A Multi-language Platform for Generating Algebraic Mathematical Word Problems
This addresses the need for more flexible educational tools in mathematics, though it is incremental as it builds on existing language generation methods.
The paper tackled the problem of generating customizable and creative algebraic mathematical word problems by using deep neural language generation, achieving over 90% accuracy in both English and Sinhala languages.
Existing approaches for automatically generating mathematical word problems are deprived of customizability and creativity due to the inherent nature of template-based mechanisms they employ. We present a solution to this problem with the use of deep neural language generation mechanisms. Our approach uses a Character Level Long Short Term Memory Network (LSTM) to generate word problems, and uses POS (Part of Speech) tags to resolve the constraints found in the generated problems. Our approach is capable of generating Mathematics Word Problems in both English and Sinhala languages with an accuracy over 90%.