FINNger -- Applying artificial intelligence to ease math learning for children

TL;DR

This paper introduces FINNger, a convolutional neural network-based application designed to make learning math more engaging and accessible for children by leveraging their familiarity with electronic devices.

Contribution

The work presents a novel CNN model, FINNger, aimed at enhancing early math education through an intuitive AI-powered application for children.

Findings

Proposed a new CNN architecture for children's math learning.

Demonstrated potential for improved engagement in early education.

Laid groundwork for future AI-based educational tools.

Abstract

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.