The Flesch reading ease score is a metric with which the legibility of texts is judged. It is a readability index, which results in a numeric value between 0 and 100. This index is based on the assumption that short words and short sentences are easier for readers to understand. The difficulty level of a text is described depending on its structure. A high Flesch score indicates good intelligibility and readability. Conversely, the readability index allows the creation of texts that are appropriate to a specific target group. The Flesch reading ease score is also called the Flesh reading ease test, Flesch grade, Flesch formula, Flesch rate, Flesch reading or readability Score.
Rudolf Flesch developed the procedure for determining the legibility of a text during his time at Columbia University in the early forties. In his dissertation, he dealt with statistical methods and applied them to the structural features of the English language. The Flesch formula originally applied only to the English language and, in particular, to pedagogical texts used in educational institutions. The aim was to be able to assess texts so that they could be written for different age groups, educational levels, and cognitive abilities.
The topics of readability and intelligibility were already popular in the US at the beginning of the 20th century. Scientists were trying to figure out how readers capture, process, and understand texts. Thorndike published a frequency dictionary in 1920, which listed the frequency of about 10,000 words for the first time. The more frequently a particular word occurs, the more familiar it is to the readers, so is the assumption. The researchers dealt with different aspects of the written language. In addition to readability and intelligibility, the syntactic structures of language or the objectives of a text were also researched. Rudolf Flesch is one of the pioneers of readability research.
There are now more than 100 different readability formulas and the processing of texts is computer-assisted. Examples are the Flesch-Kincaid formula, the Dale-Chall readability formula or the Viennese factual text formula, all of which are used in different contexts. The findings from this research area are not only used in educational texts or language learning, but also in judging textual content on websites, apps or Web applications. There are usually special tools, word processors, or algorithms that use a version of the Flesch value to evaluate text units. Which aspects are paramount and which calculation methods are used depends on the language as well as on the objectives of the calculation. It is interesting that few readability criteria can represent complex human behaviours when reading texts.
There are many different readability indexes for many languages. There are two examples of the Flesch grade in English and German.
The Flesch reading ease score (FRE) for the English language is calculated as follows:
FRE = 206,835 - 84,6 x WL - 1,015 x SL
As a rule, a text excerpt of approximately 100 words is used and extrapolated. The word length in syllables and the sentence length must first be determined for the extrapolation. If these values are calculated and used as above, a Flesch value between 0 and 100 is obtained. The following subdivisions are made here, which relate exclusively to English:
The Flesch reading score was applied to German in 1978 by Toni Amstad in his dissertation “How understandable are newspapers?” German words are longer on average. For this reason, the word factor had to be recalculated. Otherwise the calculation of the readability is the same as in the English version of the FRE.
Readability index = 180 - SL - WL x 58,5
The results were further differentiated in order to be able to make more precise statements about texts:
The type of text and the target group have a considerable influence on readability. Thus, technical documentation, specialist texts and scientific work are much lower on this scale. This does not mean that they are bad. Rather, certain Flesch grades indicate suitability for specific target groups for whom the text is intended and should be easily readable and understandable.
The Flesch reading ease score is used in modified form not only by many tools for on-page optimization, but probably also by search engines. With regard to a linguistic approach, readability indexes allow the translation of text structures into a simple formula that provides information about the text level. However, to what extent these values are used by search engines is unclear. It is undeniable that the legibility of texts has an impact on the user-friendliness of websites and web applications. Grammar, spelling, and readability are at least indirect content quality signals for Google. Astonishingly, these signals correlate with websites with a high PageRank, as Matt Cutts explains. But he emphasizes that it is difficult to use these signals for different languages, leaving the question as to what the role of readability indexes is for the Google algorithms open. However, there is no doubt that they are signals that are relevant to users because they promote the readability and understandability of texts.