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The use of non-industrial robots, called service robots, is increasing in the welfare fields to meet the demand for robot therapy among individuals with autism. The more simple communication structures and repetitive behaviors of robots, compared to humans, make it easier for children with autism to interpret communication and respond appropriately...
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Background
Robot-mediated interventions show promise in supporting the development of children on the autism spectrum.
Objectives
In this systematic review and meta-analysis, we summarize key features of available evidence on robot-interventions for children and young people on the autism spectrum aged up to 18 years old, as well as consider their...
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Citations
... With their simpler communication structures and ability of performing designated behaviours repetitively, robots can help children with ASD interpret communication easier and respond appropriately. Lee and Nagae (2021) proposed that interacting with a robot could allow for social distance to be designed and maintained depending on an individual's social interaction needs. Lee and Nagae (2021) carried out an experiment to examine the accuracy of a program designed to detect social distance and explore the existing correlations between the social responsiveness of children with ASD and social distance. ...
... With their simpler communication structures and ability of performing designated behaviours repetitively, robots can help children with ASD interpret communication easier and respond appropriately. Lee and Nagae (2021) proposed that interacting with a robot could allow for social distance to be designed and maintained depending on an individual's social interaction needs. Lee and Nagae (2021) carried out an experiment to examine the accuracy of a program designed to detect social distance and explore the existing correlations between the social responsiveness of children with ASD and social distance. In the experiment, 15 children with ASD interacted with a robot on a one-to-one basis for about 20 minutes. ...
Teknolojideki dönüşümün hayatımızda bir “sabit” haline geldiği 21. yüzyılda, öğretmenlerin teknoloji ile tutarlı ve uygun deneyimlere ne kadar sahip olduklarını ve teknolojiyi kendi sınıflarına ne kadar entegre ettiklerini belirlemek bir ihtiyaç haline gelmiştir. Bu çalışmada, 21. yüzyıl öğretmenlerinin teknoloji yeterliklerinin öz değerlendirme yoluyla belirlenmesi amaçlanmıştır. Öğretmenlerin 21. yüzyıl öğrenmeleri için teknoloji yeterliği öz değerlendirme puanları cinsiyet, branş, kıdem, kurum ve yaş değişkenleri açısından ele alınmış; öğretmenlerin bu yeterlikler kapsamında eğitimde dijital dönüşüme hazır olma durumları tartışılmıştır. Araştırmada nicel araştırma yöntemlerinden tarama modeli kullanılmıştır. Katılımcıların belirlenmesinde amaçsal örnekleme yöntemlerinden ölçüt örnekleme kullanılmış ve Milli Eğitim Bakanlığına bağlı kurumlarda görev yapan 198 öğretmenden veri toplanmıştır. Araştırma verileri Christensen ve Knezek (2017) tarafından geliştirilen ve Fidan, Debbağ ve Çukurbaşı (2020) tarafından Türkçe’ye uyarlanan “21.Yüzyıl Öğrenmeleri için Teknoloji Yeterliği Öz
Değerlendirme Ölçeği” aracılığıyla toplanmıştır. Ölçek dört alt boyut içermekte ve toplam 24 maddeden oluşmaktadır. %95 güven aralığında (p=0,05) analiz edilen verilerin öncelikle normal dağılıp dağılmadığı incelenmiştir. Elde edilen bulgulara göre ölçek verilerinin normal dağılım gösterdiği belirlenmiş ve verilerin
analizinde betimsel analiz, bağımsız örneklem t-Testi ve One-Way Anova testleri kullanılmıştır. Araştırma bulgularına göre, öğretmenlerin teknoloji yeterlikleri ile cinsiyetleri arasında istatistiksel olarak anlamlı bir fark bulunmamıştır. Öğretmenlerin teknoloji yeterlikleri ile branşları arasında ise istatistiksel olarak anlamlı bir fark bulunmuştur. Branş ortalamalarına bakıldığında fen bilimleri branşında yer alan öğretmenlerin teknoloji yeterliklerinin sosyal bilimler branşı öğretmenlerine göre daha yüksek olduğu görülmüştür. Fen bilimleri
branşındaki öğretmenlerin entegre uygulamalar ve teknolojiyle öğretim yeterlikleri sosyal bilimler branşındaki öğretmenlere göre daha yüksektir. Özel kurumlarda çalışan öğretmenlerin ortalama puanları devlet kurumlarında çalışanlara göre daha yüksek olmasına rağmen öğretmenlerin teknoloji yeterlikleri ile çalıştıkları kurum arasında
istatistiksel olarak anlamlı bir fark bulunmamıştır. Öğretmenlerin teknoloji yeterlikleri ile kıdem yılları arasında da istatistiksel olarak anlamlı bir fark bulunmuştur. Elde edilen bulgulara göre 20 yıla kadar kıdemli olan öğretmenlerin teknoloji yeterlikleri, 21 yıl ve üstü kıdemli öğretmenlere göre daha yüksektir. Öğretmenlerin teknoloji yeterlikleri ile yaş değişkeni arasında istatistiksel olarak anlamlı bir fark bulunmuştur. Bu fark 41 yaş ve altı öğretmenler lehine olup, bilişim teknolojilerini kullanarak büyüyen Y jenerasyonu dijital yerli öğretmenlerin teknolojik yeterliklerinin daha iyi olduğu görülmüştür.
The integration of artificial intelligence (AI)-based robot therapy (AIBRT) has become prominent in addressing the needs of children with disabilities, including autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), learning disabilities, and speech delays. However, questions arise regarding the effectiveness of different AI techniques in enhancing therapy for children with specific needs. This review explores current literature on AIBRT for children with disabilities, aiming to understand the efficacy and potential of various AI techniques in improving their therapy. This paper presents a comprehensive search of research articles published from 2019 to September 2023. 39 articles focusing on AI-based robot platforms, the employed treatment or therapy methods, assessment procedures during therapy, and the variables or parameters used to measure intervention effectiveness have been discussed in detail. These AI-based robot platforms have been utilized to engage individuals diagnosed with ASD, offering therapeutic interventions and assessments. In conclusion, the integration of AI and robotics in therapy shows promise for enhancing the development and quality of life for children with disabilities. The findings of this review have implications for therapists, practitioners, and researchers interested in incorporating AI applications into therapy practices. This integration can lead to improved therapy outcomes, optimized children’s development, and enhanced quality of life.
Introduction
In Industry 4.0, collaborative tasks often involve operators working with collaborative robots (cobots) in shared workspaces. Many aspects of the operator's well-being within this environment still need in-depth research. Moreover, these aspects are expected to differ between neurotypical (NT) and Autism Spectrum Disorder (ASD) operators.
Methods
This study examines behavioral patterns in 16 participants (eight neurotypical, eight with high-functioning ASD) during an assembly task in an industry-like lab-based robotic collaborative cell, enabling the detection of potential risks to their well-being during industrial human-robot collaboration. Each participant worked on the task for five consecutive days, 3.5 h per day. During these sessions, six video clips of 10 min each were recorded for each participant. The videos were used to extract quantitative behavioral data using the NOVA annotation tool and analyzed qualitatively using an ad-hoc observational grid. Also, during the work sessions, the researchers took unstructured notes of the observed behaviors that were analyzed qualitatively.
Results
The two groups differ mainly regarding behavior (e.g., prioritizing the robot partner, gaze patterns, facial expressions, multi-tasking, and personal space), adaptation to the task over time, and the resulting overall performance.
Discussion
This result confirms that NT and ASD participants in a collaborative shared workspace have different needs and that the working experience should be tailored depending on the end-user's characteristics. The findings of this study represent a starting point for further efforts to promote well-being in the workplace. To the best of our knowledge, this is the first work comparing NT and ASD participants in a collaborative industrial scenario.
