Non experimental methods
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Non Experimental Methods. Investigating Behaviour . Surveys. Questionnaires – written or verbal Interviews Structured – pre determined questions (questionnaire that is delivered face to face) Unstructured – Each question is developed as a result of the previous answer. (Clinical interview)

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Non Experimental Methods

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Non experimental methods

Non Experimental Methods

Investigating Behaviour


Surveys

Surveys

  • Questionnaires – written or verbal

  • Interviews

    • Structured – pre determined questions (questionnaire that is delivered face to face)

    • Unstructured – Each question is developed as a result of the previous answer. (Clinical interview)

    • Both can be used to collect quantitative or qualitative data.

    • What ethical issues should be considered? (3)


Non experimental methods

Task

  • What do you think the strengths and limitations would be for:

    • Questionnaires (2strengths, 2 weaknesses)

    • Structured interviews (3 and 3)

    • Unstructured (2 and 3)

    • Work in pairs or 3s to discuss the development, use and analysis of data using these techniques to help you come up with your answers.

    • Consider how you would feel if you were the participant.

    • Compare and contrast them.


Evaluation

Evaluation


Glossary of terms

Glossary of terms

  • Leading questions – a question which is worded in a way that makes one answer more liked. ‘Wouldn’t you agree . . .?’

  • Social Desirability Bias – what people think they should say rather than genuinely think/feel.

  • Interviewer Bias – what the interviewee thinks the interviewer wants.


Reliability

Reliability

  • Consistency.

  • Experimenters must ensure that the questionnaire they use is reliable to ensure that they are testing what they aim to.

  • Ie – If the same questionnaire is used with the same participant on 2 different occasions but gain different responses, if the questionnaire was reliable then we can assume that the difference can be attributed to the participant.

  • Test-retest reliability – repeating questionnaire with same participants to see if the same results are obtained and measured using a correlation coefficient.


Validity

Validity

  • That the questionnaire is measuring what it was designed to measure.

  • If answers are affected by social desirability bias, interviewer bias etc then the results lack validity.

  • Concurrent validity – comparing results from new questionnaire with an established study.


Good questionnaires

Good Questionnaires:

  • Are clear.

  • Lack bias

  • Easy to analyse – closed questions (options given, likert scale) but this makes the data quantitative rather than qualitative.

  • Good Surveys:

  • Include filler questions – misleads interviewee to reduce interviewer bias.

  • Easy qstns at start more difficult at end.

  • Pilot study


Correlational design and analysis

Correlational Design and Analysis

  • Correlational analysis is used to analyse non-experimental methods (surveys/observations/case studies) as the IV is not being manipulated and there is very little control over extraneous variables.

  • It is not a research method!


Correlational design and analysis1

Correlational Design and Analysis

  • Correlation – a relationship between two variables (co-variables).

  • Positive correlation – when 2 variables increase together.

  • Negative correlation – when 1 variable increases and the other decreases.


Zero correlation

Zero Correlation

  • Zero correlation – no relationship between the 2 variables.


Visual display

Visual Display

  • Correlations are displayed using a scattergram.

  • A dot is plotted on a scattergram for each participant’s two answers. Eg weight and hours spent exercising per week.


Statistical test

Statistical Test

  • In the same way we used T-test for our experimental methods in order to reject our null hypothesis so too do we use statistics in non-experimental methods.

  • Correlation co-efficient – never greater than 1 (+1 for positive correltaions and -1 for negative correlations).

  • 1 Is the perfect correlation but is very rare. The strength of correlation is expressed as weak, moderate or strong.

  • The closer to 1 the number is the stronger the correlation:

    • +0.76 (there is a positive and strong correlation between the co-variables)

    • -0.76 (there is a negative and strong correlation between the co-variables)

    • +0.002 (There is a very weak positive correlation between the co-variables)


Significance

Significance

  • A table of significance is used to determine whether the strength of the correlation (the number) is significant.

  • The significance is dependent upon the number of participants who took part/responded (N).

  • Even small numbers (0.02) can be significant if the N is very large.


Evaluation of investigations using correlational analysis

Evaluation of investigations using correlational analysis


Observation

Observation

  • The starting point for all investigations.

  • Must be objective.

  • If used as part of an experiment then it is a research technique. However, if used on its own it is a research method.

  • The design of these observations may vary:


Naturalistic observation

Naturalistic Observation

  • Behaviour is studied in a completely natural setting.

  • The researcher does not change anything.

  • This is different from a natural experiment as the experimenters are not looking for a relationship between an IV and a DV.


Example

Example:

  • Children aged 3- 5 observed in a playground. Activities were categorised as male, female or neutral. Praise and imitation was recorded as positive responses while criticism and stopping play were recorded as negative responses.

  • Children generally reinforced peers for gender-appropriate play and criticised gender-inappropriate play.

  • Lamb and Roopnarine, 1979


Controlled observation

Controlled Observation

  • Some variables can be controlled eg setting, objects etc.

  • Participants are likely to know they are being studied.

  • Reduces chances of behaviour being completely natural.


Example1

Example

  • Lamb and Roopnarine’s experiment could also have been carried out as a controlled observation.

  • ie The children could have been out in a playroom where the toys would have been pre chosen by the experimenters.

  • NB – this is different from Bandura’sBobo Doll experiment as they directly affected the IV (showing the children a video in advance). In this instance observation was used as a technique not a method.


Other types of observation

Other types of Observation

  • Content Analysis – observing written/verbal texts.

  • Non-participant – observer does not involve themselves simply observes.

  • Participant – Observers participate.

  • Disclosed – participant knows they are being observed.

  • Undisclosed – participant unaware they are being observed.


Example page 119

Example (page 119)

  • Leon Festinger, a social psychologist, 1950s.

  • Religious cults receiving messages from aliens detailing the end of the world.

  • Believed they would be rescued by a UFO and arranged to meet a set time and location.

  • Festingerposed as a convert in order to observe their reactions when their beliefs were unfounded.

  • The night before the predicted flood, when it was apparent that there would be no flood, the cult leader claimed that it was because of their combined prayers.

  • Observed a mixture of reactions – some didn’t believe and left the cult, others took it as evidence of the cult’s powers.


Reliability1

Reliability

  • To ensure reliability (consistency) it is always better to have at least 2 observers who produce the same record (if 2 observers have conflicting recordings their observations are not reliable).

  • Observers should be trained to increase level of reliability.

  • The extent of this consistency is call inter-observer reliability

  • Measured by correlating the results . To have inter-observer reliability the correlation must be >.80.


Validity measuring what it s supposed to

Validity (measuring what it’s supposed to)

  • Can be affected by observer bias – the observer sees what they want/expect to see rather than being objective.

  • http://www.youtube.com/watch?v=1GEEvvTiiQk

  • Using more than one observer and averaging their responses can help with this.

  • If participants know they are being observed they may change their behaviour (eg social desirability bias).

  • Results will not be valid if the coding system is flawed.


Non experimental methods

Task:

  • In pairs decide who is A and who is B.

  • Take it in turns to complete the task. Each task should take 5 minutes.

  • While one person is completing the task the other person should be recording all aspects of their behaviour: ie facial expressions, verbal cues, body language, etc


Observational techniques

Observational techniques

  • Structured vs Unstructured.

  • Unstructured (what you did): Observer records everything they believe to be relevant. No system for observing or recording behaviour.

  • Observer will note only the most obvious behaviour but these may not be the most important (did you see the moonwalking bear?).


Structured

Structured

  • Systems are put in place to ensure observations are organised and systematic.

  • Sampling procedure – knowing who you are observing and when.

  • Observation schedule – how to record the behaviour you are studying.

  • Continuous observation – Every instance of the relevant behaviour is recorded in great detail. Difficult as it requires a lot of recording if the behaviour is common.

  • Event sampling – counting the amount of times it occurs.

  • Time sampling – recording behaviour at set intervals (every 30 seconds). Can be selected from a checklist.


Observational schedule coding system behaviour checklist

Observational Schedule/Coding system/Behaviour checklist

  • Having a pre-made list of relevant behaviour to be observed which helps the observer to deconstruct the behaviour.

  • They should be objective and leave no room for observer bias.

  • Be wide spread – cover all possibilities.

  • Should be discrete – no room for overlaps

  • http://www.cs.cmu.edu/afs/cs/project/face/www/facs.htm


Research methods summary

Research Methods - Summary

  • Part 1 - http://www.youtube.com/watch?v=Lkwsrh10OXM

  • Part 2 - http://www.youtube.com/watch?v=QwcuHaJ7q0I


Case studies

Case studies

  • A detailed study of an individual/place/event.

  • How Freud collected his data – Anna O.

  • Requires a variety of research methods to develop an informed picture – interviews, tests etc.

  • Extremely in depth.

  • Time consuming (longitudinal) – carried out over a long period of time.

  • Task: What are the advantages and disadvantages of this method?

  • Try to come up with 3 of each and use your prior knowledge of this topic to help.


Evaluation1

Evaluation


Revision

Revision

  • Scholar

  • Work through the Unit 2 section of Scholar, adding to your notes and completing the interactive activities. Particularly the data analysis – nominal, ordinal and interval data section which we haven’t covered.

  • 1,3,4,2


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