Introduction
In Part one of the research process https://researchmethodsclass.com/the-research-process-from-research-idea-to-final-report/ we explained the following:
- Identifying a research idea/topic
- Preliminary literature review to identify the gap
- Research problem and stating a problem
- Stating objectives, research questions and hypotheses
- Conceptual and theoretical framework
This article will address:
- Research Design
- Population
- Sampling
- Data Collection
- Data Analysis
A useful way of understanding research is therefore to see it as a journey:
Research Idea/Topic → Literature Review/research gap → Research Problem → Objectives/Questions/Hypotheses → Conceptual/Theoretical Framework → Research Design → Population → Sample → Data Collection → Data Management → Data Analysis → Interpretation → Conclusions → Recommendations → Final Report
This blog takes you through this journey step by step.
6. Research Design
A research design is the ‘blueprint’ that enables the researcher to come up with solutions to the research questions and also guides him/her in the various stages of the research (Nachmias and Nachmias, 1996). A research design enables a researcher to determine the methods of sample selection, instruments to use and methods of analysing data. Research design should be consistent with the research approach. There are three research approaches:
- Quantitative approach – collects numerical data and statistical analysis.
- Qualitative approach – focuses on meanings, experiences, perceptions and processes.
- Mixed-methods approach – combines quantitative and qualitative approaches.
The choice of the approach and the design should be driven by the research problem and research questions rather than personal preference. The choice of design must be justified.
For example, if the purpose is to determine whether two variables are related, a correlational survey design may be appropriate. If the researcher wants to understand people’s lived experiences, a qualitative design such as phenomenology may be appropriate.
Each of the approach has the designs that the researcher should anchor the study on:
| QUANTITATIVE | QUALITATIVE | MIXED METHOD |
| Survey: types – Correlational, Longitudinal or Cross-sectional | Case Study | Concurrent Triangulation Design |
| Experimental: types- True or Quasi | Longitudinal | Concurrent Nested or Embedded Design |
| Ex-Post Facto | Phenomenology | Sequential Explanatory Design |
| Biography | Sequential Exploratory Design | |
| Grounded Theory |
7. Population
Population refers to the entire group of people, events or things of interest that the researcher wishes to investigate. A population can also be defined as all people (unit of analysis) with the characteristics that one wishes to study. Each individual in a population is called an element. Population is abbreviated as N.
There are two types of population:
- Target Population – a target population is any group of individuals that has one or more characteristics in common that are of interest to the researcher and to whom we plan to generalize our findings. This is also referred to as study population.
- Accessible population – the portion of the population to which the researcher has reasonable access; may be a subset of the target population. Access may be limited to region, state, city, county, or institution.
- It is from this population that a sample is drawn;
- It is representative of the target population.
8. Sampling
Researchers often cannot study the entire population. They therefore select a sample. Sampling is defined as the process of selecting the right individuals, objects or events from a study population. It can also be defined as the process of selecting a group of people, events, behaviours, or other elements with which to conduct a study.
A sample is a subset of the population i.e. the selected elements (people or objects) chosen for participation in a study; Sampled people are referred to as subjects, respondents or participants. Therefore, not all elements of the population will form a sample. A sample comprises of same members selected from it.
Sampling techniques/designs needs to be coherent to the approach and the design.
For quantitative research, use probability sampling designs (random sampling designs):
- Simple random sampling
- Systematic random sampling
- Stratified sampling
- Cluster sampling
- Multi-stage sampling
For qualitative research, use non-probability sampling designs (non-random designs)
- Purposive sampling
- Convenience sampling
- Snowball sampling
- Quota sampling
ASSIGNMENT: Read on inclusion criteria and exclusion criteria
9. Data Collection
There is a difference between data collection methods and data collection instruments/tools. The methods are the techniques while the instrument is the tool. For instance, interview is a method; interview guide is a tool. Just as sampling, the choice of the instrument is dependent on the approach and the design.
Common instruments include:
- Questionnaires – quantitative
- Interview guides – qualitative
- Observation guides – qualitative
- Focus group discussion guides – qualitative
- Document analysis guide – qualitative
- Tests and examinations – quantitative
- Interview schedule – quantitative
The instrument must collect information that directly addresses the research objectives.
Do not collect data simply because it is interesting. Collect data because it helps answer a research question or objective.
Once you construct the instrument, the next step is to pilot the instruments and determine their validity and reliability.
- a pilot study is a small-scale preliminary study conducted before the main study to help the researcher to identify whether the questions and language of the instruments is clear. After pilot, the researcher revises the instrument before the main data collection.
- Validity – validity measures the usefulness of the questions to measure what they are intended to measure.
- Reliability measures consistency
Before embarking on field work, ensure that you obtaining ethical approval and Research Permissions.
10. Data Analysis
Data analysis involves systematically examining data to answer the research questions and objectives. Refer to this blog for details on data analysis https://researchmethodsclass.com/data-analysis-in-research/