Trends, Limitations and Open Challenges in Automatic Readability Assessment Research

Abstract

Readability assessment is the task of evaluating the reading difficulty of a given piece of text. Although research on computational approaches to readability assessment is now two decades old, there is not much work on synthesizing this research. This article is a brief survey of contemporary research on developing computational models for readability assessment. We identify the common approaches, discuss their shortcomings, and identify some challenges for the future.Where possible, we also connect computational research with insights from related work in other disciplines such as education and psychology.

Cross-Corpus Readability Compatibility Assessment for English Texts

“…ARA has been a cross-disciplinary topic in education, psychology, and computer science for almost a century. At the core of ARA tasks lies the concept of text difficulty, which refers to the level at which learners can read and comprehend text materials [10].…”

“…For instance, the Flesch-Kincaid formula only considers text features such as sentence length and word difficulty, neglecting other factors that may impact readability. Similarly, Vajjala [10] highlighted that traditional readability formulas can only be trained and tested on specific domains or text types.…”