Learning to Grade Short Answer Questions using Semantic Similarity Measures and Dependency Graph Alignments

摘要: In this work we address the task of computerassisted assessment short student answers. We combine several graph alignment features with lexical semantic similarity measures using machine learning techniques and show that answers can be more accurately graded than if were used in isolation. also present a first attempt to align dependency graphs instructor order make use structural component automatic grading