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"The Flesch–Kincaid" (F–K) reading grade level was developed under contract to the U.S. Navy in 1975 by J. Peter Kincaid and his team. [1] Related U.S. Navy research directed by Kincaid delved into high-tech education (for example, the electronic authoring and delivery of technical information), [2] usefulness of the Flesch–Kincaid readability formula, [3] computer aids for editing tests ...
The automated readability index (ARI) is a readability test for English texts, designed to gauge the understandability of a text. Like the Flesch–Kincaid grade level, Gunning fog index, SMOG index, Fry readability formula, and Coleman–Liau index, it produces an approximate representation of the US grade level needed to comprehend the text.
The Coleman–Liau index is a readability test designed by Meri Coleman and T. L. Liau to gauge the understandability of a text. Like the Flesch–Kincaid Grade Level, Gunning fog index, SMOG index, and Automated Readability Index, its output approximates the U.S. grade level thought necessary to comprehend the text.
You should not judge your Wikipedia article by applying a readability formula to the whole Wikipedia article. A "good" score can be a bad article, and vice versa. Also, the average for the whole article is less important than whether each reader can understand the bits they actually want to read.
The formula was inspired by Rudolf Flesch's Flesch–Kincaid readability test which used word-length to determine how difficult a word was for readers to understand. [1] Edgar Dale and Jeanne Chall instead used a list of 769 words that 80% of fourth-grade students were familiar with, such as "no", "yes", and other such very basic words to ...
Readability is the ease with which a reader can understand a written text.The concept exists in both natural language and programming languages though in different forms. In natural language, the readability of text depends on its content (the complexity of its vocabulary and syntax) and its presentation (such as typographic aspects that affect legibility, like font size, line height ...
In this system, reading text is classified according to various parameters, such as word count, number of different words, number of high-frequency words, sentence length, sentence complexity, word repetitions, illustration support, etc. While classification is guided by these parameters, syllable type, an important consideration in beginning ...
Linsear Write is a readability metric for English text, purportedly developed for the United States Air Force to help them calculate the readability of their technical manuals. [1] It is one of many such readability metrics, but is specifically designed to calculate the United States grade level of a text sample based on sentence length and the ...