Evaluating Multiple Aspects of Coherence in Student Essays

Abstract

Criterion Online Essay Evaluation Service includes a capability that labels sentences in student writing with essay-based discourse elements (e.g., thesis statements). We describe a new system that enhances Criterion’s capability, by evaluating multiple aspects of coherence in essays. This system identifies features of sentences based on semantic similarity measures and discourse structure. A support vector machine uses these features to capture breakdowns in coherence due to relatedness to the essay question and relatedness between discourse elements. Intra-sentential quality is evaluated with rule-based heuristics. Results indicate that the system yields higher performance than a baseline on all three aspects.