Automatic Classification of Error Types
One of the problems of online programming courses is the lack of feedback. The main idea of this project is to cluster submitted fixes of incorrect solutions to detect frequent error types, label several largest clusters, and then use this labeled dataset to train a classifier. Such an approach allows us to show human-written hints to users who made a common mistake, making the education process more personalized and, therefore, more effective.
Project on GitHub
Automatic Classification of Error Types in Solutions to Programming Assignments at Online Learning Platform
Artyom Lobanov, Timofey Bryksin, and Alexey Shpilman