Being social in a 3D collaborative virtual learning environment : a case study of youth with autism spectrum disorder learning social competence in iSocial

2014 ◽  
Author(s):  
◽  
Xianhui Wang

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Over the past decade 3D collaborative virtual learning has gained increasing attention from researchers and practitioners in educational technology. Learners experience of presence in collaborative activities and social interactions among learners are identified as key constructs for the social dimensions of 3D collaborative virtual learning. 3D Collaborative Virtual Learning Environments (CVLEs) are beginning to be used to support learning in a variety of disciplines, including social skills learning for individuals with Autism Spectrum Disorder (ASD). This case study explores 11 youth with ASD's experience of embodied social presence and reciprocal social interaction while learning social competence in a 3D CVLE-iSocial. The findings describe youth with ASD's 1) levels of embodied presence, embodied copresence, and embodied social presence; and 2) verbal and nonverbal reciprocal social interactions across the variety of Naturalistic Practice activities in iSocial. In addition, the results of this case study inform future design by indicating associations of design features of iSocial 3D CVLE with youth with ASD's experience of embodied social presence and characteristics of reciprocal social interaction.

2022 ◽  
Vol 15 ◽  
Author(s):  
Alexandra P. Key ◽  
Yan Yan ◽  
Mary Metelko ◽  
Catie Chang ◽  
Hakmook Kang ◽  
...  

Difficulty engaging in reciprocal social interactions is a core characteristic of autism spectrum disorder. The mechanisms supporting effective dynamic real-time social exchanges are not yet well understood. This proof-of-concept hyperscanning electroencephalography study examined neural synchrony as the mechanism supporting interpersonal social interaction in 34 adolescents with autism spectrum disorder (50% female), age 10–16 years, paired with neurotypical confederates of similar age. The degree of brain-to-brain neural synchrony was quantified at temporo-parietal scalp locations as the circular correlation of oscillatory amplitudes in theta, alpha, and beta frequency bands while the participants engaged in a friendly conversation. In line with the hypotheses, interpersonal neural synchrony was significantly greater during the social interaction compared to the baseline. Lower levels of synchrony were associated with increased behavioral symptoms of social difficulties. With regard to sex differences, we found evidence for stronger interpersonal neural synchrony during conversation than baseline in females with autism, but not in male participants, for whom such condition differences did not reach statistical significance. This study established the feasibility of hyperscanning during real-time social interactions as an informative approach to examine social competence in autism, demonstrated that neural coordination of activity between the interacting brains may contribute to social behavior, and offered new insights into sex-related variability in social functioning in individuals with autism spectrum disorders.


2020 ◽  
pp. 153465012098345
Author(s):  
Mirela Cengher ◽  
Joy C. Clayborne ◽  
Adrianna E. Crouch ◽  
Julia T. O’Connor

Over 60% of children diagnosed with selective mutism are also diagnosed with Autism Spectrum Disorder. Previous research established that behavioral interventions are effective at increasing speech in children with both diagnoses. However, few studies conducted assessments to determine environmental variables that inhibit speech, and such assessments are necessary for the development of effective and efficient treatments. This case study describes an assessment that evaluated the function(s) of selective mutism. The results confirmed that the participant did not talk to avoid social interaction and that mutism occurred primarily in the presence of multiple, unfamiliar people. Our first treatment focused on increasing tolerance for social interaction, demonstrated by an increase in speech production in the presence of unfamiliar people. Our second treatment focused on increasing qualitative aspects of the participant’s speech (i.e., both responses and initiations). Finally, we taught the participant’s parents to implement the treatment in naturalistic settings, and the participant demonstrated generalization of treatment effects across people and settings. Implications for clinical practice and future research are discussed.


2020 ◽  
Vol 8 (9) ◽  
pp. 928-932
Author(s):  
Anahit Bindra ◽  

Autism Spectrum Disorder (ASD) is a life-long, pervasive neuro-development disorder that begins early in childhood and lasts throughout a persons life. It is characterised by deficits in three core areas - communication (both verbal and nonverbal), social interaction, and behaviour (which is restricted and repetitive). Case study refers to the in-depth study of a particular case. A case study employs multiple methods for collecting information such as interview, observation and psychological tests from a variety of respondents who in some way or the other might be associated with the case and can provide useful information. The information was collected by interviewing the case as well as the special educator (the teacher who assists the child at Vasant Valley school). In the case study, the details of the symptoms, causes, treatment, prevention, and management of the respondent were documented.


2014 ◽  
Vol 2 ◽  
Author(s):  
Blythe A. Corbett ◽  
Lydia R. Qualls ◽  
Blythe Valencia ◽  
Stéphanie-M. Fecteau ◽  
Deanna M. Swain

Author(s):  
Jacqueline Peng ◽  
Mengge Zhao ◽  
James Havrilla ◽  
Cong Liu ◽  
Chunhua Weng ◽  
...  

Abstract Background Natural language processing (NLP) tools can facilitate the extraction of biomedical concepts from unstructured free texts, such as research articles or clinical notes. The NLP software tools CLAMP, cTAKES, and MetaMap are among the most widely used tools to extract biomedical concept entities. However, their performance in extracting disease-specific terminology from literature has not been compared extensively, especially for complex neuropsychiatric disorders with a diverse set of phenotypic and clinical manifestations. Methods We comparatively evaluated these NLP tools using autism spectrum disorder (ASD) as a case study. We collected 827 ASD-related terms based on previous literature as the benchmark list for performance evaluation. Then, we applied CLAMP, cTAKES, and MetaMap on 544 full-text articles and 20,408 abstracts from PubMed to extract ASD-related terms. We evaluated the predictive performance using precision, recall, and F1 score. Results We found that CLAMP has the best performance in terms of F1 score followed by cTAKES and then MetaMap. Our results show that CLAMP has much higher precision than cTAKES and MetaMap, while cTAKES and MetaMap have higher recall than CLAMP. Conclusion The analysis protocols used in this study can be applied to other neuropsychiatric or neurodevelopmental disorders that lack well-defined terminology sets to describe their phenotypic presentations.


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