1. Lecture 14 – Problem Solving and Expertise 1 Three points for this lecture: 1.Knowledge influences perception. 2.Knowledge can influence perception because learning speeds up access to LTM. 3.Access to LTM is speeded up by development of a virtual short term memory, called Long Term Working Memory (LT-WM)

2. Lecture 14 – Problem Solving and Expertise 2 Point #1  Knowledge influences perception.  Knowledge can influence perception because learning speeds up access to LTM.  Access to LTM is speeded up by development of a virtual short term memory, called Long Term Working Memory (LT- WM

3. Lecture 14 – Problem Solving and Expertise 3 Knowledge influences perception Biederman, Rabinowitz, Glass, & Stacy (1974) Subjects better at identifying briefly-presented objects that were expected in a context. It’s easier to see things you expect to see. All of us use expectancies in seeing the world. But what do we expect to see?

4. Lecture 14 – Problem Solving and Expertise 4 What do we expect to see? Chase & Simon (1972) Compared chess master, intermediate and novice players. Subjects viewed chessboard in midgame, then reconstructed it from memory (0 delay). Grandmaster saw and remembered more than the other two.

5. Lecture 14 – Problem Solving and Expertise 5 How did the Grandmaster’s knowledge help him? The GM looked for patterns in the display. Two pieces classed as in the same chunk if set down less than 2 seconds apart. GM had more and larger chunks. Pieces put down in succession by GM shared more relations (e.g., type, colour, defence).

6. Lecture 14 – Problem Solving and Expertise 6 How do patterns help an expert? Chi, Feltovich, & Glaser (1981) Compared 1 st yr. undergrads (novices) and senior Ph.D. students in physics (experts). Subjects grouped physics problems. Novices classified on basis of surface; experts used underlying structure (e.g., Newton’s Second Law), ignoring surface differences.

7. Lecture 14 – Problem Solving and Expertise 7 Review We all use expectancies in ordinary perception. It’s easier to see things we expect to see (Biederman). Experts show a pronounced form of this effect – they develop precise expectations for their skill domain. Those expectations allow experts to recover the underlying structure of their domain.

8. Lecture 14 – Problem Solving and Expertise 8 Point #2  Knowledge influences perception.  Knowledge can influence perception because learning speeds up access to LTM.  Access to LTM is speeded up by development of a virtual short term memory, called Long Term Working Memory (LT-WM

9. Lecture 14 – Problem Solving and Expertise 9 How can knowledge influence perception? Perception happens fast. How can we retrieve knowledge fast enough to influence rapid perception? Two theories: 1.Superior performance based on innate ability. 2. Superior performance based on learning.

10. Lecture 14 – Problem Solving and Expertise 10 Superior performance based on talent This view has three implications: 1. People with basic training should be capable of excellent performance because they have talent. 2. Aptitude tests should be good predictors of performance even after years of experience. 3. Should be an upper limit to how good a person’s performance can be (specified by their talent).

11. Lecture 14 – Problem Solving and Expertise 11 Three implications of the talent hypothesis All three claims are false. 1. With only basic training, no-one does well. 2. Aptitude tests are poor predictors of performance after several years of experience. 3. If there is an upper limit to performance, we haven’t found it yet. (Consider Olympic athletes, ‘difficult’ violin pieces, of 100 years ago.)

12. Lecture 14 – Problem Solving and Expertise 12 Superior performance based on learning Some examples of superior performance: Blindfolded chess master, George Koltanowski could play 30 opponents at once, winning most games, drawing the others. (Koltanowski, 1985) An expert waiter, J.C., rapidly takes orders from up to 20 customers at one table. Never mixes them up. Always delivers right meal to each person. (Ericsson & Polson, 1988).

13. Lecture 14 – Problem Solving and Expertise 13 Superior performance based on learning How do these experts do this? In playing chess or taking orders, you need Fast access to a memory store. Large capacity in that memory store. But humans have two stores – one for fast access (STM) and one for large capacity (LTM).

14. Lecture 14 – Problem Solving and Expertise 14 Point #3  Knowledge influences perception.  Knowledge can influence perception because learning speeds up access to LTM.  Access to LTM is speeded up by development of a virtual short term memory, called Long Term Working Memory (LT-WM)

15. Lecture 14 – Problem Solving and Expertise 15 Virtual short-term memory Ericsson & Kintsch (1995) argue that experts have a virtual short-term memory. E & K call it, Long Term Working Memory (LT-WM). Through experience, you set up a virtual STM inside LTM – a rapid access store without the capacity limit. Based on Chase & Ericsson (1982).

16. Lecture 14 – Problem Solving and Expertise 16 Chase & Ericsson (1982) Used the digit-span task Subject hears a sequence of digits, like 7 – 4 – 9 – 5 – 1 – 3, and repeats them back. Score = number repeated back without error. Subject S.F., a long distance runner, had a digit span of over 80 digits.

17. Lecture 14 – Problem Solving and Expertise 17 How did S.F. do that? S.F. began with groups of four or five numbers, which he coded as times for distances (e.g., 3 – 5 – 9 – 6 = 3 min. 59.6 seconds, for 1 mile race). He then grouped the groups into supergroups, then grouped the supergroups, producing a hierarchical network structure. At the top of the hierarchy was a ‘node.’ That node went into STM.

18. Lecture 14 – Problem Solving and Expertise 18 3 5 6 9 4 2 8 1 7 6 1 3 5 2 9 8 6 1 5 3 4 7 3 6 8 5 2 9 1 4 7 3 2 Top-level node

19. Lecture 14 – Problem Solving and Expertise 19 Subject S.F. (Chase & Ericsson, 1982) At the end of a long session of hearing, storing, and recalling lists of digits, he could accurately retrieve all of the lists. C & E could specify a location in the network for a given list, and S.F. could tell them the digits in that location in the network in his memory. He must have been capable of very rapid storage in a long-term store.

20. Lecture 14 – Problem Solving and Expertise 20 Extending the model to expertise in general Ericsson & Kintsch expanded Chase & Ericsson’s idea into a model of general expert behaviour: Network retrieval structures are rapidly created and stored by experts. With top-level node in STM, the whole structure becomes rapidly available.

21. Lecture 14 – Problem Solving and Expertise 21 Review Information is stored in LTM. Each item is associated with a cue. All cues are related in a hierarchical retrieval structure, under a top-level node. With top-level node in STM, any item under node can be retrieved. Fast access + large capacity = LT-WM