Automated systems designed to tackle mathematical word problems leverage natural language processing to understand the problem’s text, convert it into a solvable mathematical representation, and then utilize algorithms to compute the solution. For instance, such a system could process a problem like “Jane has 5 apples and gives 2 to John. How many apples does Jane have left?” It would identify key information (5 apples, giving away 2), formulate the equation (5 – 2), and provide the answer (3).
The ability to automate the solution of word problems offers significant advantages. It can personalize learning experiences by providing tailored feedback and practice opportunities. Furthermore, it can save educators valuable time by automating grading and assessment tasks. This technology builds upon decades of research in artificial intelligence, natural language understanding, and mathematical problem-solving. Historically, automating this complex cognitive task was a considerable challenge. However, recent advancements in machine learning and AI have made significant strides in achieving practical and effective solutions.