Research Methods and Experimental Designs

Correlations are brilliant for exploring connections between variables when experiments aren't practical or ethical. Think studying social media use and mental health - you can't exactly force people to use Instagram for science! They're perfect starting points for research, but remember: correlation doesn't equal causation.

The tricky bit is that you need loads of data for reliable results, which gets expensive fast. Plus, there might be hidden third variables messing with your findings - like discovering violent games correlate with aggression, but maybe it's actually stress causing both.

Independent groups designs compare different people in each condition, which sounds simple but creates headaches with participant variables. Meanwhile, the notes mention repeated measures and matched pairs but don't give details - these are alternative ways to set up your study participants.

Opportunity sampling involves grabbing whoever's available and willing to participate. It's the "ask people walking down the street" approach - super convenient but not always representative of your target population.

Key Point: Choose your research method based on what you're investigating and what's practically possible, not just what seems easiest.

Types of Experiments

Field experiments happen in real-world settings, giving you brilliant ecological validity because people behave naturally. Participants often don't even know they're in a study, so no fake behaviour to please researchers. However, this creates ethical nightmares - no consent, no right to withdraw knowledge.

The biggest headache with field experiments is losing control over extraneous variables. You can't control the environment like in a lab, making it harder to prove your independent variable actually caused the changes you observed. Replication becomes nearly impossible too.

Laboratory experiments offer maximum control but sacrifice realism. Natural experiments study situations that occur naturally - the notes mention these but don't elaborate on their specific strengths and weaknesses.

Remember: Higher ecological validity often means lower experimental control - it's always a trade-off in psychology research.

Murdock's Serial Position Study

Ever notice how you remember the first and last items on a shopping list but forget everything in the middle? That's exactly what Murdock investigated with 103 students listening to word lists of varying lengths.

The results showed a clear serial position curve - words at the beginning benefited from the primacy effect while words at the end showed the recency effect. Basically, your brain's brilliant at remembering starts and endings but rubbish at middles.

However, the study has limitations. Using only students means we can't generalise to everyone else, especially non-students who might process information differently. The artificial lab setting might have made participants nervous, affecting their natural memory performance.

The repeated testing created additional problems - participants got bored, tired, or figured out the study's aim and started showing demand characteristics (acting to please the researcher rather than behaving naturally).

Study Tip: This demonstrates how memory position affects recall - use this knowledge when revising by paying extra attention to middle content!

Bartlett's War of the Ghosts Study

Bartlett wanted to understand how our cultural background shapes what we remember. He used serial reproduction - basically an academic version of Chinese whispers - asking UK participants to retell a Native American folk story after different time intervals.

The fascinating results showed that people didn't just forget bits randomly. Instead, they reconstructed memories using their own cultural framework. Canoes became boats, unfamiliar concepts got replaced with familiar ones, and the story got progressively shorter and more "British."

This proved we don't store memories like video recordings. Instead, we remember fragments and fill gaps using our existing knowledge and cultural expectations. Each retelling becomes our new "memory" of the original story.

The study lacked proper controls though - participants weren't given standardised instructions, and Bartlett's own biases might have influenced how he interpreted the results. Later research showed more accurate recall when participants knew accuracy mattered from the start.

Key Insight: Your memories are more like creative reconstructions than factual recordings - they're influenced by your experiences and culture.

Multi-Store Model of Memory

The Multi-Store Model by Atkinson and Shiffrin presents memory as three distinct stores: sensory, short-term, and long-term. Information flows through them like a factory production line, but only if you pay attention and rehearse properly.

Each store has different characteristics. Sensory memory lasts less than a second, short-term memory holds about 7 items for up to 30 seconds using acoustic encoding, while long-term memory has unlimited capacity and duration using semantic encoding.

The model's strength lies in research support - studies consistently show these three stores exist and differ in capacity, duration, and encoding. It also provides practical memory tips: pay attention in lessons to transfer information from sensory to short-term memory, then rehearse to get it into long-term storage.

However, it's oversimplified. The model can't explain why some unrehearsed information sticks while rehearsed material gets forgotten. It also ignores different types of long-term memory (procedural, episodic, semantic) and doesn't distinguish between maintenance and elaborative rehearsal.

Memory Hack: Use the model's principles - pay attention, then actively rehearse important information rather than just reading it repeatedly.

Theories of Perception: Nature vs Nurture

Gibson's Direct Theory argues that perception is innate - you're born knowing how to interpret the visual world. The environment provides rich information through light, texture, and movement that your eye naturally detects without needing past experience or learning.

Gregory's Constructivist Theory takes the opposite view. He claims perception is learned through experience (nurture) - your cultural background and upbringing shape how you interpret visual cues. Your perception becomes more sophisticated as you interact with the world.

Gibson struggles with visual illusions - if perception is just about detecting rich environmental information, why do our brains make perceptual errors? The visual cliff experiment supports Gibson though, showing very young infants instinctively avoid apparent drops.

Gregory handles cultural differences in perception brilliantly - people from different cultures literally see things differently because of their experiences. However, he can't explain how perception gets started initially, and babies show some perceptual abilities from birth, like preferring human faces to random patterns.

Think About It: Both theories have merit - some perception seems innate while other aspects are clearly learned through cultural experience.

Visual Illusions

The notes mention several famous visual illusions including the Ponzo, Müller-Lyer, Rubin's Vase, Kanizsa Triangle, Ames Room, and Necker Cube. These illusions demonstrate how our brain interprets visual information in ways that don't always match physical reality.

Visual illusions are crucial for understanding perception theories. They support Gregory's constructivist approach by showing how our brain actively interprets and sometimes misinterprets visual information based on past experience and expectations.

These illusions reveal that perception isn't just passive reception of visual data (as Gibson might suggest) but involves active cognitive processing. Our brain makes assumptions and fills in gaps, sometimes leading to systematic errors in what we "see."

Key Point: Visual illusions prove that perception involves more than just detecting environmental information - your brain actively constructs what you experience.

Gilchrist and Nesberg's Motivation Study

Can hunger actually make food look brighter and more appealing? Gilchrist and Nesberg tested this by having 26 students go without food for 20 hours, then comparing their perception of food pictures to a control group who ate normally.

Participants viewed slides of meals (steak, chicken, burgers, spaghetti) for 15 seconds each. When asked to adjust the lighting to match what they'd seen, the hungry group consistently made food pictures brighter, suggesting they'd perceived them as more vivid than they actually were.

This demonstrates how motivation affects perceptual set - your basic needs and desires literally change what you see. When you're hungry, food-related stimuli become more prominent and appealing, showing perception isn't just objective reality.

The study raises ethical concerns about food deprivation, even for 20 hours. Participants might not have fully understood the discomfort involved. Additionally, using pictures rather than real food and asking people to judge brightness creates an artificial situation that doesn't reflect everyday perception.

Real-World Application: This explains why food shopping when hungry leads to buying more - you literally perceive food as more appealing!

Bruner and Minturn's Perceptual Set Study

Bruner and Minturn created a clever experiment using an ambiguous figure that could be seen as either the letter 'B' or the number '13', depending on context. They wanted to test whether expectation influences what we actually perceive.

Using an independent groups design, one group saw the ambiguous figure surrounded by letters (A, ?, C) while the other saw it surrounded by numbers (12, ?, 14). The results were striking - letter group participants saw 'B' while number group participants saw '13'.

This proves that expectation is crucial for perceptual set. Your brain doesn't just passively receive visual information - it actively interprets it based on context and what you're expecting to see. Change the context, change the perception.

However, the study uses artificial stimuli that rarely occur in real life. We don't often encounter truly ambiguous figures, so the findings might not apply to everyday perception. The independent groups design also creates potential problems with participant variables - maybe some groups naturally had more people whose names began with 'B'!

Study Application: This explains why proofreading your own work is hard - you expect to see what you wrote, not the typos that are actually there.

Piaget's Cognitive Development Theory

Piaget proposed that children's thinking develops through four distinct stages: Sensorimotor, Pre-operational, Concrete Operational, and Formal Operational. Each stage has different cognitive abilities and limitations.

The key concept here is egocentrism - children under seven $in the pre-operational stage$ can only see the world from their own perspective. They genuinely think everyone sees exactly what they see. After age seven (concrete operational stage), children develop the ability to understand other viewpoints.

Piaget's theory has massively influenced education, promoting child-centred learning with focus on readiness and discovery. However, he underestimated children's abilities - studies like Hughes' policeman doll experiment show kids can think more sophisticatedly than Piaget suggested when tested differently.

The theory also assumes everyone reaches the formal operational stage (abstract, logical thinking), but research shows this isn't universal. Additionally, Piaget used a small sample of middle-class Swiss children, limiting how well his findings apply to children from different cultures and social backgrounds.

Educational Impact: Understanding these stages helps explain why certain concepts are taught at specific ages - children's brains literally aren't ready for some ideas until later stages.