Mining patterns in syntax trees to automate code reviews of student solutions for programming exercises

arXiv:2405.01579v1 Announce Type: cross
Abstract: In programming education, providing manual feedback is essential but labour-intensive, posing challenges in consistency and timeliness. We introduce ECHO, a machine learning method to automate the reuse of feedback in educational code reviews by analysing patterns in abstract syntax trees. This study investigates two primary questions: whether ECHO can predict feedback annotations to specific lines of student code based on previously added annotations by human reviewers (RQ1), and whether its training and prediction speeds are …

abstract arxiv automate challenges code cs.cy cs.lg cs.se echo education educational feedback labour machine machine learning mining patterns programming reviews solutions syntax trees type