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Complex Cognition (Fach) / Task 4 (Lektion)

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• Inductive Reasoning Inductive Strength P  Forming generalisations (which may be probable but not certain) from examples (specific -> general) P  Conclusion can contain new information P  Inductive strength – argument has strength if it is improbable (not impossible) for the premises to be true & the conclusion to be false §  Probable truth
• Types of Inductive Reasoning: Analogical Reasoning P  Apply relationship found to determine a solution P  Verbal (“A is to B what C is to ___) & pictorial analogies P  Series & matrix completion Ease of reasoning depends on complexity of the problem
• Types of Inductive Reasoning: Hypothesis testing P  2-4-6 task (Wason): peeps are given a bunch of numbers and they have to determine the rule only by offering examples, not by asking direct questions about the rule P  People tend to first develop a general idea of the rule to then construct examples P  Confirmation bias: people try to confirm their rule is true rather than trying to test/ falsify it (= fallacy of affirming the consequent) g better off testing it with counterexamples of the assumed rule
• Deductive Reasoning Deductive Validity P  General g specific P  Conclusion represents info that was already implicit in the premises (no new info added) P  Allows us to draw conclusions that are definitely valid, assuming that premises are true P  Deductive validity: argument valid only if it is impossible for the premises to be true and the conclusion to be false §  When premises are true and you reason according to logical principles, your conclusion cannot be wrong
• Propositional Reasoning (Types of deductive Reasoning) P  Proposition – claim that can be either true or false P  Compound propositions – more complicated propositions formed by using logical connectives P  Modus ponen: if A, then B and A is given then we can validly infer B P  Modus tollens: if A then B and we know B is false we know A is as well P  Denying the antecedent: fallacy in which the info that the antecedent isn’t true leads to the conclusion that the consequence isn’t either (B is true, but A doesn’t need to be true) P  Affirming the consequent: fallacy in which the consequence is thought to be true because the antecedent is said to be true ( B is thought to be true, because A is true) P  Wason’s selection task: must affirm modus ponens & tollens Matching bias: tendency to select those cards explicitly mentioned in the rule
• Syllogistic Reasoning (Types of deductive reasoning) P  Categorical syllogism: 3 premises that deal with classes of entities (include quantifiers) P  In a logical argument, premises are propositions about which arguments are made Belief bias : tendency to accept invalid conclusions that are believable rather than believe valid conclusions that are unbelievable
• Formal Reasoning All premises are suppliedProblems are self-containedOne correct answerEstablished methods of inference that apply to the problem often existIt is unambiguous when the problem is solvedContent of the problem is often limited, academic interestProblems are solved for their own sake
• Everday/Informal Reasoning Some premises are implicit, some aren’t supplied at allNot self-containedSeveral possible answers which vary in qualityEstablished procedures for solving the problem rarely existOften unclear whether current “best” solution is good enoughContent typically has potential personal relevanceProblems are often solved as a means of achieving other goals
• Effects of premise phrasing g  the way information is stated can make a reasoning task easier or harder §  More errors when premises have negatives in them §  Quantifiers such as “all” or “none” are easier to deal with than “some” §  Syntactically complex statements require more processing resources that are then missing for other reasoning processes
• Alteration of premise meaning g  people often misinterpret premises & fail to think of all possible meanings §  Everyday understanding of words such as some, all & if-then are so powerful that people have difficulties ignoring the fact that in reasoning tasks they’re defined slightly different
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• Content effect g  people reasoning with exactly the same kind of premises will perform differently depending on what the premises are about (e.g. four-card task/ Wason’s selection task with drinking vs. age instead of numbers vs. letters) §  Memory-cueing explanation – own experience lets one think of combinations
• Believability effect g  : people are likely to judge as valid any conclusion that reinforces their initial assumption, regardless of whether the conclusion follows from the premises
• Componential Aproach (Sternberg) P  Study reasoning by analysing a task into its component cognitive processes (mental subroutines) §  Reasoning as just another mental activity like problem solving & decision making P  Each component associated with several parameters (e.g. probability of usage, speed, difficulty…) P  Performance components – individual cognitive processes (encode g recognise & retrieve from memory g infer relationship g apply relationship) P  Meta-components – executive processes used in planning & monitoring (e.g. select which performance components will be used) P  Knowledge acquisition components – used whenever we acquire new information (e.g. elective encoding, combination & comparison) P  Common source of error: inability to use certain performance or meta-components effectively
• Rules/Heuristics Approach P  Treat reasoning as a special mental process g rely on special-purpose mental rules (like grammar) for inferences P  Cheng: people interpret problems in terms of what they are about and based on that use different schemata P  Braine: people can & do use the same set of abstract rules in all situations P  Cosmides: Social contract theory – evolutionary adaptive mechanism for reasoning g especially good at tasks when content is construed in terms of social costs & benefits P  Common source of error: failure to interpret a problem in terms of the appropriate rules Explains content effects
• Mental Models Approach (Johnson-Laird) g  Use deductive reasoning that may be affected by real-world knowledge g  Reasoning = constructing models to depict premises (like mental images when you read) g  Effective reasoning = assess first conclusion by attempting to construct an alternative model consistent with premises but not with the hypothesised conclusion g  The more imaginative the process the more likely the reasoner is to generate counterexamples g avoid hasty conclusions g  Deductive reasoning problems requiring the construction of several mental models are harder to solve because of the increasing demands on working memory g  Principle of truth – peeps minimise the load on working memory by tending to construct mental models that represent explicitly only what is true & not what is false g  Common source of error: failure to construct relevant models, failure to assess the implications of all the models found, failure to construct enough models Limitations g  Ignores individual differences & dual systems g  Doesn’t explain which pieces of background knowledge are used
• Heuristic–Analytic Theory (Dual Systems) Evans g  Initially use real-world knowledge that may be affected by deductive reasoning through system 2 g  System 1: heuristic(shortcut) processes (implicit) §  Makes use of task features, goals & background knowledge to construct a single hypothetical possibility/ mental model g  System 2: analytic processes (explicit)(time consuming, effortful) §  May intervene to revise/ replace model §  Likely when instructed to use abstract/ logical thinking, participants are highly intelligent, sufficient time available g  Principles: §  Singularity principle: only a single mental is considered at any given time §  Relevance principle: the most relevant mental model based on prior knowledge & current context is considered §  Satisfying principle: current model is evaluated by system 2 and accepted if adequate (often leads peeps to accept conclusions that could be true but aren’t necessarily) §  Dual Systems Theory more correct than mental model processes Limitations g  Oversimplification to make a distinction between the systems as in implicit vs. explicit g both can be both Says they are various analytical processes but doesn’t elaborate
• Brain ð  Prefrontal cortex (esp. left) may play important role in a person’s ability to integrate relations (= to build mental representations that incorporate multiple propositions/ relationships) ð  Left inferior frontal gyrus (Broca’s area!) g deductive reasoning §  Due to greater involvement of syntactical processing & working memory on deductive reasoning tasks ð  Left dorsolateral prefrontal gyrus g inductive reasoning
• Everyday Consequences of Analytic Thinking g  The willingness to engage in analytical thinking in order to override intuitive gut feelings can predict all sorts of life outcomes §  Less emotional judgements, more individualising but less binding moral values §  More able to evaluate complex trade-offs between self-interest & altruistic concerns (recognise when selfishness pays)
• Religious Belief g  Religious beliefs are just a subset of mental representations focused on superhuman agents, which in turn are a subset of supernatural reflections g  Beliefs are often triggered by inconsistencies in intuitions or by the need to provide other’s a consistent description of one’s intuition §  Lack of specific info about processes increases usage of religion to explain things §  E.g. use religion to explain the way sickness is spread as our intuitive system doesn’t give us the details g  Religious belief emerges through a converging set of intuitive processes (= system 1) g analytic processing (= system 2) can inhibit/ override it to undermine intuitive support of religious belief §  More analytical/ reflective = more sceptical about religion, epistemically suspect (paranormal) concepts g  Modified dual-process perspective – reflections are not parallel to intuitions but triggered & constrained by specific contents of intuitions
• Mortality Salience g  Induced thoughts of death impair analytical reasoning performance just as much as cognitive load would §  Reasoners allocate their executive resources to the suppression of the disturbing thought g impairs performance on syllogisms that require analytic thought g  Paradox: we can consider abstractly the prospect of our own death BECAUSE we can think analytically but the very resources that we use to think analytically are then immediately mobilised to suppress thoughts of death §  SO, we cannot use our executive resources when making decisions in situations that might remind us of our own mortality (e.g. choosing life insurance, arguing about assisted suicide)
• Cross-Cultural Perspectives on explanatory Coexistence P  Piaget: young children gradually abandon supernatural beliefs & instead acquire a more objective, rational, scientific appreciation of cause & effect P  Education & modernisation accelerate various aspects of cognitive development P  Secularisation hypothesis – with more widespread access to formal education & technology a focus on natural explanations will increasingly compete with & displace supernatural explanations §  Natural explanation: appeal to “observable & empirically verifiable phenomena of the physical/ material world” §  Supernatural explanation: appeal to phenomena that “operate outside of/ are distinct from the natural world” P  Prediction: when individuals are confronted with scientific understandings of the world they will integrate scientific explanations with pre-existing supernatural & other kinds of natural (e.g. folk biological) explanations P  Explanatory coexistence – when natural & supernatural explanations are generated to interpret the same events §  Synthetic thinking: loose integration of natural & supernatural frameworks without in-depth consideration of how they might interact §  Target-depending thinking: the 2 explanations are used to account for distinct aspects of a given phenomenon & involves different kinds of causality §  Integrated thinking: explanations become well-coordinated, use both explanations to interpret multiple levels of causality
• Research:How do individuals across diverse cultural backgrounds conceptualise & incorporate natural & supernatural explanations? (fusion of cognitive science & ethnographic research) Method P  Semi-structured interviews with 17 Ni-Vanuatu adults with diverse backgrounds & age P  Vanuatu = Melanesian island nation in the south pacific §  Low levels of industrialisation §  Christianity was only recently introduced §  Education only recently introduced Were asked questions in 3 domains: human origin, illness & death
• Results of the Research Study with religion P  Human origins: no participant provided evidence of explanatory coexistence §  Mostly biblical creationist accounts (Adam & Eve) §  Only one natural account §  Satisfied with one explanation of human origin & didn’t attempt to reconcile these beliefs with other explanations à no conflict thus no explanatory coexistence §  With increasing influence of western education explanatory coexistence might happen in the future P  Death: mostly natural processes as reasons for death and what happens to the body after §  Some target-dependent thinking – supernatural explanation for what happens after death (spirit & soul life) seen as distinct process from cause of death §  Causes of death are much more observable thus more natural explanations P  Illness: explanatory coexistence in 77% of the cases §  Synthetic thinking: generally natural explanations but also said people can get sick from their behaviour & the way they treat others but couldn’t explain how §  Given greater access to info about proximate causes for illness + the influence of Christianity
• Discussion of the research study about religion Death & Illness: people are often unsatisfied with natural explanations of death & illness and seek to understand why these things happen to them or their loved ones which explains why death & illness show more explanatory coexistence

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