Dyscalculia is a specific learning disability in math. Kids with dyscalculia may have difficulty understanding number-related concepts or using symbols or functions needed for success in mathematics.
I have come across the term very recently while researching for PO, and one of the first things that come to my mind as I read about it was – if we draw up a Markov Chain where each node is a question asked to the student (this serving itself will have to be a part of a Temporally Coherent Clustering of similar questions in a database) – where each node contains an expected probability of accuracy (based on a demographic average) and we check whether the student is reaching that level (or even improving at all between subsequent jumps within the cluster), then would that data be enough to determine whether the student has Dyscalculia?
Easier said, can we predict the chances of a student having Dyscalculia using simple Machine Learning knowledge?