2016 COLING COLING 2016

Using Argument Mining to Assess the Argumentation Quality of Essays

Abstract

AbstractArgument mining aims to determine the argumentative structure of texts. Although it is said to be crucial for future applications such as writing support systems, the benefit of its output has rarely been evaluated. This paper puts the analysis of the output into the focus. In particular, we investigate to what extent the mined structure can be leveraged to assess the argumentation quality of persuasive essays. We find insightful statistical patterns in the structure of essays. From these, we derive novel features that we evaluate in four argumentation-related essay scoring tasks. Our results reveal the benefit of argument mining for assessing argumentation quality. Among others, we improve the state of the art in scoring an essay’s organization and its argument strength.

πŸŒ‰ Interdisciplinary Bridge β€” Interdisciplinary and Natural Language Processing
πŸ“ˆ Trend Setter β€” Education
🧭 Keyword Pioneer β€” argument mining
🐣 Hot Topic Early Bird β€” argument mining
🐝 Cross-Pollinator β€” Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio