Active learning ideas
Experimental design is the 'how-to' of psychology. Students learn to move from a general idea to a testable, operationalised hypothesis. They explore the different types of experiments (lab, field, natural) and the crucial role of variables, independent, dependent, and extraneous. This topic is the foundation of all psychological research and is heavily weighted in the AQA GCSE exams.
Activity 01
Students are given a series of 'bad' experiment descriptions. In groups, they must identify the IV, DV, and at least three extraneous variables that could 'mess up' the results, then propose a way to control them.
What is a null hypothesis?
Activity 02
The class conducts the same simple memory test twice: once in a strictly controlled 'lab' (silent classroom) and once in a 'field' (the noisy canteen). They then compare the results and discuss the trade-off between control and realism.
How do researchers control extraneous variables?
Activity 03
Students are given a topic (e.g., 'Does music help you study?'). They must work in pairs to write a null hypothesis and a directional hypothesis, ensuring both are fully operationalised.
What are the strengths of a laboratory experiment?
A few notes on teaching this unit
Watch Out for These Misconceptions
A hypothesis is just a 'guess'.
In psychology, a hypothesis must be a precise, testable statement that predicts the relationship between variables. A 'hypothesis surgery' activity where students fix 'vague' guesses helps them learn to operationalise their terms.
Extraneous variables always ruin an experiment.
They only become a problem if they aren't controlled and turn into 'confounding' variables. Through peer-reviewing each other's designs, students learn that identifying and managing these variables is a standard part of good science.
Methods used in this brief
Sampling and Ethics
An examination of different sampling techniques and the ethical guidelines set by the British Psychological Society (BPS). Students will evaluate the importance of informed consent and debriefing.
8 methodologies
Data Handling and Analysis
Students develop skills in quantitative and qualitative data analysis, including calculating measures of central tendency and interpreting graphs. They will learn to draw conclusions from raw data.
8 methodologies