A Corpus-Based Readability Formula for Estimate of Arabic Texts Reading Difficulty Kulliyyah of Languages and Management 1 Kulliyyah of Islamic Revealed Knowledge and Human Sciences (original) (raw)

A Corpus-Based Readability Formula for Estimate of Arabic Texts Reading Difficulty

The present study is aimed at designing a formula for estimating the difficulty of reading Arabic texts. Flesch, Gunning Fox and Dale-Chall are some of the formulae that have been used for measuring English texts difficulty. Some of them have been automated making it easy for users to check the readability level of a particular text. A few scholars have attempted to come up with a readability formula for Arabic, but none has been automated. This study is thus conducted to find the formula that would make it possible for users to measure the difficulty level of Arabic texts online. This will greatly help in materials selection for reading comprehension and testing. This paper will present the prototype of a readability formula which is based on a corpus for estimating the difficulty of Arabic written documents.

AARI: Automatic Arabic Readability Index

Text readability refers to the ability of the reader to understand and comprehend a given text. In this research, we present our approach to develop an automatic readability index for the Arabic language: Automatic Arabic Readability Index (AARI), using factor analysis. Our results are based on more than 1196 Arabic texts extracted from the Jordanian curriculum in the subjects of: Arabic language, Islamic religion, natural sciences, and national and social education for the elementary classes (first grade through tenth grade). We conduct a comparison study to support our model using cluster analysis and Support Vector Machines (SVM). In order to facilitate the usage of our Arabic readability index, we developed two applications to compute the Arabic text readability: A standalone application and an add-on for Microsoft Word text processer. Through our presented research results and developed tools, we aim to improve the overall readability of Arabic texts, especially those targeted towards the younger generations.

ARABIC TEXT READABILITY MEASURMENT SYSTEM

Text is an important element in learning languages. It acts as an agent to provide information that supports the development language skills of a person. To enable a text is optimally served, aspects of readability need to be focused before it is presented to the target group. For this purpose, cloze test is a mechanism that could ease teachers or curricular advisor in determining the level of text readability and its suitability. Cloze test is identified to have high levels of validity and reliability, especially for the stated purpose. Thus, this study was conducted to explore the use of the cloze test as an instrument in determining the applicability of an Arabic text and to identify important elements in designing the cloze test. The result found that the Arabic Text Readability Measurement System as an alternative for conventional text readability test.

Readability of Texts: Human Evaluation Versus Computer Index

mcser.org

This paper reports a study which aimed at exploring if there is any difference between the evaluation of EFL expert readers and computer-based evaluation of English text difficulty. 43 participants including university EFL instructors and graduate students read 10 different English passages and completed a Likert-type scale on their perception of the different components of text difficulty. On the other hand, the same 10 English texts were fed into Word Program and Flesch Readability index of the texts were calculated. Then comparisons were made to see if readers' evaluation of texts were the same or different from the calculated ones. Results of the study revealed significant differences between participants' evaluation of text difficulty and the Flesch Readability index of the texts. Findings also indicated that there was no significant difference between EFL instructors and graduate students' evaluation of the text difficulty. The findings of the study imply that while readability formulas are valuable measures for evaluating level of text difficulty, they should be used cautiously. Further research seems necessary to check the validity of the readability formulas and the findings of the present study.

Arabic Readability Research: Current State and Future Directions

Procedia Computer Science, 2018

We provide a perspective on the current state of Arabic readability assessment research with the objective of considering directions and opportunities for future research. We review and assess the current state of progress in Arabic readability assessment, briefly surveying research that has been performed on texts targeted at different populations: readers of Arabic as L1, adult readers in nonacademic settings, and readers of Arabic as L2. Arabic readability assessment has followed trends in other languages, primarily English, but has faced challenges due to the specificities of Arabic and the relative scarcity of available corpora and tools, compared to languages with richer resources. We also consider whether readability assessment for Arabic should take into consideration the special situation of diglossia that exists in all Arab countries.

Mathematical and information models for evaluating readability of texts in Azerbaijani language

El-Cezeri Fen ve Mühendislik Dergisi, 2018

The article describes software that calculates the quantitative characteristics of texts in the Azerbaijani language and determines the readability of texts based on the Flesch reading-ease formula and Flesch-Kincaid grade-level formula adapted for these texts. The problems and ways to solve them, related to the calculation of certain parameters of texts explain by the examples.

TEXT DIFFICULTY: A COMPARISON OF READABILITY FORMULAE AND EXPERTS’ JUDGMENT

Teachers of English, librarians, researchers have been interested in finding the right text for the right reader for many years. In teaching Second Language (L2), text writers often try to fulfil the demand by simplifying the texts for the readers. The emerged term " readability " can be defined as " the ease of reading words and sentences " (Hargis, et al. 1998). The aim of this research was to compare the ways to find the right text for the right reader: traditional readability formulae (Flesch Reading Ease, Flesch-Kincaid Grade Level), Coh-Metrix Second Language (L2) Reading Index, which is a readability formula based on psycholinguistic and cognitive models of reading', and teachers' estimation of grade levels by using leveled texts in a web site. In order to do this, a selection of texts from a corpus of intuitively simplified texts was used (N30). Coh-Metrix Readability levels, Flesch Reading Ease, and Flesch-Kincaid Grade Levels of the texts were calculated via Coh-Metrix Web Tool. Three teachers of English were asked to decide the levels of the texts. When the relationship between Coh-metrix Readability Level, traditional formulae and the texts levels in the website was analysed via SPSS, it was found that there was weak negative correlation between Flesch-Kincaid Grade Level and the texts levels in the website (-,39). Additionally, there was weak negative correlation between the texts levels in the website and Flesch Reading Ease scores (-,41). However, there was moderate negative correlation between Coh-metrix Readability levels and the texts levels in the website (-,63), where Teacher1 and Coh-metrix Readability levels had very strong positive correlation (,95). It was identified that readability formulae can help L2 teachers when they select texts for their students for teaching and assessment purposes.

MLAR: Machine Learning based System for Measuring the Readability of Online Arabic News

Online news became one of the favorite information sources for most of the people nowadays because of its update rate and availability over the 24 hours rather than the traditional newspapers. Measuring the readability of the news articles gives a clear view for both the readers and the writers about how easily people can read and understand these articles. In this paper, we present MLAR, a new machine learning based system for Arabic text readability, and use it in measuring the readability of the Arabic online news articles from different outlets. The proposed system is able to determine the topic of each article efficiently and calculates its readability score level. The results show that readability of the online Arabic news is affected by the nature of its topic and the source outlet. The writing style of news articles in each topic differs from one outlet to another.