2016 COLING COLING 2016

Textual complexity as a predictor of difficulty of listening items in language proficiency tests

Abstract

AbstractIn this paper we explore to what extent the difficulty of listening items in an English language proficiency test can be predicted by the textual properties of the prompt. We show that a system based on multiple text complexity features can predict item difficulty for several different item types and for some items achieves higher accuracy than human estimates of item difficulty.

🧭 Keyword Pioneer — textual complexity
🐝 Cross-Pollinator — 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, Robotics, Security & Privacy, Speech & Audio