IGCSE Pscyhology Paper 1 — Research Methods Flashcards
Chapter 4: Hypothesis and Variables Independent Variable (IV)
The independent variable is the factor that the researcher intentionally manipulates to observe its effect.
In this investigation, the independent variable is whether participants are performing the task in front of an audience or on their own. This manipulation allows the researcher to examine the effect of social presence on performance.
There are two levels (or conditions) of the IV:
One group completes the task with an audience present.
The other group completes the task alone.
Having more than one level is essential, as it enables comparison. Without a second condition, we would not be able to determine whether the presence of an audience has any impact.
Chapter 4: Hypothesis and Variables Dependent Variable (DV)
The dependent variable is the outcome that the researcher measures. It is expected to change depending on the IV.
In this case, the dependent variable is the number of balls successfully thrown into a bucket (out of 20). This is the performance measure that will be recorded and analysed.
In a well-designed experiment, the only factor that should influence the dependent variable is the change in the independent variable. All other potential influences must be kept constant and controlled, to ensure the results are valid.
Chapter 4: Hypothesis and Variables Operationalisation of Variables
In any scientific investigation, it is essential that variables are defined in a clear and measurable way. This ensures that the research can be accurately conducted and replicated.
Chapter 4: Hypothesis and Variables Formulating a Testable Hypothesis
Once an investigation has been planned, it is essential to develop a testable hypothesis—a clear and precise statement that outlines the expected relationship between the variables involved in the study.
A hypothesis refers to a prediction regarding how the independent variable (IV) will influence the dependent variable (DV):
The independent variable is the factor deliberately manipulated by the researcher (in this case, whether participants perform in front of an audience or alone).
The dependent variable is the factor being measured (the number of balls successfully thrown into a bucket out of 20).
In order to ensure clarity and replicability, the variables must be operationalised—that is, defined in specific, measurable terms.
Example of an alternative hypothesis:
There is a difference in the number of balls thrown into a bucket (out of 20) by participants performing with an audience of 30 people compared to those performing the task alone.
This statement represents the alternative hypothesis, which suggests that the presence of an audience will have an effect on performance.
However, it is also necessary to consider the possibility that the independent variable may have no impact on the dependent variable. In this case, researchers also formulate a null hypothesis.
Example of a null hypothesis:
There is nodifference in the number of balls thrown into a bucket (out of 20) by participants performing with an audience of 30 people compared to those performing the task alone.
Having clearly defined both the alternative and null hypotheses, the study can proceed, and the data collected will help determine which hypothesis is supported by the evidence.
Chapter 4: Extraneous Variables
Definition of Extraneous Variables
Extraneous variables (EVs) are any unwanted variables that may interfere with the relationship between the IV and the DV. These variables are not the focus of the investigation, but if not managed properly, they can threaten the validity of the results by introducing alternative explanations for any observed effects.
It is the responsibility of the researcher to identify potential extraneous variables during the planning phase of the experiment and implement strategies to control them.
Establishing Cause and Effect
In a well-designed experiment, the only factor that should influence the dependent variable (DV) is the independent variable (IV). Any other variables that might affect the DV should be either controlled or eliminated. When the IV is the sole influence on the DV, the researcher is able to demonstrate a cause-and-effect relationship.
In the “balls in a bucket” experiment, the independent variable is whether participants perform the task in front of an audience or alone. To ensure valid results, all other conditions must remain consistent between the two experimental groups.
Controlled variables should include:
- The physical environment (e.g., the same room setup),
- The equipment used (e.g., identical balls and buckets),
- The procedure (e.g., same distance to the bucket, same instructions).
Additionally, to reduce individual differences among participants, the sample might be restricted to individuals with similar characteristics such as age, height, or eyesight—though such standardization can be more challenging in practice.
Chapter 4: Extraneous Variables Research Procedures
Scientists have learned that it’s important to plan their studies carefully to control factors that could affect the results (called extraneous variables or EVs).
Instructions to Participants:
All participants should get the same information during the study. This is called “standardized instructions.” Before the study starts, researchers write down exactly what they will say to each participant. This can include:
- Explaining the task they need to do.
- Telling them how to record their answers.
- Letting them know they can leave the study anytime.
Standardized instructions help make sure that the information given doesn’t influence the results. For example, if one participant is told to “do their best” but another is not, it could affect their performance.
Chapter 4: Extraneous Variables Standardized Procedures
Standardized Procedures: Standardized instructions are part of a broader set of rules called “standardized procedures.” This means:
All participants receive the same information at the beginning of the study.
They get the same instructions throughout.
They are tested in the same environment.
The only thing that should change is the independent variable (IV), which is the factor being tested. This is easier in a lab setting than in real-world situations (like testing the effects of coffee in a coffee shop). In a lab, it’s simpler to control the environment to prevent any factors from becoming extraneous variables.
Chapter 4: Extraneous Variables Randomization
Randomization means using chance to make decisions in the study, rather than the researcher choosing them. This helps reduce bias, which is when the researcher might unintentionally influence the outcome.
For example, when testing how people recall words (like the primacy-recency effect), the order of the words should be random. This prevents the researcher from accidentally putting easy words at the beginning, which could affect how well participants remember them. Randomizing the order of words helps avoid this as an extraneous variable.
Chapter 4: Types of Experiment Quantitative Methods
This approach involves the collection of numerical data. For instance, it may involve measuring the number of balls a participant can successfully place into a bucket, the number of correct answers they provide, or their height, among other things. This method is termed quantitative because it focuses on quantities or numerical values.
Chapter 4: Types of Experiment Qualitative Methods
This approach focuses on collecting descriptive data. For example, it may involve asking individuals to describe the quality of their memory or analyzing how men and women present themselves on television. This method is referred to as qualitative because it deals with non-numeric, descriptive information.
Experiments: Experiments represent a quantitative research method. All experiments involve two primary variables:
Independent Variable (IV): The factor that is intentionally manipulated or changed by the researcher.
Dependent Variable (DV): The factor that is measured to determine whether it changes as a result of variations in the independent variable.
In experimental research, the objective is to identify a measurable change in the dependent variable that is caused by modifications to the independent variable. The specific manner in which the independent variable is manipulated and the context in which the experiment occurs depend on the nature of the particular experiment being conducted.
Chapter 4: Types of Experiment Laboratory Experiments
A laboratory experiment is conducted in a controlled environment, where the researcher has significant control over various factors, such as what participants can see or hear. This controlled setting allows for careful manipulation of the independent variable (IV) to assess its impact on the dependent variable (DV).
Chapter 4: Types of Experiment Strengths of Laboratory Experiments
Strengths:
Control of Extraneous Variables (EVs): A key strength of laboratory experiments is the ability to control extraneous variables. This enables researchers to be more confident that any observed changes in the dependent variable are due to the independent variable, rather than external factors. This strengthens the ability to make cause-and-effect conclusions.
Standardization and Replicability: The controlled environment allows for the use of standardized procedures, meaning the experiment can be repeated by other researchers. If the results are replicated, this confirms the reliability and validity of the findings.
Chapter 4: Types of Experiment Weaknesses of Laboratory Experiments
Weaknesses:
Limited Ecological Validity: One drawback of laboratory experiments is that they may not accurately represent real-life situations. The controlled nature of the experiment may not reflect how participants would behave in everyday life. For example, performing a task in a lab setting might feel different from performing the same task in a real-world context, such as speaking in front of an audience or playing a sport. This limits the generalizability of the results.
Participant Awareness: Since participants know they are being observed in a lab, they may alter their behavior, either consciously or subconsciously, to fit what they believe the researcher expects. This is known as the Hawthorne effect and can result in data that lacks ecological validity, as the behavior observed may not reflect how participants would act in a natural setting.
Chapter 4: Types of Experiment Validity
Validity refers to the extent to which a research study measures what it claims to measure and whether the findings reflect real-life situations. In simple terms, it asks whether the results of a study are accurate, meaningful, and can be trusted as a true representation of real behaviour.
Key Point:
Validity does not mean that the researcher got the “right” answer, but that the results are realistic and applicable to real-world situations.
Importance:
Validity is one of the most important concepts in research methods. It is essential when evaluating whether an observed effect is real and whether the conclusions drawn from a study can be applied to everyday life. High validity means the results are more likely to reflect real-world behaviour, not just the behaviour of participants in a specific research setting.
Chapter 4: Types of Experiment Types of Validity - Internal Validity
The extent to which the results of a study are due to the manipulation of the independent variable (IV), and not other factors (extraneous variables).
Key Question: Did the IV really cause the change in the DV?
Example: In a memory test, if some participants are distracted by noise and others are not, internal validity is reduced.
Chapter 4: Types of Experiment Types of Validity - External Validity
The extent to which the findings of a study can be generalised beyond the research setting.
Includes:
Population Validity: Can the results apply to other people (beyond the sample)?
Ecological Validity: Do the findings apply to real-life situations?
Temporal Validity: Are the results still true over time?
Chapter 4: Types of Experiment Types of Validity - Ecological Validity
A type of external validity—refers to whether the research setting and tasks reflect real-life situations.
Key Question: Would people behave the same way in everyday life?
Example: Solving word puzzles alone in a lab may not reflect real-life memory use, so it may lack ecological validity.
Chapter 4: Types of Experiment Types of Validity - Population Validity
Refers to whether the sample used in the study represents the wider population.
Key Question: Can the results be generalised to other groups of people?
Example: A study using only university students may not apply to older adults or children.
Chapter 4: Types of Experiment Types of Validity - Temporal Validity
Refers to whether the findings still apply after time has passed.
Key Question: Are the results still relevant today?
Example: A study from the 1950s about gender roles might not apply in modern society.
Chapter 4: Types of Experiment Field Experiments
A field experiment is conducted in a natural or everyday environment, such as a school, café, or public street. Unlike a laboratory experiment, the setting is not artificially controlled. However, as in all experiments, the researcher manipulates the independent variable (IV) to observe its effect on the dependent variable (DV), while attempting to control for extraneous variables (EVs) where possible.
Chapter 4: Types of Experiment Strengths of Field Experiments
High Ecological Validity:
Field experiments are typically more realistic than laboratory experiments because they take place in natural environments. As a result, participants often behave more naturally, especially if they are unaware that they are being observed. This increases the ecological validity of the findings, making them more generalisable to real-world behaviour.
Use of Standardised Procedures:
Although the setting is natural, researchers can still implement standardised procedures, which help reduce the impact of EVs. This supports the reliability of the experiment and allows for potential replication under similar conditions.
Chapter 4: Types of Experiment Weaknesses of Field Experiments
Reduced Control Over Variables:
Conducting research in real-world environments makes it more difficult to control extraneous variables. This limits the internal validity of the study, as it becomes harder to establish a clear cause-and-effect relationship between the IV and DV. For instance, in Bickman’s study on obedience, external distractions such as varying traffic levels could have influenced participant behaviour in ways unrelated to the manipulated variable.
Ethical Issues:
Field experiments may raise significant ethical concerns, particularly regarding informed consent. Participants are often unaware they are taking part in a study, which may violate ethical guidelines. In Bickman’s study, for example, individuals became participants without their knowledge or agreement, which could be considered unethical.
