VQA-Based Educational Method For Preschooler Math Learning

Automatically solving problem is a long-standing research problem in the field of artificial intelligence and intelligence education.This problem aims to develop an algorithm that can fully automatically produce a readable solution from the preschooler'^textbook.It has been a lot of research problem in recent years with the improvement of technologies in natural language processing(NLP)and machine reasoning and the urgent need for more intelligent educational service.Since the great potential in research and applications,many visual visual question answering(VQA)problem methods have been proposed and implemented in many areas.The VQA also covers both computer vision(CV)and NLP,but unlike VQA,the visual question answering is solely focused on a specific part of the picture.Depending on the problem,and some issues still need specific common-sense reasoning can answer.Based on the elementary 1-3 grade textbook,they obtain informational images with familiar objects.There is no specific method for analyzing and understanding the only images from the preschooler's textbook.More concretely,our research content includes two aspects:Firstly,the theory of fully automatically solving arithmetic problems from textbook images.Secondly,an interactive intelligent VQA and syntax-semantics model tutoring system for preschooler math learning.