RES PROJ: Lesson 5: Methodology

• A method is a specific set of procedures or techniques that are used to gather data or information.
• A method is a define, systematic approach to collecting and analyzing data.
• Methodology is the overall approach or framework that guides the research process.
• Methodology includes the methods used to gather data.
• Research Design - This section discusses the research design that the study will use.
• Research design should be guided by the research objectives and research questions that the student want to answer.
• Types of research design:

  • Quantitative
  • Qualitative
• In quantitative research, the study will collect, analyse and present numerical data in the form of statistics.
• The statistics can be:

  • Descriptive
  • Inferential
  • Mix of both
• In qualitative research, the study collects, analyse, and presents data that is in the form of words, opinions, or thoughts of the respondents.
• Qualitative research focuses on the lived-in experiences of the respondents with regard to the problem under investigation.
• A research locale refers to the specific place or are where research is conducted.
• It encompasses various aspects such as geographical location, institutional environment, and scholarly communities.
• The local context plays a crucial role in the successful implementation of research integrity policies.
• When you choose the appropriate locale, it aligns data collection with your research goals and impacts the feasibility of data gathering.
• Population of the study refers to the entire list of your subject of interest.
• If your population is so small, the student can opt to include all the subjects in the study.
• However, if the population is large, it becomes difficult –both time-wise and resource-wise – to include all the subjects in the study.
• The population can be defined in terms of geographical location, age, income, or many other characteristics.
• The population is the entire group that you want to draw conclusions about.
• The sample is a specific group of individuals you will collect data from.
• Sampling method - how you will select a sample that is representative of the group as a whole.
• Two primary types of sampling methods:

  • Probability sampling
  • Non-probability sampling
• Probability sampling involves random selection, allowing you to make a strong statistical inferences about the whole group.
• Non-probability sampling involves non-random selection based on convenience or other criteria, allowing you to easily collect data.
• Probability sampling means that every member of the population has a chance of being selected
• Probability sampling - It is mainly used in quantitative research.
• If you want to produce results that are representative of the whole population, probability sampling techniques are the most valid choice.
• Four main types of probability sampling:

  • Simple random
  • Systematic
  • Stratified
  • Cluster sampling
• In a non-probability sample, individuals are selected based on non-random criteria, and not every individual has a chance of being included.
• If you use a non-probability sample, you should still aim to make it as representative of the population as possible.
• Non-probability sampling - In these types of research, the aim is not to test a hypothesis about a broad population, but to develop an initial understanding of a small or under-researched population.
• Four main types of non-probability sampling:

  • Convenience
  • Purposive
  • Snowball
  • Quota
• Research ethics - This section highlights the ethical considerations that would be followed during the data collection process.
• Ethical considerations vary from study to study and include:

  • Consent
  • Confidentiality
  • Anonymity
  • Potential Harm
• Consent - The researcher should seek informed consent from the respondent before the data collection begins.
• The consent can be in written or oral form.
• Confidentiality - The researcher should assure the respondents that their responses will be kept confidential.
• Anonymity - means that you don't know who the participants are and you can't link any individual participants to their data.
• Data pseudonymization - is an alternative method where you replace identifying information about participants with pseudonymous, or fake, identifiers.