title: "OverCode: Visualizing Variation in Student Solutions to Programming Problems at Scale" authors: Elena L. Glassman, Jeremy Scott, Rishabh Singh, Philip J. Guo, Robert C. Miller venue: ACM Transactions on Computer-Human Interaction (TOCHI) year: 2015 links: - Press release - Webpage tweet: OverCode lets instructors view and comment on thousands of student solutions to coding assignments abstract: > 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 teachers 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' solutions. bibtex: > @article{GlassmanTOCHI2015, author = {Glassman, Elena L. and Scott, Jeremy and Singh, Rishabh and Guo, Philip J. and Miller, Robert C.}, title = {OverCode: Visualizing Variation in Student Solutions to Programming Problems at Scale}, journal = {ACM Trans. Comput.-Hum. Interact.}, issue_date = {March 2015}, volume = {22}, number = {2}, month = mar, year = {2015}, issn = {1073-0516}, pages = {7:1--7:35}, articleno = {7}, numpages = {35}, url = {http://doi.acm.org/10.1145/2699751}, doi = {10.1145/2699751}, acmid = {2699751}, publisher = {ACM}, address = {New York, NY, USA}, keywords = {Programming education, learning at scale}, }