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Intelligent Math Tutor: Problem-Based Approach to Create Cognizance

Published:12 April 2017Publication History

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.

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  1. Intelligent Math Tutor: Problem-Based Approach to Create Cognizance

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    • Published in

      cover image ACM Conferences
      L@S '17: Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale
      April 2017
      352 pages
      ISBN:9781450344500
      DOI:10.1145/3051457

      Copyright © 2017 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 12 April 2017

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      Acceptance Rates

      L@S '17 Paper Acceptance Rate14of105submissions,13%Overall Acceptance Rate117of440submissions,27%

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