Psych 108 - Final Exam Study Guide PDF

Psych 108 - Final Exam Study Guide Exam details - Date: 12/12/24 | Time: 4:00pm to 7:00pm | Location: IV Theater 1 There will be 60 multiple-choice questions on the final exam. No notes are allowed while taking the exam. The final exam will be cumulative, however only about 1/3 of the qu...

Psych 108 - Final Exam Study Guide Exam details - Date: 12/12/24 | Time: 4:00pm to 7:00pm | Location: IV Theater 1 There will be 60 multiple-choice questions on the final exam. No notes are allowed while taking the exam. The final exam will be cumulative, however only about 1/3 of the questions will test material from before the second midterm (covered on the first two study guides). The other 2/3 will test material covered in this study guide. General Knowledge Prototype theory to semantic memory/information ○ Definition: Categories are organized around a prototype—the most typical example of that category. ○ How It Works: Items are categorized based on similarity to the prototype (e.g., robin = bird; bee = insect). ○ Prototypicality: High: Robin, sparrow (typical birds). Low: Ostrich, penguin (less typical). Context matters: In a zoo, penguins may seem more typical. ○ Characteristics of prototypes – how do they differ from non-prototypes? Typicality effect Prototypes are judged as better examples of a category and are identified more quickly than nonprototypes. Prototypes are common examples: Frequently mentioned items (e.g., robin = bird) are rated as more typical than rarely mentioned ones (e.g., penguin = bird). Faster judgments: People categorize prototypes (e.g., robin as a bird) faster than nonprototypes (e.g., penguin as a bird). Semantic priming effect Faster responses to an item when preceded by a semantically related item. Priming helps judgments for prototypes (e.g., bright red after "red"). Priming hinders judgments for nonprototypes (e.g., muddy red after "red"). Family resemblance Items in a category share overlapping attributes, but no single attribute is common to all. Prototypes have the most attributes in common with other category members (e.g., car = most prototypical vehicle: wheels, fuel, horizontal movement). Nonprototypes share fewer attributes (e.g., elevator = least prototypical vehicle).  ○ Levels of categorization Superordinate-level categories Superordinate-level categories are broad, general categories that can encompass more specific subcategories. For example, "furniture," "animal," and "tool" are superordinate-level categories. These categories can be broken down into more specific levels, like "chair" (a type of furniture), "dog" (a type of animal), or "screwdriver" (a type of tool). Basic-level categories Basic‐level categories are moderately specific. “Chair,” “dog,” and “screwdriver” are examples of basic‐level categories. How does a prototype differ from a basic level category? ○ While a prototype is an ideal representation of a category, a basic-level category is a more general term that can apply to a wide range of examples within a category. What are unique characteristics of basic-level categories? ○ Most common for labeling: We use basic-level terms like "pen" instead of broader (e.g., "writing instrument") or more specific terms (e.g., "Paper Mate Flair pen"). ○ Faster recall: People remember basic-level terms better. ○ Semantic priming: Basic-level words (e.g., "apple") help people make faster decisions. ○ Brain activation: Basic-level terms activate regions of the brain that process language and visuals. Subordinate-level categories subordinate‐level categories refer to lower‐level or more specific categories. “Desk chair,” “collie,” and “Phillips screwdriver” are examples of subordinate categories. Exemplar theory to semantic memory/information ○ What is an exemplar? An exemplar is a specific example of a concept stored in memory. The exemplar approach suggests that we categorize new stimuli by comparing them to these stored examples. For instance, your concept of "dog" would include memories of all the individual dogs you’ve encountered. ○ How does this approach differ from the prototype approach? The exemplar approach uses specific examples you've encountered to define a concept, while the prototype approach uses an idealized, average representation of the concept. Network models of semantic memory/information  ○ Network models of semantic memory propose that concepts are connected in a network. The meaning of a concept, like "apple," is shaped by its links to other concepts. 1. Collins and Loftus (1975): Concepts are connected in a network, and meaning depends on these connections. 2. ACT Theory (Anderson, 2000): Knowledge is stored in networks that help us process information. 3. PDP (Parallel Distributed Processing): Cognitive processes work through networks of interconnected units, like neurons. ○ Broadly, how do network models differ in approach to categorization models (i.e. prototype and exemplar) Network models organize knowledge in interconnected webs, where meaning comes from the relationships between concepts. In contrast, prototype and exemplar models categorize objects based on idealized averages (prototype) or specific past examples (exemplar). ○ What are nodes and spreading activation in relation to network models? In network models, nodes represent concepts, and links connect related concepts. When you think of a concept, its node gets activated, and the activation spreads to connected nodes. This spreading activation helps retrieve related information, with activation taking longer to reach more distant nodes. What are schemas and scripts? ○ Schemas are generalized, organized knowledge about situations, events, or people, helping us understand and interpret the world. For example, you have a schema for a hardware store, which includes items like wrenches and paint, but not unrelated things like psychology books. ○ A script is a type of schema that refers to a specific sequence of events in a familiar activity, like the typical order of events at a restaurant (sitting down, ordering, eating, paying). While schemas represent broader knowledge, scripts are narrower, focusing on a series of actions that happen in a particular order. ○ How are schemas related to general knowledge? Schemas are mental frameworks that help organize and interpret information. They guide how we understand familiar situations and events, allowing us to quickly apply general knowledge to new situations. ○ Understand the relationship between schemas and memory Memory selection Memory selection refers to the process by which our brains choose what information to focus on and remember, often influenced by existing schemas or expectations. For example, when recalling an event or object, we tend to remember details that fit our pre-existing  knowledge or beliefs, sometimes overlooking information that doesn't align with those schemas. Boundary extension Boundary extension refers to the tendency to remember a scene or image as having a wider view than what was actually seen. This happens because we often mentally extend the boundaries of a scene based on our expectations or prior knowledge, making the scene appear larger or more expansive in memory than it was in reality. Memory abstraction Memory abstraction is when we remember the meaning of something, not the exact words. For example, we remember the idea of "family resemblance," but not the exact sentence. People generally don't recall exact wording well, but focus on the overall meaning. ○ What is memory integration? How is it related to schematic processing? Memory integration is when our existing knowledge helps us remember new information in a way that fits with our expectations or schemas. This often leads to remembering details that weren't originally there, especially after some time has passed. Understand research on memory integration (e.g. Bartlett’s War of the Ghosts” study; research on gender stereotypes) Bartlett's "War of the Ghosts" study showed that people's memories are influenced by their own cultural knowledge. British students changed parts of a Native American story to make it fit their own understanding, omitting or altering details that didn’t make sense to them. Over time, their memory became more distorted. This demonstrates how schemas help us understand and recall information, but they can also lead to errors by making us remember things that weren’t there. Lecture material: Explain the difference between episodic and semantic memory (provide examples of each) ○ Episodic memory A person's memory for specific events that were personally experienced Ex: ○ Semantic memory A mental thesaurus organizes knowledge a person possesses about words and other verbal symbols Ex. ○ What does semantic memory allow us to do? Organize objects according to concepts  Make inferences going beyond the information given Decide which objects are similar Theories about how people represent general knowledge – what are the key characteristics/properties of these theories, what is the supporting evidence and what are challenges to or limitations of these theories: ○ Defining-attribute theory (network models of concepts) Concepts defined by a list of attributes Each attribute necessary and all jointly sufficient Boundaries clearly defined All members of the concept are equally representative Concepts organized hierarchically Properties of defining attributes network models - Hierarchically organized - Nodes – represent concepts - Pathways – represent relationship between concepts - Spreading activation moves between nodes along pathways - Economical - Properties do not need to be re-represented for each concept - Support - Sentence verification times consistent with some key predictions - Faster to verify a “canary is a bird” than “a canary is an animal” What are typicality effects? How do they cause a problem for this theory? Typicality ratings Order of listing members of a category ○ “Bluejay” listed before “Emu” for bird category Response time to verify “An X is a C” ○ “Yes” to “Are penguins birds” is slower than “Yes” to “Are sparrows birds” Inferences ○ Generalization from typical item to a category is stronger than from atypical item to category “All chickens/sparrows on a certain island have a certain bacteria in their gut. How likely is it that all birds do?” Higher probability estimates with sparrows than chickens ○ Feature analytic approach Emphasized semantic features  Defining features Necessary features of a category Birds lay eggs Characteristic features Typical but not necessary of category Birds fly Two-stage process Stage 1 ○ If high or low degree overlap of all features make a quick yes judgement Stage 2 ○ If moderate overlap consider defining features (takes more time) How does this approach deal with typicality effects? Accounts for ○ Typicality effects Typical stage 1, atypical stage 2 ○ Negation effects Goldfish is a bird – stage 1 Butterfly is a bird – stage 2 ○ Prototype theory A concept is represented by a prototypical item = central tendency Prototypes include characteristic features that are usually present, not only necessary or sufficient features What are prototypes? Prototypes involve average of multiple exemplars Posner and Keele ○ Exposed participants to multiple images of dots Each corresponding to one of two categories ○ Prototypes corresponded to average of each category ○ Prototypes never presented ○ Nevertheless people reliably sorted prototypes into appropriate category What are the 3 levels of prototypes? What are the characteristics of each level and be able to provide examples of each level. Superordinate ○ (ie animal, plant, tool) Very broad categories Difficult to image Basic ○ (ie cat, tree, saw)  Levels at which categories are represented that contain the most useful information Members tend to be similar in shape and how one interacts with them Easy to image Subordinate ○ (ie siamese cat, elm tree, hacksaw) Highly specific example What is the support for the 3-level approach to prototypes? basic -level names are used to identify objects ○ Ask people to loo at pictures and identify objects ○ People prefer to use basic-level names ○ People produce basic-level names faster than superordinate or subordinate names Basic-level names are more likely to produce the semantic riming effect ○ Priming with basic-level names is helpful Dog primes cat ○ Priming with subordinate names is not helpful Cocker spaniel does not prime cat Different levels of categorization activate different regions of the brain ○ Superordinate terms are more likely than basic-level terms to activate part of the prefrontal cortex ○ Subordinate terms are more likely than basic-level terms to activate part of the parietal region What are the issues with the prototype theory? Concepts can be unstable and variable (ie prototype ratings can shift) We often store specific information about individual examples of a category, not just prototypes ○ Exemplar theory What are exemplars? A concept is represented by all of the members (exemplars) of the concept Uses the total similarity of an object to all members of the category to determine if the object belongs in the category How does it differ from prototype theory? Previous models definitions of bird ○ Defining attribute: bird = flying animal with beak that lays eggs  ○ Prototype: bird = sparrow-like thing Exemplar models definition ○ Exemplar: {sparrow, emu, chicken, bluejay, eagle}... What are the issues with exemplar theory? Implausible that people remember every example of every category Ad hoc categories ○ People can create categories for items unlikely to have been stored together as such Example Objects that serve as platforms When is the prototype theory more suitable? When is exemplar theory more suitable? The exemplar approach may be more suitable for categories with relatively few members (so as not to overwhelm semantic memory) The prototype approach may be more suitable for categories with numerous members Both approaches may coexist ○ Different hemispheres Left – prototypes Right – exemplars What are schemas in relation to general knowledge? ○ Schema – generalized knowledge about a situations, an event, or a person ○ Schema theories explain how people process complex situations and events People encode “generic” information about a situation Use this information to understand and remember new examples of the schema ○ “This is just like what happened when…” ○ Bartlett’s War of Ghosts study and what it tells us about schemas Introduced notion of schemas Knowledge structure that influences how one interprets and remembers a situation War of the Ghosts Bartlett’s analysis of the changes - The story became shorter and more coherent - “No trace of an odd, or supernatural element is left: we have a perfectly straightforward story of a fight and a death” - Acheived by  - Omissions: ghosts ommitted early; the wound became a matter of flesh and not spirit - Rationalization: growing coherence among parts - Transformation of details into more familiar and conventional - Changing order of events ○ Impact of schemas on memory selection Verbal labels People’s memories change to fit labels Language Definition of psycholinguistics ○ ​The study of how we use language to communicate, focusing on the mental and neurological processes behind understanding, producing, and following social norms in conversation. Be able to define key terms used by psycholinguistics ○ Phoneme The smallest unit of sound in spoken language (e.g., a, k, th). English has about 40 phonemes. Changing one phoneme in a word changes its meaning (e.g., kiss → hiss). ○ Morpheme The smallest unit of meaning in a language (e.g., re-, active, -ate, -ed in reactivated). Some stand alone (giraffe), while others must attach to convey meaning (re- = repeated action). ○ Morphology The study of how morphemes combine to form words. ○ Syntax The rules for organizing words into sentences. ○ Semantics The study of meaning in language. ○ Pragmatics The social rules of language use, considering the listener's perspective (e.g., explaining "syntax" differently to a child vs. a classmate). It focuses on language in social interactions. Be able to differentiate between early theories of psycholinguistics ○ Ancient Philosophers: Greek and Indian philosophers debated the nature of language. ○ 19th Century: Wilhelm Wundt and William James speculated on language abilities. ○ Modern Psycholinguistics: Began in the 1960s, inspired by Noam Chomsky’s theories. Focused on testing linguistic theories with psychological research. Recent approaches emphasize the role of meaning in language.  ○ Chomsky’s approach Focused on syntax; grammar exists independently of meaning. Humans have an innate understanding of universal grammar. Example: "Colorless green ideas sleep furiously" shows grammar isn’t learned solely from experience. Shifted study of language from behaviorism to internal processes. Surface structures vs deep structures Surface Structure: The actual words spoken or written. Deep Structure: The underlying abstract meaning of a sentence. Research in opposition to Chomsky Transformations: Research didn’t support Chomsky’s claim that sentences with more transformations take longer to process. Universal Grammar: Many non-European languages don’t follow the universal patterns Chomsky proposed. Shift to Meaning: Psychologists began emphasizing semantics and cognition over grammar, linking language to memory, attention, and problem-solving. ○ Cognitive-functional approach This theory emphasizes that language’s main function is to communicate meaning. It also highlights how cognitive processes like attention and memory are closely linked to language comprehension and production. What methodologies have been used by psycholinguistics? (And what do they tell us about how people comprehend language?) ○ Negation and passive voice Negative sentences (e.g., "not" or "rejected") take longer to process and lead to more errors than affirmative ones. More negatives in a sentence further reduce comprehension, as cognitive processes handle positive information better. ○ Incremental interpretation Language comprehension occurs bit-by-bit as we process information. We don’t wait for the entire sentence to be spoken or read before making judgments; our interpretation is updated continuously as new information is received. ○ Self-paced reading task Participants read sentences word by word, revealing each word when they press a spacebar. The time spent on each word (measured in milliseconds) indicates processing difficulty. Higher reaction times (RTs) suggest more cognitive effort is required to understand that word. This task is used to study language comprehension. ○ Lexical ambiguity Lexical ambiguity occurs when a single word has multiple meanings. For example, "bank" can refer to a financial institution or the land along a river.  People tend to pause longer when processing ambiguous words, especially when the word appears in isolation, such as in a questionnaire. ○ Syntactic ambiguity Syntactic ambiguity arises when sentence structure causes confusion, especially without punctuation. For example, "After the Martians invaded the town that the city bordered was evacuated" can mislead readers, causing them to initially misinterpret the meaning. Shorter sentences or punctuation can help clarify the meaning. ○ Eye-tracker Tanenhaus et al. (1995) used eye-tracking to study how people process syntactic ambiguities. Participants listened to sentences like "Put the apple on the towel in the box" while viewing visual scenes. The eye-tracker measured eye movements, showing how participants interpreted the sentences in real time. ○ Good-enough approach The "good-enough approach" suggests that people often process only the general meaning of a sentence, relying on quick, heuristic judgments. This allows for fast reading but can lead to errors, as not every detail is thoroughly processed. Definition of neurolinguistics ○ is the discipline that examines the underlying neurological structures and systems that support language and language‐related processes ○ What do language disorders tell us about neurolinguistics? Language disorders offer insights into neurolinguistics by showing how different brain regions handle language. Broca’s aphasia Broca's aphasia is characterized by difficulty producing language, as Broca's area is involved in motor control for speech. People with this condition struggle with speech production but may also experience some issues with language comprehension, especially with complex sentence structures. Wernicke’s aphasia Wernicke's aphasia results from damage to Wernicke's area, which affects language comprehension. People with this condition struggle to understand basic instructions and may produce speech that is wordy and confused, but they typically have fewer pauses than those with Broca's aphasia. Dual-route approach to reading  ○ The dual-route approach to reading suggests that skilled readers use two routes: (1) a direct-access route, where they recognize words without sounding them out, and (2) an indirect-access route, where they sound out words to understand them. ○ Direct-access route (definition and supporting evidence) The direct-access route in reading involves recognizing words through visual patterns without sounding them out. This method is especially used for words with irregular spellings, such as "choir," "one," or "through," where phonetic decoding is not possible. ○ Indirect-access route (definition and supporting evidence) The indirect-access route to reading involves converting written words into sounds before accessing their meaning. This method is used especially for words with regular spellings, like "ten" or "cabinet," where the phonetic pronunciation can be directly decoded to understand the word. Approaches for how to teach reading (English) to children and how these approaches relate to the direct-access and indirect-access approaches ○ Whole-word approach The whole-word approach suggests that readers connect the written word directly to its meaning, without focusing on its phonetic sound. This method emphasizes recognizing words within context, rather than decoding sounds. However, even skilled readers struggle with context-based word prediction, achieving only about 25% accuracy in guessing missing words from incomplete sentences. ○ Phonics approach The phonics approach, supported by those who favor the indirect-access hypothesis, states that readers recognize words by sounding out individual letters. It emphasizes the importance of phoneme awareness in early reading. Research shows that phonics training is particularly helpful for children with reading difficulties. While there was once a strong debate between whole-word and phonics approaches, most current educators and researchers advocate for a compromise: children should use phonics to decode words and context to confirm their understanding. ○ Whole-language approach The whole‐language approach emphasizes meaning and enjoyment in reading instruction. It advocates for reading interesting stories and writing experiments, even before mastery of spelling. The approach stresses the importance of early reading experience, which enhances reading and language skills over time. Research shows that increased reading practice leads to better language abilities and can even improve math skills. Additionally, children benefit socially from  reading, especially when parents read to them, improving their awareness of others' thoughts and feelings. Lecture material: Linguistic relativity (provide definition) ○ The idea that the particular language we speak influences the way we think about reality ○ Whorfian hypothesis and its 3 versions Language determines or influences thinking Strong hypothesis Language determines thinking Weak hypothesis Language influences perception Weakest hypothesis Language influences memory ○ Evidence for and against linguistic relativity Color vocabulary Some languages have thousands of color words, others a handful People might differentiate and remember colors to a greater or lesser extent depending on the resources of the language that they have learned Brown & Lenneberg ○ They found a correlation between nameability and memory accuracy: ○ Easy-to-name colors were more accurately remembered than hard-to-name Heider ○ Tested the Dani, a group living in the New Guinea highlands The Dani have two color words One meaning “dark” One meaning “light” She gave them Brown and Lenneberg’s (1954) color memory test ○ Colors that were easy to name in English turned out to be better remembered by the Dani as well - Heider’s interpretation - Certain colors are inherently more distinguishable (focal) - Perception influences thought rather than thought influencing perception Counting  Chinese vs American Children ○ Chinese numerical names are compatible with the traditional 10-base numeration system Spoken numbers correspond exactly to their written equivalent: 15 is spoken as “ ten five” and 57 is spoken “five ten seven” ○ Most European systems of number words are irregular up to 100 ○ Chinese children count earlier than American children (in part) because Chinese numbers are more systematic Psycholinguistics (provide definition and understand the key concepts below) Phonology (the way sounds function in the language) ○ Basic unit = phoneme ○ Single speech sound ○ English has about 45; 9 make up half of our words ○ Dimensions: voiced (“a”); unvoiced (“s”; fricatives (“sh”); plosives (“t”); place of articulation (palate vs. lips) Morphology (study of the internal structure of words) ○ Basic unit = morpheme ○ Smallest unit of meaning (words, parts of words, etc) ○ Free (ie “old”’ “the”) vs. bound (ie “er”, “ist”) ○ Over 100,000 words formed by morpheme combinations Semantics (study of meaning) ○ Link between language and concepts ○ Denotation vs. connotation – ie “heart” Syntax the grammatical rules that govern how words can be combined into sentences Pragmatics knowledge of social rules that underlie language ○ Chomsky’s approach to psycholinguistics Humans have an innate understanding of the abstract principles of language Language is modular Language is special, nit processed the same as other cognitive tasks  Language abilities can be explained in terms of a complex system of rules and principles represented in the minds of language Transformational rules ○ Rules people use to convert deep structure into surface structure and vice versa Deep structure vs surface structure Surface structure ○ The words that are actually spoken or written Deep structure ○ The underlying meaning of a sentence What are transformational rules? ○ Rules people use to convert deep structure into surface structure What are some challenges to his approach? Factors affecting comprehension (know examples of each) ○ Negatives Negative statements require more processing time than affirmative statements Affirmative statements produce fewer errors Multiple negatives decrease performance ○ Passive voice The active form of a sentence is easier to understand than the passive form “Sara threw the ball” (active voice) “The ball was thrown by Sara” (passive voice) ○ Ambiguity “He gave her cat food” People pause longer when they are processing an ambiguous word When people encounter a potential ambiguity, the activation builds up for all the well-known meanings of the ambiguous item ○ Complex syntax “Daddy, what did you bring that book that I don’t want to be read to out of up for?” Difficult to understand Nested structure taxes working memory Neurolinguistics ○ The discipline that examines how the brain processes language ○ Be able to apply the following two examples to our understanding of language processing Aphasia difficulty communicating caused by damage to speech areas Wernicke’s aphasia  ○ ○ Broca’s aphasia ○ ○ Eye fixations in relation to reading and comprehension ○ What does the research tell us? People’s eye fixations on words correspond to the amount of time they spend processing each word ○ Factors that affect eye fixations while reading Word frequency Ambiguous pronoun End of sentence (wrap up) Mind wandering Dyslexia How does mind-wandering impact gaze duration? Dual route approach to reading ○ How do we look at a pattern of letters and actually recognize that word? ○ Dual-route approach to reading – skilled readers employ both  Direct-access route (recognize word by first sounding out the word) Indirect-access route (recognize word by first sounding out the word) ○ What characteristics influence likelihood of utilizing these routes Flexible – whether access is indirect or direct depends on: Characteristics of the reading material ○ Familiar vs unfamiliar words Characteristics of the reader ○ Ie beginning vs. advanced readers ○ Implications of the dual route approach for teaching reading to children Phonics approach (indirect access) Basic characteristics of this approach ○ Readers recognize words by trying to pronounce the individual letters in the word ○ “Sound it out” ○ Argues that speech sound is a necessary intermediate step in reading ○ Emphasizes developing children's awareness of phonemes Evidence supporting this approach ○ Phonics training helps children who have reading problems Whole-word approach (direct access) Basic characteristics of this approach ○ Argues readers can directly connect the written word– as an entire unit – with the meaning that this word represents ○ Argues that children should not learn to emphasize the way a word sounds ○ Emphasizes context within a sentence Evidence countering this approach ○ Even skilled adult readers achieve only about 25% accuracy when they look at an incomplete sentence and guess which word is missing ○ Poor readers often fail to learn to read fluently using this approach What is the current compromise of these approaches? Was large debate in education ○ Some favored whole word others favored phonics Resolution ○ Most educators and researchers now support some sort of compromise ○ All students should learn phonics  ○ Reading instructions should emphasize meaning ○ Reading instruction should be enjoyable, to increase children’s enthusiasm about learning to read Definition of reading comprehension ○ Forming an integrated representation of the text ○ Factors that encourage drawing inferences Working-memory capacity Expertise Meta-comprehension skills Understanding what one understands and what one doesn’t understand Ways to enhance meta-comprehension skills ○ Contemplate your own reading strategies Consider relevant background knowledge Reading sentences vs. skimming Monitor your understanding Notice when your mind wanders ○ Teaching meta-comprehension skills Teach students to Self explain Summarize Make predictions about possible outcomes Describe puzzling sections Question the author Deductive Reasoning and Decision Making What is the definition of decision making? ○ Decision making is the process of evaluating information and choosing between alternatives, ranging from simple choices to significant decisions. It involves using cognitive principles, including heuristics, to guide the process. ○ How does it differ from deductive reasoning? Deductive reasoning involves starting with specific premises and using logical principles to draw a conclusion, with all necessary information provided. The premises can be true or false, but formal logic rules must be followed. In contrast, decision making involves evaluating alternatives and often relies on heuristics, with more subjective judgment rather than strict logical rules. Be able to provide an example of each decision-making heuristic below. Also, provide examples of the errors we encounter when relying on these heuristics ○ Representativeness heuristic  The representativeness heuristic is a mental shortcut where people judge the likelihood of an event based on how similar it is to a typical case. For example, when tossing a coin, people often think that a sequence like T H H T H T looks more random and thus more likely than H H H T T T. This heuristic leads us to assume that random outcomes should look random, and orderly outcomes seem less likely. While this heuristic is helpful in many situations, it can also cause us to ignore important statistical details, such as sample size or base rate, and misjudge probabilities. Small-sample fallacy The small-sample fallacy occurs when people assume that a small sample is representative of the larger population. This fallacy leads to incorrect decisions, often seen in social situations or when forming stereotypes about a group based on limited observations. For example, people may generalize about a group based on just a few individuals. A way to avoid this fallacy is to interact with a larger, more diverse sample, such as through exchange programs. Base-rate fallacy The base-rate fallacy occurs when people ignore the frequency of an event (base rate) and rely on the representativeness heuristic, leading to incorrect judgments. In Kahneman and Tversky's study, participants misjudged Tom W's graduate program by focusing on stereotypes instead of base-rate data. This shows how ignoring base rates can result in poor decision-making, despite heuristics being helpful in many cases. Conjunction fallacy The conjunction fallacy occurs when people judge the probability of two events happening together (the conjunction) to be more likely than either event individually. This error arises from the representativeness heuristic, where people find a description that includes more details (e.g., "bank teller" and "feminist") more plausible, even though it's statistically less likely. The fallacy shows that people often ignore basic principles of probability, and even individuals with high SAT scores are prone to making this mistake. ○ Availability heuristic The availability heuristic involves estimating the frequency or probability of an event based on how easily examples come to mind. For instance, if you can easily recall many people from Illinois but few from Idaho, you may assume your college has more Illinois students. While this heuristic is generally helpful, it can lead to errors when factors like recency or familiarity bias memory retrieval,  distorting the decision. In contrast to the representativeness heuristic, which deals with judging similarity to a category, the availability heuristic focuses on recalling specific examples from memory. Recency bias Recency bias occurs when more recent events or experiences are more easily retrieved from memory, leading us to judge them as more frequent or probable than they really are. For example, if a recent event has been heavily covered in the media, it might seem more likely to occur again, even if this isn't statistically accurate. Familiarity bias Familiarity bias happens when we rely on familiar examples to make judgments, even if those examples don't accurately represent the broader reality. For instance, if a country is frequently mentioned in the news (like El Salvador in the past), people may overestimate its significance or size, even if the true data (like population) doesn’t support that perception. Recognition heuristic The recognition heuristic helps us make accurate decisions by comparing two categories, where we recognize one but not the other. The recognized category is assumed to be more frequent or larger. For example, when asked which Italian city, Milan or Modena, has a larger population, most people would correctly choose Milan because they recognize it more. ○ Anchoring and Adjustment heuristic (aka “anchoring effect”) he anchoring and adjustment heuristic (or anchoring effect) involves starting with an initial estimate (the anchor) and then adjusting it based on new information. While this process often leads to reasonable answers, people tend to rely too heavily on the initial anchor, making adjustments that are too small. For example, when asked to meet in 15 minutes, you might adjust slightly to 20 minutes, but fail to account for delays like finding your coat or other distractions, leading to an underestimate of the total time needed. What is ecological rationality and how does it differ from the heuristic approach to decision making? ○ Ecological rationality suggests that people use simple, adaptive heuristics suited to real-world environments, leading to effective decisions. It contrasts with the heuristic approach, which focuses on how heuristics can lead to biases and errors, especially in controlled settings. While both recognize the role of heuristics, ecological rationality emphasizes their effectiveness in natural settings.  What is the framing effect? What factors influence its likelihood? ○ The framing effect occurs when the way a decision or question is presented influences the outcome, even if the underlying information is the same. Two factors influencing its likelihood are: 1) the background context of the choice, and 2) the wording or framing of the question. For example, people may react differently to a choice depending on whether it is framed as a potential gain or a potential loss, even if the monetary value remains the same. Understand research on overconfidence in decision-making and some specific domains in which we are overconfident (e.g., political decision making and completing projects on time) ○ What factors increase overconfidence? Overconfidence in Decision-Making occurs when people overestimate the accuracy of their judgments. It is common in areas like political decisions and project completion. Factors that increase overconfidence include reliance on uncertain knowledge, confirmation bias, memory limitations, past experiences, and optimism. The planning fallacy is a key example, where people underestimate task completion time. To reduce overconfidence, strategies include breaking tasks into smaller parts, visualizing obstacles, and considering how others handle similar tasks. What is hindsight bias? Provide an example ○ Hindsight Bias is when people believe they could have predicted an event's outcome after it has already occurred, often thinking it was inevitable. This bias leads us to reconstruct past events to align with our current knowledge. ○ Example: In a study by Linda Carli (1999), participants read a story with a tragic or happy ending. Those who read the tragic version believed they could have predicted the rape, while those who read the happy version believed they could have predicted the marriage proposal. This bias influenced their memory, causing them to recall details that aligned with the ending they read, even though those details weren’t in the story. Compare and contrast “maximizers” and “satisficers” ○ Maximizers seek the best option by examining many choices, often leading to regret and higher depressive symptoms. Satisficers are content with a satisfactory option and experience less regret and better emotional well-being. Maximizers tend to be more dissatisfied due to their exhaustive search for the best choice. Lecture Material: Definition of Deductive reasoning ○ Formal procedure that ensures accuracy if rules of logic are followed ○ Given some promises that are true, one can reach a conclusion that must also be true ○ Example:  All men are mortal Socrates is a man Therefore, socrates is mortal Belief Bias effect ○ The belief-bias effect When people make judgements based on prior beliefs and general knowledge, rather than on the rules of logic Consider this syllogism All fruit grow on trees Potatoes are not a fruit Therefore, potatoes do not grow on trees ○ This seems to be a reasonable conclusion, but then consider the following: Equivalent seems invalid All fruit grow on trees Leaves are not fruit Therefore, leaves do not grow on trees ○ Now the conclusion appears to be ridiculous and false Yet, the reasoning is exactly the same as in the first example Wason Card Selection task ○ Each card has a letter on one side and a digit on the other ○ Determine by turning over the minimum number of cards if this rule is true: if there is a vowel on one side, there is an even number on the other side ○ Wason selection task - If vowel then even number on the other side - Must turn over A - Because a vowel, want to see if even number on other side - Must turn over 3 - Only 15% of college students get this correct - Must be sure there us not a vowel on the other side - 2 card doesn’t matter - Rule does not state that all even numbers have to have vowels - X card doesn’t matter - Rule does not specify anything about consonants ○ Confirmation bias The standard wason selection task People tend to try to confirm or support a hypothesis rather than try to disprove it Applications  People seek confirming evidence when self-diagnosing disorders (ie insomnia) Both medical students and psychiatrists tend to select information consistent with their original diagnosis rather than investigate information that might be consistent with another diagnosis Definition of decision making ○ Assessing information and choosing song two or more alternatives Be able to define key characteristics and differentiate between theories about decision making ○ Classical decision theory Assumed decision theory Knew all the options available Understood pros and cons of each option Rationally made their final choice Goal was to maximize value of decision ○ Satisficing To obtain an outcome that is good enough Do not consider total range of options Consider options one by one until one meets our minimum standards of acceptabulity Don’t reach optimal solution, but also don’t spend eternity searching for one ○ Individual differences in decision-making style and psychological well-being Satisficers vs maximizers Maximizers – tend to examine as many options as possible (maximizing decision–making style); may lead to “choice overload” Satisficers – tend to settle for something that is satisfactory (satisficing decision-making lifestyle) Examined careers of college students ○ Maximizers made more money ○ Satisficers were happier with their jobs General differences ○ Maximizers tend to experience more regret following a choice than satisficers ○ Maximizers tended to experience more depressive symptoms that satisficers ○ Kahneman and Tversky Proposed that a small number of heuristics guide human decision making The same strategies that normally guide us toward the correct decision may sometimes lead us astray  Decision making heuristics (define, know the main characteristics and provide an example of each of the following heuristics) Representativeness heuristic ○ People judge tht a sample is likely if it is similar to the population from which the sample was selected ○ This heuristic is so persuasive that people often ignore important statistical information that they should consider Can be accurate Can also lead to errors Most will overuse representativeness ○ A certain town is served by two hospitals. In the larger hospital about 45 babies are born each day, and in the smaller hospital about 15 babies are born each day. As you know, about 50% of all babies are boys. However, the exact percentage varies from day to day. Sometimes it may be higher than 50% sometimes lower For a period of 1 year, each hospital recorded the days on which more than 60% of the babies born were boys. Which hospital do you think recorded more such days The larger hospital The smaller hospital About the same (that is, whithin 5% of each other) Answer: the smaller hospital ○ Role of sample size A large sample is statistically more likely than a small sample to reflect the true proportions in a population Small-sample fallacy – assume a small sample will be representative of the population from which it was selected Availability heuristic ○ Making judgments about the frequency of likelihood of an event based on how easily instances come to mind ○ Actual frequency influences how easily evidence comes to mind but so do other factors Media Vividness ○ Role of media and vividness  Anchoring and adjustment heuristic ○ Participants asked to calculate in 5 seconds the answer to one of the following problems: ○ The order of presentation for these two groups had a significant impact on their estimates ○ The correct anwer, in both cases, is 40,320! ○ Begin by guessing a first approximation (an anchor) ○ Make adjustments to that number on the basis of additional information ○ Often leads to a reasonable answer ○ Can lead to errors in some cases ○ Role of presentation order Framing effect ○ Suppose you have invested in stock equivalent to the sum of $60,000 in a company that just filed a claim for bankruptcy. They offer two alternatives in order to save some of th einvested money: Positive framing Negative framing The wording of a question and the framing effect Overconfidence ○ People tend to have unrealistic optimism about their abilities, judgments and skills ○ Study on the planning fallacy Students asked to give best and worst case scenario of how long it would take to complete an asssignemnt Hindsight bias  ○ Hindsight bias occurs when people deel that they “knew it all along” ○ They believe that an event is more predictable after it become sknown than it was before it became known - Applications of hindsight bias - Scientific findings - People think they would have predicted any outcome - Medical diagnosis - People think they would have made an accurate diagnosis - Political events - Think they would have predictied the outcome - Business decisions - Think thue would have anticipated which companies did well or failed Problem Solving and Creativity Defining problem solving and its 3 components ○ the processes necessary to reach a goal, typically in situations where the solution is not immediately obvious. ○ Initial state The situation at the start of a problem. Example: "I need to reach Jim to start our social psychology project but don't know his last name, email address, or phone number." ○ Goal state The point at which the problem is solved. Example: "I have Jim's last name and email address." ○ Obstacles Restrictions that make it challenging to move from the initial state to the goal state. Example: "Jim wasn't in class yesterday," "The professor is away this afternoon," and "The project draft is due Friday." Relationship between attention and problem solving ○ Attention is essential for identifying relevant information and avoiding distractions. Negative thoughts can divide attention and hinder problem-solving. Effective problem solvers focus on key details, look for inconsistencies, and strategically prioritize important information. Methods (and potential challenges) of problem representation  ○ Problem representation involves translating the problem into a format that aids in solving it. Effective representations, such as symbols, matrices, and diagrams, increase the likelihood of finding a solution. Strong working memory helps keep relevant information in mind, improving problem-solving ability. ○ Symbols Symbols help represent abstract problems, like in algebra. Challenges include errors in translating words to symbols, such as reversing variables or oversimplifying relational information, leading to incorrect representations. ○ Matrices A matrix is a grid that helps track complex, categorical information and is effective for problem-solving. Using the correct labels is crucial for accuracy, and matrices work best when the information is stable. ○ Diagrams Diagrams help represent abstract information clearly and simplify complex problems, such as using hierarchical trees to show relationships. They free up mental space for other problem-solving tasks and can improve skills with training. ○ Visual images Some people use visual imagery and mental simulation to solve problems. Visual images can help overcome the limits of concrete representations and provide insights. Strong visual-imagery skills are beneficial, especially when constructing figures or imagining scenarios. Problem solving strategies ○ Algorithm vs heuristic An algorithm is a method that always guarantees a solution, but it can be time-consuming and inefficient. In contrast, heuristics are quicker strategies that may not guarantee a solution but often provide a faster, more efficient way to approach a problem. Exhaustive search An exhaustive search is an algorithm where all possible answers are tried using a set system. While this method guarantees a solution, it can be inefficient. More sophisticated strategies, like focusing on likely combinations (e.g., using common two-letter starts in an anagram), reduce the number of possibilities and lead to faster solutions than trying every option. Analogy approach The analogy approach involves solving a new problem by applying a solution from a similar, earlier problem. It's widely used in problem  solving and creativity across various fields, such as engineering, art, and science. For example, engineers use analogies frequently, and the Wright brothers used the analogy of bird wings to design airplane wings with adjustable tips. Means-ends heuristic The means-end heuristic involves breaking a problem into smaller subproblems and reducing the gap between the initial and goal states for each. It focuses on identifying the desired outcome and the methods to reach it, making it a flexible and effective problem-solving strategy. For example, a student used a stapler to fix her skirt hem by first identifying a tool and then locating it. Hill-climbing heuristic The hill-climbing heuristic involves choosing the option that seems to lead most directly to a goal, similar to picking the steepest path when hiking. While useful with limited information, it can lead to short-term solutions that overlook better long-term outcomes. For example, a student might take a job right after graduation instead of pursuing further education for greater long-term benefits. ○ Factors that influence problem solving Expertise Expertise is exceptional skill and performance in a specific area, often linked to superior memory and detailed knowledge. While 10 years of experience was once considered necessary, research shows it’s not always a predictor of success. Expertise is typically domain-specific, meaning experts excel in their field but may not perform well outside of it. Knowledge base ○ Experts have a more organized and extensive knowledge base than novices, allowing them to solve problems more effectively. Training in diverse settings with detailed feedback helps experts build the necessary schemas for efficient problem-solving. Memory ○ Experts have specialized memory for their field, like chess players recalling 50,000 chess patterns. They excel in remembering familiar arrangements but not random ones, as their memory works best with established schemas. Problem-solving strategies  ○ Experts and novices differ in problem-solving strategies. Experts use the means-ends heuristic effectively, breaking problems into subproblems and solving them systematically. They also focus on structural similarities in problems, while novices often focus on surface similarities and approach problems more haphazardly. Speed and accuracy ○ Experts solve problems faster and more accurately than novices due to automatic operations and parallel processing. Experts can quickly respond to stimuli, and on tasks like solving anagrams, they consider multiple solutions simultaneously. Novices, by contrast, often use slower, serial processing. Metacognitive skills ○ Experts excel in metacognitive skills, such as self-monitoring, which helps them judge problem difficulty and allocate time efficiently. They also recover quickly from errors and assess the usefulness and creativity of ideas, as seen in expert inventors. Mental set A mental set occurs when you persist in using a previously successful solution, even when a simpler method would work. This often leads to ineffective problem solving, as you stop considering alternative strategies. In a classic experiment, participants used a complex method to solve a series of problems, but struggled when simpler solutions were possible, illustrating how prior experiences can hinder problem solving. Fixed vs. growth mindset ○ A fixed mindset is the belief that your abilities, such as intelligence, are static and cannot be improved, leading to a tendency to give up when faced with challenges. In contrast, a growth mindset is the belief that abilities can be developed through effort, motivating individuals to persist and seek improvement. Both mental sets and mindsets are influenced by previous experiences, but while a fixed mindset limits growth, a growth mindset encourages continual learning and adaptation. Functional fixedness Functional fixedness occurs when we restrict an object to its typical use, hindering creative problem-solving. For example, in Duncker's candle  problem, the solution involves using a matchbox to hold the candle instead of just holding matches. It can also be overcome in emergencies, like doctors using limited tools on a plane to save a life. Stereotypes Stereotypes, like the belief that men are better at math than women, can influence performance through stereotype threat. For example, a female student may underperform on a math test due to the anxiety caused by the stereotype. Research shows that females perform better when not reminded of gender differences. Stereotype threat likely impacts performance by increasing anxiety and reducing working memory, either through heightened arousal or the effort to suppress negative thoughts. Insight vs non-insight problems Insight problems are solved suddenly when a new approach emerges, often after initial incorrect assumptions. People with large working memory solve them quickly. In contrast, non-insight problems are solved gradually using memory and reasoning. Insight involves a sudden realization, often breaking through incorrect assumptions and limiting top-down processing. ○ Explain research on metacognition during problem solving Metacognitive research shows that confidence builds gradually in non-insight problems (e.g., algebra) but suddenly surges in insight problems when a solution is found. Metcalfe (1986) demonstrated this by having participants rate their confidence while solving an insight problem, showing a slow increase followed by a sharp jump when the correct answer was discovered. This pattern distinguishes insight problems from non-insight ones. What are the primary characteristics of creativity? ○ Creativity involves solutions that are both novel and useful. Some theorists view it as a product of ordinary problem-solving, while others believe it's limited to exceptional individuals in specific fields. J.P. Guilford (1967) linked creativity to divergent thinking, where multiple responses are generated. However, simply measuring the number of ideas isn't enough—creativity also requires that solutions be both new and practical. ○ How is motivation related to creativity? Motivation affects creativity in two ways: intrinsic and extrinsic. Intrinsic motivation, where people engage in tasks because they find them enjoyable, enhances creativity. In contrast, extrinsic motivation, driven by rewards, can reduce creativity, though feedback can help. Prabhu et al. (2008) found that high intrinsic motivation, boosted by self-efficacy, leads to more creative work, while perseverance was not consistently linked to creativity. Lecture material: What is problem solving? ○ Used when you want to reach a certain goal, but the solution is not immediately obvious ○ Two types of problem solving Well-defined vs. ill-defined Well defined steps to solution are clearly circumscribed ○ Subtract 35 from 492 ○ Drive to atlanta with good directions Ill defined steps to solution are vague ○ Solve world hunger ○ Have an interesting career Three components ○ Initial state ○ Goal state ○ Obstacles ○ Three components of problem solving Initial state Goal state Obstacles ○ How do we represent problems? Paying attention to important information Identify and attend to the most relevant information ○ Effective problem solvers read the description of a problem very carefully, attend to inconsistencies Methods of representing the problem Finding a way to characterize the elements of the problem that enable its effective solution Factors that influence representation success Working memory capacity Expertise Sources of error Translating into symbols ○ Eight times as many cats as dog ☑️ 8xC=D 8xD=C ○ Oversimplification The engines rate in still water is 12 miles per hour more than the rate of the current The engines rate in still water is 12 miles per hour Methods of representing the problem  Matrices ○ Matrix – grid showing all possible combinations of items ○ Most useful for complex, stable, categorical information Diagrams Represent abstract information in a concrete fashion Reduce large amount of complicated information into a concrete form Examples ○ Instructions for assembling objects ○ Origami More accurate with both a verbal description and a step by step diagram rather than only a verbal description Analogy use ○ Use better understood problem to solve new problem ○ Analogy = superficial features are different, but same at a deep level Solar system and atom ○ Analogies are missed unless people are given hints that they are related, or multiple related stories ○ People are too influenced by superficial similarities Means-end analysis/heuristics ○ Heuristics Strategies not guaranteed to be correct, but generally helpful ○ The means end heuristic Identify the “ends” you want and then figure out the “means” to reach them Divide the problem into sub-probelms Try to reduce the difference between the initial state and the goal state for each of the sub-problems One of the most effective and flexible problem solving strategies ○ Hill climbing technique (problem of local maxima) Choose the step that moves closest to the goal Challenge Can get stuck in local maxima – ○ States that are closer to the goal than any neighboring states, but still are not the goal  Leave local maxima by back-tracking or adding randomness ○ Factors that influence problem solving Memory Memory skills of experts tend to be very specific Speed and accuracy Problem solving operations become more automatic Metacognitive skills Experts are better than novices at ○ Monitoring their own problem solving ○ Judging the difficulty of the problem ○ Allocating time ○ Monitoring the usefulness of ideas ○ Recovering from errors Experts underestimate the amount of time novices will require to solve a problem in the experts’ area of specialization Expertise Mental set Using the same solution from previous problems, even though the problem sould be solved by a different and easier method Close mind prematurely, stop thinking Overactive top down processing Functional fixedness ○ Assign stable uses to an object ○ Fail to think about the features of the object that might be useful in helping problem solving ○ Overactive top down processing ○ Insight vs non-insight problems Noninsight problem – gradual solutions Insight problem – seems impossible until sudden solution appears; light buld, “aha” Requires overcoming mental set Provide examples of each  What are the key differences between these types of problems? What do these differences tell us about metacognition? ○ Metacognition during probelm solving Participants asked to periodically provide warmth ratings as they solved insight and noninsight problems ○ Results Warmth ratings grow as solution approaches for noninisght problems No increase in warth ratings for insight problems ○ Demonstrates solution for noninsight problems is gradual but sudden for insight problems ○ Relationship between insight problem solving anf recognzing out of focus picture Schooler et al 1996 Correlation between out of focus picture identification and ○ Insight picture solving.45 ○ Noninsight problem solving 0 Relationship between right/left hemisphere differences and insight problems Fiore and Schooler ○ Gave participants insight problems ○ Presented solutions to right or left visual field ○ Gave problem again More likely to solve problem when hint presented to left visual field (right hemisphere) Right left hemisphere differences in insight problem solving: Fiore and Schooler, 1997  ○ Effects of physical distance and temporal distance on insight Physical distance ○ Insight problems thought to be composed in a distant research institute were solved more accurately than when the same problems were thought to be composed in a nearby institute Temporal distance ○ Imagine yourself a year from now (Distal) versus tomorrow (proximal) ○ Effect on insight problem solving Creative Brain documentary Cognitive Development Over the Lifespan Lifespan development of memory o Memory develops throughout life, with cognitive abilities emerging through biological and environmental interactions. Infants and children demonstrate memory despite limited skills, while older adults' performance may be influenced by factors like health and education. Some age-related memory differences persist even when controlling for these variables. This section covers memory development in infancy, childhood, and older adulthood. Explain two research techniques used to measure infants’ memory skills ▪ Conjugate Reinforcement Technique: Infants can remember actions, even after a delay, such as kicking a mobile to make it move. ▪ Context Effects: Infants’ memory is influenced by familiar environments, with stronger recall when tested in the same setting as the original memory. Recognizing mother ▪ Research shows that even very young infants can recognize their mother. For example, three-day-old infants can visually distinguish their  mother from a stranger. Infants also exhibit impressive auditory recognition, such as distinguishing their mother's voice from that of a stranger. A study by Kisilevsky and colleagues (2003) tested unborn infants by playing either their mother's voice or a stranger’s voice. The infants' heart rates changed more when they heard their mother's voice, indicating recognition before birth. Conjugate reinforcement technique ▪ The conjugate reinforcement technique measures infant memory by connecting a ribbon from the infant's ankle to a mobile, so their kicks make the mobile move. After training, retention is tested by observing how many kicks occur after a delay, revealing memory retention. This method shows that infant memory improves over the first 18 months of life. How do young children compare to adults in the following domains? What are the similarities and differences? Working memory ▪ Children's working memory improves significantly as they grow. For instance, a two-year-old can recall about two numbers, while a nine-year-old can recall six. Research shows that children's working memory involves the same components as adults'—the central executive, phonological loop, and visuospatial sketchpad. These memory skills correlate with academic performance, with children excelling in reading, writing, or math depending on their strengths in specific memory areas. Long-term memory ▪ Young children typically excel at recognition memory but struggle with recall memory. In a study by Myers and Perlmutter (1978), two-year-olds recognized 80% of objects and four-year-olds recognized 90%. However, when tested for recall, the two-year-olds remembered only 20%, and the four-year-olds recalled 40%. Recall memory requires active memory strategies, which children do not develop until middle childhood. Recognition Recall Autobiographical memories ▪ Autobiographical memory refers to memory for personal experiences. As children's language skills develop around age 2, they can create a life narrative and remember experiences more accurately. This shows the link between language development and memory. Source monitoring ▪ Source monitoring refers to identifying the origin of a memory. Children under age seven often struggle to distinguish between reality and fantasy. For example, a child may believe an imaginary event, like a trip to the moon, actually happened. They also have trouble differentiating real-life experiences from those seen in storybooks or videos. Memory strategies  ▪ Young children have difficulty using memory strategies, which contribute to their poor recall compared to adults. Memory strategies are intentional activities designed to enhance memory, but children may not recognize their usefulness. Their working memory is often not developed enough to select and apply strategies effectively, a skill that improves as they grow older, particularly during elementary school. Utilization deficiency ▪ Utilization deficiency refers to the problem where young children fail to use memory strategies effectively, meaning these strategies don't improve their recall. In contrast, older children are better at recognizing the usefulness of strategies, choosing them more carefully, and using them consistently. They are also more likely to apply a variety of strategies and monitor their effectiveness when learning multiple items. Rehearsal ▪ Rehearsal, repeating items to remember them, helps maintain information in working memory. Four- and five-year-olds don't spontaneously rehearse, but by age seven, children begin to use it. Younger children can benefit from learning this strategy, even though they may not naturally use it, such as children with reading disorders who recall more when taught rehearsal. However, they often don't realize that using strategies can enhance memory. Organizational strategies ▪ Organizational strategies, like categorizing and grouping, are effective for memory, but young children are less likely than older children to spontaneously use them. In a study by Moely et al. (1969), younger children didn't group similar pictures together, while older children did. When younger children were encouraged to organize, they saw the benefit and improved their recall. Imagery ▪ Imagery is a powerful memory tool for adults, and research shows that six-year-olds can be trained to use it effectively. However, young children typically don't use imagery spontaneously, and this ability doesn't develop until adolescence. Even college students often don't use this strategy frequently enough. Eyewitness testimony ▪ Children's eyewitness testimony is less accurate than adults', with younger children being particularly vulnerable to stereotypes and misleading suggestions. A study by Leichtman and Ceci (1995) showed that children exposed to stereotypes or incorrect suggestions were more likely to misremember events. Social factors, like emotional questioning or complex language, also affect children's accuracy, and they are often  reluctant to say, "I don't know" or change their statements under pressure. How do older adults compare to younger adults in the following domains? What are the similarities and differences? Working memory ▪ Older adults perform similarly to younger adults on simple working memory tasks, like digit-span tests, where they are asked to recall numbers in order. However, age differences become apparent in more complex tasks that require manipulating or ignoring irrelevant information. For example, in a task where participants must remember and report words in alphabetical order, younger adults performed better than older adults. These age differences highlight the challenges older adults face in tasks that require cognitive manipulation, such as those needed in high-stakes jobs like air traffic control. Long-term memory ▪ Older adults generally perform well on tasks involving semantic memory, such as crossword puzzles, where they may even outperform younger adults. They also excel at tasks they can do automatically. However, age differences appear in more complex tasks, like source monitoring, where older adults may struggle more than younger adults. The impact of aging on long-term memory depends on the task's difficulty, with older adults handling simpler tasks well but showing more challenges with tasks requiring more effort or complex processing. Prospective memory ▪ Older adults often struggle with prospective memory tasks, such as remembering to buy items during a shopping task, where they tend to make more errors than younger adults. This difficulty is linked to declines in working memory, as prospective memory requires individuals to keep reminding themselves to complete tasks. However, older adults perform better when environmental cues, like a book near the door, prompt them to remember tasks. In some cases, they may even outperform younger adults, especially in tasks with clear cues, like taking daily medication. Implicit memory ▪ Older adults generally perform as well as younger adults on implicit memory tasks, such as recognizing familiar letter sequences more quickly than unfamiliar ones. Research shows that age differences in implicit memory are minimal, with only slight deficits observed in some cases. Since implicit memory does not require effortful remembering, older adults perform similarly to younger adults on tasks that involve familiarity rather than conscious recall. Recognition memory ▪ Research shows that long-term recognition memory remains stable or declines only slowly with age. For example, a study  found that 20-year-olds correctly recognized 67% of words previously presented, while 70-year-olds recognized a similar 66%. This suggests that recognition memory is less affected by aging compared to other memory types. Explicit recall memory ▪ Older adults often struggle more with explicit recall tasks compared to younger adults. In a study by Aizpurua et al. (2009), older adults (ages 56-72) recalled fewer details from a video compared to younger adults (ages 19-25). However, both