Social and Cognitive Psychology: Obedience and Memory

Social and Cognitive Psychology Topic A: Social Psychology Obedience  Theories of obedience, including agency theory and social power theory.  Research into obedience, including Milgram’s (1963) research into obedience and three of his variation studies: rundown office block (Experiment 10),...

Social and Cognitive Psychology Topic A: Social Psychology Obedience  Theories of obedience, including agency theory and social power theory.  Research into obedience, including Milgram’s (1963) research into obedience and three of his variation studies: rundown office block (Experiment 10), telephonic instructions (Experiment 7), and ordinary man gives orders (Experiment 13) as they demonstrate situational factors that encourage dissent.  1.1.3 Factors affecting obedience and dissent/resistance to obedience, including individual differences (personality and gender), situation and culture. Conformity  1.1.4 Types and explanations of conformity.  1.1.5 Research into conformity including Asch (1951) and his variation studies (1952, 1956).  1.1.6 Minority influence (Moscovici, 1976).  1.1.7 Factors affecting conformity and minority influence, including individual differences (personality), situation and culture. Self-reporting data  1.2.1 Designing and conducting questionnaires and interviews, considering researcher effects.  1.2.2 Primary and secondary data.  1.2.3 Unstructured, semi-structured and structured interviews, open, closed (including ranked scale) questions  1.2.4 Alternative hypotheses. Sample selection and sampling techniques  1.2.5 Random, stratified, volunteer, and opportunity sampling techniques. Quantitative data  1.2.6 (List A) Analysis of quantitative data: calculating measures of central tendency (mean, median, and mode), data tables (frequency tables and summary tables), graphical presentation (bar chart, histogram), measures of dispersion (range and standard deviation), percentages, ratios, fractions.  1.2.7 Normal and skewed distribution.  1.2.8 Analysis of qualitative data using thematic analysis Ethical guidelines  1.2.9 British Psychological Society (BPS) code of ethics and conduct (2009), including risk management when carrying out research in psychology. Classic study  1.3.1 Moscovici et al. (1969) Influence of a Consistent Minority on the Responses of a Majority in a Color Perception Task. Contemporary study  1.3.2 Burger (2009) Replicating Milgram: Would people still obey today? One contemporary study chosen: 1.3.4 Haun et al. (2014) Children Conform to the Behavior of Peers; Other Great Apes Stick with What They Know Topic B: Cognitive Psychology Models of memory  2.1.1 The multi-store model of memory (Atkinson and Shiffrin, 1968), including information processing, encoding, storage, retrieval, capacity and duration.  2.1.2 The working memory model (Baddeley and Hitch, 1974) including the phonological loop, central executive, visuospatial sketchpad, episodic buffer.  2.1.3 Reconstructive memory (Bartlett, 1932), including schema theory. Experiments and experimental design  2.2.1 Designing and conducting experiments, including field and laboratory experiments.  2.2.2 Independent and dependent variables.  2.2.3 Experimental and null hypotheses.  2.2.4 Directional (one-tailed) and non-directional (two-tailed) tests and hypotheses.  2.2.5 Experimental and research designs: repeated measures, independent groups and matched pairs, the issues with each and possible controls.  2.2.6 Operationalization of variables, extraneous variables and confounding variables.  2.2.7 The use of control groups, counterbalancing, randomization and order effects.  2.2.8 Situational and participant variables.  2.2.9 Objectivity, reliability and validity (internal, predictive and ecological).  2.2.10 Experimenter effects, demand characteristics and control issues.  2.2.11 List A from Topic A.  2.2.12 (List B) Decision making and interpretation of inferential statistics:  levels of measurement  Wilcoxon signed ranks test of difference (also covering Spearman's rank correlation coefficient (formula) and Spearman's rank (critical values table) and Chi-squared distribution once Unit 2 has been covered)  probability and levels of significance (p≤.10 p≤.05 p≤.01) observed and critical values, and sense checking of data  one- or two-tailed regarding inferential testing  Type I and type II errors.  2.2.13 Case studies of brain-damaged patients related to research into memory, including the case of Henry Molaison (HM). Classic study  2.3.1 Bartlett (1932) War of the Ghosts Contemporary study  2.3.2 Schmolck et al. (2002) Semantic knowledge in patient HM and other patients with bilateral medial and lateral temporal lobe lesions. One contemporary study from the chosen:  2.3.4 Sacchi et al. (2007) Changing history: doctored photographs affect memory for past public events. Practical investigation  2.4.1 One practical research exercise to gather data relevant to topics covered in cognitive psychology. This practical research exercise must adhere to ethical principles in both.  Agency Theory (Milgram, 1974)  Explanation: Milgram proposed that people operate in two psychological states:  Autonomous State – Individuals act according to their own conscience and take responsibility for their actions.  Agentic State – Individuals see themselves as agents of an authority figure and shift responsibility onto them. This shift occurs due to binding factors, such as fear of appearing rude or fear of punishment, which keep individuals obedient.  Supporting Evidence:  Milgram’s Baseline Study (1963) showed that 65% of participants obeyed to the maximum 450V shock, demonstrating the agentic shift, as they frequently deferred responsibility to the experimenter.  Real-World Applications – The theory explains historical events like Nazi Germany, where soldiers claimed they were "just following orders" (e.g., Eichmann trial).  Hofling’s Nurse Study (1966) found that 21 out of 22 nurses obeyed an unknown doctor’s orders to administer a dangerous drug dose, supporting the idea of agentic shift in hierarchical structures.  Criticisms:  Individual Differences – Not everyone obeys; some participants in Milgram’s study resisted, suggesting personality (e.g., authoritarianism) plays a role.  Overly Deterministic – The theory implies people have little free will, ignoring moral courage (e.g., whistleblowers).  Cultural Bias – Collectivist cultures (e.g., China) may obey more due to social norms rather than agentic shift. Social Power Theory (French & Raven, 1959)  Explanation: This theory identifies five types of power that influence obedience:  Legitimate Power – Authority figures have formal rights (e.g., police).  Reward Power – Ability to give rewards for compliance.  Coercive Power – Ability to punish disobedience.  Expert Power – Authority has superior knowledge.  Referent Power – Obedience due to admiration (e.g., celebrities).  Supporting Evidence:  Bickman’s Uniform Study (1974) found higher obedience when an experimenter wore a security guard uniform (legitimate power) compared to civilian clothes.  Milgram’s Variation Studies showed obedience dropped when authority lacked legitimacy (e.g., Experiment 13 – ordinary man gave orders).  Real-World Example – Doctors (expert power) are more likely to be obeyed in medical settings.  Criticisms:  Doesn’t Explain Dissent – Some people resist authority despite power differences (e.g., political protesters).  Oversimplifies Power – Power dynamics are more complex (e.g., gender, race influence obedience beyond these categories).   Cultural Limitations – Some cultures respect different power structures (e.g., religious leaders may have more influence than political ones). Milgram’s Baseline Study (1963)  Aim: To test how far ordinary people would obey an authority figure, even when harming another person.  Procedure:  40 Male volunteers (20-50 yrs.) were told it was a "memory study."  A "teacher" (participant) administered fake electric shocks (15V-450V) to a "learner" (confederate) for incorrect answers.  The experimenter used verbal prods (e.g., "You must continue") to enforce obedience.  Findings:  65% of participants obeyed to 450V (lethal shock).  Participants showed extreme distress (sweating, trembling) but continued.  Conclusion: Ordinary people are highly obedient to authority, even when it conflicts with their morals.  Evaluation (Strengths):  High Internal Validity – Milgram controlled variables (e.g., scripted prods, standardized procedure).  Real-World Applications – Helps explain atrocities like the Holocaust or abusive regimes.  Reliability – Replicated in different settings (e.g., Sheridan & King’s 1972 study with real shocks to puppies).  Evaluation (Weaknesses):  Ethical Issues – Deception (participants thought shocks were real) and psychological harm (extreme stress).  Lacks Population Validity – Only American men were tested; women and other cultures may respond differently.  Artificial Setting – Lab experiments lack ecological validity (real-life obedience may differ). Milgram’s Variation Studies  Experiment 10: Rundown Office Block  Aim: To test if the prestige of the setting affects obedience.  Procedure: The study was moved from Yale University to a rundown office.  Findings: Obedience dropped to 47.5% (vs. 65% in the original).  Conclusion: A less legitimate setting reduces obedience.  Evaluation (Strengths):  Supports Agency Theory – When authority appears less legitimate, people are less likely to enter the agentic state.  Practical Applications – Explains why people may resist corrupt authorities in non-prestigious settings.  Controlled Comparison – Only location changed; other variables constant.  Evaluation (Weaknesses):  Still High Obedience – Nearly half still obeyed, suggesting other factors (e.g., personality) matter.  Demand Characteristics – Participants may have guessed the study’s purpose.  Experiment 7: Telephonic Instructions  Aim: To test if physical presence of authority affects obedience.  Procedure: The experimenter gave orders over the phone instead of in person.  Findings: Obedience dropped to 20.5%.  Conclusion: Reduced authority presence decreases obedience.  Evaluation (Strengths):  Strong Support for Social Power Theory – Legitimate power weakens without direct presence.  Real-World Relevance – Explains why people may disobey remote orders (e.g., online scams vs. face-to-face coercion).  Highlights Importance of Proximity – Key factor in obedience studies.  Evaluation (Weaknesses):  Some Still Obeyed – Shows individual differences (some people still followed phone instructions).  Ethical Concerns – Participants still experienced stress.  Experiment 13: Ordinary Man Gives Orders  Aim: To test if authority status affects obedience.  Procedure: A confederate (ordinary man) replaced the experimenter.  Findings: Obedience dropped to 20%.  Conclusion: People obey less when authority lacks legitimacy.  Evaluation (Strengths):  Supports French & Raven’s Legitimate Power – Obedience requires perceived authority.  Consistent with Other Variations – Aligns with telephonic and rundown office findings.  Useful for Understanding Resistance – Explains defiance in corrupt regimes.  Evaluation (Weaknesses):  Not All Disobeyed – 20% still obeyed, suggesting some people are naturally more submissive.  Cultural Bias – Some cultures may obey non-legitimate figures (e.g., gang leaders). Factors Affecting Obedience & Dissent  Individual Differences  Personality (Adorno et al., 1950 – Authoritarian Personality)  Findings: People with authoritarian traits (rigid, submissive to authority) are more obedient.  Support: o Milgram’s Follow-Ups found some participants had authoritarian tendencies.  oReal-World Example – Nazi supporters scored high on authoritarianism scales.  Criticisms: o Not Everyone Obeys – Some high-authoritarians resist (e.g., whistleblowers). o Correlation ≠ Causation – Authoritarianism may be a result of upbringing, not just personality.  Gender Differences  Sheridan & King (1972): Found 100% obedience in women administering real shocks to puppies.  Milgram’s Later Studies: Found no significant gender difference in obedience.  Conclusion: Gender may play a minor role, but situational factors are stronger.  Situational Factors  Proximity to Authority/Victim:  Obedience decreases when authority is absent or victim is visible (Milgram’s touch proximity variation).  Uniform:  Bickman (1974): People obeyed a "security guard" more than a civilian.  Gradual Commitment  Small initial compliance leads to greater obedience (foot-in-the-door effect).  Cultural Factors  Collectivist Cultures (e.g., China) show higher obedience than individualist cultures (e.g., USA).  Smith & Bond (1998): Found obedience rates varied across cultures in Milgram replications. Types of Conformity  Compliance  Superficial, public change in behavior to fit in, but no private attitude change.  Example: Laughing at a joke you don’t find funny to avoid standing out.  Identification  Adopting group norms to be part of a group, even if temporary.  Example: Changing your dress code at a new workplace.  Internalization  Deep, permanent change in both behavior and beliefs.  Example: Adopting vegetarianism after being convinced by ethical arguments.  Explanations of Conformity  Normative Social Influence (NSI)  Definition: Conforming to gain social approval and avoid rejection.  Key Study: Asch (1951) – Participants conformed to avoid standing out.   Real-World Example: Peer pressure in teenagers to drink/smoke.  Evaluation: o Supported by Asch’s Research – Many participants admitted they knew the answer was wrong but conformed to fit in. o Explains Compliance – Useful for understanding temporary behavioral changes. o Doesn’t Explain Internalization – Doesn’t account for deep belief changes.  Informational Social Influence (ISI)  Definition: Conforming because we believe others know well (especially in ambiguous situations).  Key Study: Sherif (1935) – Autokinetic effect showed people conformed to group norms in uncertain situations.  Real-World Example: Following emergency evacuation orders because others are doing so.  Evaluation: o Explains Internalization – People genuinely change beliefs when uncertain. o Useful in Crisis Situations – Explains why people follow crowds in emergencies. o Less Relevant in Clear Situations – Doesn’t apply when the correct answer is obvious (e.g., Asch’s unambiguous lines). Asch’s Baseline Study (1951)  Aim: To investigate if people would conform to an obviously wrong majority.  Procedure:  123 male students tested in groups of 6-8 (only 1 real participant, rest confederates).  Participants judged line lengths; confederates gave wrong answers on 12/18 trials.  Findings:  75% conformed at least once.  Average conformity rate: 37% on critical trials.  5% conformed on every trial.  Conclusion: People conform even when the answer is clear due to NSI.  Evaluation (Strengths):  High Internal Validity – Controlled lab setting removed extraneous variables.  Demonstrated NSI Effect – Showed power of group pressure.  Reliable – Replicated with consistent results.  Evaluation (Weaknesses):  Artificial Task – Low ecological validity (unlike real-world conformity).  Ethical Issues – Deception (participants didn’t know others were confederates).  Gender/Cultural Bias – Only American men tested; later studies found women and collectivist cultures conform more. Asch’s Variation Studies  Group Size (1952)  Aim: To see how group size affects conformity.  Findings:  1 confederate: Almost no conformity.  2 confederates: Conformity rose to 13%.  3 confederates: Peaked at 32%.  Beyond 3: No further increase.  Conclusion: Conformity peaks with 3-4 people; larger groups don’t increase pressure.  Evaluation:  Practical Applications – Explains why small peer groups are influential.  Lacks Real-World Generalizability – In real life, larger groups (e.g., protests) can increase conformity.  Unanimity (1956)  Aim: To test if a dissenter reduces conformity.  Procedure: One confederate gave the correct answer.  Findings: Conformity dropped to 5%.  Conclusion: A single ally breaks group pressure.  Evaluation:  Supports NSI – Shows fear of standing alone drives conformity.  Useful for Minority Influence – Explains how one dissenter can inspire resistance.  Task Difficulty (1956)  Aim: To see if ambiguity increases conformity.  Procedure: Made line differences smaller (harder task).  Findings: Conformity increased.  Conclusion: ISI plays a role when uncertainty is high.  Evaluation:  Supports ISI – People rely on others more when unsure.  Contrasts with Baseline Study – Shows conformity isn’t purely NSI. Moscovici’s Blue-Green Slide Study  Aim: To see if a consistent minority could influence a majority.  Procedure:  Groups of 6 (2 confederates, 4 real participants) judged slide colors.  Confederates consistently called blue slides "green."  Findings:  8% of participants conformed to the minority.  32% conformed at least once.  Conclusion: A consistent, committed minority can change majority views over time.  Key Factors in Minority Influence  Consistency – Unwavering stance gains attention.  Commitment – Shows confidence (e.g., sacrifices made by activists).  Flexibility – Being slightly adaptable (Nemeth, 1986) increases influence.  Evaluation (Strengths):  Real-World Applications – Explains social change (e.g., civil rights movement).  Supports Internalization – Minority influence leads to deep belief changes.  Scientific Rigor – Controlled lab study with measurable effects.  Evaluation (Weaknesses):  Artificial Task – Judging colors lacks real-world relevance.  Low Conformity Rates – Only 8% fully conformed; minority influence is slow.  Gender Bias – Only female participants; men may resist differently. Factors Affecting Conformity & Minority Influence  Individual Differences (Personality)  Locus of Control (Rotter, 1966):  Internals (believe they control life) resist conformity more.  Externals (blame outside forces) conform more.  Authoritarian Personality (Adorno, 1950):  High authoritarians conform more to authority but resist minority views.  Situational Factors  Group Size – Asch found 3-4 people maximizes conformity.  Unanimity – A single dissenter drastically reduces conformity.  Task Difficulty – Ambiguity increases ISI (Sherif’s autokinetic effect).  Cultural Factors  Collectivist Cultures (e.g., China) conform more due to group harmony values.  Individualist Cultures (e.g., USA) value independence, so conform less.  Factors Strengthening Minority Influence  Consistency Over Time – Civil rights activists repeated the same message for decades.  Snowball Effect – Gradually, more people adopt the minority view until it becomes majority.  Social Cryptoamnesia – People forget the origin of the change (e.g., women’s voting rights now seem obvious). Self-reporting data  Explanation: Self-report methods involve participants providing information about themselves through questionnaires or interviews. These can be:  Quantitative (closed questions, numerical data).  Qualitative (open questions, descriptive data). Researcher effects occur when the presence or behavior of the researcher influences participants' responses.  Supporting Evidence (Strengths of Self-Reports)  High Ecological Validity – Participants describe real-life experiences (e.g., Beck’s Depression Inventory measures real symptoms).  Flexibility – Can gather both quantitative and qualitative data (e.g., structured interviews for stats, unstructured for depth).  Cost-Effective – Questionnaires can be distributed to large samples quickly (e.g., online surveys).  Criticisms (Weaknesses of Self-Reports)  Social Desirability Bias – Participants may lie to appear favorable (e.g., over reporting healthy habits in health surveys).  Researcher Effects – Interviewer’s tone or appearance may alter responses (e.g., male participants may underreport aggression to a female interviewer).  Low Reliability – Responses can vary daily (e.g., mood affects answers in personality tests). Primary and Secondary Data  Explanation  Primary Data: Collected firsthand for a specific study (e.g., Milgram’s obedience experiments).  Secondary Data: Pre-existing data used for new research (e.g., government crime statistics used to study aggression trends).  Supporting Evidence (Strengths of Primary Data)  High Control – Researchers design methods to fit hypotheses (e.g., Loftus & Palmer’s leading questions study).  Up-to-Date – Avoids outdated or irrelevant data.  Tailored to Research Aims – Specific questions can be asked (e.g., a clinical psychologist designing a depression survey).  Criticisms (Weaknesses of Primary Data)  Time-Consuming & Expensive – Requires recruitment, data collection, and analysis.  Researcher Bias – May unconsciously influence results (e.g., leading questions in interviews).  Limited Generalizability – Small samples may not represent populations.  Supporting Evidence (Strengths of Secondary Data)  Cost-Effective – No need for new data collection (e.g., using NHS records for mental health trends).  Large Sample Sizes – Often uses national databases (e.g., crime statistics).  Longitudinal Comparisons – Can track changes over time (e.g., changing attitudes in census data).  Criticisms (Weaknesses of Secondary Data)  Outdated/Incomplete – May lack recent or specific details needed.  No Control Over Variables – Original study may have flaws (e.g., biased sampling).  Ethical Issues – Privacy concerns if data wasn’t anonymized properly. Types of Interviews and Questions  Unstructured Interviews  Definition: Informal, open-ended questions (e.g., "Tell me about your childhood").  Strengths:  Rich Qualitative Data – Deep insights (e.g., Freud’s case studies).  Flexibility – Follow-up questions can explore new themes.  High Validity – Participants express true feelings.  Weaknesses:  Hard to Analyze – Subjective interpretation needed.   Researcher Bias – Interviewer may steer responses.  Low Reliability – Not standardized; difficult to replicate.  Semi-Structured Interviews  Definition: Mix of fixed and open questions (e.g., "How often do you feel anxious? Can you describe an example?").  Strengths:  Balanced Data – Quantitative + qualitative insights.  Comparable Responses – Some standardization allows analysis.  Adaptability – Can probe interesting answers.  Weaknesses:  Moderate Reliability – Less consistency than fully structured.  Still Time-Consuming – Requires skilled interviewers.  Structured Interviews  Definition: Fixed, scripted questions (e.g., "On a scale of 1–5, how stressed are you?").  Strengths:  High Reliability – Easy to replicate (e.g., DSM-5 diagnostic interviews).  Quick Analysis – Numerical data simplifies stats.  Reduced Bias – Less interviewer influence.  Weaknesses:  Low Depth – Misses nuanced explanations.  Artificial Responses – Forced-choice answers may not reflect true feelings.  Question Types  Open Questions  Example: "How does social media affect your mood?"  Strengths: Detailed responses.  Weaknesses: Hard to quantify.  Closed Questions  Example: "Do you feel stressed? (Yes/No)"  Strengths: Easy to analyze.  Weaknesses: Lacks detail.  Ranked Scales (Likert Scales)  Example: "Rate your happiness from 1 (very unhappy) to 5 (very happy)."  Strengths: Standardized measurements.  Weaknesses: May oversimplify complex feelings. Alternative Hypotheses  Explanation  Alternative Hypothesis (H₁): Predicts a significant effect (e.g., "Caffeine increases memory recall").  Null Hypothesis (H₀): Predicts no effect (e.g., "Caffeine has no effect on memory").  Supporting Evidence (Strengths of Hypotheses Testing)  Scientific Rigor – Allows statistical testing (e.g., p median).  Negative Skew: Long tail on the left (mean < median).  Strengths:  Highlights Outliers – Useful for identifying anomalies.  Weaknesses:  Requires Non-Parametric Tests – Limits statistical option Qualitative Data Analysis (Thematic Analysis)  Explanation: Identifying recurring themes in non-numerical data (e.g., interview transcripts).  Strengths:  Rich Insights – Captures depth of human experiences.  Flexible – Can adapt to different research questions.  Weaknesses:  Subjective – Researcher bias may influence theme selection.  Time-Consuming – Requires detailed manual analysis. BPS Ethical Guidelines (2009)  Key Principles:  Informed Consent – Participants must agree knowingly.  Right to Withdraw – Can leave at any time without penalty.  Confidentiality – Data must be anonymized.  Strengths:  Protects Participants – Minimizes harm.  Professional Standard – Ensures credible research.  Weaknesses:  May Limit Research – Some studies (e.g., covert observations) can’t follow all guidelines.  Risk Management  Assessing Harm – Researchers must weigh benefits vs. risks.  Debriefing – Post-study explanation to mitigate distress. Moscovici et al. (1969) – Influence of a Consistent Minority on Majority Responses  Aim: To investigate whether a consistent minority could influence the majority in a color perception task, challenging the traditional view that only majorities influence individuals (Asch’s conformity research).  Procedure  Participants: 32 groups of 6 women (2 confederates, 4 naïve participants).  Design: Lab experiment with two conditions:  Consistent Minority Condition: Confederates always called blue slides "green."  Inconsistent Minority Condition: Confederates called blue slides "green" two-thirds of the time.  Task: Participants viewed 36 blue slides (varying brightness) and judged their color aloud.  Control Group: No confederates; tested natural perception of slide colors.  Findings  Consistent Minority Condition:  8.4% of participants agreed with the minority at least once.  32% of participants conformed to the minority at least once across all trials.  Inconsistent Minority Condition:  Only 1.25% agreement with the minority.  Control Group: Participants correctly identified slides as blue 0.6% of the time (baseline error rate).  Conclusion:  A consistent minority can influence majority views, but inconsistency destroys this effect.  Minority influence is weaker but more enduring than majority influence (conversion theory).  Evaluation (Strengths)  Strong Evidence for Minority Influence  Scientific Contribution: Moscovici’s study was the first to experimentally prove that minorities can change majority opinions, challenging Asch’s focus on majority influence.   Real-World Applications: Explains how social change occurs (e.g., civil rights movements, environmental campaigns).  High Control: Standardized procedure (same slides, scripted confederate responses) increases internal validity.  Supports Conversion Theory  Consistency Matters: The study confirmed that minorities must be consistent to exert influence, aligning with Moscovici’s theory that minorities create cognitive conflict, leading to deeper processing (conversion).  Long-Term Influence: Unlike majority conformity (which is often superficial), minority influence leads to private attitude change (e.g., participants later showed shifts in color perception).  Reliability & Replications  Replicated Findings: Later studies (e.g., Nemeth, 1986) confirmed that consistency is key in minority influence.  Controlled Variables: The use of a control group ruled out natural misperception of colors.  Evaluation (Weaknesses)  Ethical Issues  Deception: Participants were unaware of the true purpose (minority influence study).  Psychological Stress: Some participants may have felt confused or doubted their perception.  2. Low Ecological Validity  Artificial Task: Judging slide colors is far removed from real-life minority influence (e.g., political movements).  Gender Bias: Only female participants were used—men may respond differently (e.g., research suggests women may conform more).  Limited Immediate Influence  Weak Effects: Only 8.4% agreement per trial suggests minorities have limited power compared to majority influence (Asch: 75% conformed at least once).  Demand Characteristics: Participants may have guessed the study’s aim, reducing validity. Burger (2009) – Replicating Milgram’s Obedience Study  Aim: To investigate whether obedience levels in a Milgram-style experiment would remain high in a contemporary setting (decades after the original study) and address ethical concerns by modifying Milgram’s procedure to prevent extreme distress.  Procedure  Sample:  29 men and 41 women (aged 20-81) recruited through community advertisements.  Participants were screened to exclude those with psychological issues or who might react badly to the study.  Modified Milgram:  Stopped at 150V: Unlike Milgram (who went up to 450V), Burger stopped the experiment when participants administered a 150V shock (the point where the learner first protested).   No Extreme Stress: Participants were told they could withdraw at any time, and the experiment was carefully monitored for distress.  Two-Step Screening: Ensured participants understood the right to withdraw.  Baseline Condition:  Similar to Milgram’s original setup, with a confederate "learner" protesting at higher voltages.  The experimenter used the same verbal prods (e.g., "Please continue").  Modeled Refusal Condition (New Variation):  Before the experiment, participants saw a confederate refuse to continue.  This tested whether seeing dissent would reduce obedience.  Findings  Obedience Rates:  70% of participants were willing to continue beyond 150V (compared to 82.5% in Milgram’s equivalent point).  No significant gender difference in obedience levels.  Modeled Refusal Condition:  Obedience dropped slightly (to 63%) when participants saw someone else refuse.  However, the difference was not statistically significant.  Conclusion  People still obey authority at high rates today, suggesting that social influence mechanisms remain strong.  Situational factors (like seeing dissent) have a minor but not drastic effect on obedience.  Evaluation (Strengths)  Ethical Improvements Over Milgram  Burger’s study avoided the extreme distress seen in Milgram’s experiment by:  Stopping at 150V (before severe protests).  Allowing participants to withdraw easily.  Screening for vulnerable individuals.  Why this matters: Shows obedience can be studied ethically, making replication possible in modern psychology.  High Internal Validity (Well-Controlled)  Standardized procedure (same prods, same learner script).  Comparison to Milgram’s baseline was valid because the 150V checkpoint was used in both studies.  Why this matters: Increases confidence that results are due to obedience, not confounding variables.  Real-World Relevance  Demonstrates that obedience to harmful authority persists today, explaining modern issues like: o Workplace harassment (employees following unethical orders). o Military obedience (e.g., Abu Ghraib abuses).  Why this matters: Proves Milgram’s findings weren’t just a product of 1960s culture.  Evaluation (Weaknesses)  Lack of Full Milgram Replication (Stopping at 150V)   Burger did not test obedience up to lethal levels (450V), so we don’t know if modern participants would go as far as Milgram’s.  Why this is a problem: Obedience at lower shocks doesn’t necessarily predict extreme obedience.  Demand Characteristics (Participants May Have Guessed the Aim)  Milgram’s study was less known in the 1960s, but today, many people are aware of obedience experiments.  Some participants might have pretended to obey to "play along."  Why this is a problem: Could artificially inflate obedience rates.  Cultural & Historical Differences Not Fully Addressed  Burger’s sample was American—would other cultures show the same results? Society has changed since Milgram (more awareness of ethics, authority distrust).  Why this is a problem: Limits generalizability to other time periods and cultures. Han et al. (2014) – "Children Conform to the Behavior of Peers; Other Great Apes Stick With What They Know"  Aim: To investigate whether human children (compared to other great apes) conform to peer behavior even when they know a better alternative exists. The study aimed to understand the evolutionary roots of social conformity.  Procedure  Participants:  Human Children: 96 German 2-year-olds.  Great Apes: 12 orangutans, 12 chimpanzees, 12 bonobos (all raised in similar environments).  Task Design:  Participants were trained to associate a ball with a reward (food for apes, stickers for children).  Three conditions:  Individual Condition: No social influence; participants chose between two containers (one with a reward).  Peer Influence Condition: Three peers (confederates) consistently chose the non-rewarded container before the participant’s turn.  Reverse Condition: The rewarded container was switched to test if participants reverted to their original choice.  Measures  Conformity: Whether participants copied peers’ incorrect choice.  Persistence: Whether participants stuck to their original correct choice.  Findings  Children:  Conformed to peers 50% of the time in the Peer Influence Condition, even when they knew the other choice was better.  In the Reverse Condition, many children switched back to their original choice, showing some flexibility.  Great Apes:   Did not conform to peers; they consistently chose the correct (rewarded) container.  Showed no significant change in behavior when peers chose incorrectly.  Conclusions  Human children show social conformity, even when it goes against their own knowledge.  Great apes rely more on individual learning and do not conform to group behavior when they know a better option exists.  Suggests that human conformity may be a uniquely evolved social trait, possibly linked to complex human culture.  Evaluation (Strengths)  Cross-Species Comparison – Provides strong evidence for evolutionary differences in social learning between humans and apes.  Unlike previous studies (e.g., Asch, 1951), this directly compares humans with closely related species.  Helps explain why human societies rely more on cultural norms than ape societies.  Controlled Experimental Design – High internal validity due to:  Standardized procedure (same task for all participants).  Clear operationalization of conformity (switching to incorrect choice).  Use of confederates to ensure consistent peer influence.  Real-World Applications – Explains why children adopt behaviors even when irrational (e.g., fashion trends, peer pressure in schools).  Supports theories of cultural transmission (e.g., Boyd & Richerson, 1985).  Evaluation (Weaknesses)  Artificial Task – The experiment used a simple choice task, which may not reflect real-world conformity (low ecological validity).  In real life, conformity involves complex social dynamics (e.g., bullying, social acceptance).  Limited Sample Diversity – Only tested German 2-year-olds and captive apes.  Cultural differences? Would children from collectivist cultures (e.g., Japan) conform more?  Wild apes might behave differently (captive apes may have learned human-like behaviors).  Alternative Explanations – Children may have interpreted the task differently (e.g., thought peers knew something they didn’t).  Some studies (e.g., Whiten et al., 2005) show apes can conform in certain contexts. Practical Study  The Multi-Store Model of Memory (Atkinson & Shiffrin, 1968)  The Multi-Store Model (MSM) proposes that memory consists of three separate stores:  Sensory Register (SR) – Briefly holds sensory information (iconic = visual, echoic = auditory).  Encoding: Raw sensory input.  Capacity: Very large.  Duration: Less than 0.5 sec (iconic), 2-4 sec (echoic).  Short-Term Memory (STM) – Limited-capacity store for temporary information.  Encoding: Mainly acoustic.  Capacity: 7±2 items (Miller’s Magic Number).  Duration: ~18-30 sec (Peterson & Peterson, 1959).  Long-Term Memory (LTM) – Permanent, unlimited storage.  Encoding: Mainly semantic.  Capacity: Unlimited.  Duration: Potentially lifelong.  Key Process:  Attention moves information from SR → STM.  Rehearsal maintains STM and transfers it to LTM.  Supporting Evidence  Serial Position Effect (Glanzer & Cunitz, 1966)  Findings: Participants recall words from the start (primacy effect, LTM) and end (recency effect, STM) of a list better than middle words.  Why it supports MSM: Shows separate STM and LTM stores.  Case Study of HM (Scoville & Milner, 1957)  Findings: HM could not form new LTMs after hippocampus removal but had intact STM.  Why it supports MSM: Demonstrates distinct STM and LTM systems.  Peterson & Peterson (1959) – STM Duration  Findings: Without rehearsal, memory decayed after ~18 sec.  Why it supports MSM: Confirms STM’s limited duration.  Evaluation (Strengths)  High Experimental Validity – Supported by controlled lab studies (e.g., Peterson & Peterson, 1959), ensuring cause-and-effect conclusions.  Clear Structure – Provides a simple, testable framework for understanding memory stages (SR, STM, and LTM).  Real-World Applications – Helps explain memory techniques (e.g., rehearsal for exam revision).  Evaluation (Weaknesses)  Overly Simplistic  Evidence: Working Memory Model (Baddeley & Hitch, 1974) shows STM is not a single store.   Why it weakens MSM: STM has multiple components (e.g., phonological loop, visuospatial sketchpad).  Rehearsal is Not the Only Way to LTM  Evidence: Flashbulb memories (e.g., 9/11) are stored without rehearsal (Craik & Lockhart, 1972 – Levels of Processing). Why it weakens MSM: Emotional/semantic encoding bypasses rehearsal.  LTM is Not a Single Store  Evidence: Tulving (1985) proposed episodic, semantic, and procedural LTM.  Why it weakens MSM: LTM is more complex than MSM suggests. The Working Memory Model (Baddeley & Hitch, 1974)  The Working Memory Model (WMM) replaces STM with four components:  Central Executive (CE) – Controls attention and coordinates subsystems.  Phonological Loop (PL) – Processes auditory info (inner ear = phonological store, inner voice = articulatory rehearsal).  Visuospatial Sketchpad (VSS) – Processes visual/spatial info.  Episodic Buffer (added later, 2000) – Integrates info from PL, VSS, and LTM into a coherent episode.  Supporting Evidence  Dual-Task Performance (Baddeley & Hitch, 1976)  Findings: People struggle with two visual tasks (VSS overload) but can do visual + verbal tasks (separate stores).  Why it supports WMM: Shows PL and VSS are independent.  Phonological Similarity Effect (Baddeley, 1966)  Findings: Recall is worse for similar-sounding words (e.g., cat, cap) than dissimilar words (e.g., pen, cow).  Why it supports WMM: Confirms PL’s acoustic encoding.  Case Study of KF (Shallice & Warrington, 1970)  Findings: KF had poor verbal STM but intact visual STM after brain damage.  Why it supports WMM: Shows PL and VSS are separate.  Evaluation (Strengths)  Strong Explanatory Power – Accounts for dual-task performance (e.g., driving while talking) better than MSM.  Empirical Support – Lab experiments (e.g., phonological similarity effect) enhance reliability.  Practical Usefulness – Informs strategies for learning (e.g., using visual and verbal methods together).  Evaluation (Weaknesses)  Central Executive is Vague   Evidence: No clear explanation of how CE works (Eslinger & Damasio, 1985 – CE damage studies).  Why it weakens WMM: CE is poorly defined.  Ignores Emotional Memory  Evidence: Flashbulb memories (e.g., 9/11) involve emotional processing not explained by WMM.  Why it weakens WMM: Emotion affects memory but isn’t accounted for.  Episodic Buffer is a Late Addition  Evidence: Added in 2000, suggesting the model was incomplete.  Why it weakens WMM: Raises questions about initial validity. Reconstructive Memory (Bartlett, 1932) & Schema Theory  Bartlett (1932) argued memory is not a perfect recording but is reconstructed using past experiences (schemas).  Key Study: "War of the Ghosts"  Procedure: British participants read a Native American folk tale and recalled it later.  Findings:  Memory was distorted to fit Western schemas (e.g., "canoe" → "boat").  Simplification & Rationalization occurred.  Conclusion: Memory is an active reconstruction, not passive storage.  Supporting Evidence  Loftus & Palmer (1974) – Leading Questions  Findings: Changing verbs ("smashed" vs. "hit") altered speed estimates in car crash recall.  Why it supports Reconstructive Memory: Shows memory is flexible and influenced by schemas.  Allport & Postman (1947) – Stereotype Influence  Findings: White participants misremembered a Black man holding a razor in a fight scene.  Why it supports Reconstructive Memory: Schemas (racial stereotypes) distorted recall.  Brewer & Treyens (1981) – Office Schema Study  Findings: Participants falsely recalled office-consistent items (e.g., books) but forgot unusual ones (e.g., skull).  Why it supports Reconstructive Memory: Schemas influence what we remember.]  Evaluation( Strengths)  High Ecological Validity – Explains real-life memory errors (e.g., eyewitness testimony distortions).  Holistic Approach – Considers how past experiences (schemas) shape memory, not just storage.  Useful in Legal Settings – Highlights the unreliability of memory in court cases.  Evaluation (Weaknesses)  Lacks Scientific Rigor  Evidence: Bartlett’s study was qualitative (subjective interpretations).  Why it weakens Theory: Hard to replicate objectively.  Doesn’t Explain Accurate Recall  Evidence: Some memories (e.g., flashbulb memories) are highly accurate.  Why it weakens Theory: Not all memory is reconstructed.  Schemas Are Overused Explanations  Evidence: Cohen (1993) argued schemas are too vague to test scientifically.  Why it weakens Theory: Hard to falsify. Designing and conducting Experiments  Laboratory Experiments  Explanation:  Conducted in a controlled environment where the researcher manipulates the IV and measures the DV.  High control over extraneous variables.  Strengths:  High Internal Validity – Control over variables ensures that changes in the DV are likely due to the IV (e.g., Loftus & Palmer’s 1974 car crash study).  Replicability – Standardized procedures allow for replication to test reliability (e.g., Asch’s conformity experiments).  Precision – Accurate measurement of variables due to controlled conditions.  Weaknesses:  Low Ecological Validity – Artificial setting may not reflect real-world behavior (e.g., Milgram’s obedience study lacked real-world consequences).  Demand Characteristics – Participants may alter behavior due to awareness of being studied (e.g., Hawthorne effect).  Ethical Issues – Some lab experiments involve deception or stress (e.g., Zimbardo’s Stanford Prison Experiment).  Field Experiments  Explanation:  Conducted in a natural setting where the IV is still manipulated by the researcher.  Strengths:  Higher Ecological Validity – Natural environment increases generalizability (e.g., Paladin’s subway Samaritan study).  Reduced Demand Characteristics – Participants are unaware they are being studied, leading to more natural behavior.  Real-World Applications – Useful for studying social behaviors in authentic settings (e.g., Bickman’s uniform study).  Weaknesses:  Less Control Over Extraneous Variables – Unpredictable factors may influence results (e.g., weather in a field study).  Ethical Concerns – Lack of informed consent if participants are unaware (e.g., covert observations).  Harder to Replicate – Natural settings vary, reducing reliability. Independent and Dependent Variables  Independent Variable (IV)  The variable manipulated by the researcher to observe its effect (e.g., noise levels in a memory test).  Dependent Variable (DV)  The variable measured to see if the IV has an effect (e.g., recall accuracy in a memory test).  Evaluation: ✅Clear Cause-and-Effect – Experiments establish whether the IV directly affects the DV. ❌Operationalization Issues – Poorly defined variables reduce validity (e.g., "aggression" could be measured differently). Experimental and Null Hypotheses  Experimental Hypothesis  Predicts a significant effect of the IV on the DV (e.g., "Caffeine increases reaction time").  Null Hypothesis  States no effect (e.g., "Caffeine has no effect on reaction time").  Evaluation: ✅Scientific Rigor – Forces researchers to disprove the null hypothesis, reducing bias. ❌Type I error, or false positive, occurs when you reject a true null hypothesis, meaning you conclude there's an effect when there isn't. Conversely, ❌ Type II error, or false negative, occurs when you fail to reject a false null hypothesis, meaning you miss a real effect. Directional (One-Tailed) vs. Non-Directional (Two-Tailed) Hypotheses  Directional Hypothesis  Predicts the direction of the effect (e.g., "Alcohol slows reaction time"). ✅More Specific – Useful when prior research suggests a clear effect. ❌Risk of Missing Unexpected Results – If the effect is opposite, it’s ignored.  Non-Directional Hypothesis  Predicts an effect but not the direction (e.g., "Alcohol affects reaction time"). ✅More Flexible – Captures unexpected findings. ❌Less Precise – Doesn’t guide analysis as clearly. Experimental Designs  Repeated Measures  Same participants in all conditions. ✅Controls Participant Variables – No individual differences. ❌Order Effects – Practice or fatigue may skew results.  Independent Groups  Different participants in each condition. ✅No Order Effects – Fresh participants per condition. ❌Participant Variables – Individual differences may confound results.  Matched Pairs  Participants matched on key variables, then split into groups. ✅Balances Individual Differences – More control than independent groups. ❌Time-Consuming – Difficult to match participants perfectly. Operationalization, Extraneous & Confounding Variables  Operationalization  Defining variables in measurable terms (e.g., "aggression" as "number of shocks administered"). ✅Increases Reliability – Clear measurement criteria. ❌May Lack Validity – Oversimplifies complex behaviors.  Extraneous Variables (EVs)  Nuisance variables that could affect the DV (e.g., noise, temperature).  ✅Controlled in Labs – Enhances internal validity. ❌Hard to Control in Field Studies – Reduces reliability.  Confounding Variables  Variables that systematically change with the IV (e.g., if caffeine group also slept less). ✅Identified in Good Designs – Controlled via randomization. ❌Undermines Validity – If unnoticed, results are misleading. Control Groups, Counterbalancing, Randomization & Order Effects  Control Groups  Group with no IV manipulation for comparison. ✅Baseline Comparison – Shows if IV truly affects DV. ❌Ethical Issues – May withhold treatment (e.g., placebo in drug trials).  Counterbalancing  Alternating order of conditions to balance order effects. ✅ Reduces Practice/Fatigue Effects – E.g., ABBA design. ❌Complex for Many Conditions – Hard to implement in large studies.  Randomization  Randomly allocating participants to conditions. ✅Minimizes Bias – Distributes participant variables evenly. ❌Chance Imbalances – Small samples may still have uneven groups. Situational & Participant Variables  Situational Variables  Environmental factors (e.g., lighting, noise). ✅Controlled in Labs – Increases internal validity. ❌ Hard to Control in Real-World Studies – Affects field experiments.  Participant Variables  Individual differences (e.g., age, IQ). ✅ Matched Pairs Minimizes These – Improves validity. ❌Independent Groups Vulnerable – May skew results. Objectivity, Reliability & Validity  Objectivity  Unbiased measurement (e.g., using quantitative data). ✅Reduces Researcher Bias – More scientific. ❌May Miss Nuance – Qualitative insights lost.  Reliability  Consistency of findings (test-retest, inter-rater). ✅Replicability Strengthens Confidence – E.g., Asch’s conformity. ❌Artificial Settings May Inflate – Lab reliability ≠ real-world.  Validity  Internal: Does the IV cause the DV?  Ecological: Does it apply to real life?  Predictive: Can it forecast behavior? ✅High Control Improves Internal Validity ❌Trade-Off with Ecological Validity Experimenter Effects, Demand Characteristics & Control Issues  Experimenter Effects   Researcher’s behavior influences outcomes (e.g., Rosenthal’s Clever Hans). ✅Double-Blind Controls this – Neither participant nor does researcher know condition. ❌Hard in Small Studies – Researcher may unconsciously cue participants.  Demand Characteristics  Participants guess aims and alter behavior. ✅ Single-Blind Helps – Participants unaware of hypotheses. ❌Reduces Validity – Participants may please/resist researcher. Levels of Measurement  Explanation: Data can be classified into four levels of measurement, which determine the appropriate statistical tests:  Nominal Data – Categories with no numerical order (e.g., gender, yes/no responses).  Example: Classifying participants as "obedient" or "disobedient."  Statistical Test: Chi-squared (χ²) (non-parametric).  Ordinal Data – Ordered categories but intervals are not equal (e.g., Likert scales, rankings).  Example: Ranking participants' stress levels from 1 (low) to 5 (high).  Statistical Test: Wilcoxon signed-rank test, Spearman’s rank correlation.  Interval Data – Numerical data with equal intervals but no true zero (e.g., temperature in °C).  Example: IQ scores (0 does not mean "no intelligence").  Statistical Test: Parametric tests (t-test, Pearson’s r).  Ratio Data – Numerical data with equal intervals and a true zero (e.g., reaction time, height).  Example: Time taken to complete a task (0 seconds means no time).  Statistical Test: Parametric tests (t-test, ANOVA).  Evaluation: ✅ Helps Choose Correct Tests – Ensures appropriate statistical analysis (e.g., non-parametric for nominal/ordinal). ✅ Avoids Misinterpretation – Prevents using parametric tests on non-interval data. ❌ Not Always Clear-Cut – Some data can be ambiguous (e.g., treating Likert scales as interval in some studies). Wilcoxon Signed-Ranks Test (Difference Test)  Explanation:  Used for: Comparing two related (repeated measures) sets of ordinal data.  Example: Testing if participants' stress levels differ before and after an exam.  Procedure:  Calculate the difference between paired scores.  Rank the absolute differences (ignoring signs).  Sum the ranks for positive and negative differences separately.  The smaller sum is the observed value (T).  Compare to critical value (from Wilcoxon table) at a chosen significance level (p ≤ 0.05).  Interpretation:  If T ≤ critical value → significant difference (reject null hypothesis).   If T > critical value → no significant difference (retain null hypothesis).  Evaluation: ✅ Handles Non-Normal Data – Robust for small, skewed samples. ✅ More Powerful than Sign Test – Uses magnitude of differences, not just direction. ❌ Less Powerful Than t-test – Loses some data precision by ranking. Spearman’s Rank Correlation Coefficient (rs)  Explanation:  Used for: Assessing the strength and direction of a monotonic relationship between two ordinal/interval variables.  Example: Is there a correlation between stress levels and exam performance?  Formula:  Interpretation:  Rs ranges from -1 (perfect negative correlation) to +1 (perfect positive correlation).  0 = no correlation.  Critical Values Table:  Compare calculated rs to critical values (based on sample size and significance level, e.g., p ≤ 0.05).  If rs≥ critical value → significant correlation.  Evaluation: ✅ Works with Ordinal Data – No assumption of normal distribution. ✅ Easy to Compute – Simple ranking method. ❌ Only Measures Monotonic Relationships – Misses non-linear trends. Probability and Levels of Significance (p-values)  Explanation:  P-value: Probability that results are due to chance.  Common significance levels:  P ≤ 0.10 (10% chance of Type I error – lenient).  P ≤ 0.05 (5% chance – standard in psychology).  P ≤ 0.01 (1% chance – strict).  Example:  If p = 0.03 → significant at p ≤ 0.05 (reject null hypothesis).  If p = 0.07 → not significant at p ≤ 0.05 (retain null hypothesis).  Evaluation: ✅ Standardized Threshold – Allows consistency across studies. ✅ Reduces Type I Errors – Lower p-values reduce false positives. ❌ Arbitrary Cut-Offs – p = 0.051 vs. 0.049 treated very differently. Observed vs. Critical Values & Sense Checking  Explanation:  Observed Value: Calculated test statistic (e.g., T in Wilcoxon, rsrs in Spearman’s).  Critical Value: Threshold from statistical tables for significance.  Decision Rule:  If observed ≥ critical (for some tests, ≤) → significant.  Sense Checking: Ensure results align with data (e.g., a negative correlation shouldn’t be reported as positive).  Example:  Wilcoxon: T = 5, critical = 8 → significant (since T ≤ critical).  Spearman’s: rs= 0.60, critical = 0.50 → significant.  Evaluation: ✅ Objective Decision-Making – Removes researcher bias. ✅ Prevents False Conclusions – Checks for consistency. ❌ Over-Reliance on Tables – Critical values vary by sample size. One-Tailed vs. Two-Tailed Tests  Explanation:  One-Tailed Test: Predicts direction of effect (e.g., "Group A will score higher than Group B").  More powerful (easier to find significance).  Critical value is stricter in one direction.  Two-Tailed Test: Predicts any difference (e.g., "Groups will differ").  More conservative (harder to find significance).  Splits alpha level (e.g., p ≤ 0.025 per tail for p ≤ 0.05 total).  Example:  One-tailed Wilcoxon: Only checks if scores increase (not decrease).  Two-tailed Spearman’s: Checks for any correlation (positive or negative).  Evaluation: ✅ One-Tailed Increases Power – Useful for directional hypotheses. ✅ Two-Tailed More Rigorous – Avoids missing unexpected effects. ❌ One-Tailed Can Miss Effects – Ignores results in the "wrong" direction. Type I and Type II Errors  Explanation:  Type I Error (False Positive): Incorrectly rejecting the null hypothesis (claiming an effect when none exists).  Controlled by p-value (e.g., p ≤ 0.05 means 5% risk).  Type II Error (False Negative): Failing to reject a false null hypothesis (missing a real effect).  Reduced by increasing power (larger sample size, stronger effect).  Example:  Type I: Concluding a drug works when it doesn’t.  Type II: Concluding a drug doesn’t work when it does.  Evaluation: ✅ Balancing Errors Possible – Adjusting p-values and sample sizes. ✅ Real-World Implications – Critical in medical/psychological research. ❌ Trade-Off between Errors – Reducing Type I increases Type II risk. Case Study: Henry Molaison (HM) – Scoville & Milner (1957)  Background & Aim  HM suffered from severe epilepsy, leading to bilateral medial temporal lobe removal (including hippocampus) in 1953 at age 27.  Aim: To understand how brain damage affects memory.  Procedure  Studied over 50+ years using:  Cognitive testing (memory tasks, IQ tests).  Interviews & observations (e.g., recognizing doctors but not recalling visits).  Brain scans (post-mortem) confirming hippocampal damage.  Findings  Severe Anterograde Amnesia – Could not form new long-term memories (e.g., didn’t remember daily events).  Intact Short-Term Memory (STM) – Could hold conversations briefly but forgot them quickly.  Preserved Procedural Memory – Learned motor tasks (e.g., mirror drawing) despite no conscious recall.  Retrograde Amnesia (Partial) – Lost memories from ~11 years before surgery but retained older ones.  Conclusions  The hippocampus is critical for forming new explicit (declarative) memories but not for implicit (procedural) memory.  Supports the distinction between STM and LTM in the Multi-Store Model.  Evaluation (Strengths)  Revolutionized Memory Research – First clear evidence that the hippocampus is vital for memory consolidation  High Ecological Validity – Real-life memory deficits studied in depth over decades.  Supported Cognitive Theories – Confirmed separate memory systems (e.g., procedural vs. declarative).  Evaluation (Weaknesses)  Generalizability Issues – Unique case (rare surgery); may not apply to all amnesia patients.  Lack of Pre-Surgery Data – No baseline memory tests before HM’s operation.  Ethical Concerns – HM could not give informed consent due to his condition. Other Key Case Studies  Clive Wearing (Severe Anterograde & Retrograde Amnesia)  Cause: Herpes simplex encephalitis damaged his hippocampus and adjacent cortex.  Findings:  No new memories (STM lasted seconds).  Intact procedural memory (could still play piano).  Emotional memory preserved (recognized his wife but didn’t know why).  Contribution: Reinforced HM’s findings, showing multiple memory systems.  Patient KF (Shallice & Warrington, 1970)  Brain Damage: Parietal lobe lesion impaired STM but spared LTM.  Findings:  Digit span of only 2 items (vs. average 7±2).  Could form new long-term memories.  Contribution: Supported the Working Memory Model (damage to phonological loop).  Patient EP (Squire et al., 1989)  Damage: Medial temporal lobes (like HM).  Findings:  Severe anterograde amnesia but intact semantic memory (knew historical facts).  Contribution: Showed semantic and episodic memory separation. Theoretical Contributions  Multi-Store Model (Atkinson & Shiffrin, 1968)  Supported by HM & KF:  HM showed STM intact but LTM impaired.  KF showed STM impaired but LTM intact.  Limitation: Oversimplifies memory (doesn’t explain procedural memory preservation).  Working Memory Model (Baddeley & Hitch, 1974)  Supported by KF:  His phonological loop damage explained poor verbal STM.  Limitation: Doesn’t fully explain HM’s deficits.  Tulving’s Memory Systems (1985)  Episodic (HM/Clive) vs. Semantic (EP) vs. Procedural (HM/Clive) distinctions confirmed.  Evaluation of Brain-Damaged Case Studies (Strengths)  Unique Insights – Reveal brain-memory links that experiments cannot.  Longitudinal Data – HM studied for 50+ years, providing rich qualitative/quantitative data.  Real-World Applications – Helped develop treatments for amnesia (e.g., memory rehabilitation).  Evaluation of Brain-Damaged Case Studies (Weaknesses)  Case-Specific – Brain damage varies; hard to generalize.  No Control Over Variables – Pre-existing conditions may confound results.  Ethical Issues – Patients cannot consent; privacy concerns (e.g., HM’s identity revealed post-mortem Classic Study: Bartlett (1932) – War of the Ghosts  Aim: To investigate how cultural schemas influence memory by testing how British participants recalled a Native American folk tale ("War of the Ghosts").  Procedure  Participants: British students unfamiliar with Native American culture.  Method: Serial reproduction (chain storytelling) and repeated reproduction (same person recalls over time).   Material: Participants read the unfamiliar story and recalled it after different delays (minutes to years).  Findings  Distortions: Story became shorter and more conventional (e.g., "canoes" became "boats").  Rationalization: Unfamiliar elements (e.g., "ghosts") were omitted or altered to fit Western schemas.  Levelling: Less important details were dropped.  Sharpening: Some details were exaggerated to fit expectations.  Conclusion: Memory is not a perfect recording but a reconstructive process influenced by schemas (mental frameworks based on prior knowledge).  Evaluation (Strengths)  Real-World Applications – Explains why eyewitness testimony is unreliable (memory changes over time).  Pioneering Work – First to challenge the idea of memory as a passive recording, introducing reconstructive memory theory.  Ecological Validity – Used meaningful material (a story) rather than nonsense syllables (like Ebbinghaus).  Evaluation (Weaknesses)  Lack of Control – No standardized procedure (e.g., different delays for different participants).  Qualitative Data – Subjective interpretation of distortions (hard to measure objectively).  Ethnocentric Bias – Only tested British participants; may not generalise to other cultures. Contemporary Study: Schmolck et al. (2002) – Semantic Memory in Patient HM  Aim: To investigate how different brain regions (medial vs. lateral temporal lobes) affect semantic (general knowledge) and episodic (personal event) memory.  Procedure  Participants:  Patient HM (bilateral medial temporal lobe damage).  Other patients with lateral temporal lobe damage.  Healthy controls.  Task: Recall of famous public events (semantic memory) and personal events (episodic memory).  Findings  HM – Severe episodic memory impairment (couldn’t recall personal events) but intact semantic memory (could recall facts).  Lateral Lobe Patients – Impaired semantic memory but normal episodic memory.  Conclusion  Medial temporal lobe (hippocampus) is crucial for episodic memory.  Lateral temporal lobe is more involved in semantic memory.  Evaluation (Strengths)  High Scientific Rigor – Controlled case studies with brain scans (objective evidence).   Supports Memory Models – Confirms Tulving’s (1985) distinction between episodic and semantic memory.  Real-World Applications – Helps understand amnesia and brain injury treatment.  Evaluation (Weaknesses)  Small Sample – Only a few brain-damaged patients (limits generalisability).  Case Study Limitations – Cannot establish cause-and-effect (natural brain damage, not manipulated).  Lacks Ecological Validity – Lab-based memory tests may not reflect real-life memory use. Contemporary Study Choice: Sacchi et al. (2007) – Doctored Photos Affect Memory  Aim: To test if manipulated photographs could distort memory of past public events.  Procedure  Participants: Italian university students.  Method: Shown doctored photos of a 1969 protest (either with or without police presence).  Task: Later asked to recall the event and rate their confidence.  Findings  False Memory Creation – 45% of those shown doctored photos recalled the false detail (police presence).  Confidence – Some participants were highly confident in their false memories.  Conclusion: Photographs can alter reconstructive memory, leading to false beliefs about the past.  Evaluation (Strengths)  Strong Experimental Control – Randomized groups and standardized images.  Real-World Implications – Warns about media manipulation (e.g., fake news altering public memory).  Supports Bartlett’s Theory – Shows memory is reconstructive and prone to distortion.  Evaluation (Weaknesses)  Artificial Setting – May not reflect how people process real-life media.  Ethical Concerns – Deliberately implanting false memories could distress participants.  Cultural Specificity – Only tested Italians; may not apply universally. Practical Study 