students' performance is of much interest which reflects their understanding on the subjects. Particularly it is desired students to manage well in fundamental knowledge in order to build a strong foundation for post-secondary studies and career. In this paper, improved conditional generative adversarial network based deep support vector machine (ICGAN-DSVM) algorithm has been proposed to predict students' performance under supportive learning via school and family tutoring. Owning to the nature of the students' academic dataset is generally low sample size. ICGAN-DSVM offers dual benefits for the nature of low sample size in students' academic dataset in which ICGAN increases the data volume whereas DSVM enhances the prediction accuracy with deep learning architecture. Results with 10-fold cross-validation show that the proposed ICGAN-DSVM yields specificity, sensitivity and area under the receiver operating characteristic curve (AUC) of 0.968, 0.971 and 0.954 respectively. Results also suggest that incorporating both school and family tutoring into the prediction model could further improve the performance compared with only school tutoring and only family tutoring. To show the necessity of ICGAN and DSVM, comparison has been made between ICGAN and traditional conditional generative adversarial network (CGAN). Also, the proposed kernel design via heuristic based multiple kernel learning (MKL) is compared with typical kernels including linear, radial basis function (RBF), polynomial and sigmoid. The prediction of student's performance with and without GAN is presented which is followed by comparison with DSVM and with traditional SVM. The proposed ICGAN-DSVM outperforms related works by 8-29% in terms of performance indicators specificity, sensitivity and AUC.

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Program Implementation of Educational Electronic Resource for Inclusive Education of People with Visual Impairment

Tulashvili

Lukianchuk

Lishchyna

et al. 2023

Lecture Notes on Data Engineering and Communications Technologies

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Effects of New Supportive Technologies for Blind and Deaf Engineering Students in Online Learning

Cited by 47 publications

References 13 publications

Technological Platforms for Inclusive Practice at University: A Qualitative Analysis from the Perspective of Spanish Faculty Members

Technological Platforms for Inclusive Practice at University: A Qualitative Analysis from the Perspective of Spanish Faculty Members

Predicting Students’ Performance With School and Family Tutoring Using Generative Adversarial Network-Based Deep Support Vector Machine

Program Implementation of Educational Electronic Resource for Inclusive Education of People with Visual Impairment

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