Sun 14 Jun 2015 16:00 - 16:40 at C120-C121 - Session4

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. In addition to boosting the students’ engagement, such a technology also enables individual instructional scaffolding of problem progressions and data-driven problem complexity research in a wide spectrum of educational domains, such as algebra, language comprehension, or programming.

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 synthesizes the problem narrative and its mathematical model from the logical encoding of the specification as a labeled logical plot graph. Human judges found our problems as solvable as the textbook problems, with a slightly more artificial language.

Sun 14 Jun
Times are displayed in time zone: (GMT-07:00) Tijuana, Baja California change

16:00 - 18:00: PLOOC 2015 - Session4 at C120-C121
PLOOC-2015-papers16:00 - 16:40
Alex PolozovUniversity of Washington, Eleanor O'RourkeUniversity of Washington, Adam SmithUniversity of Washington, Luke ZettlemoyerUniversity of Washington, Sumit GulwaniMicrosoft Research, Zoran PopovicUniversity of Washington
PLOOC-2015-papers16:40 - 17:20
Peter-Michael OseraUniversity of Pennsylvania, Steve Zdancewic
PLOOC-2015-papers17:20 - 18:00
Elena GlassmanMIT, Jeremy ScottMIT, Rishabh SinghMicrosoft Research, Philip GuoUniversity of Rochester, Robert MillerMIT