Research Methods

→ The goals of research:

• Describing behaviours - naming and classifying various observable, measurable behaviours.

• Understanding - the causes of behaviour.

• Predicting - forecasting behaviour accurately.

• Controlling - altering conditions that influence behaviours.

→ Positive use - to control unwanted behaviours (smoking, tantrums).

→ Negative use - to control peoples’ behaviours without their knowledge.

→ The difference between THEORIES and HYPOTHESIS in research:

• Theory: The Big Picture - a theory is a set of principles, built on observations and other verifiable facts, that explain some phenomenon and predicts its future behaviour.

• Hypothesis: Informed Predictions - a testable prediction consistent with our theory.

• Empirical evidence - the information received by means of the senses, particularly by observation and documentation of patterns and behaviour through experimentation.

• Operational definitions - the statement of procedures that the researcher uses in order to measure a specific variable. This allows the researcher to describe in a specific way what they mean when using a certain term.

→ Enhancing objectivity through reflexivity:

• Reflexivity - the researcher’s need to constantly be aware of how and why they’re conducting the research, and to recognize at what points their own beliefs and opinions on this topic might have influenced data collection or analysis. It: 1) Is important in all types of research 2) Is an internal and external process (it should be shared in one’s research study) and 3) Sometimes involves conducting an interview with a colleague to try to answer the aforementioned questions.

→ The principles of reliability and validity:

• Reliability - refers to whether the measures we use are accurate. Inter-rater reliability, Test-retest reliability and Replicability should be considered.

• Inter-rater reliability - the extent to which 2 or more observers agree. This addresses the issue of consistency in the implementation of a rating system. Therefore, low inter-rate reliability values refer to a low degree of agreement between 2 observers.

• Test-retest reliability - a measure of reliability obtained by administering the same test twice over a period of time to a group of individuals. The scores from time 1 and time 2 can then be correlated in order to evaluate the stability of the test over time.

• Validity - refers to whether the measures we use are measuring what they’re supposed to be. One would need to check whether: 1) Researchers chose the appropriate tool to study the phenomenon they intend to study 2) Anything extraneous to the research had an impact on the data gathered 3) Researchers obtained objectivity during the study 4) Researchers can generalise the findings to the entire population 5) The research was close enough to a real-life situation.

→ Validity: Demand characteristics and the Hawthorne effect:

Aim: Understanding what factors increase productivity.

1920s - Hawthorne electrical plant (USA)

Procedure: 5 female workers assessed over 2 years under a number of conditions (ex: different levels of illumination or timing of breaks).

Results: Productivity increased whatever the change (even when conditions were returning back to the original ones). Workers responded to higher attention provided by management and researchers (Independent Variable).

The Hawthorne Effect - occurs when participants try to perform in a way that they think meets the expectations of the researcher’.

Demand characteristics - the effects on participants’ behaviours when they try to guess the aim of research they’re taking part in.

→ Sampling:

• This is when researchers’ take observations about a predetermined number of participants chosen from the population and use them for their research. This saves time and resources.

• Sampling bias - refers to a tendency to over- or under- represent one or more categories in a population. In order to avoid this, we opt for random sampling, which is a technique for making sure that every individual in a population has an equal chance of being in the sample.

→ Q1: How do we gather our sample?

Sampling Techniques:

• Opportunity/Convenience sampling - using whoever is available (ex: asking passers-by to participate).

• Stratified/Quota sampling - a sample based on categories that characterize the target population. Once such categories are identified, quotas are set for each one and participants are chosen randomly for each one (ex: age, gender, ethnicity).

• Cluster sampling - a sample based on a random selection of 1 or more sections of the target population. Participants are then chosen at the random from these clusters (ex: selecting the Southern region and randomly select participants).

• Purposive sampling - basing your selections of participants on who’s likely to offer the most relevant information for the topic you’re researching.

• Snowball sampling - involves selecting key people as participants and asking them to provide you with further important contacts for your study.

Note: The first 3 are usually used for quantitative research and the last 2 for qualitative research.

→ Qualitative and Quantitative methodology:

Note: Empirical evidence is information received by means of the series, particularly by observation and documentation of patterns and behaviour through experimentation.

→ Quantitative and Qualitative methods:

→ Experimental data collection methods:

• Experiment - a way of conducting research where one condition is changed. This is considered one of the most effective ways of gathering evidence to support theories, as it eliminated a lot of alternative explanations of cause and effect.

• Hypothesis - the researchers statement regarding the expected outcome of the study. 2 types of hypotheses: 1) Experimental/Research Hypothesis- predicts that there’s a relationship between the independent and dependent variable, the former causes an effect on the later (ex: Production {DV} will be lower in a noisy environment {IV}), 2) Null Hypothesis- predicts that there’s no relationship between the independent and dependent variable, contradicting the experimental hypothesis (ex: There’s no difference between work produced in a noisy and silent environment).

• 2 types of experimental hypotheses: 1) Directional- predicts the ‘direction’ of the results (ex: Students who do their homework when switching off messenger produce better work than those who keep it on), 2) Non-Directional- doesn’t predict the direction of the results (ex: There’s a difference in the level of work produced by students who keep messenger on and those who don’t).

→ Variables in experiments: