Inferring student coding goals using abstract syntax trees

Abstract

The rapidly growing demand for programming skills has driven improvements in the technologies delivering programming education to students. Intelligent tutoring systems will potentially contribute to solving this problem, but development of effective systems has been slow to take hold in this area. We present a novel alternative, abstract Syntax Tree Retrieval, which uses case-based reasoning to infer student goals from previous solutions to coding problems. Without requiring programmed expert knowledge, our system demonstrates that accurate retrieval is possible for basic problems. We expect that additional research will uncover more applications for this technology, including more effective intelligent tutoring systems.