A Survey of Question Answering for Math and Science Problem

TL;DR

This survey reviews the progress and challenges in developing AI systems capable of solving standardized math and science problems, highlighting the gap between current capabilities and human-level understanding.

Contribution

It provides a comprehensive overview of existing question answering methods for math and science, identifying key challenges and future opportunities in the domain.

Findings

Current AI systems struggle with middle school level questions

Significant gaps remain before AI can pass standardized science tests

Opportunities exist for improving reasoning and understanding in AI

Abstract

Turing test was long considered the measure for artificial intelligence. But with the advances in AI, it has proved to be insufficient measure. We can now aim to mea- sure machine intelligence like we measure human intelligence. One of the widely accepted measure of intelligence is standardized math and science test. In this paper, we explore the progress we have made towards the goal of making a machine smart enough to pass the standardized test. We see the challenges and opportunities posed by the domain, and note that we are quite some ways from actually making a system as smart as a even a middle school scholar.