2011 |
Masuri, M G; Musa, N S; Isa, K A M The effects of animal assisted therapy in improving attention among autistic children Conference 2011, ISBN: 9781467300193, (cited By 0). Abstract | Links | BibTeX | Tags: Animals, Autism, Autistic Children, Behavioral Research, Children with Autism, Errors, Performance Tests, Sensory Integration, Student Performance, Students, Three Phasis @conference{Masuri2011813, title = {The effects of animal assisted therapy in improving attention among autistic children}, author = {M G Masuri and N S Musa and K A M Isa}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84858995499&doi=10.1109%2fCHUSER.2011.6163849&partnerID=40&md5=1f29b24b9c2f78766401528f4e40a41d}, doi = {10.1109/CHUSER.2011.6163849}, isbn = {9781467300193}, year = {2011}, date = {2011-01-01}, journal = {2011 IEEE Colloquium on Humanities, Science and Engineering, CHUSER 2011}, pages = {813-818}, abstract = {Objective. This study examines the effect of Animal Assisted Therapy (AAT) towards improving attention among Autistic children. Method. A single case study using ABA design was used to measure duration of attention and errors omitted using Mesulam Continuous Performance Test (CPT) across three phases among 4 participants. Task Behavior/ Completion section in School Function Assessment (SFA) was given to teachers to rate student performance before and after intervention phase. Results. Results from this study showed that AAT did not improve attention and task behavior among 4 participants. However there is noted slight increase in attention among participants during the intervention phase. All participants also had slight decrease in attention during withdrawal phase. Decreases in numbers of errors omitted in CPM were noted in all participants during intervention phase. Conversely, all participants except participant 4 had increase in numbers of errors omitted during withdrawal phase. Result from Task behavior also showed no improvement. Conclusions. The findings from this study demonstrate that AAT did not improve attention and task behavior among Autistic children. However, the findings suggest that AAT can be one of treatment approach among Autistics children. Further study with longer timelines is needed to demonstrate a much better outcome as well as to ensure that the impact of the interventions really give an effect to the sample. © 2011 IEEE.}, note = {cited By 0}, keywords = {Animals, Autism, Autistic Children, Behavioral Research, Children with Autism, Errors, Performance Tests, Sensory Integration, Student Performance, Students, Three Phasis}, pubstate = {published}, tppubtype = {conference} } Objective. This study examines the effect of Animal Assisted Therapy (AAT) towards improving attention among Autistic children. Method. A single case study using ABA design was used to measure duration of attention and errors omitted using Mesulam Continuous Performance Test (CPT) across three phases among 4 participants. Task Behavior/ Completion section in School Function Assessment (SFA) was given to teachers to rate student performance before and after intervention phase. Results. Results from this study showed that AAT did not improve attention and task behavior among 4 participants. However there is noted slight increase in attention among participants during the intervention phase. All participants also had slight decrease in attention during withdrawal phase. Decreases in numbers of errors omitted in CPM were noted in all participants during intervention phase. Conversely, all participants except participant 4 had increase in numbers of errors omitted during withdrawal phase. Result from Task behavior also showed no improvement. Conclusions. The findings from this study demonstrate that AAT did not improve attention and task behavior among Autistic children. However, the findings suggest that AAT can be one of treatment approach among Autistics children. Further study with longer timelines is needed to demonstrate a much better outcome as well as to ensure that the impact of the interventions really give an effect to the sample. © 2011 IEEE. |
2009 |
Yusoff, Mohd N; Wahab, Abdul M H; Aziz, M A; AshaÁri, Jalil F ESSE: Learning disability classification system for autism and dyslexia Journal Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5614 LNCS (PART 1), pp. 395-402, 2009, ISSN: 03029743, (cited By 2). Abstract | Links | BibTeX | Tags: Autism, Centralized Decision Making, Classification System, Decision Making, Errors, Expert Systems, Human Computer Interaction, Human Errors, Knowledge Engineering, Knowledge Management, Knowledge-Based Classification, Learning Disorder, Malaysia, Special Education, Teaching @article{MohdYusoff2009395, title = {ESSE: Learning disability classification system for autism and dyslexia}, author = {N Mohd Yusoff and M H Abdul Wahab and M A Aziz and F Jalil AshaÁri}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-76249116153&doi=10.1007%2f978-3-642-02707-9_45&partnerID=40&md5=f51c6dd35a86b7eef7ee117d1daa41dd}, doi = {10.1007/978-3-642-02707-9_45}, issn = {03029743}, year = {2009}, date = {2009-01-01}, journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {5614 LNCS}, number = {PART 1}, pages = {395-402}, abstract = {This paper presents an Expert System for Special Education (ESSE) based on scenario in Malaysia. This system is developed through the process of knowledge-gaining which is gathered from various expertise in chosen domain. Realizing the limitation of traditional classification system that teachers adopted, we developed ESSE to automate a centralized decision making system. ESSE is also able to provide consistent answers for repetitive decisions, processes and tasks. Besides, teachers using this system hold and maintain significant level of information pertaining both learning disabilities, thus reduce amount of human errors. ESSE knowledge-based resulted from the knowledge engineering called Qualifiers and Choice. Both are gathered from the analysis of symptoms that are experienced by Autism and Dyslexia patients. Every type of disability is divided to several categories and sub-category to facilitate question's arrangement. This paper presents a review of Expert System for Special Education (ESSE), problems arises and the knowledge-based classification systems. © 2009 Springer Berlin Heidelberg.}, note = {cited By 2}, keywords = {Autism, Centralized Decision Making, Classification System, Decision Making, Errors, Expert Systems, Human Computer Interaction, Human Errors, Knowledge Engineering, Knowledge Management, Knowledge-Based Classification, Learning Disorder, Malaysia, Special Education, Teaching}, pubstate = {published}, tppubtype = {article} } This paper presents an Expert System for Special Education (ESSE) based on scenario in Malaysia. This system is developed through the process of knowledge-gaining which is gathered from various expertise in chosen domain. Realizing the limitation of traditional classification system that teachers adopted, we developed ESSE to automate a centralized decision making system. ESSE is also able to provide consistent answers for repetitive decisions, processes and tasks. Besides, teachers using this system hold and maintain significant level of information pertaining both learning disabilities, thus reduce amount of human errors. ESSE knowledge-based resulted from the knowledge engineering called Qualifiers and Choice. Both are gathered from the analysis of symptoms that are experienced by Autism and Dyslexia patients. Every type of disability is divided to several categories and sub-category to facilitate question's arrangement. This paper presents a review of Expert System for Special Education (ESSE), problems arises and the knowledge-based classification systems. © 2009 Springer Berlin Heidelberg. |
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2011 |
The effects of animal assisted therapy in improving attention among autistic children Conference 2011, ISBN: 9781467300193, (cited By 0). |
2009 |
ESSE: Learning disability classification system for autism and dyslexia Journal Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5614 LNCS (PART 1), pp. 395-402, 2009, ISSN: 03029743, (cited By 2). |