Missing letter effect

When testing for the missing letter effect, prose passages are used which incorporate a mix of common function words and rare content words. Common function words are words that are used and seen very frequently and regularly in every day texts. These words are connector words for content words and consist of pronouns, articles, prepositions, conjunctions, and auxiliary verbs. Common examples of function words include “the”, “and”, “on”, “of” and “for” and majority of these words are short in length, consisting of usually around 1-4 letters. Because of their frequency and commonness, these words are seldom paid attention to or consciously observed. Content words usually consist of nouns and regular verbs and are more rare than frequent function words. These word types are usually given and paid more attention to. The word “ant” is an example of a rare content word in comparison to a structurally similar looking frequent function word like “and”. == Letter detection tasks ==

Letter detection tasks are ones that are set up and used to prove and measure the missing letter effect. Participants of this task are given prose passages or continuous texts to read and are told to circle every occurrence of a target letter. The missing letter effect is determined when target letters are missed or not circled, and these omissions or letter detection errors occur more when reading frequent function words than in rare content words. Saint-Aubin and Poirier reported from their experiment that there are higher accounts of letter detection omissions of the same word when it the word is presented as a definite article than when the word is a pronoun. ==Hypotheses==

Early Two primary hypotheses tried to explain the missing letter effect: Healy (1994) emphasized identification processes playing a crucial role, almost entirely focusing on word frequency. This hypothesis is primarily referred to as the unitization model and relates to familiar visual configuration. This is termed the "alternative structural hypothesis". Within this hypothesis, rather than putting focus on familiarity as a determinant of this effect, it is “the word’s role in syntactic structure of a sentence” which encompasses common function words “receding into the background…to allow more meaningful content words to be brought into the foreground”. Contemporary A new model called the guidance-organization (GO) model was recently proposed to potentially explain the missing letter effect. It is a combination of the two models proposed by Healy, Koriat, and Greenberg and illuminates the idea that word frequency and function together influence the rate of letter detection errors and omissions. In short, the GO model “is an account of how readers coordinate text elements to achieve on-line integration” and analysis of meaning of the text. Klein and Saint-Aubin proposed the attentional-disengagement model similarly includes aspects of the two earlier models but emphasizes the role of attention in reading and comprehension. In this model, letter detection errors increase, and the magnitude of the missing letter effect increases when there is a rapid attentional disengagement from a word in which a target letter is embedded. The timing of attentional disengagement from a “target-containing” word, essentially produces the missing letter effect where attention disengages faster from functional words than content words. == Influential Factors ==

Age (Development) Developmental change, grade level and generally reading skills increase with age, and all of these factors have some influence on the missing letter effect. The number of letter detection errors and size of the missing letter effect increases with age. The letters at the start and end of words, or the first and last letter of a word, contribute to how people read and recognize words. When readers take part in the letter detection task and are given a connected text to read, there are less letter detection errors of a target letter (for example ‘t’) when it is situated as the initial letter of a word (e.g. tree) compared to when it is embedded into words (e.g. path). Drewnowski and Healy account for this where the initial letter of a word is “more separable from the rest of the word” and is “easier to detect because it can be processed individually”. When letters are transposed in words within a text, the last letter of these words is important in assisting target letter detection. The pace of reading is reduced when letters are transposed in words which allows for more comprehensive processing and provides a reason for why the last letter of a word can be identified more easily. Drewnowski and Healy's (1980) experiments exhibit additional findings of significantly less letter detection errors when target letters embedded in a letter sequence are then embedded into other words than when the letter sequence appears as a “separate function word”. For example, more letter detection errors of the target letter ‘t’ are made when the function word “the” is embedded into the content word “thesis” rather than when “the” appears on its own in a text. == See also ==