Screen4SpLDs - Development of an Automated Pre-Screening Tool for Specific Learning Disabilities in Children.

Screen4SpLDs - 开发针对儿童特定学习障碍的自动预筛查工具。

• 批准号: EP/Y002121/1
• 负责人: PRATHEEPAN YOGARAJAH
• 金额: $ 21.76万
• 依托单位: University of Ulster
• 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
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FY002121%2F1
• 关键词: Screen4SpLDs; Development; Automated; Pre; Screening

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.

特殊学习障碍是当今社会常见的一个术语，它以不同的方式表现出来，给日常生活带来各种困难。对一个人来说，可能是缺乏注意力，对另一个人来说，可能是难以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。早期发现和治疗特殊发育障碍至关重要，因为它可以启动干预措施，为患有特殊发育障碍的儿童提供最佳结果。在年轻时不处理特殊发育障碍会对成年后的发展产生重大影响，并导致高昂的经济成本，超过哮喘、智力残疾和糖尿病的终生成本，严重缺乏专门的教育工作者来进行特殊发育障碍筛查并随后在诊断后提供治疗。世界上近90%的儿童生活在低收入和中等收入国家。由于专业知识有限，包括中低收入国家有限的筛查、诊断和治疗资源，早期发现和早期干预spld的挑战更加严峻。例如，在全球南方，评估可持续发展目标的熟练人力资源和工具非常有限。因此，这些儿童没有得到诊断，并被社区通过污名化和标签化来负面强化。这些因素都会导致低自尊和行为问题，从而进一步干扰他们的学习能力。在往往已经陷入贫困的脆弱社区，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。我们的目标是通过开发和试点低成本的移动应用程序来解决这些发展问题，以筛查spld，从而进行早期干预。特殊学习障碍可能会以一种视觉上可以区分的方式影响笔迹。拟议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。提出的解决方案只需要在手机上拍摄手写图像的照片并将其传递给预测模型并获得预测结果。根据建议的解决方案，spld筛查可以在家中进行，在学校学习区域，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，易用，较少的培训要求，结果的准确性和可靠性。这个应用程序可以从个人到国家层面用于筛查儿童的spld。这将减轻特殊教育工作者短缺的负担，这对中低收入国家来说将是一个巨大的解脱。总的来说，这将通过提供获得最佳保健和教育服务的机会，减少弱势和边缘化儿童面临的不平等现象。这将改善所有人接受的优质教育，从而促进更广泛的社会改善。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是显著的。此外，创造机会对更大的人口进行筛查，将提高社会对弱势群体的认识，减少耻辱感，并加强公众和家长对弱势群体管理和支持受影响家庭的参与。