Research Process
The research process consists of a series of actions or steps that are necessary for effectively conducting and completing research.
Various steps of research process are :
- Formulating the Research Problem
- Conducting an Extensive Literature Review
- Developing the Hypotheses
- Preparing the Research Design
- Determining the Sample Design
- Collecting the Data
- Executing the Project
- Analyzing the Data
- Hypothesis Testing
- Generalizations and Interpretation
- Preparing the Report or Presenting Results
1. Formulating the Research Problem (Identifying the Problem)
This is the first and most important step in the research process, identifying research question. A research problem can be any question you want answered or an assumption you wish to challenge. It's crucial for the problem to be defined unambiguously, as this helps in discriminating relevant data from irrelevant data and dictates almost every subsequent step.
Key considerations in selecting a research problem include personal interest, the magnitude of the study, clarity on measuring concepts, your level of expertise, relevance to your profession, data availability, and ethical issues.
Key Steps in formulating research problem:
- Understand the problem thoroughly
- Rephrase it into meaningful analytical terms
- Discuss with colleagues or experts for clarity and better understanding
There are two types of research problems,
- Problems related to states of nature
- Problems related to relationships between variables
2. Extensive Literature Review
After identifying the problem, literature review is conducted to:
Establish theoretical roots for the study, clarify ideas, and improve your research methodology by acquainting you with what others have done in similar areas.
This process helps in understanding the subject area, conceptualizing the research problem clearly, and focusing the study on existing knowledge gaps, thereby enhancing its relevance. It prevents duplication of effort.
Reviewing the literature involves searching for existing literature, reviewing selected works, and developing theoretical and conceptual frameworks.
3. Development of working hypotheses
Based on the literature review, a clear working hypotheses is formulate to guide the research.
Hypotheses are tentative assumptions or hunches that are tested through a study. While not essential for all studies, they bring clarity, specificity, and focus to a research problem.
Purpose of Hypotheses:
- Define the research boundaries
- Sharpen focus on important parts of the problem
- Help structure analysis
Methods of Developing Hypotheses:
- Discussions with colleagues or experts
- Review of data, records, and past research
- Exploratory personal investigation involving fieldwork or interviews for better insight
4. Preparing the Research Design
A research design outlines the framework for collecting and analyzing data. It should be tailored to suit the research problem and objectives.
The research design is a plan, structure, and strategy of investigation that helps obtain answers to research questions validly, objectively, accurately, and economically. It is the conceptual structure or blueprint within which research is conducted, detailing procedures and logistical arrangements, measurement procedures, sampling strategy, analysis frame, and time-frame.
Research designs must be flexible for exploratory studies to consider many aspects of a phenomenon, but rigid for descriptive studies to minimize bias and maximize reliability.
The preparation of the Research Design, appropriate for a particular research problem, involves :
Defining Methods of data collection and study population
Skills and availability of staff and researcher
Explanation of the way in which the collected information will be organized and the reasoning leading to the selection; Analysis plans.
Time constraints for research
Financial resources available
5. Determining sample design
Sampling involves selecting a few respondents (a sample) from a larger group (the sampling population) to infer about the entire population. The sample design is the definite plan for obtaining this sample, outlining the technique or procedure for selecting sampling units.
A good sample design minimizes sampling error and controls systematic bias, leading to generalizable results.
A brief mention of the important sample designs are:
- Deliberate sampling
- Simple Random sampling
- Systematic sampling
- Stratified sampling
- Quota sampling
- Cluster sampling and area sampling
- Multi-stage sampling
- Sequential sampling
6. Collecting the data.
This is the phase where, after formulating the problem, developing a design, constructing an instrument, and selecting a sample, you actually gather the information from which inferences and conclusions will be drawn.
The quality of collected data heavily relies on the researcher's ability to manage factors affecting data quality. Data collection methods vary by cost, time, and required resources.
Data collected may be from:
Primary sources : first-hand information gathered for the specific study, such as through observation, interviews, or questionnaires
Secondary sources : Previously collected by others, already existing information, like census data or published reports
7. Executing the project.
The execution of the project is a very important step to ensure that the data collected are adequate and dependable. This step involves proceeding systematically and timely with the data collection plan.
Key Aspects for reliable data collection:
- Systematic and timely implementation
- Proper training for data collectors
- Use of instruction manuals
- Monitor for unanticipated issues
- Ensure statistical control
- Handle non-response issues with sub-sampling and expert intervention
Execution of the project is a very important step in the research process :
The data to be collected should be adequate and dependable
The project should be executed in a systematic manner and in time.
The data are to be collected through interviewers.
The training may be given with the help of instruction manuals.
Manuals explain clearly the job of the interviewers at each step.
A careful watch should be kept for unanticipated factors in order to keep the survey as much realistic as possible.
The steps should be taken to ensure that the survey is under statistical control, so that the collected information is in accordance with the pre-defined standard of accuracy.
If some of the respondents do not cooperate, then some suitable methods should be designed to tackle this problem.
To deal with the non-response problem, make a list of the non-respondents and take a small sub-sample of them.
Then with the help of experts vigorous efforts can be made for securing response.
8. Analysis of data
Once data is collected, the next task is to analyze it, making sense of the information and finding answers to research questions.
Step is analysis involves: editing, coding, classification, and tabulation
Classification and coding of raw data
Tabulation and summarization
Application of statistical tools (percentages, coefficients, etc.)
Tests of significance to validate relationships or findings
After the collection of data the next task is of analysis of the data. The analysis of data requires a number of operations. Such as :
Establishment of categories, the application of these categories to raw data through coding, tabulation and then drawing.
The unwieldy data should be converted into a few manageable groups and tables for further analysis.
The raw data should be classified into some purposeful and usable categories. Coding operation is done at this stage.
Through this coding the categories of data are transformed into symbols
Editing is the procedure that improves the quality of the data for coding. With coding the stage is ready for tabulation.
Tabulation is a part of the technical procedure wherein the classified data are put in the form of tables.
Analysis work is based on the computation of various percentages, coefficients, etc., by applying various well defined statistical formulae.
In the process of analysis, relationships or differences supporting or conflicting with original or new hypotheses should be subjected to tests of significance to determine with what validity data can be said to indicate any conclusion(s).
9. Hypothesis testing.
After data analysis, the researcher is in a position to test the hypotheses formulated earlier. This involves determining whether the collected facts support or contradict the hypotheses.
Statisticians have developed various tests, such as Chi-square, t-test, and F-test, for this purpose. The outcome of hypothesis testing is either accepting or rejecting the hypothesis based on evidence.
If no initial hypotheses were made, generalizations derived from the data might be stated as hypotheses for future research.
10. Generalizations and interpretation.
Interpretation is the task of drawing inferences from the collected facts after analytical or experimental study, essentially a search for broader meaning of research findings.
If a hypothesis is repeatedly tested and upheld, it may lead to generalizations or the building of a theory, which is considered the real value of research.
This interpretive process can also generate new questions, prompting further research.
For studies without initial hypotheses, findings are explained based on existing theories.
11. Preparation of the report or thesis
This is the final and most crucial step in the research process, as it communicates the study's findings and their implications to supervisors and readers. A well-written report is essential for effectively conveying the hard work and quality of the research.
The report should be clear, concise, objective, and demonstrate intellectual rigor, free from ambiguity and based on verifiable evidence.
Report Structure:
Preliminary Pages
- Title page
- Date
- Acknowledgments
- Foreword
- Table of contents
- List of tables/graphs
Main Text
- Introduction
- Summary of findings
- Detailed report
- Conclusions
End Matter
- References
- Appendices (if any)
Criteria for Good Research
Clearly defined purpose and use of common concepts: The objective of the research should be explicitly stated, and any concepts used within the study should be clearly defined to avoid ambiguity.
Detailed methodology: Research procedure described sufficiently to allow replication. Ensuring continuity and further advancement of knowledge.
- This includes explaining how the study was carried out, its basic design, experimental manipulations (if any), data collection methods (e.g., questionnaires, interviews), instructions given to observers, and details about the sample used.
Objective procedural design which yields objective results:
- Objectivity means that each step is taken in an unbiased manner, and conclusions are drawn without introducing the researcher's vested interest.
- The design of the research should be carefully planned to minimize bias and maximize the reliability of the collected and analyzed data.
Transparency and frankness about flaw-limitations in design and findings:
- Researchers should openly report any flaws in the procedural design and estimate their potential effects on the findings.
Adequate data analysis with proper statistical tools:
- The methods of analysis used must be appropriate for the data type. This includes ensuring the validity and reliability of the data.
Valid and reliable conclusions confined to the justified data of research:
- Conclusions drawn from the study must be directly supported by the research data and limited to what the data adequately provides a basis for.
Conducted by an experienced and ethical researcher:
- Unethical practices include introducing bias, inappropriate methodology, incorrect reporting, and improper use of information.
Qualities of Good Research:
Systematic: Good research is structured with specified steps followed in a logical sequence, adhering to well-defined rules.
Logical: Research is guided by logical reasoning, utilizing induction (reasoning from part to whole) and deduction (reasoning from premise to conclusion), which enhances the meaningfulness of findings for decision-making.
Empirical: Conclusions are based on tangible evidence gathered from real-life experiences or observations, using concrete data that provides external validity to the results.
Replicable: This quality ensures that research results can be verified by repeating the study which helps confirm or disprove findings and allows for further advancement.