Lecture 10:

Lecture 10:

1. Semantic networks = network of unitary nodes with labelled links, good for hierarchies - properties inherited, can predict sentence verification times (more links=longer) but also depends on familiarity

2. Problem with definitions = not as sharp as needed, need sufficient and necessary conditions which are rarely found

3. Meaning influence sentence comprehension? Integrate word meaning and world knowledge at the same time

4. Schema = integrated knowledge structure for things, captures common aspects of life, allowing us to form expectations/ draw inferences

5. Types of inferences = logical - based on meaning of the word, bridging - establishing coherence between current and preceeding text, elaborative - use of world knowledge

6. Peterson and Peterson - duration of STM, recall 3 nonsense syllables in intervals of 3s, limited duration no longer than 15/18s

7. Baddeley et al - word length effect, word span immediately recalled is greater for short than long words, both visually and auditory presented words

8. Eysenck and Eysenck - distinctiveness - used nouns with irregular pronounciation, in condition when word was said in an irregular way (distinctive memory trace) recognition was good

9. Ebbinghaus - learned list of nonsense sylablles, relearned 21mins - 31 days later, forgetting = rapid in first hour, then slowed

10. Talarico and Rubin - flashbulb memories, compared consistency of memories norm/9/11 - 12 weeks, no more consistency or lack of change but felt more accurate

11. Geiselman et al - compared CI to standard interview, viewed film of crime, questioned 48 hours later, no difference in no. of errors but 50% more recall of accurate info