Experiments & Education (AQA A Level Sociology): Revision Note

Experiments allow for tight control of variables through random allocation and standardised procedures.

In education, it is difficult to isolate variables such as class size, school ethos, and streaming.

Data is collected systematically, producing clear, measurable outputs (e.g., test scores, IQ points).

Establishing cause-and-effect relationships (e.g. between teacher expectations and achievement) is time-consuming.

Simulations or the use of secondary data can reduce the chances of ethical issues arising.

Studies involving real pupils raise ethical concerns such as deception, unequal treatment, and psychological harm.

Informed consent can be obtained in controlled environments, allowing for clearer safeguarding protocols.

Young participants may not fully understand the nature of the research, raising concerns about informed consent and vulnerability.

Favoured by positivists for producing objective, reliable data and allowing theory testing.

Controlled designs often have a narrow focus, ignoring broader structural influences like poverty or school culture.

Enables researchers to test specific hypotheses and examine variables like labelling or self-fulfilling prophecy.

The Hawthorne effect may distort results—teachers or students may change their behaviour if they know they’re being studied.

Produces quantitative data suitable for statistical analysis and comparisons between schools, classes and teachers.

Interpretation is subjective, as researchers may disagree on what counts as positive or negative teacher behaviour.

High replicability, as standardised designs allow the experiment to be repeated to test reliability.

Controlled settings do not reflect real classrooms, limiting ecological validity and generalisability.

Take place in real-world settings (e.g., classrooms, schools), avoiding the artificiality of lab conditions.

Control is limited, as external factors such as school ethos, timetable, or pupil background affect outcomes.

Can study past or ongoing events (e.g., policy changes) using available data, making them cost-effective.

Finding a link between teacher labelling and academic performance takes time, so it is unlikely to be investigated.

Ethical concerns are reduced when existing data is used or when studies are non-intrusive.

Field experiments involving real pupils may still raise concerns over deception, consent, or unequal treatment.

More acceptable in school settings, as they observe natural behaviour without disrupting learning.

Vulnerability of participants (especially children) requires strict safeguarding—some may not fully understand the research.

Favoured by both positivists (for larger datasets) and interpretivists (for natural context and meaning).

Replication is difficult – school contexts are unique, and policy impacts (e.g., Covid-19) can't be reproduced exactly.

Useful for evaluating the real-world impact of education policies using comparative or longitudinal data.

The Hawthorne effect may still occur—staff and pupils may alter behaviour when they know they’re being studied.

Often use larger, more representative samples than lab experiments, improving generalisability.

Establishing causal relationships is harder, as many variables are uncontrolled.

Realistic setting increases ecological validity – findings are more reflective of everyday school life.

Interpretation may be subjective, especially in identifying what constitutes a positive or negative outcome.