Reasoning. Lindsay Anderson. The Papers. “The probabilistic approach to human reasoning”- Oaksford , M., & Chater , N. “Two kinds of Reasoning” – Rips, L. J. “Deductive Reasoning” – Johnson-Laird, P. N. What is reasoning?.
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“The probabilistic approach to human reasoning”- Oaksford, M., & Chater, N.
“Two kinds of Reasoning” – Rips, L. J.
“Deductive Reasoning” – Johnson-Laird, P. N.
Deduction: general -> specific
Induction: specific -> general
People have successful reasoning in everyday life, but they perform poorly on laboratory reasoning tasks
- argue that systematic deviations from logic represent unavoidable performance errors
- working memory limitations restrict reasoning ability
According to both: people rational in principle but err in practice
To resolve conflict, Other theorists propose that there are 2 types of rationality:
Still, how is everyday success explained?
Allow “strengthening of antecedent”
-“if something is a bird it flys”
-If tweety is a bird, then can infer that tweety flies
-Strengthening antecedent means that when given further info, like “tweety is an ostrich” you still infer that “tweey flies”
-Do this in standard logic because ostrich still a bird
-This new info about ostrich should defeat the previous conclusion that tweety flies
-If tweety a bird, then probability of flying is high
-If tweety an ostrich, probability of flying is 0
Applying probability approach to these areas explains ppl’s lab performance as rational attempt to make sense of the lab tasks by using strategies adapted for coping with everyday uncertainty
- In terms of deductive correctness
- In terms of inductive strength
- Deductively correct- max value on continuum
- Strong argument- high value on continuum
Implies only assess argument in terms of strength
But, maybe other ways people assess arguments (e.g., plausibility)?
Participantsevaluated arguments in terms of correctness and strength
DeductionCondition: valid/not valid, then rated condifence
InductionCondition: strong/not strong, then rated degree of strength
Varied, wording of instructions to check whether results depended on wording (no effect)
For unitary to be correct, increases in deductive correctness should mimic increases in inductive strength (b/c reflecting differences on same underlying one-dimensional scale)
As can see, this is not happening
3 Principle Approaches to Deductive Performance:
1. Deduction as process based on Factual Knowledge
* 2. Deduction as formal, syntactic process
* 3. Deduction as semantic process based on mental models
Deduction controversial: may rely on 1 of the above, or some combination
Problem: This theory does not explain why we can reason about the unknown
Rip’s Theory (& others)- proposes reasoners extract logical forms of premises and use rules to derive conclusions
- Rules for sentential connectives like “if” and “or” and for quantifiers like “all” and “some”
- Based on natural deduction, so have rules for introducing and eliminating sentential connectives
With rules, complications arise:
Ex: introducing “And”
Therefore A and B
Therefore A and (A and B)
Therefore A and [A and (A and B)]
As you can see, this gets very messy
- its structure and content capture what is common about all the ways the possibility can occur
(in the context of these phenomena, author discusses evidence for/against 3 main theories so you can arrive at your own conclusion)