A good teaching method is incomprehensible for an autistic child. The autism spectrum disorder is a very diverse phenomenon. It is said that no two autistic children are the same. So, something that works for one child may not be fit for another. The same case is true for their education. Different children need to be approached with different teaching methods. But it is quite hard to identify the appropriate teaching method. As the term itself explains, the autism spectrum disorder is like a spectrum. There are multiple factors to determine the type of autism of a child. A child might even be diagnosed with autism at the age of 9. Such a varied group of children of different ages, but specialized educational institutions still tend to them more or less the same way. This is where machine learning techniques can be applied to find a better way to identify a suitable teaching method for each of them. By analyzing their physical, verbal and behavioral performance, the proper teaching method can be suggested much more precisely compared to a diagnosis result. As a result, more children with autistic spectrum disorder can get better education that suits their needs the best.
翻译:良好的教学方法对于自闭症儿童来说是无法理解的。 自闭症谱系障碍是一个非常多样的现象。 据说没有两个自闭症儿童是相同的现象。 因此, 适合一个孩子的东西可能不适合另一个孩子。 同一情况适用于他们的教育。 不同的孩子需要不同的教学方法。 但是很难找到合适的教学方法。 正如这个词本身所解释的那样, 自闭症谱障碍就像一个谱。 确定儿童自闭症类型有许多因素。 甚至可能有一个孩子在9岁时被诊断为自闭症, 这样的不同年龄组的儿童, 专业教育机构仍然或多或少地倾向于他们。 这是机器学习技术可以用来找到适合他们每个人的教学方法的。 通过分析他们的身体、言语和行为表现, 适当的教学方法可以比诊断结果更精确得多。 结果, 更多的自闭症谱障碍儿童可以得到更适合他们需要的更好的教育。