Screen4SpLDs - Development of an Automated Pre-Screening Tool for Specific Learning Disabilities in Children.
Screen4SpLDs - Development of an Automated Pre-Screening Tool for Specific Learning Disabilities in Children.
批准号:
EP/Y002121/1
负责人:
PRATHEEPAN YOGARAJAH
金额:
$21.76万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2024
资助国家:
英国
项目状态:
未结题
起止时间:
2024 至 --
中文摘要
特殊性学习障碍是当今社会的一个常见术语,它以不同的方式表现出来,会给人们的日常生活带来各种困难。对一个人来说,这可能是缺乏注意力,对另一个人来说,这可能是努力流利地阅读或进行基本的数学计算;这些是不同的学习障碍群体。早期发现和治疗SLD至关重要,因为它可以启动干预措施,为患有SLD的儿童提供最佳结果。在年轻时不解决SLD对成年的发展有重大影响,并导致高昂的经济成本,超过哮喘,智力残疾和糖尿病的终身成本,特别教育工作者严重短缺,以进行SLD筛查并随后提供诊断后的治疗。世界上近90%的儿童居住在低收入和中等收入国家(LMIC)。由于专业知识有限,包括中低收入国家筛查、诊断和治疗资源有限,早期发现和早期干预特发性肝病的挑战更加严峻。例如,在全球南方,评估特殊和次级发展中国家的熟练人力资源和工具非常有限。因此,这些儿童得不到诊断,并受到社区的侮辱和标签的消极强化。这些因素都导致低自尊和行为问题,进一步干扰他们的学习能力。在往往已经贫困的弱势社区,这是一种恶性循环,因为最佳教育是打破这种恶性循环的主要方法。我们的目标是针对这些发展问题,开发和试点低成本的移动的应用程序为基础的解决方案,用于筛查SPLD,这将导致早期干预。特定的学习障碍可能会影响手写的方式,可以在视觉上区分。这项研究的目的是评估深度学习的能力,以区分那些有SpLD的人和那些没有的人,从他们的笔迹。该方案只需在移动的手机上对手写体图像进行拍照,并将其传递给预测模型,得到预测结果,即可在家中、学校学习区进行SPLD筛查,无需任何额外的特殊设置。这个应用程序的重要因素是简单,易于使用,培训需求少,结果的准确性和可靠性。该应用程序可以从个人到国家层面为儿童筛查SpLD。这将减轻特殊教育工作者短缺的负担,对中低收入国家来说将是一个巨大的缓解,这将通过提供获得最佳保健和教育服务的机会,从总体上减少弱势和边缘化儿童面临的不平等。这将导致提高所有人接受的优质教育,从而有助于更广泛的社会进步。除了对儿童的直接影响外,对家庭和社区发展的溢出效应也很大。此外,创造一个筛查更多人群的机会将提高社会对SPLD的认识,减少耻辱感,并加强公众和家长参与管理SPLD和支持受影响家庭。
英文摘要
Specific Learning Disabilities (SpLDs) is a common term in today's society, which manifests in different ways and can cause various difficulties in daily life. For one person it might be the lack of attention, for another, it might be struggling to read fluently or conduct basic mathematical calculations; these are different groups of Learning Disabilities. Early detection and treatment of SpLDs are crucial, as it enables the start of interventions that support the best outcomes for children living with SLDs. Not addressing SLDs at a young age has a major influence on development into adulthood and results in a high economic cost, exceeding the lifetime costs of asthma, intellectual disability, and diabetes have a huge shortage of special educators to conduct SLDs screening and subsequently providing treatment post diagnosis. There are nearly 90% of the world's children reside in Low and Middle-Income Countries (LMICs). The challenge of early detection and early intervention of SpLDs is exacerbated by limited expertise, including limited screening, diagnostic and treatment resources in LMICs. For instance, in the Global South, the skilled human resource and tools to assess SpLDs are very limited. Thus, these children are undiagnosed and negatively reinforced by the community by stigmatizing and labelling them. These factors all lead to low self-esteem and behavior problems that further interfere with their ability to learn. In vulnerable communities, which are often already poverty stricken, this operates as a vicious cycle, simply because optimal education is the main method of breaking this vicious cycle. We aim to target these developmental issues by developing and piloting low-cost mobile app-based solution for the screening of SpLDs that will lead to early intervention. Specific learning disorder may affect handwriting in a way that can be visually distinguished. The purpose of the proposed research is to evaluate the ability of deep learning to distinguish between those who have SpLDs and those who do not, from their handwriting. The proposed solution requires no more than taking a photo of the handwritten image on a mobile phone and passing it to the prediction model and getting the prediction results.Based on the proposed solution, the SpLDs screening can be conducted at home, in a school study area without any additional special setting. The important factors of this app are simplicity, ease of use, less training requirement, the accuracy of the results, and reliability. This app can serve from individual to national level for screening SpLDs in children. This will reduce the burden of the shortage of special educators, and this will be a huge relief for LMICs.This will, in general, reduce the inequalities faced by vulnerable and marginalized children, by providing an opportunity to receive optimal health and educational services. This will lead to the improvement of quality education received by ALL which in turn will contribute to wider societal improvements. In addition to the direct impact on the child, the spillover effects on the family and community development are significant. Further, creating an opportunity to screen a larger population will increase societal awareness of SpLDs and reduce the stigma and enhance public and parent involvement and engagement in managing SpLDs and supporting the affected families.
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国内基金
海外基金
水稻边界发育缺陷突变体abnormal boundary development(abd)的基因克隆与功能分析
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批准号:32070202
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项目类别:面上项目
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资助金额:58.0万元
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批准年份:2020
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负责人:汪泉
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依托单位:
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
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批准号:--
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项目类别:--
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资助金额:40万元
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批准年份:2020
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负责人:Vikrant Gupta
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依托单位: