An Investigation into Online Content’s Readability in Light of a Brain-Based Model: A Case from the Sultanate of Oman

In the context of the rapid dissemination of information, scaffolding the readability of online content is critical. This study introduces the brainling model as a novel approach to measuring readability, which heeds readers’ cognition, senses, emotions, and cultural background in conjunction with language. To achieve the aims, two texts covering a general topic were selected, both possessing the same readability level according to the Flesch Reading Ease scale. However, one of the texts was modified in accordance with the brainling components (i.e., cogling, emoling, sensoling, and cultuling). Following each reading text, five multiple-choice comprehension questions, a ۱۰-‎item Likert scale for ‎readability, and a scale for the text’s difficulty level scale were designed. The Google Form was used to collect responses from ۲۰۹ individuals with intermediate language ‎proficiency at an educational institution in Oman. ‎ After verifying ‎the reliability and validity of the questions and scales, significantly higher mean scores ‎were ‎observed for the readability scale components of clarity and engagement in the brainling-based ‎‎modified text, compared to the unmodified text. Moreover, ‎the results obtained from the text difficulty scale, readers rated the brainling-based text as easier to comprehend. Furthermore, based on the reading comprehension test, participants achieved higher scores when reading the brainling-based text. These findings demonstrate that modifying a text based on the brainling model, which integrates both brain and linguistic structures, significantly enhances clarity, engagement, text difficulty, and reading comprehension scores. Adopting the brainling approach can be a solution for fostering mutual ‎understanding and collaboration ‎among culturally diverse members and alleviating challenges such as misunderstanding, that may ‎hinder ‎goal achievement.

کلیدواژه ها:

Language comprehension ، Text difficulty ، Readability ، Online content ، Brainling model