Intelligent math tutor: Problem-based approach to create cognizance

Abstract

Mathematical word problems (or story problems) allow students to apply their mathematical problem solving ability to other subjects and real-world situations. Word problems build higher-order thinking, critical problem-solving, and reasoning skills. Generally solving a word problem is associated with mathematical modeling of a real word situation or a concept of another subject which is embedded in the problem. Manually creating word problems require knowledge of other topics a student is learning in parallel. Besides this, modeling mathematics with some other dissociated concept is a time-consuming and labor-intensive task. Due to lack of this integrated knowledge of other topics being taught, the substantive breadth of word problems is often very narrow and is limited to very few concepts. To address this limitation, we built a tool called Intelligent Math Tutor (IMT), which automatically generates mathematical word problems such that teachings from other subjects from a given curriculum can also be incorporated. Our tool thus widens the scope of word problems and uses this problem-solving based approach to indirectly create cognizance in its students. To the best of our knowledge, our tool is the first of its kind tool which explicitly blends knowledge from multiple dissociated subjects and uses it to enhance the cognizance of its learners.