5 accepted papers
Recent developments in Natural Language Processing (NLP) for argument mining offer new opportunities to analyze the argumentative units (AUs) in student essays. These advancements can be leveraged to provide automatically generated feedback and exercises for students engaging in online argumentative…
In this paper, we present the DARIUS (Digital Argumentation Instruction for Science) corpus for argumentation quality on 4589 essays written by 1839 German secondary school students. The corpus is annotated according to a fine-grained annotation scheme, ranging from a broader perspective like conten…
In this paper, we investigate the role of arguments in the automatic scoring of cohesion in argumentative essays. The feature analysis reveals that in argumentative essays, the lexical cohesion between claims is more important to the overall cohesion, while the evidence is expected to be diverse and…
When scoring argumentative essays in an educational context, not only the presence or absence of certain argumentative elements but also their quality is important. On the recently published student essay dataset PERSUADE, we first show that the automatic scoring of argument quality benefits from ad…
Automatic content scoring systems are widely used on short answer tasks to save human effort. However, the use of these systems can invite cheating strategies, such as students writing irrelevant answers in the hopes of gaining at least partial credit. We generate adversarial answers for benchmark c…