What is Research Process

What is Research Process

The research process consists of a series of actions or steps necessary to effectively carry out research. These 11 actions or steps are important .

1. Problem formulation:

At the outset, the researcher must decide what aspect of a subject he wants to investigate and formulate a research problem.

2. Literature survey

Once the problem is formulated, the researcher should do a literature search.

Academic journals, conference proceedings, government reports, books, etc. must be tapped depending on the nature of the problem.

3. Hypothesis development

After a thorough literature review, researchers should state working hypotheses.

Working hypothesis is a tentative assumption to test logical or empirical consequences. It’s crucial to research.

4. Research design

After framing a hypothesis, we must prepare a research design, or the conceptual framework for research.

Such a design facilitates efficient, maximally informative research.

Research design optimises effort, time, and money to collect relevant evidence. All this depends on the research purpose.

5. Sample design:

A sample design is a predetermined plan for obtaining a sample from a given population.

Census inquiries require a lot of time, money, and energy, making them impractical.

Probability or non-probability sample designs exist.

With probability samples, each element’s inclusion probability is known, but non-probability samples do not.

6. Data collection:

There are a variety of methods for gathering relevant data, each with its own set of advantages and disadvantages in terms of time, money, and other resources at the researcher’s disposal.

Experiments and surveys collect primary data.

In a survey, the following methods can be used to collect data:

  • Observation
  • Interviews
  • By phone,
  • Through questionnaires or
  • schedules.

7. Project execution

Research project execution is crucial.

If the project is executed correctly, the data will be reliable.

Unanticipated factors should be monitored to keep the survey realistic.

8. Data analysis

Data analysis requires establishing categories, applying them to raw data through coding, tabulation, and statistical inference.

After tabulation, analysis work involves calculating percentages, coefficients, etc. using well-defined statistical formulae.

In the analysis process, relationships of differences supporting or conflicting with original or new hypothesis should be tested for significance to determine data validity.

9. Hypothesis testing

After analysing the data, the researcher can test his hypotheses.

Are the facts in favour of the hypothesis or against it?

This is a common question that can be answered using ‘t’ and ‘F’ tests.

Statistics developed the F test for the purpose.

Testing a hypothesis accepts or rejects it. If the researcher had no hypotheses, data-based generalisations may be stated.

10. Generalizations and interpretation

Researcher’s ability to generalise, or construct a theory, depends on the number of times a hypothesis is tested and found to be correct.

Research’s real value is in its ability to generalise. If the researcher had no hypothesis, he may explain his findings with a theory. It is interpretation

11. Report/thesis preparation:

The researcher must then write up his findings.

The report should have an introduction, body, and conclusion.

Title, acknowledgements, forward, and index appear on the first page. Introduction, literature review, and methodology should be in the report.

Research criteria:

Scientific research should meet these criteria:

(a) The research’s purpose and common concepts should be clear.

(b) The research procedure should be detailed enough for another researcher to repeat it for further advancement, maintaining continuity.

(c) The research should be carefully planned to yield objective results.

(d) The researcher should report procedural design flaws and estimate their effects on findings.

(e) Data analysis should reveal its significance, using appropriate methods. Check data validity and reliability.

(f) Only conclusions supported by the research should be drawn.

(g) Research can be trusted more if the researcher is experienced, reputable, and honest.



Related Posts

Leave a Reply

Your email address will not be published. Required fields are marked *