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Complex Cognition (Subject) / Task 3 (Lesson)

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• Well-defined problems ð  – all aspects of the problem are clearly specified (= initial state, goal, methods available) (e.g. maze or chess) §  Used in research as there’s an optimal strategy and errors/deficiencies can easily be identified
• Ill-defined problems ð  – definition of problem is underspecified, initial state, goal state & methods unclear (e.g. keys locked in car) Most everyday problems
•  Knowledge-rich problems can only be solved with considerable amounts of prior knowledge
•  Knowledge-lean problems ð  – can be solved without prior knowledge as necessary info is provided by problem statement
• Major Aspects of Problem Solving 1.     It’s purposeful (goal-directed) 2.     Involves controlled rather than automatic processes 3.     A problem only exists if someone lacks the relevant knowledge to produce an immediate solution
• Factors influencing problem solving: Past Experience P  Past experience generally increases our ability to solve problems P  BUT functional fixedness – fail to solve a problem because we assume from past experience that any given object has a limited number of uses (e.g. candle + box of nails/video in prediscussion) §  Support: younger children (= less experience) outperformed older children Einstellung – mental set in which people use a familiar strategy even where there is a simpler alternative or the problem cannot be solved using it
• Factors Influencing Problem-Solving: Incubation (Things happening without awareness) g  The finding that a problem is solved more easily when it is put aside for some time (Wallas) §  Fairly small but highly significant effect §  Stronger effect for creative problems with multiple solutions & when long preparation time prior to g  Wallas: subconscious keeps processing g  Simon: forget control information which makes it easier to adopt a new approach §  Support: in an experiment there was an effect only when the break allowed misleading information to be forgotten
• Incubation (Things happening without awareness): Finding meta-analysis g  Creative problems benefit more than linguistic/ visual problems §  Multiple solution nature g widening of search of knowledge network, doesn’t support restructuring g  Longer preparation periods = larger incubation effect §  Exhaust search in one domain g more likely to explore new domain in second phase g  Linguistic problems: low cognitive load tasks gave strongest incubation effect Prevents narrow attentional focus while leaving room for processing
• Factors influencing Problem Solving Expertise P  Chunking theory: memory chunks contain more information & more chunks are stored P  Template theory: chunks that are used frequently develop into more complex data structures g few large templates (= more general) rather than large number of chunks §  Template = core (= similar to fixed info stored in chunks) + slots (=contain variable info) thus are more flexible P  Routine expertise – using acquired knowledge to solve familiar problems efficiently (focus of template theory) P  Adaptive expertise – using acquired knowledge to develop strategies for dealing with novel problems
• Gestalt Approach P  Trial-and-error learning – a solution is reached by producing fairly random responses rather than by a process of thought P  Reproductive thinking – re-use of previous experiences/ knowledge to solve a current problem (Thorndike’s cat experiment) P  Productive thinking – solving a problem by developing an understanding of the problem’s underlying structure (Gestalt approach) §  Object the fact that there’s a purely arbitrary relationship between the cats’ behaviour and the desired consequence (reframing/restructuring a problem, elevator example)
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• Insight-Problems P  The experience of suddenly realising how to solve a problem “ahaaaa experience” P  Involves replacing one way of thinking about a problem with a new & more efficient way g cognitive conflict P  Non-insight problems: “warmth” (closeness to solution) gradually rises P  Insight problems: warmth stays rather low until it suddenly rises before solution §  However, as tasks can be solved in various ways you cannot say that there are specific tasks (not) involving insight (e.g. remote associate problems)
• Representational Change Theory – Ohlsson P  Largely based on gestalt approach combined with information-processing approach, emphasising insight §  Main difference to gestalt: more detailed explanation of how one gets to insight P  The way in which a problem is currently represented/ structured in the solver’s mind serves as a memory probe to retrieve related knowledge from LTM (= operators/ possible actions) g The retrieval process is based on spreading activation among concepts/ items of knowledge in LTM gImpasse/ block occurs when the way a problem is represented does not permit retrieval of the necessary operators/ possible actions g Impasse is broken when the problem representation is changed (= INSIGHT!) g new mental representation acts as new memory probe P  Ways of changing a problem representation §  Elaboration/ additional info §  Constraint relaxation g inhibitions on what is regarded as permissible are removed §  Re-encoding g some aspect of the problem is reinterpreted P  Limitations §  Often not possible to predict when/how the representation of a problem will change §  Single-factor theory – constraint relaxation as single solution to insight problems (actually only has modestly beneficial effect) §  De-emphasised individual differences
• Problem Space Hypothesis – Newell & Simon P  Problem space – an abstract description of all the possible states that can occur in a problem situation P  Said it’s possible to produce a computer simulation of human problem solving (= general problem solver) g actually wasn’t P  Rely heavily on heuristics (= rules of thumb)(what people use) that produce approx. accurate answers (unlike algorithms that guarantee solution) (what general problem solver does) §  Means-ends analysis – heuristic method based on creating a sub-goal to reduce the difference between the current & goal state g  Support: few fast moves g break g few fast moves g … §  Hill climbing – change the present state of a problem into one apparently closer to the goal (e.g. maze)g simpler than means-ends §  Progress monitoring – insufficiently rapid progress toward solution leads to the adaption of a different strategy g  Support: 9-dot-problem g less likely to experience criterion failure = less likely to shift strategies P  Limitations §  General problem solver better than humans at remembering what happened to a problem but worse at planning future moves (focuses on single move while humans can think several moves ahead) §  Everyday problems are not well-defined like the ones they used §  Approach best suited for multiple-move-problems not insight problems §  De-emphasised individual differences in strategy & speed
• ANALOGICAL PROBLEM SOLVING P  Positive transfer – past experience helps §  Far transfer – positive transfer to a dissimilar context §  Near transfer – positive transfer to a similar context P  Negative transfer – past experience disrupts ability to solve current problem P  Three dimensions determining transfer distance: task similarity, context similarity, time interval P  Three main types of problem similarity: §  Superficial similarity – solution irrelevant details (e.g. objects) §  Structural similarity – causal relations among some main components §  Procedural similarity – procedures for turning the solution principle into concrete operations
• DELIBERATE PRACTICE – ERICSSON P  A wide range of expertise can be developed through deliberate practice (more important than non-deliberate practice) P  Four aspects: 1.       Task is at an appropriate level of difficulty 2.       Learner is given informative feedback 3.       Learner has adequate chances to repeat the task 4.       Learner has opportunity to correct his/her errors P  Long-term working memory – used by experts to store relevant information in LTM to access it through retrieval cues in WM §  Serves to reduce limitations on processing capacity P  3 requirements for LTWM to function effectively §  Person has extensive knowledge of relevant information §  Activity must be very familiar so you can predict which info needs to be retrieved §  Stored info must be associated with appropriate retrieval cues so that those cues actually lead to retrieval P  Limitations §  Assumes there’s no such thing as innate talent (not plausible!) and practice is the only important factor (what about IQ?) §  Disregards motivational factors §  More applicable to narrow/ less complex skills (e.g. idiot savants) than broad/ complex skills
• Brain: Insight P  Right hemisphere plays an important role §  Support: When solution word to remote associate problem was shown to both hemispheres separately, the right responded much faster P  Anterior superior temporal gyrus in the right hemisphere only activated when solutions involved insight P  Integration of weakly active & distant associations occurs mostly in the right hemisphere (strong activation of closely connected associations mostly in left hemisphere) g relevant for insight P  Anterior cingulate cortex activated during cognitive conflict P  There’s a preparation for conflict resolution as those 2 areas are activated even before the problems were presented P  Problems solved without insight were preceded by increased activity in occipital area g increased visual attention Lateral frontal cortex imposes constraints on processing g when damaged: easier changing of representation thus allows for quick solving
• Brain: Frontal Cortex P  Especially DLPC are more consistently activated during problem solving than other brain parts §  When damaged: impaired in making difficult moves (e.g. moving away from goal) P  Right DLPC more important for tower problems while left more important for water jar problem Adaptive control of thought model (ACT-R) (Anderson)
• "MULTICULTURAL EXPERIENCE ENHANCES CREATIVITY" Creative Cognition Approach P  Creative cognition approach – creative processes are similar to everyday processes §  Everyone has the potential to become creative as long as he/she uses ordinary processes effectively to produce extraordinary ideas P  2 kinds of cognitive processes implicated in creative thinking §  Generative processes – actively retrieve & seek relevant info to generate candidate ideas with differing creative potential g  Conceptual expansion – seemingly irrelevant concepts are added to an existing one to expand conceptual boundaries §  Explorative processes – determine which ideas should be further processes P  Multicultural experiences predict creative outcomes & processes (= tendency to access unconventional knowledge & ideas) §  Relationship especially strong when people adapt & are open to new experiences (more creative when you’ve lived somewhere, not just travelled) §  Focus less on one possible representation §  Only in contexts where there is no need for a firm answer or existential/ mortality concerns
• Design Thinking P  Structured methodology for generating innovation 1.       Developing empathy & defining user needs 2.       Ideation – explore possible solutions for improving user experience 3.       Prototyping & testing P  Demands that old assumptions & pre-existing beliefs are regarded thus unnatural & a challenge for the human brain P  Gotta focus on metacognition to notice when we’re slipping into cognitive traps
• Cognitive Traps Top-Down Processing: Leads to encoding failures (= disregarding of important details) Solution -> Enable bottom up processing through multiple observers/ observations Inattentional Blindness: Failure to see things in plain sight because attention is directed elsewhere (e.g. invisible gorilla)  Solution ->Look for the unexpected to find surprises that can lead to breakthroughs Confirmation Bias: Dismiss data that contradicts prior beliefs Solution -> Make a concentrated effort to capture evidence that challenges pre-existing beliefs Fixation: Inability to see a problem from a fresh perspective (= get stuck on ideas within a particular category) g become attached to a particular mental set (= framework of thinking about a problem based on past solutions, shaped by habit/ desire) Solutions:->  Reframing of problem statements/ questions ->  Assuming alternative identities to generate social distance g enhances abstract & divergent thinking ->  Imposing constraints in brainstorming (“brainstorming defibrillators”) ->  Remove power of social influence by writing down ideas prior to group session Sunk Cost Trap: Learning & adaption becomes constraint by heavy emotional investment in an initial idea Solution: Parallel rather than serial prototyping even within a single idea
• What are design processes? P  Form of complex problem solving that can be explained by the cognitive model P  Multiple stages: encode task information to create problem space consisting of task-relevant knowledge g designing (= searching for task-relevant concepts within the problem space + elaborating & integrating those to design a solution) P  Where can individuals search for ideas? §  Common approach is to seek inspiration in examples (serves as cue to retrieve relevant concepts) §  Fixated: generate more example-related ideas Inspired: search for ideas in less common domains to produce novel ideas
• Do examples induce fixation or inspiration? Method P  Meta-analysis: statistical analysis combining the results of multiple specific studies P  43 studies were included §  Examples in studies were non-negative (= didn’t violate task requirements) §  Included control (no example) condition Examined individual rather than group design problem solving
• Do examples induce fixation or inspiration? Results P  Degree of copying: people tend to copy ideas from examples regardless of the quality of the examples presented P  Variety: produce less variety as compared to controls P  Quantity: the more they copy from an example the smaller the number of ideas generated P  Novelty & quality: improved P  Number of examples: benefit more from looking at one rather than multiple examples §  Multiple examples lead to more diffused rather than focused search strategy §  Difficult to conduct multi-domain search because of our limited cognitive resources P  Common-ness: higher quality & novelty when examples were uncommon §  Leads individuals to search in less typical domains g facilitates novel conceptual combination P  Timing: larger positive impact of example when presented at beginning of problem solving §  Because then no sunk cost effect
• Do Examples induce fixation or inspiration? Discussion P  Attention allocation explanation – presence of examples should direct individuals to allocate their attention to example-related domains §  Examples modify the search strategy from a broad one to a focused one §  Narrows scope of search (= reducing variety) but allows more in-depth exploration and thus increases likelihood of generating innovative & high-quality ideas Answer to broader research question: yes, examples can but don’t have to be inspiring g depending on number, common-ness & timing
• Inductive Reasoning Inductive Strength P  Forming generalisations (which may be probable but not certain) from examples (specific g 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 (Watson): 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 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
• Types of deductive reasoning: Propositional 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
• Types of deductive reasoning: Syllogistic 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
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• 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
• Everyday/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
• 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 people are likely to judge any conclusion as valid that reinforces their initial assumption, regardless of whether the conclusion follows from the premises

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