Psychology · Year 10 · Research Methods · 4.º Período

Experimental Designs and Sampling

This topic introduces different experimental designs, including independent groups and repeated measures. Students will also evaluate various sampling methods used to select participants.

TL;DR:Once a hypothesis is set, researchers must decide on the best design and sampling method. Students learn about independent groups, repeated measures, and matched pairs designs, evaluating the pros and cons of each. They also explore how to select a representative sample using methods like random, systematic, and stratified sampling.

• National Curriculum Attainment Targets
• GCSE Psychology (AQA) 3.2.1.3: Experimental designs
• GCSE Psychology (AQA) 3.2.1.4: Sampling methods

About This Topic

Once a hypothesis is set, researchers must decide on the best design and sampling method. Students learn about independent groups, repeated measures, and matched pairs designs, evaluating the pros and cons of each. They also explore how to select a representative sample using methods like random, systematic, and stratified sampling.

This topic is crucial for understanding the validity and reliability of psychological research. It teaches students to look critically at who was studied and how the experiment was structured. Students grasp this concept faster through structured discussion and peer explanation of how different designs might lead to different conclusions.

Key Questions

1. What are the advantages of a repeated measures design?
2. How do researchers select a representative sample?
3. What is the difference between random and stratified sampling?

Watch Out for These Misconceptions

Common Misconception

Random sampling just means picking people at random on the street.

What to Teach Instead

That is actually 'opportunity sampling.' Random sampling requires that every member of the target population has an equal chance of being chosen, usually via a computer or hat. A 'sampling hat' activity can demonstrate this difference.

Common Misconception

Repeated measures is always the best design because you need fewer people.

What to Teach Instead

While it uses fewer participants, it can suffer from 'order effects' where people get better or bored. A quick task where students do a puzzle twice can show how 'practice effects' can bias the results.

Active Learning Ideas

Simulation Game

Sampling the School

Students are tasked with getting a 'representative sample' of the class. They must try out different methods (random, opportunity, systematic) and compare their results to see which method produced the most diverse and fair group.

30 min·Small Groups

Stations Rotation

Design Dilemmas

Set up stations with different research scenarios. At each station, students must choose between independent groups or repeated measures, justifying their choice based on issues like order effects or participant variables.

40 min·Small Groups

Inquiry Circle

The Bias Detective

Groups are given famous (or made-up) studies with flawed sampling or designs. They must identify the 'bias' (e.g., only using students) and propose a better sampling method or design to improve the study's validity.

35 min·Small Groups

Frequently Asked Questions

What are order effects in psychology?

Order effects occur in a repeated measures design when the sequence in which tasks are performed influences the results. This could be due to practice (getting better) or fatigue (getting tired or bored), which can make the results less valid.

What is the difference between random and stratified sampling?

Random sampling gives everyone in a population an equal chance of being picked. Stratified sampling involves dividing the population into sub-groups (like age or gender) and then picking people from those groups in proportion to the whole population.

Why is a representative sample important?

A representative sample ensures that the people in the study reflect the diversity of the larger target population. This allows researchers to 'generalise' their findings, meaning they can be reasonably sure the results apply to everyone, not just the small group they tested.

How can active learning help students understand experimental designs?

Active learning allows students to experience the 'flaws' of each design firsthand. For example, by participating in a repeated measures task, they can feel the impact of order effects, which makes the theoretical solutions (like counterbalancing) much more meaningful.