# Cognitively Driven Arabic Text Readability Assessment Using Eye-Tracking
## 1 Introduction
This is linked to [PERSON] and [PERSON]'s [13] eye-mind hypothesis, which proposes that there is no discernible delay between eye fixation and cognitive processing. Eye-tracking provides objective measurements of reader behavior, and it is effective in detecting processing problems during naturalistic reading [14]. Recent advances in the development of eye-tracking technology have led to research into the indirect behavior of readers and text difficulties [12; 15; 16]. However, substantial scholarship has focused on the quantification and automatic calculation of textual complexity in accordance with different linguistic features [11]. However, few studies have used eye-tracking to improve text readability. Eye-tracking experimentation has only been used for evaluation. Thus, while using gaze data to explore reading processes is not a new idea [17], it remains underexploited as a research tool in readability assessment [11]. Eye-tracking experimentation may well be time and resource intense. Still, it represents a more naturalistic approach to exploring reading processes and permits text re-reading to be examined [8; 9]. Motivated by the potential benefit of using physiological eye-tracking data and the insufficiency of the investigation of these data in text readability prediction, this research proposes incorporating eye-movement data for automatic readability assessment, particularly for the Arabic language. Offering human reading data while reading Arabic text could serve different applications in addition to readability assessment, which would be a great contribution for Arabic. The study is concerned primarily with eye-tracking and linguistic text features associated with text difficulty. Thus, a document's graphical components that may affect readability have not been considered, such as font size, images, or tables [2]. The main contribution of this study is to discover how incorporating eye-tracking data for Arabic readability assessment has the potential to improve this task, particularly given that research on the readability of Arabic texts has used simple features that do not consider the reader in its prediction. This prevents these simple measures from reflecting the correct level of difficulty. To the best of our knowledge, this is the first study to incorporate eye movement data into the Arabic text readability task. Hopefully, this study's results will help evaluate and adjust current and future Arabic texts found in educational, medical, industrial, and other contexts. Eventually, effective readability assessment will contribute to increasing the prevalence of Arabic written information [18]. Additionally, assessing reading difficulties will benefit not only Arabic natives but also Arabic learners, based on the results of [12; 17; 19; 20], which indicate that measuring text difficulty for a language's learners can be efficiently estimated by the native speakers of this language. The rest of the paper is organized as follows. Section 2 describes some required background knowledge related to text readability assessments and eye-tracking. Section 3 surveys existing studies targeting readability assessment with and without using eye-tracking data. Section 4 illustrates the primary research objectives and presents a conducted pilot study and all experimental procedure details. Section 5 illustrates the results and a discussion of them. Finally, we conclude in Section 6 with future work.