Transposed letter effect are letter-position specific when detecting words, so our recognition of words is based on what letters it contains, where the letters are placed within that word and the length of the word itself. Another example is the bayesian reader model created by Norris (2006) which also assumes that the letters in a word are associated with their specific location. Many experiments (for example, Perea and Lupker, 2003) have shown if you use transposed-letter priming, (for example, priming judge with jugde) you will see a priming effect but if the prime is a word where two letters are changed to other
Learning to read vowel-pairs that help to make up words that go beyond the basic level.The faster a child can see that the word "together" is "to-ge-ther", the faster the reader will become a more fluent reader. As children move forward with their reading skills, they learn a great deal about what is really inside a word; the stem, roots, prefixes and suffixes that make up morphemes of the language. By this stage, children already know about the common bound morphemes such as "s" and "ed" because these are attached to many words. Decoding readers become exposed to many types of morphemes such