Research Proposal Research Paper

Title Title
Abstract Abstract
Introduction Introduction
Statement of Problem Statement of Problem and Delimitations
Research Questions Research Questions
Research Objectives Research Objectives
Literature Review Literature Review
Theoretical Framework Theoretical Framework
Research Methodology Research Methodology
Significance of Research Data Collection
References Data Analysis
Findings
Discussion
Conclusion
Recommendations and Suggestions
References

Abstract

Definition and Purpose of Abstracts

An abstract is a short summary of your (published or unpublished) research paper, usually about
a paragraph ( 150-250 words) long. A well-written abstract serves multiple purposes:

 an abstract lets readers get the gist or essence of your paper or article quickly, in order to
decide whether to read the full paper;
 an abstract prepares readers to follow the detailed information, analyses, and arguments
in your full paper;
 and, later, an abstract helps readers remember key points from your paper.

It’s also worth remembering that search engines and bibliographic databases use abstracts, as
well as the title, to identify key terms for indexing your published paper. So what you include in
your abstract and in your title are crucial for helping other researchers find your paper or article.

If you are writing an abstract for a course paper, your professor may give you specific guidelines
for what to include and how to organize your abstract. Similarly, academic journals often have
specific requirements for abstracts. So in addition to following the advice on this page, you
should be sure to look for and follow any guidelines from the course or journal you’re writing
for.

The Contents of an Abstract

Abstracts contain most of the following kinds of information in brief form. The body of your
paper will, of course, develop and explain these ideas much more fully. As you will see in the
samples below, the proportion of your abstract that you devote to each kind of information—and
the sequence of that information—will vary, depending on the nature and genre of the paper that
you are summarizing in your abstract. And in some cases, some of this information is implied,
rather than stated explicitly. The Publication Manual of the American Psychological Association,
which is widely used in the social sciences, gives specific guidelines for what to include in the
abstract for different kinds of papers—for empirical studies, literature reviews or meta-analyses,
theoretical papers, methodological papers, and case studies.

Here are the typical kinds of information found in most abstracts:

1. the context or background information for your research; the general topic under study;
the specific topic of your research
2. the central questions or statement of the problem your research addresses
3. what’s already known about this question, what previous research has done or shown
4. the main reason(s), the exigency, the rationale, the goals for your research—Why is it
important to address these questions? Are you, for example, examining a new topic? Why
is that topic worth examining? Are you filling a gap in previous research? Applying new
methods to take a fresh look at existing ideas or data? Resolving a dispute within the
literature in your field? . . .
5. your research and/or analytical methods
6. your main findings, results, or arguments
7. the significance or implications of your findings or arguments.

Your abstract should be intelligible on its own, without a reader’s having to read your entire
paper. And in an abstract, you usually do not cite references—most of your abstract will describe
what you have studied in your research and what you have found and what you argue in your
paper. In the body of your paper, you will cite the specific literature that informs your research.

Write clearly and concisely

A good abstract is short but impactful, so make sure every word counts. Each sentence should
clearly communicate one main point.

To keep your abstract or summary short and clear:

 Avoid passive sentences: Passive constructions are often unnecessarily long. You can
easily make them shorter and clearer by using the active voice.
 Avoid long sentences: Substitute longer expressions for concise expressions or single
words (e.g., “In order to” for “To”).
  Avoid obscure jargon: The abstract should be understandable to readers who are not
familiar with your topic.
 Avoid repetition and filler words: Replace nouns with pronouns when possible and
eliminate unnecessary words.
 Avoid detailed descriptions: An abstract is not expected to provide detailed definitions,
background information, or discussions of other scholars’ work. Instead, include this
information in the body of your thesis or paper.

Introduction

After the title and abstract, the introduction is the next thing your audience will read, so it’s
vital to begin strongly. The introduction is your opportunity to show readers and reviewers why
your research topic is worth reading about and why your paper warrants their attention.

The introduction serves multiple purposes. It presents the background to your study, introduces
your topic and aims, and gives an overview of the paper. A good introduction will provide a
solid foundation and encour- age readers to continue on to the main parts of your paper—the
methods, results, and discussion.

In this article, we present 10 tips for writing an effective introduction. These tips apply
primarily to full papers and letters reporting original research results. Although some tips will
be more suited to papers in certain fields, the points are broadly applicable.
1 Start broadly and then narrow down

In the first paragraph, briefly describe the broad research area and then narrow down to your
particular focus. This will help position your research topic within the wider field, making the
work accessible to a broader audience, not just to specialists in your field.

2 State the aims and importance

Papers rejected for “not showing the importance of the topic” or “lacking clear motivation”
usually neglect this point. Say what you want to achieve and why your reader should be
interested in finding out whether you achieve it. The basic structure can be as simple as
“We aim to do X, which is important because it will lead to Y.”

3 Cite thoroughly but not excessively

Once you’ve narrowed your focus to the specific topic of your study, you should thoroughly
cover the most recent and most relevant literature pertaining to your study. Your review of the
literature should be complete, but not overly long— remember, you’re not writing a review
article. If you find that your introduction is too long or overflowing with citations, one possible
solution is to cite review articles, rather than all the individual articles that have already been
summarized in a review.
4 Avoid giving too many citations for one point

A sentence may cite too many studies at once. Although references might provide a good
overview of the topic, yet sometimes the sentence don’t provide enough context or explanation
for the past studies. If all of these references are worth cit- ing, they should be discussed in
greater specificity.

5 Clearly state your hypothesis or research question

For research in empirical sciences, stating a hypothesis can be an effective way of framing the
research. For example, instead of stating “In this study, we show that X is related to Y by
method A,” you could say, “In this study, we hypoth- esize that X is related to Y, and we use
method A to test this hypothesis.” For research in formal sciences or explora- tory research,
consider stating a research question instead: “In this study, we examine the following research
question: Is X related to Y?” Note that the research question doesn’t always have to be stated
in the interrogative form (with a question mark); instead, you can put the question into a
declarative sentence: “In this study, we investigate whether X is related to Y.” Hypotheses and
research questions are effective because they help give shape to the paper and serve as
important “signpost phrases” that guide readers through your paper smoothly.

6 Consider giving an overview of the paper

An organizational overview is more common in some fields than others. It is particularly

common in technology, but less so in medicine. In the last paragraph of your introduction,
consider giving a section-by-section overview of your paper if it is appropriate for your field.
For example, “In Section II, we describe our analysis methods and the datasets we used. In
Section III we present the results. In Section IV, we discuss the results and compare our
findings with those in the literature. In Section V, we state our conclusions and suggest
possible topics for future research.”

7 Keep it short

Try to avoid an overly long introduction. A good target is 500 to 1000 words, although
checking the journal’s guidelines and past issues will provide the clearest guidance.

8 Show, don’t tell

One goal of the introduction is to explain why your research topic is worthy of study. One of
the most common pitfalls is to simply say, “Subject X is important.” Instead of simply saying
that the topic is important, show why the topic is important. For example, instead of writing
 “The development of new materials is important for the automotive indus- try,” you could
write, “The development of new materials is necessary for the automotive industry to
produce stronger, lighter vehicles, which will improve safety and fuel economy.”

9 Don’t bury your readers in detail

In the introduction, if your paper is in a field that commonly summarizes the study’s main
results before starting the methods, you should avoid stating too many detailed results because
these results need the development in the other sections of your paper to be properly
understood. Instead of saying “We find that our algorithm requires 55% of the memory and
45% of the computation time of the conventional algorithm,” it is usually better to give a
general overview of the findings in the introduction: “Here we compare the proposed
algorithm with a conventional algorithm in terms of memory use and computational speed,
showing that the proposed algorithm is both smaller and faster.” Some older style guides
suggest holding back the main result to build suspense, but now journals in many fields—
medicine being a notable exception—encourage giving a preview of your main results in the
introduction.

Problem Statement |
A problem statement is a concise and concrete summary of the research problem you seek to
address. It should:

 Contextualize the problem. What do we already know?

 Describe the exact issue your research will address. What do we still need to know?
 Show the relevance of the problem. Why do we need to know more about this?
 Set the objectives of the research. What will you do to find out more?

The problem statement should frame your research problem, giving some background on what is
already known.

Practical research problems

For practical research, focus on the concrete details of the situation:

 Where and when does the problem arise?

 Who does the problem affect?
 What attempts have been made to solve the problem?

The problem statement should also address the relevance of the research. Why is it important that
the problem is addressed? Don’t worry, this doesn’t mean you have to do something
groundbreaking or world-changing. It’s more important that the problem is researchable,
feasible, and clearly addresses a relevant issue in your field.

Research Questions

A research question pinpoints exactly what you want to find out in your work. A good research
question is essential to guide your research paper, dissertation, or thesis.

All research questions should be:

 Focused on a single problem or issue

 Researchable using primary and/or secondary sources
 Feasible to answer within the timeframe and practical constraints
 Specific enough to answer thoroughly
 Complex enough to develop the answer over the space of a paper or thesis
 Relevant to your field of study and/or society more broadly

You will usually write a single research question to guide your progress in a research paper
or academic essay. Your answer then forms your thesis statement—the central assertion or
position that your paper will argue for.A bigger research project, such as a thesis or dissertation,
may necessitate multiple research questions or problem statements. However, they should all be
clearly connected and focused around a central research problem.
You can follow these steps to develop a strong research question:

 Choose your topic

 Do some preliminary reading about the current state of the field
 Narrow your focus to a specific niche
 Identify the research problem that you will address

The way you frame your question depends on what your research aims to achieve. The table
below shows some examples of how you might formulate questions for different purposes.

Using your research problem to develop your research question

Example research problem Example research question(s)

Teachers at the school do not have the skills to recognize What practical techniques can
or properly guide gifted children in the classroom. teachers use to better identify and
guide gifted children?

Young people increasingly engage in the “gig economy,” What are the main factors influencing
 Example research problem Example research question(s)

rather than traditional full-time employment. However, it young people’s decisions to engage in
is unclear why they choose to do so. the gig economy?

Chances are that your main research question likely can’t be answered all at once. That’s why
sub-questions are important: they allow you to answer your main question in a step-by-step
manner.

Good sub-questions should be:

 Less complex than the main question

 Focused only on 1 type of research
 Presented in a logical order

Here are a few examples of descriptive and framing questions:

 Descriptive: According to current government arguments, how should a European bank

tax be implemented?
 Descriptive: Which countries have a bank tax/levy on financial transactions?
 Framing: How should a bank tax/levy on financial transactions look at a European level?

Keep in mind that sub-questions are by no means mandatory. They should only be asked if you
need the findings to answer your main question. If your main question is simple enough to stand
on its own, it’s okay to skip the sub-question part. As a rule of thumb, the more complex your
subject, the more sub-questions you’ll need.

Try to limit yourself to 2 or 3 sub-questions, maximum. If you feel you need more than this, it
may be indication that your main research question is not sufficiently specific. In this case, it’s is
better to revisit your problem statement and try to tighten your main question up.

Why are research objectives important?

Objectives can help you stay focused and steer your research in the required direction. They help
define and limit the scope of your research, which is important to efficiently manage your
resources and time. The objectives help to create and maintain the overall structure, and specify
two main things—the variables and the methods of quantifying the variables.

A good research objective:

 defines the scope of the study

 gives direction to the research
 helps maintain focus and avoid diversions from the topic
 minimizes wastage of resources like time, money, and energy

Research objectives
Research objectives can be broadly classified into general and specific objectives.4 General
objectives state what the research expects to achieve overall while specific objectives break this
down into smaller, logically connected parts, each of which addresses various parts of the
research problem. General objectives are the main goals of the study and are usually fewer in
number while specific objectives are more in number because they address several aspects of the
research problem.

Example (general objective): To investigate the factors influencing the financial performance of
firms listed in the New York Stock Exchange market.

Example (specific objective): To assess the influence of firm size on the financial performance of
firms listed in the New York Stock Exchange market.

Research objectives can be written using the following steps:7

1. Brainstorming your objectives

1. State your main research question clearly and concisely.
2. Describe the ultimate goal of your study, which is similar to the research question but states the
intended outcomes more definitively.
3. Divide this main goal into subcategories to develop your objectives.
4. Limit the number of objectives (1-2 general; 3-4 specific)

2. Using the right language

1. Start each objective with an action verb like assess, compare, determine, evaluate, etc., which
makes the research appear more actionable.
2. Use specific language without making the sentence data heavy.

Literature Review

An effective review will summarise all the current articles (2-3 years), critically review their
content and point out the gaps in the literature requiring further research. The gaps then lead to
your research question and what your study will potentially add to the literature.

First paragraph: This paragraph should give a broad outline of the problem, the context in which
the study is being done and the background to the problem. Beware of overused statements:
“One third of the world’s population is infected with tuberculosis”. This is common knowledge
and does not grab the reviewers’ or readers’ attention – in fact, it is just boring. Just like in
clinical medicine where you have only 2 or 3 minutes to gain the trust of your patient, when you
write, you have 2 or 3 sentences in the first paragraph, to grab the interest of the reader/reviewer.

Second (and perhaps third) paragraph: This paragraph(s) narrows down to the published
research in the area you are interested in. Here you critically review the available knowledge.
Compare and contrast findings by groups of authors (and give references as 3-7) rather than
mentioning each study separately. Combining the findings of various published studies requires
careful synthesis and understanding of the available literature. Such a way often makes it much
easier to group the literature together. These paragraphs show whether you have insight into and
have really thought about the studies that you refer to.

Third and fourth paragraph: This paragraph(s) now narrows down even further with a critical
analysis of the limitations of previous studies or gaps/opportunities in the literature. How do you
write a review of the literature for your proposal? Look at previous published studies carefully
and you will see that they usually mention their limitations in the last few paragraphs and often
also mention future research ideas.

Fifth and possibly sixth paragraph: This paragraph(s) should now make it absolutely clear
exactly what your study is about as well as what it will add to the literature. Included in these
paragraphs should be your research question.

What are common mistakes in writing the review for a scientific research proposal?

1. Too much data/information: If there is too much data/information, especially when there is no
clear connection between the various studies reviewed, you will lose your reader and not build a
logical train of thought. This especially occurs if you do not synthesise the findings of the
different studies.

2. Too little data: It is often incorrectly assumed that the readers know the field and scientific
issues being discussed. Be careful not to make jumps in logic. You need a good balance between
too much and too little data: rather err on the side of too much data.

3. Unclear exactly what your study will contribute to the literature: Be very clear exactly what
the gaps/limitations are in the literature and how your study will address these gaps/limitations.

4. Confusing structure of the literature review: Think through very carefully the structure of the
review. Make sure there is a common thread running through the review. Your review is part of
your research proposal and not a stand-alone review. Avoid mentioning facts in your literature
review that you never refer to again in the methods, limitations, analysis of your research
proposal.
5. Avoid personal anecdotes: This is a scientific review and anecdotes should be avoided. If you
have completed a pilot study you might consider adding some of the possible outcomes but
rather save this for the feasibility section of the proposal.

6. Avoid duplication.

7. Get an early evaluation of your scientific review of the literature from your mentor. This will
help you refine your review before you re-write it.

8. Re-evaluate and re-write. Unluckily most of us have to re-write the review a number of times.

9. And lastly – remember that your literature review is a constant process – by the time your
proposal has been approved by the Ethics Committee, the chances are good that new studies have
been published since you wrote your proposal. Before you implement your study, ensure that you
are still up to date with the literature and if you have kept a record of your search criteria and key
words, this is easy! Keep up with the newest literature throughout your study.

Features of a Good Literature Review

Cite: Stick to cited articles or information sources, as they are your facts. Avoid personal
opinion.

Compare: Compare different articles to each other looking for agreements and disagreement.

Contrast: Look for articles that disagree and contrast the strengths and weaknesses leading to
research opportunities.

Critique: Identify what are the gaps in the literature and what are the research opportunities.

Connect: Synthesise what you have learned. How does this lead to your research question?

Concise: Keep your review to the point and avoid duplication.

Construct: Construct your review that it is orderly and systematic with a thread leading to your
question.

Check: Check that you have the newest information and re-check prior to writing your paper.

Theoretical Framework

A theoretical framework is a foundational review of existing theories that serves as a roadmap

for developing the arguments you will use in your own work. A theoretical framework in
research can be defined as a set of concepts, theories, ideas, and assumptions that help you
understand a specific phenomenon or problem. It can be considered a blueprint that is borrowed
by researchers to develop their own research inquiry. A theoretical framework in research helps
researchers design and conduct their research and analyze and interpret their findings. It explains
the relationship between variables, identifies gaps in existing knowledge, and guides the
development of research questions, hypotheses, and methodologies to address that gap.

Theories are developed by researchers to explain phenomena, draw connections, and make
predictions. In a theoretical framework, you explain the existing theories that support your
research, showing that your paper or dissertation topic is relevant and grounded in established
ideas.

In other words, your theoretical framework justifies and contextualizes your later research, and
it’s a crucial first step for your research paper, thesis, or dissertation. A well-rounded theoretical
framework sets you up for success later on in your research and writing process.

Why do you need a theoretical framework?

Before you start your own research, it’s crucial to familiarize yourself with the theories and
models that other researchers have already developed. Your theoretical framework is your
opportunity to present and explain what you’ve learned, situated within your future research
topic.

There’s a good chance that many different theories about your topic already exist, especially if
the topic is broad. In your theoretical framework, you will evaluate, compare, and select the most
relevant ones.

By “framing” your research within a clearly defined field, you make the reader aware of the
assumptions that inform your approach, showing the rationale behind your choices for later
sections, like methodology and discussion. This part of your dissertation lays the foundations
that will support your analysis, helping you interpret your results and make
broader generalizations.

Theoretical vs. conceptual framework

The terms “theoretical framework” and “conceptual framework” are often used interchangeably
but there are key differences between the two:

 Theoretical and conceptual frameworks basically differ in terms of scope.

 While a theoretical framework explores the relationship between things in a given
phenomenon in a broad and general way, a conceptual framework is more specific and
represents the researcher’s idea on how the research problem will be explored.
 A conceptual framework includes the ideas that are used to define research and evaluate
data. They usually fall within a theoretical framework and are often laid out using visuals
and graphics. Like theoretical frameworks, they're often included at the beginning of a
paper or experiment.
 Conceptual frameworks consist of variables, concepts, theories and parts of other existing
frameworks.
 Benefits of a theoretical framework
There are several benefits of a theoretical framework in research:2

 Provides a structured approach allowing researchers to organize their thoughts in a coherent

way.
 Helps to identify gaps in knowledge highlighting areas where further research is needed.
 Increases research efficiency by providing a clear direction for research and focusing efforts on
relevant data.
 Improves the quality of research by providing a rigorous and systematic approach to research,
which can increase the likelihood of producing valid and reliable results.
 Provides a basis for comparison by providing a common language and conceptual framework for
researchers to compare their findings with other research in the field, facilitating the exchange of
ideas and the development of new knowledge.

Significance of a Study
The significance of a study is its importance. It refers to the contribution(s) to and impact of the
study on a research field. The significance also signals who benefits from the research findings
and how.
A study’s significance should spark the interest of the reader. Researchers will be able to
appreciate your work better when they understand the relevance and its (potential) impact. Peer
reviewers also assess the significance of the work, which will influence the decision
made (acceptance/rejection) on the manuscript.
1. Make your research problem your starting point
Your problem statement can reveal information about the outcome of your research study and
who will benefit from it.
“How will the solutions to my research problem be beneficial?” This will give you an idea of
how valuable it is to conduct your research.
Assume your research question is “How effective is lemongrass (Cymbopogon citratus) in
lowering blood glucose levels in swiss mice (Mus musculus)?”
Finding a link between lemongrass use and lower blood glucose levels could lead to the
following outcomes:
 Increased public awareness of the plant’s medicinal properties
 The community has a greater appreciation for the value of lemongrass.
 Adoption of lemongrass tea as a low-cost, easily accessible, and natural remedy for
lowering blood glucose levels.
Once you’ve determined the broad benefits of your research, it’s time to narrow it down to
specific beneficiaries.

2. Describe how your research will add to the existing body of knowledge in the field
Consider the areas that previous studies should have covered. Then, explain how your research
addresses those unexplored areas. By doing so, you can persuade your readers that you are
researching something new and adding value to the field.
3. Describe how your research will help society
In this section, explain how your research will benefit society. Consider how the findings of your
research will affect your community.
For example, in the study on using lemongrass tea to lower blood glucose levels, your research
will help the community understand the importance of lemongrass and other herbal plants. As a
result, the community will be encouraged to promote medicinal plant cultivation and use.

4. Mention the specific people or organizations who will benefit from your research
Using the same example as before, this study’s findings will help people looking for an
alternative supplement to prevent high blood glucose levels.

5. Indicate how your research will aid future studies in the field
You must also specify how your research will be incorporated into the literature of the field you
are researching and how it will benefit future researchers. In our previous example, you could
say that future researchers will be able to investigate other capabilities of herbal plants in
preventing various diseases based on the data and analysis provided by your research.

6. Particular significance
Your problem statement can help you determine the specific contribution of your research. This
can be accomplished by observing a one-to-one correspondence between the problem’s purpose
and the study’s objectives.
For example, if your research question is “Is there a significant relationship between WhatsApp
usage and student spelling performance in English?” Perhaps one of your study’s contributions
could be “The study will identify common errors in spelling and grammar by WhatsApp users
and recommend its appropriate use in a manner that can improve better spelling performance.”

7. Literature voids
Consider the following to justify the need for the study:
 The gaps in related literature that must be addressed
 Where literature is scarce on the identified gaps
 Where the available literature suggests additional work on the identified gaps.

What Is a Research Methodology?

Methodology in research is defined as the systematic method to resolve a research problem
through data gathering using various techniques, providing an interpretation of data gathered and
drawing conclusions about the research data. Essentially, a research methodology is the blueprint
of a research or study (Murthy & Bhojanna, 2009, p. 32). As such, the methodology in research
proposal is of utmost importance.

Methodology vs. Methods

The confusion between “methodology" and “methods" in research is a common occurrence,
especially with the terms sometimes being used interchangeably. Methods and methodology in
the context of research refer to two related but different things: method is the technique used in
gathering evidence; methodology, on the other hand, “is the underlying theory and analysis of
how a research does or should proceed" (Kirsch & Sullivan, 1992, p. 2). Similarly, Birks and
Mills (2011, p. 4) define methodology as “a set of principles and ideas that inform the design of a
research study." Meanwhile, methods are “practical procedures used to generate and analyze data
(Birks and Mills, 2011, p. 4).

To summarize these definitions, methods cover the technical procedures or steps taken to do the
research, and methodology provides the underlying reasons why certain methods are used in the
process.

Quantitative
This approach is often used by researchers who follow the scientific paradigm (Haq, 2014, p. 1).
This method seeks to quantify data and generalize results from a sample of a target population.

Qualitative
Unlike the quantitative approach that aims to count things in order to explain what is observed,
the qualitative research framework is geared toward creating a complete and detailed description
of your observation as a researcher .

Mixed methods
A contemporary method sprung from the combination of traditional quantitative and qualitative
approaches.

How to write an effective methodology section?

 Introduce your methods. Introduce the methodological approach used in investigating

your research problem. In one of the previous sections, your methodological approach
can either be quantitative, qualitative, or mixed methods. Look for a methodology in
research example that you can use as a reference.
 Establish methodological connection. Explain the relevance of your methodological
approach to the overall research design. Keep in mind that the connection between your
methods and your research problem should be clear. This means that your methodology
of research must be appropriate to achieve your paper’s objective—to address the
research problem you presented. To wit, if you need help to write your research problem,
refer to our article on what is a research question.
 Introduce your instruments. Indicate the research instruments you are going to use in
collecting your data and explain how you are going to use them. These tools and
instruments can be your surveys, questionnaires for interviews, observation, etc. If your
methods include archival research or analyzing existing data, provide background
information for documents, including who the original researcher is, as well as how the
data were originally created and gathered. Keep in mind that aside from your
methodology in research paper, the identification of the research instrument is equally
significant.
 Discuss your analysis. Explain how you are going to analyze the results of your data
gathering process. Depending on your methodology, research for ways on how you can
 best execute your study either by using statistical analysis or exploring theoretical
perspectives to support your explanation of observed behaviors.
 Provide background information. When using methods that your readers may be
unfamiliar with, make sure to provide background information about these methods. It
would also help if you can provide your research methodology meaning so you can
present a clear and comprehensive research context.
 Discuss sampling process. Sampling procedures are vital components of your
methodology. Explain the reason behind your sampling procedure. For example, if you
are using statistics in your research, indicate why you chose this method as well as your
sampling procedure. If you are going to do interviews, describe how are you going to
choose the participants and how the interviews will be conducted.
 Address research limitations. Make sure to address possible limitations you may
encounter in your research, such as practical limitations that may affect your data
gathering process. If there are potential issues you anticipate to encounter in the process,
indicate your reason why you still decide to use the methodology despite the risk (SHU
Library, n.d.).

Data Collection Methods

Data collection methods are techniques and procedures for gathering information for research
purposes. They can range from simple self-reported surveys to more complex experiments and
can involve either quantitative or qualitative approaches.

Some common data collection methods include surveys, interviews, observations, focus groups,
experiments, and secondary data analysis. The data collected through these methods can then be
analyzed and used to support or refute research hypotheses and draw conclusions about the
study’s subject matter.

Understanding Data Collection Methods

Data collection methods encompass a variety of techniques and tools for gathering both
quantitative and qualitative data. These methods are integral to the data collection process,
ensuring accurate and comprehensive data acquisition. Quantitative data collection methods
involve systematic approaches to collecting data, like numerical data, such as surveys, polls, and
statistical analysis, aimed at quantifying phenomena and trends. Qualitative data collection
methods focus on capturing non-numerical information, such as interviews, focus groups, and
observations, to delve deeper into understanding attitudes, behaviors, and motivations.

Employing a combination of quantitative and qualitative data collection techniques can enrich
organizations’ datasets and gain comprehensive insights into complex phenomena.

1. Surveys: Surveys collect data from the target audience and gather insights into their
preferences, opinions, choices, and feedback related to their products and services. Most survey
software offers a wide range of question types.
You can also use a ready-made survey template to save time and effort. Online surveys can be
customized to match the business’s brand by changing the theme, logo, etc. They can be
distributed through several channels, such as email, website, offline app, QR code, social media,
etc.

2. Polls: Polls comprise one single or multiple-choice question. They are useful when you need
to get a quick pulse of the audience’s sentiments. Because they are short, it is easier to get
responses from people.

Like surveys, online polls can be embedded into various platforms. Once the respondents answer
the question, they can also be shown how they compare to others’ responses.

3. Interviews: In face-to-face interviews, the interviewer asks a series of questions to the

interviewee in person and notes down responses. If it is not feasible to meet the person, the
interviewer can go for a telephone interview.

This form of data collection is suitable for only a few respondents. It is too time-consuming and
tedious to repeat the same process if there are many participants.

4. Delphi Technique: In the Delphi method, market experts are provided with the estimates and
assumptions of other industry experts’ forecasts. Experts may reconsider and revise their
estimates and assumptions based on this information. The consensus of all experts on demand
forecasts constitutes the final demand forecast.

5. Focus Groups: Focus groups are one example of qualitative data in education. In a focus
group, a small group of people, around 8-10 members, discuss the common areas of the research
problem. Each individual provides his or her insights on the issue concerned.

6. Questionnaire: A questionnaire is a printed set of open-ended or closed-ended questions that

respondents must answer based on their knowledge and experience with the issue. The
questionnaire is part of the survey, whereas the questionnaire’s end goal may or may not be a
survey.

Data Analysis in Research

Definition of research in data analysis: According to LeCompte and Schensul, research data
analysis is a process used by researchers to reduce data to a story and interpret it to derive
insights. The data analysis process helps reduce a large chunk of data into smaller fragments,
which makes sense.
Three essential things occur during the data analysis process — the first is data organization.
Summarization and categorization together contribute to becoming the second known method
used for data reduction. It helps find patterns and themes in the data for easy identification and
linking. The third and last way is data analysis – researchers do it in both top-down and bottom-
up fashion.

On the other hand, Marshall and Rossman describe data analysis as a messy, ambiguous, and
time-consuming but creative and fascinating process through which a mass of collected data is
brought to order, structure and meaning.

We can say that “the data analysis and data interpretation is a process representing the
application of deductive and inductive logic to the research and data analysis.”

Why analyze data in research?

Researchers rely heavily on data as they have a story to tell or research problems to solve. It
starts with a question, and data is nothing but an answer to that question. But, what if there is no
question to ask? Well! It is possible to explore data even without a problem – we call it ‘Data
Mining’, which often reveals some interesting patterns within the data that are worth exploring.

Irrelevant to the type of data researchers explore, their mission and audiences’ vision guide them
to find the patterns to shape the story they want to tell. One of the essential things expected from
researchers while analyzing data is to stay open and remain unbiased toward unexpected
patterns, expressions, and results. Remember, sometimes, data analysis tells the most unforeseen
yet exciting stories that were not expected when initiating data analysis. Therefore, rely on the
data you have at hand and enjoy the journey of exploratory research.

Types of data in research

Every kind of data has a rare quality of describing things after assigning a specific value to it.
For analysis, you need to organize these values, processed and presented in a given context, to
make it useful. Data can be in different forms; here are the primary data types.

 Qualitative data: When the data presented has words and descriptions, then we call
it qualitative data. Although you can observe this data, it is subjective and harder to
analyze data in research, especially for comparison. Example: Quality data represents
everything describing taste, experience, texture, or an opinion that is considered quality
data. This type of data is usually collected through focus groups, personal qualitative
interviews, qualitative observation or using open-ended questions in surveys.
 Quantitative data: Any data expressed in numbers of numerical figures are
called quantitative data. This type of data can be distinguished into categories, grouped,
measured, calculated, or ranked.
 Categorical data: It is data presented in groups. However, an item included in the
categorical data cannot belong to more than one group. Example: A person responding to
 a survey by telling his living style, marital status, smoking habit, or drinking habit comes
under the categorical data.

Data analysis in qualitative research

Data analysis and qualitative data research work a little differently from the numerical data as the
quality data is made up of words, descriptions, images, objects, and sometimes symbols. Getting
insight from such complicated information is a complicated process. Hence it is typically used
for exploratory research and data analysis.

Finding patterns in the qualitative data

Although there are several ways to find patterns in the textual information, a word-based method
is the most relied and widely used global technique for research and data analysis. Notably, the
data analysis process in qualitative research is manual. Here the researchers usually read the
available data and find repetitive or commonly used words.

There are several techniques to analyze the data in qualitative research, but here are some
commonly used methods,

 Content Analysis: It is widely accepted and the most frequently employed technique for
data analysis in research methodology. It can be used to analyze the documented
information from text, images, and sometimes from the physical items. It depends on
the research questions to predict when and where to use this method.
 Narrative Analysis: This method is used to analyze content gathered from various sources
such as personal interviews, field observation, and surveys. The majority of times,
stories, or opinions shared by people are focused on finding answers to the research
questions.
 Discourse Analysis: Similar to narrative analysis, discourse analysis is used to analyze
the interactions with people. Nevertheless, this particular method considers the social
context under which or within which the communication between the researcher and
respondent takes place. In addition to that, discourse analysis also focuses on the lifestyle
and day-to-day environment while deriving any conclusion.
 Grounded Theory: When you want to explain why a particular phenomenon happened,
then using grounded theory for analyzing quality data is the best resort. Grounded theory
is applied to study data about the host of similar cases occurring in different settings.
When researchers are using this method, they might alter explanations or produce new
ones until they arrive at some conclusion.

Methods used for data analysis in quantitative research

After the data is prepared for analysis, researchers are open to using different research and data
analysis methods to derive meaningful insights. For sure, statistical analysis plans are the most
favored to analyze numerical data. In statistical analysis, distinguishing between categorical data
and numerical data is essential, as categorical data involves distinct categories or labels, while
numerical data consists of measurable quantities. The method is again classified into two groups.
First, ‘Descriptive Statistics’ used to describe data. Second, ‘Inferential statistics’ that helps in
comparing the data.

Descriptive statistics

This method is used to describe the basic features of versatile types of data in research. It
presents the data in such a meaningful way that pattern in the data starts making sense.
Nevertheless, the descriptive analysis does not go beyond making conclusions. The conclusions
are again based on the hypothesis researchers have formulated so far. Here are a few major types
of descriptive analysis methods.

Measures of Frequency

 Count, Percent, Frequency

 It is used to denote home often a particular event occurs.
 Researchers use it when they want to showcase how often a response is given.

Measures of Central Tendency

 Mean, Median, Mode

 The method is widely used to demonstrate distribution by various points.
 Researchers use this method when they want to showcase the most commonly or
averagely indicated response.

Measures of Dispersion or Variation

 Range, Variance, Standard deviation

Findings:

The Results section of a scientific research paper represents the core findings of a study derived
from the methods applied to gather and analyze information. It presents these findings in a
logical sequence without bias or interpretation from the author, setting up the reader for later
interpretation and evaluation in the Discussion section.

The Results section should include the findings of your study and ONLY the findings of your
study. The findings include:
 Data presented in tables, charts, graphs, and other figures (may be placed into the text or on
separate pages at the end of the manuscript)
 A contextual analysis of this data explaining its meaning in sentence form

 All data that corresponds to the central research question(s)

 All secondary findings (secondary outcomes, subgroup analyses, etc.)

How to write a results section

Here are a few best practices:

 Your results should always be written in the past tense.

 While the length of this section depends on how much data you collected and analyzed, it
should be written as concisely as possible.
 Only include results that are directly relevant to answering your research questions.
Avoid speculative or interpretative words like “appears” or “implies.”
 If you have other results you’d like to include, consider adding them to
an appendix or footnotes.
 Always start out with your broadest results first, and then flow into your more granular
(but still relevant) ones. Think of it like a shoe store: first discuss the shoes as a whole,
then the sneakers, boots, sandals, etc.

Discussion:

The discussion section is where you delve into the meaning, importance, and relevance of
your results.

It should focus on explaining and evaluating what you found, showing how it relates to
your literature review and paper or dissertation topic, and making an argument in support of your
overall conclusion. It should not be a second results section.

There are different ways to write this section, but you can focus your writing around these key
elements:

 Summary: A brief recap of your key results

 Interpretations: What do your results mean?
 Implications: Why do your results matter?
 Limitations: What can’t your results tell us?
 Recommendations: Avenues for further studies or analyses

Conclusion:

The conclusion of a research paper is where you wrap up your ideas and leave the reader with a
strong final impression. It has several key goals:
  Restate the problem statement addressed in the paper
 Summarize your overall arguments or findings
 Suggest the key takeaways from your paper

An effective conclusion for a research paper reminds your readers of the strength and impact of
your argument. Concluding statements can also help to refocus the reader's attention on the most
important points and supporting evidence of your arguments or position that you presented in
your research. Conclusions can also serve as a basis for continuing research, creating new ideas
to resolve an issue you highlighted in your paper or offering new approaches to a topic.

Here are some helpful tips to keep in mind when you write your research paper conclusion:

 Keep your thesis, main points and summarizing facts clear and concise.
 If you get overwhelmed, try sticking to a basic summarizing format for your conclusion.
 Synthesize your information by providing questions and answers, results, suggestions or
a resolution to your arguments.
 Include only the most relevant points and arguments you presented in your paper.

Here are some common pitfalls to avoid when writing a conclusion for a research paper:

 Avoid beginning your conclusion with statements like "in conclusion" or "in summary,"
as these basic statements can come across as redundant.
 Do not include completely new information in your conclusion.
 Don't wait until your conclusion to state your thesis.
 Steer clear of rambling and be concise and straightforward as possible. Stick to the
implications of your research rather than the methodologies and results of your studies
(which should be in the body of your paper).
 Resist the urge to apologize if you have doubts regarding your research paper. If you feel
the need to address the weaknesses of the research, stick to discussing any limitations you
faced.
 Avoid being overly emotional rather than analytical in your conclusion.

Recommendations

Research recommendations are suggestions for future research based on the findings of a
research study. It is a significant element in the research paper structure, as it is critical to your
discussion section and conclusion. While conducting research and analyzing gathered data, you
may come across ideas or results that only partially align with the scope of your research topic.
Alternatively, your findings offer possible implications or causal relationships between the
aspects not covered in existing research.
This section will provide practical solutions for further research based on your conclusions and
findings. The particular goals of this section depend on the research nature and usually include
the following:

 Providing strategies to address the issues considered in the paper;

 Delivering suggestions on how the investigation findings can be applied in practice;

 Identifying gaps in the subject area and suggesting ways to extend existing knowledge;

 Enhancing reliability and validity of the research findings.

References

There are two famous styles of references. APA and MLA.

APA

A basic reference list entry for a journal article in APA must include:

 Author or authors. The surname is followed by first initials.

 Year of publication of the article (in round brackets).
 Article title.
 Journal title (in italics).
 Volume of journal (in italics).
 Issue number of journal in round brackets (no italics).
 Page range of article.
 DOI or URL
 The first line of each citation is left adjusted. Every subsequent line is indented 5-7
spaces.

Example:

Ruxton, C. (2016). Tea: Hydration and other health benefits. Primary Health Care, 26(8), 34-
42. https://doi.org/10.7748/phc.2016.e1162
MLA

Author Last Name, First Name. “Title of the Article.” Journal/Magazine/Newspaper Title, vol.,
no., Day Month Year OR Season, Permalink or shortened URL. Accessed Day Month Year.

Ramlal, Mohan. "The Classical Music Culture of South India." Indialogs: Spanish Journal of
India Studies, vol. 1, 01 July 2014, pp. 134-45, revistes.uab.cat/indialogs/article/view/v1-
ramanan/pdf. Accessed 10 Aug. 2017.