Research Designs & Terminology Flashcards
What is the difference between ontology and epistemology?
Ontology is the philosophical field revolving around (the study of) the nature of reality (all that is or exists), and the different entities and categories within reality.
Epistemology is the philosophical field revolving around (the study of) knowledge and how to reach it.
What is the difference between realism, critical realism, and relativism?
Realism: there is a real world ‘out there’ that is directly knowable
Critical realism: reality is ‘out there’ but we can’t access it directly, only imperfectly, because perspectives on reality are subjective and partial
Relativism:reality is not permanent and objective, but socially constructed and determined
What is the difference between positivism, contextualism, and constructionism?
Positivism: there is a single objective ‘real world’ which can be known
we can know truth / reality, but only through objective means, by removing subjectivity
therefore the researcher must be outside the knowledge derived from data
Contextualism: there is no one single reality, instead ‘ reality’ is determined by time, place, context, experience
within those limitations, it is possible to know and learn about people’s contextualised realities but this knowledge also reflects the researcher’s position
Constructionism: the world does not exist separately from our creation or perception of it
knowledge is socially created
we can study what people ‘know’ and how ‘realities’ are created
What is difference between qualitative and quantitative?
Qualitative
- small n
- flexible
- themes and expressions
- rich, deep level of information
- inductive
- develop theories
- exploratory
Quantitative - large n systematic, rigorous - measured with instruments - objective - deductive - test theories - explanatory
What are the ethical guidelines in conducting research?
Protection and welfare of participants Informed consent Use of deception? Debrief participants Right to withdraw Privacy in observational research Confidentiality General Data Protection Regulation
How do you establish causality?
Need to demonstrate 3 things:
Is there an association?
Time order of events
Non-spuriousness
What is an experiment?
A research design in which a variable is actively changed or manipulated and scores on another variable are measured to determine whether there is an effect
Key terms: Variable Manipulated Measured Effect
What is a variable?
Any property or characteristic of some event, object or person that may have different values at different times depending on the conditions
Experiments involve:
controlling
measuring
recording
What are the different types of variable in research?
Independent variables: Something that is systematically manipulated by the experimenter in order to determine the causal effect this may have on other variables
Dependent variables: Something that is measured or recorded by the experimenter. The amount it will vary is dependent upon variations in the independent variable(s)
Discrete variables: a variable whose value is obtained by counting. e.g., number of red marbles in a jar, number of heads when flipping three coins and students’ grade level.
Continuous Variable: If a variable can take on any value between its minimum value and its maximum value, [it’s also quantitative] e.g., age, eye colour, height, number of siblings, gender, or number of pets
Confounding variables: any other variable that also has an effect on your dependent variable. They are like extra independent variables that are having a hidden effect on your dependent variables. Confounding variables can cause two major problems:
-> Increase variance and introduce bias.
Extraneous variables: any variables that you are not intentionally studying in your experiment or test. When you run an experiment, you’re looking to see if one variable (the independent variable) has an effect on another variable (the dependent variable).
What are the different types of extraneous variables?
a. Situational Variables: These are aspects of the environment that might affect the participant’s behavior, e.g. noise, temperature, lighting conditions, etc. Situational variables should be controlled so they are the same for all participants
b. Participant / Person Variable: This refers to the ways in which each participant varies from the other, and how this could affect the results e.g. mood, intelligence, anxiety, nerves, concentration
c. Experimenter / Investigator Effects: The experimenter unconsciously conveys to participants how they should behave - this is called experimenter bias.
The experiment might do this by giving unintentional clues to the participants about what the experiment is about and how they expect them to behave. This affects the participants’ behavior.
The experimenter is often totally unaware of the influence which s/he is exerting and the cues may be very subtle but they may have an influence nevertheless.
Also, the personal attributes (e.g. age, gender, accent, manner etc.) of the experiment can affect the behavior of the participants.
d. Demand Characteristics: these are all the clues in an experiment which convey to the participant the purpose of the research.
Participants will be affected by: (i) their surroundings; (ii) the researcher’s characteristics; (iii) the researcher’s behavior (e.g. non-verbal communication), and (iv) their interpretation of what is going on in the situation.
What are the different levels of measurement?
Nominal
Ordinal
Interval
Ratio
How to remove participant confounds?
Randomly assign participants to conditions
Alternatively: could match participants in the different conditions
What is the difference between and within participants?
‘Between-participants’ / ‘independent-measures’ design: Assign a different group of participants to each condition
‘Within-participants’ / ‘repeated-measures’ design: Assign all participants to all conditions
What are the different developmental designs?
Longitudinal (Microgenetic): a research design that involves repeated observations of the same variables (e.g., people) over short or long periods of time (i.e., uses longitudinal data)
Cross-sectional: a type of observational study that analyzes data from a population, or a representative subset, at a specific point in time—that is, cross-sectional data.
Sequential: A cross-sequential design is a method used in research that combines a longitudinal design as well as a cross-sectional design. This dual study is used to correct flaws that might be found in either of these designs alone. For instance, in sociology a cross-sectional study will study a group of people who have factors in common (age, gender, location, education, etc.) to determine how that effects some aspect of their lives in a short-term. A longitudinal study will study this same group over a long term (years or even decades) to see how their lives are affected.
What are the advantages/disadvantages of developmental designs?
Carry-over effects
Counterbalancing
Bias in experiments: demand characteristics and experimenter bias
