A group of researchers has employed machine learning- a type of artificial intelligence able to analyze and sort large amounts of data. The A.I. was able to able to spot patterns of learning difficulties that were not previously observed by researchers.
Lead members from the joint study made by the Medical Research Council and the Cambridge University Brain Science unit agree that the study has proved the need of intensive cognitive resting, in order to identify the problems from the early stages and correct the issue as soon as possible.
Most of the children that encounter learning difficulties already have a clinical diagnosis which explains the issues at least partly, like ADHD, dyslexia or various forms of autism. This study was more inclusive, as it also took into consideration children from all difficulty degrees, in order to also understand the differences between the difficulties themselves and how the children perceive them.
One doctor that lead the study has noted that establishing an exact diagnosis is the first step on the road to recovery, as it allows a parent to anticipate key difficulties that may be faced by a child in question and allow everyone to focus on those particular needs.
His primary issue is the fact that a diagnostic is just a label, and manifestation can vary from one child to another, even if they have the exact same problem.
Two major difficulty groups seemed to have the highest rate of occurrence: memory skills and spoken words understanding.
Short-term memory issues usually mean that the child needs extra time in order to understand and deal with Math and other topics that require memorization.
Children with spoken word interpretation difficulties have a problem in understanding explanations, which make the process of leaning time-consuming as they also seem to have problems when reading.
The results show the value of machine-learning and will also help in the creation of more efficient educational guidelines.
Agnes is a technical writer, being in touch with reports to come up with the latest tech leaks.