FINNger -- Applying artificial intelligence to ease math learning for children
This work addresses the gap in math learning for pre-school children by integrating technology into education, though it appears incremental as it builds on existing methods for educational apps.
The authors tackled the problem of children's difficulty in learning mathematics by developing an intuitive application that leverages children's ease with technology, using a novel convolutional neural network named FINNger to combine fun activities with educational improvement.
Kids have an amazing capacity to use modern electronic devices such as tablets, smartphones, etc. This has been incredibly boosted by the ease of access of these devices given the expansion of such devices through the world, reaching even third world countries. Also, it is well known that children tend to have difficulty learning some subjects at pre-school. We as a society focus extensively on alphabetization, but in the end, children end up having differences in another essential area: Mathematics. With this work, we create the basis for an intuitive application that could join the fact that children have a lot of ease when using such technological applications, trying to shrink the gap between a fun and enjoyable activity with something that will improve the children knowledge and ability to understand concepts when in a low age, by using a novel convolutional neural network to achieve so, named FINNger.