Personalized mathematical word problem generation

Oleksandr Polozov, Eleanor O'Rourke, Adam M. Smith, Luke Zettlemoyer, Sumit Gulwani, Zoran Popović

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Scopus citations

Abstract

Word problems are an established technique for teaching mathematical modeling skills in K-12 education. However, many students find word problems unconnected to their lives, artificial, and uninteresting. Most students find them much more difficult than the corresponding symbolic representations. To account for this phenomenon, an ideal pedagogy might involve an individually crafted progression of unique word problems that form a personalized plot. We propose a novel technique for automatic generation of personalized word problems. In our system, word problems are generated from general specifications using answer-set programming (ASP). The specifications include tutor requirements (properties of a mathematical model), and student requirements (personalization, characters, setting). Our system takes a logical encoding of the specification, synthesizes a word problem narrative and its mathematical model as a labeled logical plot graph, and realizes the problem in natural language. Human judges found our problems as solvable as the textbook problems, with a slightly more artificial language.

Original languageEnglish (US)
Title of host publicationIJCAI 2015 - Proceedings of the 24th International Joint Conference on Artificial Intelligence
EditorsMichael Wooldridge, Qiang Yang
PublisherInternational Joint Conferences on Artificial Intelligence
Pages381-388
Number of pages8
ISBN (Electronic)9781577357384
StatePublished - Jan 1 2015
Event24th International Joint Conference on Artificial Intelligence, IJCAI 2015 - Buenos Aires, Argentina
Duration: Jul 25 2015Jul 31 2015

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
Volume2015-January
ISSN (Print)1045-0823

Other

Other24th International Joint Conference on Artificial Intelligence, IJCAI 2015
CountryArgentina
CityBuenos Aires
Period7/25/157/31/15

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Polozov, O., O'Rourke, E., Smith, A. M., Zettlemoyer, L., Gulwani, S., & Popović, Z. (2015). Personalized mathematical word problem generation. In M. Wooldridge, & Q. Yang (Eds.), IJCAI 2015 - Proceedings of the 24th International Joint Conference on Artificial Intelligence (pp. 381-388). (IJCAI International Joint Conference on Artificial Intelligence; Vol. 2015-January). International Joint Conferences on Artificial Intelligence.