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To determine the difficulty of text, readability formulas can be used. The research was made to find readability formula for Latvian. Readability formulas for English were used as guidelines. The novelty was the use of eye movement tracking during reading to obtain quantitative data that lead to readability formula. Eye fixation durations were gath...
Contexts in source publication
Context 1
... are readability formulas. Some readability formulas for English are given in Table 1. ...
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... to this the correlation was seen when Spache readability formula was used (see Fig. 1(b)) (R = 0.74). For other formulas given in Table 1 no strict correlation between values of formulas and average fixation duration values were observed. Literature shows that Spache formula was developed for primary and elementary school 15 , but Flesch-Kincaid formula was developed for adults above grade 6 9 . ...
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... parameter to track is the success for the reader to understand and remember the text. To derive readability formulas for English (see Table 1) the parameter to test were answers of readers after texts were read -they, for example, filled close test. In this case it would mean that the track of answers of readers have to be made. ...
Citations
... Different eye movement recording systems have been developed over the last twenty years, thereby rendering the collection of quality recording a more viable proposition [65]. Therefore, eye-tracking and its implications have been employed in multiple linguistics and psycholinguistics studies to identify the text spans that attract or deter eye movements [40], such as [14,39,40,[65][66][67][68]. ...
... Table 3 shows the selected eye-tracking features and their descriptions as per [78]. We selected these features based on their indications in reading, as mentioned in the background section and based on several previous studies [8,12,14,40,63,68]. Table 3. Used eye-tracking features for each interest area (IA). ...
Using physiological data helps to identify the cognitive processing in the human brain. One method of obtaining these behavioral signals is by using eye-tracking technology. Previous cognitive psychology literature shows that readable and difficult-to-read texts are associated with certain eye movement patterns, which has recently encouraged researchers to use these patterns for readability assessment tasks. However, although it seems promising, this research direction has not been explored adequately, particularly for Arabic. The Arabic language is defined by its own rules and has its own characteristics and challenges. There is still a clear gap in determining the potential of using eye-tracking measures to improve Arabic text. Motivated by this, we present a pilot study to explore the extent to which eye-tracking measures enhance Arabic text readability. We collected the eye movements of 41 participants while reading Arabic texts to provide real-time processing of the text; these data were further analyzed and used to build several readability prediction models using different regression algorithms. The findings show an improvement in the readability prediction task, which requires further investigation. To the best of our knowledge, this work is the first study to explore the relationship between Arabic readability and eye movement patterns.
... Moreover, with machine-learning developments, non-traditional texts, like those found in many web sites, can be categorized for greater accessibility. Some of these advances concern even observing eye tracking while reading [16] [19]. For Italian, the work by Dell'Orletta and colleagues [17] aims at automatically assessing the readability of newspaper texts with the specific task of text simplification, not for specifically analyzing and studying literary texts and their statistics, as I do in this paper. ...
... The research was done to obtain a readability formula for primary school texts in Latvian by using eye tracking. It was found that average eye fixation durations of the 3 rd grade readers for specific texts correlate with Spache readability formula [5] thus giving assurance that Spache formula can be used also for Latvian (a detailed report of this research is in the review process [6]). Yet, it was convincing that the readability formula as a single tool is not enough precise to determine the difficulty of texts, to characterize the texts and readers. ...
Statistics of languages are calculated by counting characters, words, sentences, word rankings. Some of these random variables are also the main “ingredients” of classical readability formulae. Revisiting the readability formula of Italian, known as GULPEASE, shows that of the two terms that determine the readability index G – the semantic index G_C, proportional to the number of characters per word, and the syntactic index G_F, proportional to the reciprocal of the number of words per sentence −, G_F is dominant because G_C is, in practice, constant for any author throughout seven centuries of Italian Literature. Each author can modulate the length of sentences more freely than he can do with the length of words, and in different ways from author to author. For any author, any couple of text variables can be modelled by a linear relationship y=mx, but with different slope m from author to author, except for the relationship between characters and words, which is unique for all. The most important relationship found in the paper is, in author’s opinion, that between the short−term memory capacity, described by Miller’s “7∓2 law”, and the word interval, a new random variable defined as the average number of words between two successive punctuation marks. The word interval can be converted into a time interval through the average reading speed. The word interval is spread in the same of Miller’s law, and the time interval is spread in the same range of short−term memory response times. The connection between the word interval (and time interval) and short−term memory appears, at least empirically, justified and natural, and should further investigated. Technical and scientific writings (papers, essays etc.) ask more to their readers. A preliminary investigation of these texts shows clear differences: words are on the average longer, the readability index G is lower, word and time intervals are longer. Future work done on ancient languages, such as Greek or Latin, could bring us a flavor of the short term−memory features of these ancient readers.
