A review on Virtual Reality for educating students with learning disabilities

Tatale, Subhash; Bhinid, Nivedita; Parmar, Rishob; Pcnvar, Shubham

doi:10.1109/iccubea47591.2019.9128570

Cited by 3 publications

(1 citation statement)

References 8 publications

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“…ere were several studies which reviewed virtual realitybased education research focusing on specific target learners such as training professionals [9], soft skills training of employees [10], students with learning disabilities [47], children with social skills deficits [48], individuals with autism spectrum disorder [49], patients with dementia [50], and patients with paranoia [51].…”

Section: Introductionmentioning

confidence: 99%

A Systematic Review of Virtual Reality-Based Education Research Using Latent Dirichlet Allocation: Focus on Topic Modeling Technique

Kim

2022

Mobile Information Systems

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Using virtual reality in the context of education is becoming important since this technology enhances learners’ motivation and performance with transfer of learning, problem-solving skills, educational equity, and multisensory learning. Along with the 4th Industrial Revolution and COVID-19, the attention on virtual reality has been increased again. Some studies reviewed the trends of research on virtual reality-based education, mostly focusing on specific subject matters or areas. The purpose of the study is to investigate the change of research trends in the virtual reality-based education field by implementing the topic modeling analysis based on latent Dirichlet allocation (LDA) technique with 6,755 articles published in the last 30 years (between 1992 and 2022). As a result of this study, it was revealed that the research on virtual reality-based education was clearly divided into the following four periods; 1992–2011, 2012–2016, 2017–2019, and 2020–2022. The main topics for each period were suggested. Here are three major findings of this study. First, it is identified that the weight of “virtual reality for learning and teaching” has increased in recent years. Second, conversely, it is identified that the proportion of “virtual reality in medical education” has decreased relatively recently. It means it is possible to interpret that the proportion of other topics has relatively increased. Third, the topics of “virtual reality education platform” and “virtual reality-based education in rehabilitation” continue to maintain a certain weight. Limitations of this study and further research suggestions are provided based on the results of the study.

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Section: Introductionmentioning

confidence: 99%

A Systematic Review of Virtual Reality-Based Education Research Using Latent Dirichlet Allocation: Focus on Topic Modeling Technique

Kim

2022

Mobile Information Systems

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Real-Time Interactive AR for Cognitive Learning

Jain,

Bhirud,

Tatale

et al. 2023

Signals and Communication Technology

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Adaptive Learning and Correlative Assessment of Differential Usage Patterns for Students with-or-without Learning Disabilities via Learning Analytics

Modak,

Gharpure,

2023

ACM Trans. Asian Low-Resour. Lang. Inf. Process.

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Learning Disabilities (LD) can be categorized into logical, analytical, grammatical, Vocabularyulary, sequential, and inference disabilities. Analysis of such disabilities assists students to identify and strengthen their weak areas. A wide variety of analysis models are proposed by researchers to perform such tasks, but most of these models are highly complex, and cannot be scaled for multimodal parameter sets. To overcome these issues, this text proposes a model for correlative assessment of differential usage patterns in students with-or-without learning disabilities via multimodal analysis. The proposed model initially collects real-time inference sets for students with Learning Disabilities (LD), and without LDs. These sets consist of question-specific recorded responses for ‘Addition’, ‘Carry Propagation’, ‘Basic to Advanced Grammar’, ‘Direct, Inference and Vocabulary Comprehension’, ‘Finding odd-man-out’, ‘Sequencing’, and ‘Pseudo and Sight Spelling’ for different question sets. Answers to these questions and their metadata were processed via a correlative engine which assisted in evaluation of correctness, time needed per question per category, number of skips, number of revisits, and unanswered ratio for different students. This evaluation was combined with temporal analysis in order to identify per-category progress of students. Based on this progress, students were either upgraded to next level, or given lower-level questions, which assisted them to incrementally improve their grades. The model proved that the performance of LD students is 55% less than the non LD students and an average of 18 LD students have achieved an average of 33% of improvement after having multiple attempts of the adaptive lessons. The model uses a correlation function, which enables to identify answering patterns of LD and non-LD students with 98.4% accuracy, thus can be used for clinical scenarios.

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A review on Virtual Reality for educating students with learning disabilities

Cited by 3 publications

References 8 publications

A Systematic Review of Virtual Reality-Based Education Research Using Latent Dirichlet Allocation: Focus on Topic Modeling Technique

A Systematic Review of Virtual Reality-Based Education Research Using Latent Dirichlet Allocation: Focus on Topic Modeling Technique

Real-Time Interactive AR for Cognitive Learning

Adaptive Learning and Correlative Assessment of Differential Usage Patterns for Students with-or-without Learning Disabilities via Learning Analytics

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