methods, design types- experimental

• what is an aim?


  General statement that describes purpose of study eg time of day effects student performance
• what is a hypothesis 


  A clear, precise, testable and operationalised statement about what one predicts the outcome of the study will be.

  this includes the independent and dependent variable clearly stating how variables will be measured, operationalised.
• What is operationalisation

  Clearly defining variables in terms of measurements
• What is the independent variable

  A factor the researcher manipulates / changes eg how does gender effect personality. Gender would be the independent variable
• What is a dependent variable 


  The factor measured in experiment that is affected by the independent variable eg innhow does gender effect peresonality. Personality is the independent variable, an MBTI test would make it more measurable/ operationalised.
• What is a directional hypothesis 


  Predicting the direction of the effect. Also known as one tailed hypothesis
• example of directional hypotheses


  Teenagers who watch horror films have more friends than teenagers who watch action films.
• what is a non directional hypotheses

  States that a effect will occur, also known as two tailed hypotheses results can go both ways. This is usually when previous research has been conducted on a topic
• example of non directional hypotheses


  Teenagers who watch horror films have a difference in number of friends compared to their peers who watch action films
• Explain an experimental hypotheses

  Operationalised variables

  Clear testable statement

  can be one tailed (directional) or two tailed (non directional )
• when have a directional hypothesis/ non directional ?


  Directional - when there is evidence / past research that suggests the hypothesis is true.

  Non directional - when there is contradictory evidence (shows that results can go either way) to suggest hypotheses is unlikely. Or no previous evidence
• Define demand characteristics 


  Any cue from the researcher or situation that means participants guess the aim of the study therefore changing their behaviour.
• Define randomisation 


  Then use of chance to reduce the effects of bias when designing materials and deciding order of conditions
• Define order effects 


  When participants behaviour changes eg they get better or worse in the second condition of an Independent variable in repeated measures design due to practice or boredom
• define random allocation to groups 


  Attempting to control participant variables in an independent groups design. This ensures that each participant had the same chance of being in one condition than another.
• Define investigators effect


  Any effects researcher has on outcome of the study that affects the dependent variable eg instructions given differences, participants treatment during the study.
• Define confounding variables


  A variable other than the independent variable that may affect the dependent variable varies systematically with the independent variable.
• Define counterbalancing


  Attempting to control for order effects in repeated measures designs. This is where half the participants experience conditions in one order, the other half in a separate order.
• define extraneous variables


  Variable other than the independent variable that may affect the dependent variable if not controlled
• Define standardisation


  Using the same formalised instructions for all participants in a study
• what is the experimental design- independent groups?


  different participants are used for the two conditions of the independent variable
• what are repeated measures?


  the same participants are used for both conditions of the independent variable
• what is matched pairs experimental design?


  different participants are used for the two conditions of the independent variable but they are matched before the experiment to control for characteristic similarities
• define extraneous variables


  other than the independent variable factors that may affect the dependent variable

  • confounding variables- participant and situational
  • demand characteristics
  • order effects
  • researcher bias/ investigator effects
• explain two confounding variables- situational and participant variables


  these both (otehr than the IV) affect the DV

  • Partipant variables are individual differences between participants that effect dv eg age, ability, gender, IQ, life's experiences
  • situational variables are features of the situation that may affect the dependent variable- noise, time of day, weather, current mood
• explain another extraneous variable- demand characteristics


  clues given in the study that allow participants to guess the aim and expected results and either preform as expected or against the researcher's aims
• extraneous variable define order effects


  A negative of repeated measures- participants may preform better/worse in the second condition of the independent variable eg in practice, boredom and fatigue could results change
• a further extraneous variable define investigators effects


  bias, expectations and subjectivity when people conduct experiments on other people.

  • loose procedures- not treating all participants the same- giving them different instructions
  • subtle cues eg body langugage that leads participants to behave in certain ways eg encouragement/ smiling at one group
  • fudging results that dont fit in researchers expected pattern
• strengths of repeated measures


  less participants needed

  no participant variables
• limits of repeated measures


  order effects are a greater problem

  demand characteristics are more likely
• independent groups strengths


  no order effects

  demand characteristics less likely
• limits of independent groups


  participant variables may affect the dv (factor that is being measured) more than the independent variable affects the dv

  more participants are needed
• matched pair design strengths


  • participant variables reduced
  • no order effects
  • demand characteristics less likely
• limits of matched pairs design


  need information to match participants on and pre testing may be needed which is expensive and time consuming
• why does task difficulty need to be controlled in a repeated measures design?


  to allow the results to be fair and reduce bias
• what is randomisation


  using chance to reduce effects of bias when designing materials and deciding the order of conditions, allows chance to play a part
• what is standardisation


  using the same set of formalised instructions for all participants in the study. helps control investigator effects loose procedures subtle cues, fudging effects, so does randomistaion
• how to control participant variables in independent and dependent groups?


  random allocation where participants are allocated across the conditions of the independent variable randomly so there is a more likely mix of candidates
• what controls order effects in repeated measures


  counterbalancing- participant sample is divided in half, with each half completing the independent variables in different orders
• Explain types of experiments


  lab

  field

  natural

  quasi