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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 ...
If the percentage of difficult words is above 5%, then add 3.6365 to the raw score to get the adjusted score, otherwise the adjusted score is equal to the raw score. Difficult words are all words that are not on the word list, but it has to be considered that the word list contains the basic forms of e.g. verbs and nouns.
The number of words per sentence and the percentage of unfamiliar words determine the reading age. The original formula was: Grade Level = ( 0.141 × Average sentence length ) + ( 0.086 × Percentage of unique unfamiliar words ) + 0.839 {\displaystyle {\mbox{Grade Level}}=\left(0.141\times {\mbox{Average sentence length}}\right)+\left(0.086 ...
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.
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.
There are dozens of two-letter words that can be used interchangeably with words already on the board. By creating new words and linking them with existing words you can end up with a very high score.
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 ...
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