Word Recognition and Processing

Word Recognition

• Tasks: Eye-tracking measures reading time (longer = harder recognition); naming tasks measure time from word appearance to spoken response; lexical decision tasks involve identifying words from letter strings.
• Semantic Priming: Faster responses when a semantically related word precedes the target word.
• Category Decision Tasks: Deciding if a word belongs to a category.
• Factors Affecting Recognition: Word length (shorter words are recognised faster); word frequency (more common words recognised faster); presentation context (words relevant to context recognised faster); orthographic neighbourhood effects (similar spelling = faster recognition); phonological neighbourhood effects (similar sounds = faster recognition).
• Tulving and Gold (1963): Predictable (context-relevant) words recognised faster than unpredictable (context-irrelevant) words .
• Models: Logogen model (input activates a word unit above a threshold), Interactive Activation Model (network with layers, bottom-up and top-down processing), Dual Route Model (direct and indirect pathways from visual input to meaning [familiar/unfamiliar words]).
• Word Superiority Effect: Letters recognised faster within words than in isolation.
• Transposed Letter Effect: Readers may overlook typos in the middle of a word.
• Reading Difficulties: Surface dyslexia (problems with direct route, irregular words); phonological dyslexia (problems with indirect route, unfamiliar words).

Sentence Processing

• Concepts: Lexicon (word meanings); syntax (word arrangement); parsing (combining lexicon and syntax); pragmatics (contextual interpretation).
• Ambiguity: Global ambiguity (multiple possible meanings in a sentence); garden path (a sentence that initially suggests one meaning but later reveals another).
• Models: Minimal attachment (preference for simplest sentence structure); late closure (attach new information to the most recent clause); constraint satisfaction (multiple sources of information to resolve ambiguity).
• Figurative Language: Metaphors (comparing things), idioms (fixed phrases with special meanings), irony (contradiction between expectations and outcome).

Discourse Processing

• Concept: Understanding and integrating larger amounts of text or speech.
• Inferences: Filling in gaps using prior knowledge. Types of inferences include logical, bridging, and elaborative inferences.
• Theories: Constructionist approach (readers create mental models & make automatic inferences); minimalist approach (inferences depend on reader's intentions).
• Calvo et al. (2006): Anticipating future events influences inference-making.
• Schemas (Schank & Abelson, 1977): Frames (knowledge about items/objects); scripts (sequences of actions).
• Event Indexing: Representation of events (protagonist, temporality, causality, spatiality, intentionality).
• Experimental Representations: Reading activates sensorimotor experiences.

Mental Representations in Discourse Processing

• Schemas: Frameworks of general knowledge stored in LTM, affecting comprehension.
• Frames: Represent knowledge about objects.
• Scripts: Represent sequences of events associated with experiences or activities.
• Bransford & Johnson (1972): Schemas aid comprehension and recall, especially with context.
• Event indexing (Zwaan & Radvansky): Mental representation of events based on protagonist, temporality, causality, spatiality, intentionality.
• Claus & Kelter (2006): Mismatched event indexes affect comprehension and memory.
• Experimental representations (Barsalou, 2008): Reading activates sensorimotor experiences from real life.