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Our experience in school, especially at an early age, often defines us, as well as our perception of ourselves and our abilities. Sometimes children may have difficulties in school because of their learning abilities or their development because many young children can develop differently, have different needs and learning styles. different. Their learning experiences at school play an important role in their future decision making in terms of what they dream of doing when they grow up as well as their perception of their abilities. Although a child may struggle in a particular area, it does not mean that he is fighting for the same reason as another child who is struggling in that same area. Doctors and teachers can work with children to ensure the best quality of their education, but some learning abilities can sometimes remain undiagnosed. To help solve this problem, researchers at Cambridge University have discovered a new way to use machine learning algorithms to diagnose why some children have difficulties. What they found was that their algorithm found learning difficulties that did not match those of a previous medical diagnosis, which helped to better understand why children are struggling.
Researchers at the University of Cambridge have worked with 550 children with academic difficulties. They did not separate the children according to their diagnosis, rather they examined the group as a whole. The inclusion of all difficulties and diagnosis allowed the authors to examine the entire spectrum of diagnosis, as well as their overlap. The artificial intelligence algorithm measured the cognitive skills of each child such as listening, problem solving, vocabulary, memory and spatial visualization. Results indicated that children belong to one of four groups: "1) children with severe cognitive difficulties and serious reading, spelling and math problems; 2) children with cognitive abilities and typical learning profiles for their age; 3) children with working memory problems; and 4) children with phonological difficulties. " The researchers found that two groups, the difficulty with the skills of working memory, related to difficulty in mathematics, and the difficulty to work on the treatment of sounds in words, attributed to the difficulty of reading comprehension, shared a link. That is, children who had problems in math also had reading comprehension problems. This is an important point of view as previous research in this area has not identified this link. This indicates that we need to go beyond past rigid labels and focus more on an individualistic approach to learning difficulties. The authors indicate that this research is used to use more innovative algorithms in machine learning to better identify and help children and their parents to manage and understand learning difficulties.
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Our experience in school, especially at an early age, often defines us, as well as our perception of ourselves and our abilities. Sometimes children may have difficulties in school because of their learning abilities or their development because many young children can develop differently, have different needs and learning styles. different. Their learning experiences at school play an important role in their future decision making in terms of what they dream of doing when they grow up as well as their perception of their abilities. Although a child may struggle in a particular area, it does not mean that he is fighting for the same reason as another child who is struggling in that same area. Physicians and teachers can work with children to ensure the best quality of schooling, but some learning skills may not be diagnosed at times. To help solve this problem, researchers at Cambridge University have discovered a new way to use machine learning algorithms to diagnose why some children have difficulties. What they found was that their algorithm found learning difficulties that did not match those of a previous medical diagnosis, which helped to better understand why children are struggling.
Researchers at the University of Cambridge have worked with 550 children with academic difficulties. They did not separate the children according to their diagnosis, rather they examined the group as a whole. The inclusion of all difficulties and diagnosis allowed the authors to examine the entire spectrum of diagnosis, as well as their overlap. The artificial intelligence algorithm measured the cognitive skills of each child such as listening, problem solving, vocabulary, memory and spatial visualization. Results indicated that children belong to one of four groups: "1) children with severe cognitive difficulties and serious reading, spelling and math problems; 2) children with cognitive abilities and typical learning profiles for their age; 3) children with working memory problems; and 4) children with phonological difficulties. " The researchers found that two groups, the difficulty with the skills of working memory, related to difficulty in mathematics, and the difficulty to work on the treatment of sounds in words, attributed to the difficulty of reading comprehension, shared a link. That is, children who had problems in math also had reading comprehension problems. This is an important point of view as previous research in this area has not identified this link. This indicates that we must go beyond rigid labels and put more emphasis on an individualistic approach to learning difficulties. The authors indicate that this research is used to use more innovative algorithms in machine learning to better identify and help children and their parents to manage and understand learning difficulties.
