Planning and conducting research

Welcome to Your Research Journey!

Ever wondered how psychologists actually find things out? They don't just guess; they follow a strict "blueprint" called research methods. In this chapter, we are going to look at the Planning and Conducting Research stage. Think of this as the "architect's plan" for an experiment. If the plan is weak, the whole house falls down! Don't worry if it seems like a lot of terms at first—we’ll take it one step at a time.

1. Aims and Hypotheses

Before a psychologist starts, they need to know what they are looking for.

The Research Aim and Question

The research aim is a general statement of what the researcher intends to investigate (the purpose of the study).
The research question is the specific question the researcher wants to answer.
Example: "To investigate if caffeine affects memory" (Aim). "Does drinking one cup of coffee improve recall of a word list?" (Question).

Types of Hypotheses

A hypothesis is a clear, testable statement predicting the outcome of the study. You need to know four types:

• Alternative Hypothesis: Predicts that there will be a significant difference or relationship.
• Null Hypothesis: Predicts that there will be no significant difference. Any difference found is just down to chance.
• One-tailed (Directional) Hypothesis: Predicts the specific direction of the results.
Example: "Students who drink coffee will remember more words than those who don't."
• Two-tailed (Non-directional) Hypothesis: Predicts there will be a difference, but doesn't say which way.
Example: "There will be a difference in the number of words remembered between the coffee group and the no-coffee group."

Quick Review: Use a one-tailed hypothesis if previous research suggests which way the results will go. Use a two-tailed hypothesis if it's a brand-new area of study!

2. Populations and Sampling

You can't test everyone in the world, so you need a smaller group.

Key Terms

• Target Population: The entire group of people the researcher is interested in (e.g., "Teenagers in the UK").
• Sample: The actual people who take part in the study.

Sampling Techniques

• Random Sampling: Every member of the target population has an equal chance of being picked (like pulling names out of a hat).
• Snowball Sampling: You find one participant, and they "recruit" their friends, who recruit their friends. Great for hard-to-reach groups!
• Opportunity Sampling: You simply ask whoever is available at the time (e.g., asking people in the canteen).
• Self-selected Sampling: Participants volunteer themselves (e.g., replying to an advert in a newspaper).

Memory Aid: Remember ROSS (Random, Opportunity, Self-selected, Snowball) to help you list the techniques!

3. Experimental Designs

This is about how you organize your participants into groups.

• Independent Measures Design: Different participants are used in each condition of the IV.
Example: Group A drinks coffee, Group B drinks water.
• Repeated Measures Design: The same participants take part in all conditions.
Example: Everyone drinks water on Monday and coffee on Tuesday.
• Matched Participants Design: Different participants are in each condition, but they are "paired up" based on similar traits (like IQ or age). One twin might go to Group A, the other to Group B.

Common Mistake: Don't confuse "Sampling" (how you get people) with "Design" (how you sort them into groups)!

4. Research Designs

Sometimes we study people over time.

• Longitudinal Research: Studying the same group of people over a long period (months or years). Like a "time-lapse" of their lives!
• Cross-sectional Research: Comparing different groups of people at the same point in time (e.g., comparing 5-year-olds, 10-year-olds, and 15-year-olds today).

5. Variables and Operationalisation

To make a study scientific, we must be precise.

• Independent Variable (IV): The thing the researcher changes or manipulates.
• Dependent Variable (DV): The thing the researcher measures.
• Operationalisation: Defining variables in a way that makes them measurable.
Example: Instead of saying "Intelligence," you say "Score on a 20-minute IQ test."

Extraneous Variables

These are "nuisance" variables that might ruin your results if you don't control them.
• Researcher variables: The researcher's behavior or appearance affects the participant.
• Situational variables: Factors in the environment (like noise or temperature).
• Participant variables: Individual differences between people (like mood or natural ability).

Key Takeaway: We want to control extraneous variables so we can be sure the IV is the only thing causing the change in the DV.

6. Designing Observations

If you are watching people, you need a system so you don't miss anything.

• Behavioural Categories: Breaking down a stream of behavior into specific, measurable actions.
Example: If observing "aggression," you might check boxes for "hitting," "shouting," or "pushing."
• Time Sampling: Recording behavior at specific time intervals (e.g., every 30 seconds).
• Event Sampling: Recording every single time a specific behavior happens, no matter when it occurs.

7. Designing Self-Reports

Self-reports involve asking people about themselves via questionnaires or interviews.

• Open Questions: Allow participants to answer in their own words (provides rich detail).
• Closed Questions: Fixed responses (e.g., Yes/No) that are easy to turn into statistics.

Rating Scales

Psychologists love scales to measure attitudes:
• Numerical Rating Scale: Assigning a number (e.g., 1 to 10).
• Likert Rating Scale: Asking how much someone agrees (Strongly Disagree to Strongly Agree).
• Semantic Differential Rating Scale: Using opposite adjectives at either end of a scale.
Example: Happy [ ] [ ] [ ] [ ] [ ] Sad.

Did you know? The Likert scale is named after its creator, Rensis Likert! It’s the most common way psychologists measure attitudes today.

Summary: Planning Checklist

Before starting your research, make sure you have:
1. A clear Aim and Hypothesis.
2. A Target Population and Sampling Technique.
3. A decided Experimental Design (e.g., Repeated Measures).
4. Operationalised your IV and DV.
5. Controlled your Extraneous Variables.

Don't worry if this seems tricky at first! The more you look at actual studies (Core Studies), the more these "blueprint" steps will make sense.