Sun 14 Jun 2015 17:20 - 18:00 at C120-C121 - Session4

In MOOCs, a single programming exercise may produce thousands of solutions from learners. Understanding solution variation is important for providing appropriate feedback to students at scale. The wide variation among these solutions can be a source of pedagogically valuable examples, and can be used to refine the autograder for the exercise by exposing corner cases. We present OverCode, a system for visualizing and exploring thousands of programming solutions. OverCode uses both static and dynamic analysis to cluster similar solutions, and lets instructors further filter and cluster solutions based on different criteria. We evaluated OverCode against a non-clustering baseline in a within-subjects study with 24 teaching assistants, and found that the OverCode interface allows teachers to more quickly develop a high-level view of students’ understanding and misconceptions, and to provide feedback that is relevant to more students.

Sun 14 Jun
Times are displayed in time zone: Tijuana, Baja California change

16:00 - 18:00: Session4PLOOC at C120-C121
16:00 - 16:40
Personalized Mathematical Word Problem Generation
P: Alex PolozovUniversity of Washington, Eleanor O'RourkeUniversity of Washington, Adam SmithUniversity of Washington, Luke ZettlemoyerUniversity of Washington, Sumit GulwaniMicrosoft Research, Zoran PopovicUniversity of Washington
16:40 - 17:20
Making Proof Tutors out of Proof Assistants
P: Peter-Michael OseraUniversity of Pennsylvania, Steve Zdancewic
17:20 - 18:00
OverCode: Visualizing Variation in Student Solutions to Programming Problems at Scale
Elena GlassmanMIT, Jeremy ScottMIT, P: Rishabh SinghMicrosoft Research, Philip GuoUniversity of Rochester, Robert MillerMIT