Cognitive Modelling

1. Cognitive Modelling Rebecca Schnittger

2. Exemplar-based theory • “When classifying an item in a category, we compare it to all previous members of all categories. The category to which the item has the highest summed membership is the item’s membership category” (Costello, 2010).

3. A Change from the Traditional • Traditional exemplar-based theory examines the importance of the dimensions as a whole BUT • The importance of the dimensions changes depending on which category you are looking at.

4. A Change from the Traditional (2) • Therefore a single model looking at the importance of the dimensions as a whole is too simplistic. • It is necessary to have a model which examines the importance of the dimensions with reference to the different categories. A B C

5. Single Category Decisions What else will influence decisions? • Individuals will only use information from the single category training set when making a single category decision in the test sets.

7. Deciding on Attention Parameters What was considered? • How often did a symptom appear within a particular category compared to how often it appeared overall? • How often did a symptom occur within a particular disease compared to how many times that disease occurred? • How often did a disease occur compared to how often other diseases occurred?

8. Deciding on Attention Parameters (2) S Values:

9. Did it work? • It is necessary to compare the models predicted membership scores for the test items to the average membership scores given by people during the experiment. • Rescale the data so it’s directly comparable: • formula: (x*20)-10 • Correlation: Looks at the degree of relationship between the predicted scores and the given scores.

10. Did it work? • Sounds fairly good right? BUT A correlation only looks at the degree of relationship – it doesn’t actually consider how similar in value the predicted and given scores are. • For instance two sets of scores may correlate very highly even though one set contains very high numbers and the other set contains very low numbers. • Solution? Graphs are an easy way to visualise similarity.

14. Making decisions about conjunctives?

15. What influences people's decisions when deciding whether a test item is a conjunctive? A • In single category decisions we ignored the information from the training sets relating to the Category A&B. • However when making decisions about conjunctives this information becomes important. B C

16. What influences people's decisions when deciding whether a test item is a conjunctive? • Items and dimensions that were salient during single item decision making are now particularly so. • Include the Category A&B training samples when making a decision • Therefore it is necessary to recalculate the attention parameters for each dimension within each category.

17. Changing the attention parameters • Still base them on: • How often a symptom appeared within a particular category compared to how often it appeared overall. • How often a symptom occurred within a particular disease compared to how many times that disease occurred. • How often did a disease occur compared to how often other diseases occurred. BUT • Include: • The Category A&B training samples • Increase saliency of particular categories

18. New Attention Parameters • S Values: • Attention parameters for conjunctive decisions Vs single-item decisions: • In Category A attention parameters remained unchanged from the original single-category decision attention parameters • In Category B, dimension 1 became less memorable therefore making Dimension 3 the most memorable dimension. • In Category C, the order of dimension precedence remained unchanged although some dimensions became slightly more or less memorable due to increased/decreased saliency.

19. What influences people's decisions when deciding whether a test item is a conjunctive? So far we’ve examined the factors that would necessitate changes to the attention parameters. • But what about other factors influencing the decision making of conjunctives? • Overall people will be slightly less likely to make a positive decision for a conjunctive option as they may believe the test item fits one of the single-item categories better and be cautious about stating it belongs to both (Multiply all conjunctive predictions by K=0.9).

20. What influences people's decisions when deciding whether a test item is a conjunctive? • Overall people will be less likely to make a positive decision about a conjunctive item as few samples of conjunctions were given in the training set. • This effect will be stronger for Categories A&C and B&C than for the Category A&B as these were not present in the training set and may be thought to be less common or not exist (Multiply conjunctive predictions for A&C and B&C by K=0.8, and for A&B by K=0.9).

21. Normalised Sum • membership(x, A&B) = normalised sum (A,B) = (((membership(x,A) + membership(x,B)) – membership(x,A))* membership(x,B))

22. Predicted Vs Actual Scores • Rescale the data so it’s directly comparable: • formula: (x*20)-10 • Correlation: Looks at the degree of relationship between the predicted scores and the given scores.