1. From Prototypes to Abstract Ideas A review of On The Genesis of Abstract Ideas by MI Posner and SW Keele Siyi Deng

2. Concept and Categorization ► What cognitive events happen when you think about a chair? ► How is the concept of chair represented in the cognitive system? ► Surely, a seat at a formal dining table is “ chair", but what about a recliner, a stool, a couch, or a tree stump?

3. Categorization and Concepts ► Why do we need categories? Because they make our life easier. (Coding of experience and Licensing of inferences.) ► Categorization and Concepts are inseparable, concept is a mental representation of a category. ► How we think and what we can learn is largely determined by how we represent concepts.

4. Similarity ► It seems that our rule of categorization is to maximize within-category similarity while minimize between-category similarity. ► One traditional approach to measure similarity is to assign objects to locations in a multidimensional space thus the metric distance between any two of them could be measured in the Geometric standard.

5. Similarity An example of a two-dimensional space for representing the similarity relations among some common fruits and the category of fruit itself.

6. Abstract Ideas ► Posner and Keele ’ s designed a series of experiments to study how does general information about individual objects is abstracted and what is stored during the learning process.

7. Abstract Ideas Hypotheses about abstraction: I. The prototype is abstracted and it alone is stored) II. The abstracted prototype is stored in addition to the individual instances. III. Prototype only enjoy a higher recognition level than individual instances. IV. No abstraction takes place during learning.

8. The Dot Pattern Prototype Test ► The method developed by Posner and Keele to investigate the origin and storage of concept representations. ► Using patterns of dots, rather than well- known concepts (such as “ chair ” ). ► Use statistical distortion rules to get patterns varied around a prototype. ► Benefit of dots: systematic and controlled.

9. The Dot Pattern Prototype Test ► Nine Dots within a 30 x 30 matrix to form prototype patterns of a triangle, letter M and letter F, as well as a random pattern. ► For each of the four prototypes, six distortions were constructed at each of three different levels (1, 5 and 7.7 bits/dot).

10. Example Pattern of Dots

11. Posner and Keele ’ s Experiments ► Experiment I In the first step, 3 distorted versions (ranging from small distortion to large distortion) of a same prototype were presented to 3 different groups of participants, this is the learning process. After learning, in the second step, they were asked to classify some more major distortions, together with a control group (no learning).

12. Experiment I ► Results: In the first step, Level 1 Group (which learn the small distortion version) performs better than Level 5 Group (large distortion version). However, during the second step, Group 5 are significantly better than Group 1.

13. Posner and Keele ’ s Experiments ► Experiment II The purpose of this Exp. Is to eliminate some potential problems that might affect performance in Exp. I. In Exp. II, the learning procedure was similar to that of Exp. I. Then subjects were asked to classify patterns into one of the four categories they had learned during the first step.

14. Experiment II ► Results: Once again, Ss who had been trained with the high variability patterns did better in the second step.

15. Conclusion of Exp I, II ► The result of the first 2 Exp. favors the hypnoses that it is not the prototype alone that being stored. ► It also indicates that Ss are learning something about the individual patterns.

16. Posner and Keele ’ s Experiments ► Experiment III The purpose of this Exp. is to judge directly whether Ss are also learning information about the prototype. In Exp. III, all Ss learned the large distortion version. They were then asked to classify the following patterns: old distortion they just learned, the prototype of the old distortion, and control patterns at varying distances from the old patterns.

17. Experiment III ► Results: Old distortions, schema, and new Level 5 patterns have nearly identical mean distances from the memorized patterns, but the old distortions and schema are better recognized than the Level 5s and are not different from each other.

18. General Conclusions ► The prototype (schema) is more easily classified than other new patterns which are also within the learned category. ► The Exp. I and II suggests against the hypothesis that only abstracted prototype is stored. Instead, variability shows its importance in the training process.

19. Time of Abstraction ► When does the abstraction take place? ► During the learning task? ► When the Schema patter is first shown?

20. What is Abstracted ► Mental image? ► Verbal description?

21. Thanks! Q & A