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},
}