1 Cognitive Psychology C81COG 2. Cognitive Processes In Word Recognition & Reading Dr Jonathan Stirk

2 Some background reading Chapter 2 – Underwood, G & Batt, V (1996). Reading and understanding. Blackwell: Cambridge, USA.

3 Overview & Questions How do we recognise visually presented words? – BOAT vs. BORT Some words are recognised more easily than others – Some sources of difficulty Word recognition by word detectors – A theory of word recognition Do we recognise whole words, or their components? – Words and morphemes Word frequency and context as examples of difficulty – How do the theories provide explanations?

4 Word length – Longer words take longer to recognise Morphemic complexity – The more morphemes in a word, the more difficult it will be to recognise the word Word frequency – Commonly used words are recognised more easily than infrequent words Context of presentation – Predictable words are recognised more easily than those in neutral or incongruent contexts Orthographic irregularity – Words which obey the spelling-to-sound rules of the language are easier to recognise (SHIP SHOE SHARE vs. COVE, LOVE) Recognising Words (Some Causes of Recognition Difficulty)

5 Treismans (1960) Model of Attention (Also Formal Model of Word Recognition) We have an internal store of known words – LEXICON Treismans model accounts for frequency and sentence context effects Word detectors are dictionary units in her model B CA

6 Mortons (1969, 1979) logogen' System LOGOGENS as word detectors c.f. Treisman's dictionary units Each logogen has an activation threshold which needs to be met before it fires Parallel model

7 An analogy of Logogen model! You can think of a logogen as a collector of evidence When enough evidence is collected (i.e. the strength of the hammer hitting the bell!) then the threshold is reached, the logogen fires and the word is recognised Activation Threshold

8 Words and Morphemes (What's in Your Mental Dictionary?) Line1 free morpheme Lines1 free morpheme + 1 bound morpheme Underline2 free morphemes(compound word) Base + s"inflectional" morpheme added Base + ment"derivational" morphemes Wait + ing added

9 Evidence for the Use of Morphemes in Word Recognition Taft & Forster (1975) - lexical decision task "Is the following letter string a word or not?" Tible Cat Negative responses are slower for certain kinds of non-words:

10 Evidence for the Use of Morphemes in Word Recognition E1 pertoire < juvenate real word stem which does not exist as free morphemes (bound stem) E2 bescue < bevive non-words formed as below REvive becomes BEvive (vive is a real stem) REscue becomes BEscue (scue does not exist as a real stem- pseudostem) Prefix (meaning to repeat) Non-Prefix (illegal prefix) Inappropriate but possible/legitimate prefix

Affix stripping (Taft, 1981) 11 From Underwood & Batt p.65

12 Frequency Effects in Word Recognition Common, high-frequency words (e.g. RAT) are recognised more easily than uncommon, low- frequency words with the same number of letters (e.g. GNU) 1. The girl noticed the rat run across the playground 2. The girl noticed the gnu run across the playground

13 Frequency Effects in Word Recognition For words presented against noisy backgrounds, recognition accuracy is best for high frequency words Faster responses are given to high frequency words in tasks involving –Lexical decisions task (is this a word or not?) –Naming task –Category decision task (e.g. Does the word name a piece of furniture?) CAT, FEET, CHAIR, COMA, TABLE

14 Models of the Frequency Effect (Why Are Frequent Words Easier To Recognise?) Threshold Models (e.g. Treisman, Morton) Treisman's "dictionary units" have individual thresholds for activation Mortons logogens do too High frequency words have lower thresholds, and therefore require less stimulus information before the word detector is activated

– High frequency words have a lower threshold for firing –E.g. cat vs. cot cat [kæt] cot [kot] Low freq takes longer Thanks to Julie Simner (Edinburgh) for this analogy

An alternative model of word recognition 16 Access Files (like card file system in a library) Visual code Auditory code

17 Models of the Frequency Effect Search Models [e.g. Taft, Forster (autonomous serial search model] Recognising words is a matter of searching through our word memories, looking for a match between words we know and the word newly presented On the basis of probability, we first search frequently used word memories

18 Context helps word recognition Study: TULVING & GOLD (1963) Subjects read an incomplete sentence e.g "The skiers were buried alive by the sudden __________" and then attempt to recognise a single word,. e.g avalanche (relevant context) or inflation (misleading context)

19 Tulving & Gold (1963) Q. Will increasing the amount of semantically related information that is available before the target word is presented affect the minimum amount of time needed to identify the word? A target word is presented at varying exposure durations, starting too brief for recognition, and increasing until the word is recognised They measured the stimulus exposure necessary for recognition with relevant context and with misleading context The amount of context (relevant or misleading) also varied (up to 8 words of context)

20 Relevant context helps recognition Misleading context makes recognition difficult Exposure duration necessary for recognition of the word (msec) Amount of context provided (no. of words) 08 Tulving & Gold (1963)

21 Models of the Context Effect Threshold models – The cognitive component of the logogen model explains how sentence context can affect recognition – The semantic information from the sentence partially activates logogens, lowering their threshold – This decreases the amount of information needed from the word itself to fire the logogen