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Scope of the Research – Writing Guide and Examples

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Scope of the Research

Scope of research refers to the range of topics, areas, and subjects that a research project intends to cover. It is the extent and limitations of the study, defining what is included and excluded in the research.

The scope of a research project depends on various factors, such as the research questions , objectives , methodology, and available resources. It is essential to define the scope of the research project clearly to avoid confusion and ensure that the study addresses the intended research questions.

How to Write Scope of the Research

Writing the scope of the research involves identifying the specific boundaries and limitations of the study. Here are some steps you can follow to write a clear and concise scope of the research:

• Identify the research question: Start by identifying the specific question that you want to answer through your research . This will help you focus your research and define the scope more clearly.
• Define the objectives: Once you have identified the research question, define the objectives of your study. What specific goals do you want to achieve through your research?
• Determine the population and sample: Identify the population or group of people that you will be studying, as well as the sample size and selection criteria. This will help you narrow down the scope of your research and ensure that your findings are applicable to the intended audience.
• Identify the variables: Determine the variables that will be measured or analyzed in your research. This could include demographic variables, independent variables , dependent variables , or any other relevant factors.
• Define the timeframe: Determine the timeframe for your study, including the start and end date, as well as any specific time intervals that will be measured.
• Determine the geographical scope: If your research is location-specific, define the geographical scope of your study. This could include specific regions, cities, or neighborhoods that you will be focusing on.
• Outline the limitations: Finally, outline any limitations or constraints of your research, such as time, resources, or access to data. This will help readers understand the scope and applicability of your research findings.

Examples of the Scope of the Research

Some Examples of the Scope of the Research are as follows:

Title : “Investigating the impact of artificial intelligence on job automation in the IT industry”

Scope of Research:

This study aims to explore the impact of artificial intelligence on job automation in the IT industry. The research will involve a qualitative analysis of job postings, identifying tasks that can be automated using AI. The study will also assess the potential implications of job automation on the workforce, including job displacement, job creation, and changes in job requirements.

Title : “Developing a machine learning model for predicting cyberattacks on corporate networks”

This study will develop a machine learning model for predicting cyberattacks on corporate networks. The research will involve collecting and analyzing network traffic data, identifying patterns and trends that are indicative of cyberattacks. The study aims to build an accurate and reliable predictive model that can help organizations identify and prevent cyberattacks before they occur.

Title: “Assessing the usability of a mobile app for managing personal finances”

This study will assess the usability of a mobile app for managing personal finances. The research will involve conducting a usability test with a group of participants, evaluating the app’s ease of use, efficiency, and user satisfaction. The study aims to identify areas of the app that need improvement, and to provide recommendations for enhancing its usability and user experience.

Title : “Exploring the effects of mindfulness meditation on stress reduction among college students”

This study aims to investigate the impact of mindfulness meditation on reducing stress levels among college students. The research will involve a randomized controlled trial with two groups: a treatment group that receives mindfulness meditation training and a control group that receives no intervention. The study will examine changes in stress levels, as measured by self-report questionnaires, before and after the intervention.

Title: “Investigating the impact of social media on body image dissatisfaction among young adults”

This study will explore the relationship between social media use and body image dissatisfaction among young adults. The research will involve a cross-sectional survey of participants aged 18-25, assessing their social media use, body image perceptions, and self-esteem. The study aims to identify any correlations between social media use and body image dissatisfaction, and to determine if certain social media platforms or types of content are particularly harmful.

When to Write Scope of the Research

Here is a guide on When to Write the Scope of the Research:

• Before starting your research project, it’s important to clearly define the scope of your study. This will help you stay focused on your research question and avoid getting sidetracked by irrelevant information.
• The scope of the research should be determined by the research question or problem statement. It should outline what you intend to investigate and what you will not be investigating.
• The scope should also take into consideration any limitations of the study, such as time, resources, or access to data. This will help you realistically plan and execute your research.
• Writing the scope of the research early in the research process can also help you refine your research question and identify any gaps in the existing literature that your study can address.
• It’s important to revisit the scope of the research throughout the research process to ensure that you stay on track and make any necessary adjustments.
• The scope of the research should be clearly communicated in the research proposal or study protocol to ensure that all stakeholders are aware of the research objectives and limitations.
• The scope of the research should also be reflected in the research design, methods, and analysis plan. This will ensure that the research is conducted in a systematic and rigorous manner that is aligned with the research objectives.
• The scope of the research should be written in a clear and concise manner, using language that is accessible to all stakeholders, including those who may not be familiar with the research topic or methodology.
• When writing the scope of the research, it’s important to be transparent about any assumptions or biases that may influence the research findings. This will help ensure that the research is conducted in an ethical and responsible manner.
• The scope of the research should be reviewed and approved by the research supervisor, committee members, or other relevant stakeholders. This will ensure that the research is feasible, relevant, and contributes to the field of study.
• Finally, the scope of the research should be clearly stated in the research report or dissertation to provide context for the research findings and conclusions. This will help readers understand the significance of the research and its contribution to the field of study.

Purpose of Scope of the Research

Purposes of Scope of the Research are as follows:

• Defines the boundaries and extent of the study.
• Determines the specific objectives and research questions to be addressed.
• Provides direction and focus for the research.
• Helps to identify the relevant theories, concepts, and variables to be studied.
• Enables the researcher to select the appropriate research methodology and techniques.
• Allows for the allocation of resources (time, money, personnel) to the research.
• Establishes the criteria for the selection of the sample and data collection methods.
• Facilitates the interpretation and generalization of the results.
• Ensures the ethical considerations and constraints are addressed.
• Provides a framework for the presentation and dissemination of the research findings.

Advantages of Scope of the Research

Here are some advantages of having a well-defined scope of research:

• Provides clarity and focus: Defining the scope of research helps to provide clarity and focus to the study. This ensures that the research stays on track and does not deviate from its intended purpose.
• Helps to manage resources: Knowing the scope of research allows researchers to allocate resources effectively. This includes managing time, budget, and personnel required to conduct the study.
• Improves the quality of research: A well-defined scope of research helps to ensure that the study is designed to achieve specific objectives. This helps to improve the quality of the research by reducing the likelihood of errors or bias.
• Facilitates communication: A clear scope of research enables researchers to communicate the goals and objectives of the study to stakeholders, such as funding agencies or participants. This facilitates understanding and enhances cooperation.
• Enables replication : A well-defined scope of research makes it easier to replicate the study in the future. This allows other researchers to validate the findings and build upon them, leading to the advancement of knowledge in the field.
• Increases the relevance of research: Defining the scope of research helps to ensure that the study is relevant to the problem or issue being investigated. This increases the likelihood that the findings will be useful and applicable to real-world situations.
• Reduces the risk of scope creep : Scope creep occurs when the research expands beyond the original scope, leading to an increase in the time, cost, and resources required to complete the study. A clear definition of the scope of research helps to reduce the risk of scope creep by establishing boundaries and limitations.
• Enhances the credibility of research: A well-defined scope of research helps to enhance the credibility of the study by ensuring that it is designed to achieve specific objectives and answer specific research questions. This makes it easier for others to assess the validity and reliability of the study.
• Provides a framework for decision-making : A clear scope of research provides a framework for decision-making throughout the research process. This includes decisions related to data collection, analysis, and interpretation.

Scope of the Research Vs Scope of the Project

About the author.

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Scope and Delimitations – Explained & Example

• By DiscoverPhDs
• October 2, 2020

What Is Scope and Delimitation in Research?

The scope and delimitations of a thesis, dissertation or research paper define the topic and boundaries of the research problem to be investigated.

The scope details how in-depth your study is to explore the research question and the parameters in which it will operate in relation to the population and timeframe.

The delimitations of a study are the factors and variables not to be included in the investigation. In other words, they are the boundaries the researcher sets in terms of study duration, population size and type of participants, etc.

Difference Between Delimitations and Limitations

Delimitations refer to the boundaries of the research study, based on the researcher’s decision of what to include and what to exclude. They narrow your study to make it more manageable and relevant to what you are trying to prove.

Limitations relate to the validity and reliability of the study. They are characteristics of the research design or methodology that are out of your control but influence your research findings. Because of this, they determine the internal and external validity of your study and are considered potential weaknesses.

In other words, limitations are what the researcher cannot do (elements outside of their control) and delimitations are what the researcher will not do (elements outside of the boundaries they have set). Both are important because they help to put the research findings into context, and although they explain how the study is limited, they increase the credibility and validity of a research project.

Guidelines on How to Write a Scope

A good scope statement will answer the following six questions:

• Why – the general aims and objectives (purpose) of the research.
• What – the subject to be investigated, and the included variables.
• Where – the location or setting of the study, i.e. where the data will be gathered and to which entity the data will belong.
• When – the timeframe within which the data is to be collected.
• Who – the subject matter of the study and the population from which they will be selected. This population needs to be large enough to be able to make generalisations.
• How – how the research is to be conducted, including a description of the research design (e.g. whether it is experimental research, qualitative research or a case study), methodology, research tools and analysis techniques.

To make things as clear as possible, you should also state why specific variables were omitted from the research scope, and whether this was because it was a delimitation or a limitation. You should also explain why they could not be overcome with standard research methods backed up by scientific evidence.

How to Start Writing Your Study Scope

Use the below prompts as an effective way to start writing your scope:

• This study is to focus on…
• This study covers the…
• This study aims to…

Guidelines on How to Write Delimitations

Since the delimitation parameters are within the researcher’s control, readers need to know why they were set, what alternative options were available, and why these alternatives were rejected. For example, if you are collecting data that can be derived from three different but similar experiments, the reader needs to understand how and why you decided to select the one you have.

Your reasons should always be linked back to your research question, as all delimitations should result from trying to make your study more relevant to your scope. Therefore, the scope and delimitations are usually considered together when writing a paper.

How to Start Writing Your Study Delimitations

Use the below prompts as an effective way to start writing your study delimitations:

• This study does not cover…
• This study is limited to…
• The following has been excluded from this study…

Examples of Delimitation in Research

Examples of delimitations include:

• research objectives,
• research questions,
• research variables,
• target populations,
• statistical analysis techniques .

Examples of Limitations in Research

Examples of limitations include:

• Issues with sample and selection,
• Insufficient sample size, population traits or specific participants for statistical significance,
• Lack of previous research studies on the topic which has allowed for further analysis,
• Limitations in the technology/instruments used to collect your data,
• Limited financial resources and/or funding constraints.

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Frequently asked questions

How do i determine scope of research.

Scope of research is determined at the beginning of your research process , prior to the data collection stage. Sometimes called “scope of study,” your scope delineates what will and will not be covered in your project. It helps you focus your work and your time, ensuring that you’ll be able to achieve your goals and outcomes.

Defining a scope can be very useful in any research project, from a research proposal to a thesis or dissertation . A scope is needed for all types of research: quantitative , qualitative , and mixed methods .

To define your scope of research, consider the following:

• Budget constraints or any specifics of grant funding
• Your proposed timeline and duration
• Specifics about your population of study, your proposed sample size , and the research methodology you’ll pursue
• Any inclusion and exclusion criteria
• Any anticipated control , extraneous , or confounding variables that could bias your research if not accounted for properly.

Frequently asked questions: Methodology

Quantitative observations involve measuring or counting something and expressing the result in numerical form, while qualitative observations involve describing something in non-numerical terms, such as its appearance, texture, or color.

To make quantitative observations , you need to use instruments that are capable of measuring the quantity you want to observe. For example, you might use a ruler to measure the length of an object or a thermometer to measure its temperature.

Inclusion and exclusion criteria are predominantly used in non-probability sampling . In purposive sampling and snowball sampling , restrictions apply as to who can be included in the sample .

Inclusion and exclusion criteria are typically presented and discussed in the methodology section of your thesis or dissertation .

The purpose of theory-testing mode is to find evidence in order to disprove, refine, or support a theory. As such, generalisability is not the aim of theory-testing mode.

Due to this, the priority of researchers in theory-testing mode is to eliminate alternative causes for relationships between variables . In other words, they prioritise internal validity over external validity , including ecological validity .

Convergent validity shows how much a measure of one construct aligns with other measures of the same or related constructs .

On the other hand, concurrent validity is about how a measure matches up to some known criterion or gold standard, which can be another measure.

Although both types of validity are established by calculating the association or correlation between a test score and another variable , they represent distinct validation methods.

Validity tells you how accurately a method measures what it was designed to measure. There are 4 main types of validity :

• Construct validity : Does the test measure the construct it was designed to measure?
• Face validity : Does the test appear to be suitable for its objectives ?
• Content validity : Does the test cover all relevant parts of the construct it aims to measure.
• Criterion validity : Do the results accurately measure the concrete outcome they are designed to measure?

Criterion validity evaluates how well a test measures the outcome it was designed to measure. An outcome can be, for example, the onset of a disease.

Criterion validity consists of two subtypes depending on the time at which the two measures (the criterion and your test) are obtained:

• Concurrent validity is a validation strategy where the the scores of a test and the criterion are obtained at the same time
• Predictive validity is a validation strategy where the criterion variables are measured after the scores of the test

Attrition refers to participants leaving a study. It always happens to some extent – for example, in randomised control trials for medical research.

Differential attrition occurs when attrition or dropout rates differ systematically between the intervention and the control group . As a result, the characteristics of the participants who drop out differ from the characteristics of those who stay in the study. Because of this, study results may be biased .

Criterion validity and construct validity are both types of measurement validity . In other words, they both show you how accurately a method measures something.

While construct validity is the degree to which a test or other measurement method measures what it claims to measure, criterion validity is the degree to which a test can predictively (in the future) or concurrently (in the present) measure something.

Construct validity is often considered the overarching type of measurement validity . You need to have face validity , content validity , and criterion validity in order to achieve construct validity.

Convergent validity and discriminant validity are both subtypes of construct validity . Together, they help you evaluate whether a test measures the concept it was designed to measure.

• Convergent validity indicates whether a test that is designed to measure a particular construct correlates with other tests that assess the same or similar construct.
• Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related. This type of validity is also called divergent validity .

You need to assess both in order to demonstrate construct validity. Neither one alone is sufficient for establishing construct validity.

Face validity and content validity are similar in that they both evaluate how suitable the content of a test is. The difference is that face validity is subjective, and assesses content at surface level.

When a test has strong face validity, anyone would agree that the test’s questions appear to measure what they are intended to measure.

For example, looking at a 4th grade math test consisting of problems in which students have to add and multiply, most people would agree that it has strong face validity (i.e., it looks like a math test).

On the other hand, content validity evaluates how well a test represents all the aspects of a topic. Assessing content validity is more systematic and relies on expert evaluation. of each question, analysing whether each one covers the aspects that the test was designed to cover.

A 4th grade math test would have high content validity if it covered all the skills taught in that grade. Experts(in this case, math teachers), would have to evaluate the content validity by comparing the test to the learning objectives.

Content validity shows you how accurately a test or other measurement method taps  into the various aspects of the specific construct you are researching.

In other words, it helps you answer the question: “does the test measure all aspects of the construct I want to measure?” If it does, then the test has high content validity.

The higher the content validity, the more accurate the measurement of the construct.

If the test fails to include parts of the construct, or irrelevant parts are included, the validity of the instrument is threatened, which brings your results into question.

Construct validity refers to how well a test measures the concept (or construct) it was designed to measure. Assessing construct validity is especially important when you’re researching concepts that can’t be quantified and/or are intangible, like introversion. To ensure construct validity your test should be based on known indicators of introversion ( operationalisation ).

On the other hand, content validity assesses how well the test represents all aspects of the construct. If some aspects are missing or irrelevant parts are included, the test has low content validity.

• Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related

Construct validity has convergent and discriminant subtypes. They assist determine if a test measures the intended notion.

The reproducibility and replicability of a study can be ensured by writing a transparent, detailed method section and using clear, unambiguous language.

Reproducibility and replicability are related terms.

• A successful reproduction shows that the data analyses were conducted in a fair and honest manner.
• A successful replication shows that the reliability of the results is high.
• Reproducing research entails reanalysing the existing data in the same manner.
• Replicating (or repeating ) the research entails reconducting the entire analysis, including the collection of new data . 

Snowball sampling is a non-probability sampling method . Unlike probability sampling (which involves some form of random selection ), the initial individuals selected to be studied are the ones who recruit new participants.

Because not every member of the target population has an equal chance of being recruited into the sample, selection in snowball sampling is non-random.

Snowball sampling is a non-probability sampling method , where there is not an equal chance for every member of the population to be included in the sample .

This means that you cannot use inferential statistics and make generalisations – often the goal of quantitative research . As such, a snowball sample is not representative of the target population, and is usually a better fit for qualitative research .

Snowball sampling relies on the use of referrals. Here, the researcher recruits one or more initial participants, who then recruit the next ones. 

Participants share similar characteristics and/or know each other. Because of this, not every member of the population has an equal chance of being included in the sample, giving rise to sampling bias .

Snowball sampling is best used in the following cases:

• If there is no sampling frame available (e.g., people with a rare disease)
• If the population of interest is hard to access or locate (e.g., people experiencing homelessness)
• If the research focuses on a sensitive topic (e.g., extra-marital affairs)

Stratified sampling and quota sampling both involve dividing the population into subgroups and selecting units from each subgroup. The purpose in both cases is to select a representative sample and/or to allow comparisons between subgroups.

The main difference is that in stratified sampling, you draw a random sample from each subgroup ( probability sampling ). In quota sampling you select a predetermined number or proportion of units, in a non-random manner ( non-probability sampling ).

Random sampling or probability sampling is based on random selection. This means that each unit has an equal chance (i.e., equal probability) of being included in the sample.

On the other hand, convenience sampling involves stopping people at random, which means that not everyone has an equal chance of being selected depending on the place, time, or day you are collecting your data.

Convenience sampling and quota sampling are both non-probability sampling methods. They both use non-random criteria like availability, geographical proximity, or expert knowledge to recruit study participants.

However, in convenience sampling, you continue to sample units or cases until you reach the required sample size.

In quota sampling, you first need to divide your population of interest into subgroups (strata) and estimate their proportions (quota) in the population. Then you can start your data collection , using convenience sampling to recruit participants, until the proportions in each subgroup coincide with the estimated proportions in the population.

A sampling frame is a list of every member in the entire population . It is important that the sampling frame is as complete as possible, so that your sample accurately reflects your population.

Stratified and cluster sampling may look similar, but bear in mind that groups created in cluster sampling are heterogeneous , so the individual characteristics in the cluster vary. In contrast, groups created in stratified sampling are homogeneous , as units share characteristics.

Relatedly, in cluster sampling you randomly select entire groups and include all units of each group in your sample. However, in stratified sampling, you select some units of all groups and include them in your sample. In this way, both methods can ensure that your sample is representative of the target population .

When your population is large in size, geographically dispersed, or difficult to contact, it’s necessary to use a sampling method .

This allows you to gather information from a smaller part of the population, i.e. the sample, and make accurate statements by using statistical analysis. A few sampling methods include simple random sampling , convenience sampling , and snowball sampling .

The two main types of social desirability bias are:

• Self-deceptive enhancement (self-deception): The tendency to see oneself in a favorable light without realizing it.
• Impression managemen t (other-deception): The tendency to inflate one’s abilities or achievement in order to make a good impression on other people.

Response bias refers to conditions or factors that take place during the process of responding to surveys, affecting the responses. One type of response bias is social desirability bias .

Demand characteristics are aspects of experiments that may give away the research objective to participants. Social desirability bias occurs when participants automatically try to respond in ways that make them seem likeable in a study, even if it means misrepresenting how they truly feel.

Participants may use demand characteristics to infer social norms or experimenter expectancies and act in socially desirable ways, so you should try to control for demand characteristics wherever possible.

A systematic review is secondary research because it uses existing research. You don’t collect new data yourself.

Ethical considerations in research are a set of principles that guide your research designs and practices. These principles include voluntary participation, informed consent, anonymity, confidentiality, potential for harm, and results communication.

Scientists and researchers must always adhere to a certain code of conduct when collecting data from others .

These considerations protect the rights of research participants, enhance research validity , and maintain scientific integrity.

Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe.

Research misconduct means making up or falsifying data, manipulating data analyses, or misrepresenting results in research reports. It’s a form of academic fraud.

These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement but a serious ethical failure.

Anonymity means you don’t know who the participants are, while confidentiality means you know who they are but remove identifying information from your research report. Both are important ethical considerations .

You can only guarantee anonymity by not collecting any personally identifying information – for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, or videos.

You can keep data confidential by using aggregate information in your research report, so that you only refer to groups of participants rather than individuals.

Peer review is a process of evaluating submissions to an academic journal. Utilising rigorous criteria, a panel of reviewers in the same subject area decide whether to accept each submission for publication.

For this reason, academic journals are often considered among the most credible sources you can use in a research project – provided that the journal itself is trustworthy and well regarded.

In general, the peer review process follows the following steps:

• First, the author submits the manuscript to the editor.
• Reject the manuscript and send it back to author, or
• Send it onward to the selected peer reviewer(s)
• Next, the peer review process occurs. The reviewer provides feedback, addressing any major or minor issues with the manuscript, and gives their advice regarding what edits should be made.
• Lastly, the edited manuscript is sent back to the author. They input the edits, and resubmit it to the editor for publication.

Peer review can stop obviously problematic, falsified, or otherwise untrustworthy research from being published. It also represents an excellent opportunity to get feedback from renowned experts in your field.

It acts as a first defence, helping you ensure your argument is clear and that there are no gaps, vague terms, or unanswered questions for readers who weren’t involved in the research process.

Peer-reviewed articles are considered a highly credible source due to this stringent process they go through before publication.

Many academic fields use peer review , largely to determine whether a manuscript is suitable for publication. Peer review enhances the credibility of the published manuscript.

However, peer review is also common in non-academic settings. The United Nations, the European Union, and many individual nations use peer review to evaluate grant applications. It is also widely used in medical and health-related fields as a teaching or quality-of-care measure.

Peer assessment is often used in the classroom as a pedagogical tool. Both receiving feedback and providing it are thought to enhance the learning process, helping students think critically and collaboratively.

• In a single-blind study , only the participants are blinded.
• In a double-blind study , both participants and experimenters are blinded.
• In a triple-blind study , the assignment is hidden not only from participants and experimenters, but also from the researchers analysing the data.

Blinding is important to reduce bias (e.g., observer bias , demand characteristics ) and ensure a study’s internal validity .

If participants know whether they are in a control or treatment group , they may adjust their behaviour in ways that affect the outcome that researchers are trying to measure. If the people administering the treatment are aware of group assignment, they may treat participants differently and thus directly or indirectly influence the final results.

Blinding means hiding who is assigned to the treatment group and who is assigned to the control group in an experiment .

Explanatory research is a research method used to investigate how or why something occurs when only a small amount of information is available pertaining to that topic. It can help you increase your understanding of a given topic.

Explanatory research is used to investigate how or why a phenomenon occurs. Therefore, this type of research is often one of the first stages in the research process , serving as a jumping-off point for future research.

Exploratory research is a methodology approach that explores research questions that have not previously been studied in depth. It is often used when the issue you’re studying is new, or the data collection process is challenging in some way.

Exploratory research is often used when the issue you’re studying is new or when the data collection process is challenging for some reason.

You can use exploratory research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

To implement random assignment , assign a unique number to every member of your study’s sample .

Then, you can use a random number generator or a lottery method to randomly assign each number to a control or experimental group. You can also do so manually, by flipping a coin or rolling a die to randomly assign participants to groups.

Random selection, or random sampling , is a way of selecting members of a population for your study’s sample.

In contrast, random assignment is a way of sorting the sample into control and experimental groups.

Random sampling enhances the external validity or generalisability of your results, while random assignment improves the internal validity of your study.

Random assignment is used in experiments with a between-groups or independent measures design. In this research design, there’s usually a control group and one or more experimental groups. Random assignment helps ensure that the groups are comparable.

In general, you should always use random assignment in this type of experimental design when it is ethically possible and makes sense for your study topic.

Clean data are valid, accurate, complete, consistent, unique, and uniform. Dirty data include inconsistencies and errors.

Dirty data can come from any part of the research process, including poor research design , inappropriate measurement materials, or flawed data entry.

Data cleaning takes place between data collection and data analyses. But you can use some methods even before collecting data.

For clean data, you should start by designing measures that collect valid data. Data validation at the time of data entry or collection helps you minimize the amount of data cleaning you’ll need to do.

After data collection, you can use data standardisation and data transformation to clean your data. You’ll also deal with any missing values, outliers, and duplicate values.

Data cleaning involves spotting and resolving potential data inconsistencies or errors to improve your data quality. An error is any value (e.g., recorded weight) that doesn’t reflect the true value (e.g., actual weight) of something that’s being measured.

In this process, you review, analyse, detect, modify, or remove ‘dirty’ data to make your dataset ‘clean’. Data cleaning is also called data cleansing or data scrubbing.

Data cleaning is necessary for valid and appropriate analyses. Dirty data contain inconsistencies or errors , but cleaning your data helps you minimise or resolve these.

Without data cleaning, you could end up with a Type I or II error in your conclusion. These types of erroneous conclusions can be practically significant with important consequences, because they lead to misplaced investments or missed opportunities.

Observer bias occurs when a researcher’s expectations, opinions, or prejudices influence what they perceive or record in a study. It usually affects studies when observers are aware of the research aims or hypotheses. This type of research bias is also called detection bias or ascertainment bias .

The observer-expectancy effect occurs when researchers influence the results of their own study through interactions with participants.

Researchers’ own beliefs and expectations about the study results may unintentionally influence participants through demand characteristics .

You can use several tactics to minimise observer bias .

• Use masking (blinding) to hide the purpose of your study from all observers.
• Triangulate your data with different data collection methods or sources.
• Use multiple observers and ensure inter-rater reliability.
• Train your observers to make sure data is consistently recorded between them.
• Standardise your observation procedures to make sure they are structured and clear.

Naturalistic observation is a valuable tool because of its flexibility, external validity , and suitability for topics that can’t be studied in a lab setting.

The downsides of naturalistic observation include its lack of scientific control , ethical considerations , and potential for bias from observers and subjects.

Naturalistic observation is a qualitative research method where you record the behaviours of your research subjects in real-world settings. You avoid interfering or influencing anything in a naturalistic observation.

You can think of naturalistic observation as ‘people watching’ with a purpose.

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.

Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.

You can organise the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomisation can minimise the bias from order effects.

Questionnaires can be self-administered or researcher-administered.

Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or by post. All questions are standardised so that all respondents receive the same questions with identical wording.

Researcher-administered questionnaires are interviews that take place by phone, in person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.

In a controlled experiment , all extraneous variables are held constant so that they can’t influence the results. Controlled experiments require:

• A control group that receives a standard treatment, a fake treatment, or no treatment
• Random assignment of participants to ensure the groups are equivalent

Depending on your study topic, there are various other methods of controlling variables .

An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.

A true experiment (aka a controlled experiment) always includes at least one control group that doesn’t receive the experimental treatment.

However, some experiments use a within-subjects design to test treatments without a control group. In these designs, you usually compare one group’s outcomes before and after a treatment (instead of comparing outcomes between different groups).

For strong internal validity , it’s usually best to include a control group if possible. Without a control group, it’s harder to be certain that the outcome was caused by the experimental treatment and not by other variables.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analysing data from people using questionnaires.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviours. It is made up of four or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with five or seven possible responses, to capture their degree of agreement.

Individual Likert-type questions are generally considered ordinal data , because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyse your data.

A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (‘ x affects y because …’).

A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses. In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess. It should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).

Cross-sectional studies are less expensive and time-consuming than many other types of study. They can provide useful insights into a population’s characteristics and identify correlations for further research.

Sometimes only cross-sectional data are available for analysis; other times your research question may only require a cross-sectional study to answer it.

Cross-sectional studies cannot establish a cause-and-effect relationship or analyse behaviour over a period of time. To investigate cause and effect, you need to do a longitudinal study or an experimental study .

Longitudinal studies and cross-sectional studies are two different types of research design . In a cross-sectional study you collect data from a population at a specific point in time; in a longitudinal study you repeatedly collect data from the same sample over an extended period of time.

Longitudinal studies are better to establish the correct sequence of events, identify changes over time, and provide insight into cause-and-effect relationships, but they also tend to be more expensive and time-consuming than other types of studies.

The 1970 British Cohort Study , which has collected data on the lives of 17,000 Brits since their births in 1970, is one well-known example of a longitudinal study .

Longitudinal studies can last anywhere from weeks to decades, although they tend to be at least a year long.

A correlation reflects the strength and/or direction of the association between two or more variables.

• A positive correlation means that both variables change in the same direction.
• A negative correlation means that the variables change in opposite directions.
• A zero correlation means there’s no relationship between the variables.

A correlational research design investigates relationships between two variables (or more) without the researcher controlling or manipulating any of them. It’s a non-experimental type of quantitative research .

A correlation coefficient is a single number that describes the strength and direction of the relationship between your variables.

Different types of correlation coefficients might be appropriate for your data based on their levels of measurement and distributions . The Pearson product-moment correlation coefficient (Pearson’s r ) is commonly used to assess a linear relationship between two quantitative variables.

Controlled experiments establish causality, whereas correlational studies only show associations between variables.

• In an experimental design , you manipulate an independent variable and measure its effect on a dependent variable. Other variables are controlled so they can’t impact the results.
• In a correlational design , you measure variables without manipulating any of them. You can test whether your variables change together, but you can’t be sure that one variable caused a change in another.

In general, correlational research is high in external validity while experimental research is high in internal validity .

The third variable and directionality problems are two main reasons why correlation isn’t causation .

The third variable problem means that a confounding variable affects both variables to make them seem causally related when they are not.

The directionality problem is when two variables correlate and might actually have a causal relationship, but it’s impossible to conclude which variable causes changes in the other.

As a rule of thumb, questions related to thoughts, beliefs, and feelings work well in focus groups . Take your time formulating strong questions, paying special attention to phrasing. Be careful to avoid leading questions , which can bias your responses.

Overall, your focus group questions should be:

• Open-ended and flexible
• Impossible to answer with ‘yes’ or ‘no’ (questions that start with ‘why’ or ‘how’ are often best)
• Unambiguous, getting straight to the point while still stimulating discussion
• Unbiased and neutral

Social desirability bias is the tendency for interview participants to give responses that will be viewed favourably by the interviewer or other participants. It occurs in all types of interviews and surveys , but is most common in semi-structured interviews , unstructured interviews , and focus groups .

Social desirability bias can be mitigated by ensuring participants feel at ease and comfortable sharing their views. Make sure to pay attention to your own body language and any physical or verbal cues, such as nodding or widening your eyes.

This type of bias in research can also occur in observations if the participants know they’re being observed. They might alter their behaviour accordingly.

A focus group is a research method that brings together a small group of people to answer questions in a moderated setting. The group is chosen due to predefined demographic traits, and the questions are designed to shed light on a topic of interest. It is one of four types of interviews .

The four most common types of interviews are:

• Structured interviews : The questions are predetermined in both topic and order.
• Semi-structured interviews : A few questions are predetermined, but other questions aren’t planned.
• Unstructured interviews : None of the questions are predetermined.
• Focus group interviews : The questions are presented to a group instead of one individual.

An unstructured interview is the most flexible type of interview, but it is not always the best fit for your research topic.

Unstructured interviews are best used when:

• You are an experienced interviewer and have a very strong background in your research topic, since it is challenging to ask spontaneous, colloquial questions
• Your research question is exploratory in nature. While you may have developed hypotheses, you are open to discovering new or shifting viewpoints through the interview process.
• You are seeking descriptive data, and are ready to ask questions that will deepen and contextualise your initial thoughts and hypotheses
• Your research depends on forming connections with your participants and making them feel comfortable revealing deeper emotions, lived experiences, or thoughts

A semi-structured interview is a blend of structured and unstructured types of interviews. Semi-structured interviews are best used when:

• You have prior interview experience. Spontaneous questions are deceptively challenging, and it’s easy to accidentally ask a leading question or make a participant uncomfortable.
• Your research question is exploratory in nature. Participant answers can guide future research questions and help you develop a more robust knowledge base for future research.

The interviewer effect is a type of bias that emerges when a characteristic of an interviewer (race, age, gender identity, etc.) influences the responses given by the interviewee.

There is a risk of an interviewer effect in all types of interviews , but it can be mitigated by writing really high-quality interview questions.

A structured interview is a data collection method that relies on asking questions in a set order to collect data on a topic. They are often quantitative in nature. Structured interviews are best used when:

• You already have a very clear understanding of your topic. Perhaps significant research has already been conducted, or you have done some prior research yourself, but you already possess a baseline for designing strong structured questions.
• You are constrained in terms of time or resources and need to analyse your data quickly and efficiently
• Your research question depends on strong parity between participants, with environmental conditions held constant

More flexible interview options include semi-structured interviews , unstructured interviews , and focus groups .

When conducting research, collecting original data has significant advantages:

• You can tailor data collection to your specific research aims (e.g., understanding the needs of your consumers or user testing your website).
• You can control and standardise the process for high reliability and validity (e.g., choosing appropriate measurements and sampling methods ).

However, there are also some drawbacks: data collection can be time-consuming, labour-intensive, and expensive. In some cases, it’s more efficient to use secondary data that has already been collected by someone else, but the data might be less reliable.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organisations.

A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship.

A confounder is a third variable that affects variables of interest and makes them seem related when they are not. In contrast, a mediator is the mechanism of a relationship between two variables: it explains the process by which they are related.

If something is a mediating variable :

• It’s caused by the independent variable
• It influences the dependent variable
• When it’s taken into account, the statistical correlation between the independent and dependent variables is higher than when it isn’t considered

Including mediators and moderators in your research helps you go beyond studying a simple relationship between two variables for a fuller picture of the real world. They are important to consider when studying complex correlational or causal relationships.

Mediators are part of the causal pathway of an effect, and they tell you how or why an effect takes place. Moderators usually help you judge the external validity of your study by identifying the limitations of when the relationship between variables holds.

You can think of independent and dependent variables in terms of cause and effect: an independent variable is the variable you think is the cause , while a dependent variable is the effect .

In an experiment, you manipulate the independent variable and measure the outcome in the dependent variable. For example, in an experiment about the effect of nutrients on crop growth:

• The  independent variable  is the amount of nutrients added to the crop field.
• The  dependent variable is the biomass of the crops at harvest time.

Defining your variables, and deciding how you will manipulate and measure them, is an important part of experimental design .

Discrete and continuous variables are two types of quantitative variables :

• Discrete variables represent counts (e.g., the number of objects in a collection).
• Continuous variables represent measurable amounts (e.g., water volume or weight).

Quantitative variables are any variables where the data represent amounts (e.g. height, weight, or age).

Categorical variables are any variables where the data represent groups. This includes rankings (e.g. finishing places in a race), classifications (e.g. brands of cereal), and binary outcomes (e.g. coin flips).

You need to know what type of variables you are working with to choose the right statistical test for your data and interpret your results .

Determining cause and effect is one of the most important parts of scientific research. It’s essential to know which is the cause – the independent variable – and which is the effect – the dependent variable.

You want to find out how blood sugar levels are affected by drinking diet cola and regular cola, so you conduct an experiment .

• The type of cola – diet or regular – is the independent variable .
• The level of blood sugar that you measure is the dependent variable – it changes depending on the type of cola.

No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both.

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

To ensure the internal validity of your research, you must consider the impact of confounding variables. If you fail to account for them, you might over- or underestimate the causal relationship between your independent and dependent variables , or even find a causal relationship where none exists.

A confounding variable is closely related to both the independent and dependent variables in a study. An independent variable represents the supposed cause , while the dependent variable is the supposed effect . A confounding variable is a third variable that influences both the independent and dependent variables.

Failing to account for confounding variables can cause you to wrongly estimate the relationship between your independent and dependent variables.

There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control, and randomisation.

In restriction , you restrict your sample by only including certain subjects that have the same values of potential confounding variables.

In matching , you match each of the subjects in your treatment group with a counterpart in the comparison group. The matched subjects have the same values on any potential confounding variables, and only differ in the independent variable .

In statistical control , you include potential confounders as variables in your regression .

In randomisation , you randomly assign the treatment (or independent variable) in your study to a sufficiently large number of subjects, which allows you to control for all potential confounding variables.

In scientific research, concepts are the abstract ideas or phenomena that are being studied (e.g., educational achievement). Variables are properties or characteristics of the concept (e.g., performance at school), while indicators are ways of measuring or quantifying variables (e.g., yearly grade reports).

The process of turning abstract concepts into measurable variables and indicators is called operationalisation .

In statistics, ordinal and nominal variables are both considered categorical variables .

Even though ordinal data can sometimes be numerical, not all mathematical operations can be performed on them.

A control variable is any variable that’s held constant in a research study. It’s not a variable of interest in the study, but it’s controlled because it could influence the outcomes.

Control variables help you establish a correlational or causal relationship between variables by enhancing internal validity .

If you don’t control relevant extraneous variables , they may influence the outcomes of your study, and you may not be able to demonstrate that your results are really an effect of your independent variable .

‘Controlling for a variable’ means measuring extraneous variables and accounting for them statistically to remove their effects on other variables.

Researchers often model control variable data along with independent and dependent variable data in regression analyses and ANCOVAs . That way, you can isolate the control variable’s effects from the relationship between the variables of interest.

An extraneous variable is any variable that you’re not investigating that can potentially affect the dependent variable of your research study.

A confounding variable is a type of extraneous variable that not only affects the dependent variable, but is also related to the independent variable.

There are 4 main types of extraneous variables :

• Demand characteristics : Environmental cues that encourage participants to conform to researchers’ expectations
• Experimenter effects : Unintentional actions by researchers that influence study outcomes
• Situational variables : Eenvironmental variables that alter participants’ behaviours
• Participant variables : Any characteristic or aspect of a participant’s background that could affect study results

The difference between explanatory and response variables is simple:

• An explanatory variable is the expected cause, and it explains the results.
• A response variable is the expected effect, and it responds to other variables.

The term ‘ explanatory variable ‘ is sometimes preferred over ‘ independent variable ‘ because, in real-world contexts, independent variables are often influenced by other variables. This means they aren’t totally independent.

Multiple independent variables may also be correlated with each other, so ‘explanatory variables’ is a more appropriate term.

On graphs, the explanatory variable is conventionally placed on the x -axis, while the response variable is placed on the y -axis.

• If you have quantitative variables , use a scatterplot or a line graph.
• If your response variable is categorical, use a scatterplot or a line graph.
• If your explanatory variable is categorical, use a bar graph.

A correlation is usually tested for two variables at a time, but you can test correlations between three or more variables.

An independent variable is the variable you manipulate, control, or vary in an experimental study to explore its effects. It’s called ‘independent’ because it’s not influenced by any other variables in the study.

Independent variables are also called:

• Explanatory variables (they explain an event or outcome)
• Predictor variables (they can be used to predict the value of a dependent variable)
• Right-hand-side variables (they appear on the right-hand side of a regression equation)

A dependent variable is what changes as a result of the independent variable manipulation in experiments . It’s what you’re interested in measuring, and it ‘depends’ on your independent variable.

In statistics, dependent variables are also called:

• Response variables (they respond to a change in another variable)
• Outcome variables (they represent the outcome you want to measure)
• Left-hand-side variables (they appear on the left-hand side of a regression equation)

Deductive reasoning is commonly used in scientific research, and it’s especially associated with quantitative research .

In research, you might have come across something called the hypothetico-deductive method . It’s the scientific method of testing hypotheses to check whether your predictions are substantiated by real-world data.

Deductive reasoning is a logical approach where you progress from general ideas to specific conclusions. It’s often contrasted with inductive reasoning , where you start with specific observations and form general conclusions.

Deductive reasoning is also called deductive logic.

Inductive reasoning is a method of drawing conclusions by going from the specific to the general. It’s usually contrasted with deductive reasoning, where you proceed from general information to specific conclusions.

Inductive reasoning is also called inductive logic or bottom-up reasoning.

In inductive research , you start by making observations or gathering data. Then, you take a broad scan of your data and search for patterns. Finally, you make general conclusions that you might incorporate into theories.

Inductive reasoning is a bottom-up approach, while deductive reasoning is top-down.

Inductive reasoning takes you from the specific to the general, while in deductive reasoning, you make inferences by going from general premises to specific conclusions.

There are many different types of inductive reasoning that people use formally or informally.

Here are a few common types:

• Inductive generalisation : You use observations about a sample to come to a conclusion about the population it came from.
• Statistical generalisation: You use specific numbers about samples to make statements about populations.
• Causal reasoning: You make cause-and-effect links between different things.
• Sign reasoning: You make a conclusion about a correlational relationship between different things.
• Analogical reasoning: You make a conclusion about something based on its similarities to something else.

It’s often best to ask a variety of people to review your measurements. You can ask experts, such as other researchers, or laypeople, such as potential participants, to judge the face validity of tests.

While experts have a deep understanding of research methods , the people you’re studying can provide you with valuable insights you may have missed otherwise.

Face validity is important because it’s a simple first step to measuring the overall validity of a test or technique. It’s a relatively intuitive, quick, and easy way to start checking whether a new measure seems useful at first glance.

Good face validity means that anyone who reviews your measure says that it seems to be measuring what it’s supposed to. With poor face validity, someone reviewing your measure may be left confused about what you’re measuring and why you’re using this method.

Face validity is about whether a test appears to measure what it’s supposed to measure. This type of validity is concerned with whether a measure seems relevant and appropriate for what it’s assessing only on the surface.

Statistical analyses are often applied to test validity with data from your measures. You test convergent validity and discriminant validity with correlations to see if results from your test are positively or negatively related to those of other established tests.

You can also use regression analyses to assess whether your measure is actually predictive of outcomes that you expect it to predict theoretically. A regression analysis that supports your expectations strengthens your claim of construct validity .

When designing or evaluating a measure, construct validity helps you ensure you’re actually measuring the construct you’re interested in. If you don’t have construct validity, you may inadvertently measure unrelated or distinct constructs and lose precision in your research.

Construct validity is often considered the overarching type of measurement validity ,  because it covers all of the other types. You need to have face validity , content validity, and criterion validity to achieve construct validity.

Construct validity is about how well a test measures the concept it was designed to evaluate. It’s one of four types of measurement validity , which includes construct validity, face validity , and criterion validity.

There are two subtypes of construct validity.

• Convergent validity : The extent to which your measure corresponds to measures of related constructs
• Discriminant validity: The extent to which your measure is unrelated or negatively related to measures of distinct constructs

Attrition bias can skew your sample so that your final sample differs significantly from your original sample. Your sample is biased because some groups from your population are underrepresented.

With a biased final sample, you may not be able to generalise your findings to the original population that you sampled from, so your external validity is compromised.

There are seven threats to external validity : selection bias , history, experimenter effect, Hawthorne effect , testing effect, aptitude-treatment, and situation effect.

The two types of external validity are population validity (whether you can generalise to other groups of people) and ecological validity (whether you can generalise to other situations and settings).

The external validity of a study is the extent to which you can generalise your findings to different groups of people, situations, and measures.

Attrition bias is a threat to internal validity . In experiments, differential rates of attrition between treatment and control groups can skew results.

This bias can affect the relationship between your independent and dependent variables . It can make variables appear to be correlated when they are not, or vice versa.

Internal validity is the extent to which you can be confident that a cause-and-effect relationship established in a study cannot be explained by other factors.

There are eight threats to internal validity : history, maturation, instrumentation, testing, selection bias , regression to the mean, social interaction, and attrition .

A sampling error is the difference between a population parameter and a sample statistic .

A statistic refers to measures about the sample , while a parameter refers to measures about the population .

Populations are used when a research question requires data from every member of the population. This is usually only feasible when the population is small and easily accessible.

Systematic sampling is a probability sampling method where researchers select members of the population at a regular interval – for example, by selecting every 15th person on a list of the population. If the population is in a random order, this can imitate the benefits of simple random sampling .

There are three key steps in systematic sampling :

• Define and list your population , ensuring that it is not ordered in a cyclical or periodic order.
• Decide on your sample size and calculate your interval, k , by dividing your population by your target sample size.
• Choose every k th member of the population as your sample.

Yes, you can create a stratified sample using multiple characteristics, but you must ensure that every participant in your study belongs to one and only one subgroup. In this case, you multiply the numbers of subgroups for each characteristic to get the total number of groups.

For example, if you were stratifying by location with three subgroups (urban, rural, or suburban) and marital status with five subgroups (single, divorced, widowed, married, or partnered), you would have 3 × 5 = 15 subgroups.

You should use stratified sampling when your sample can be divided into mutually exclusive and exhaustive subgroups that you believe will take on different mean values for the variable that you’re studying.

Using stratified sampling will allow you to obtain more precise (with lower variance ) statistical estimates of whatever you are trying to measure.

For example, say you want to investigate how income differs based on educational attainment, but you know that this relationship can vary based on race. Using stratified sampling, you can ensure you obtain a large enough sample from each racial group, allowing you to draw more precise conclusions.

In stratified sampling , researchers divide subjects into subgroups called strata based on characteristics that they share (e.g., race, gender, educational attainment).

Once divided, each subgroup is randomly sampled using another probability sampling method .

Multistage sampling can simplify data collection when you have large, geographically spread samples, and you can obtain a probability sample without a complete sampling frame.

But multistage sampling may not lead to a representative sample, and larger samples are needed for multistage samples to achieve the statistical properties of simple random samples .

In multistage sampling , you can use probability or non-probability sampling methods.

For a probability sample, you have to probability sampling at every stage. You can mix it up by using simple random sampling , systematic sampling , or stratified sampling to select units at different stages, depending on what is applicable and relevant to your study.

Cluster sampling is a probability sampling method in which you divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample.

The clusters should ideally each be mini-representations of the population as a whole.

There are three types of cluster sampling : single-stage, double-stage and multi-stage clustering. In all three types, you first divide the population into clusters, then randomly select clusters for use in your sample.

• In single-stage sampling , you collect data from every unit within the selected clusters.
• In double-stage sampling , you select a random sample of units from within the clusters.
• In multi-stage sampling , you repeat the procedure of randomly sampling elements from within the clusters until you have reached a manageable sample.

Cluster sampling is more time- and cost-efficient than other probability sampling methods , particularly when it comes to large samples spread across a wide geographical area.

However, it provides less statistical certainty than other methods, such as simple random sampling , because it is difficult to ensure that your clusters properly represent the population as a whole.

If properly implemented, simple random sampling is usually the best sampling method for ensuring both internal and external validity . However, it can sometimes be impractical and expensive to implement, depending on the size of the population to be studied,

If you have a list of every member of the population and the ability to reach whichever members are selected, you can use simple random sampling.

The American Community Survey  is an example of simple random sampling . In order to collect detailed data on the population of the US, the Census Bureau officials randomly select 3.5 million households per year and use a variety of methods to convince them to fill out the survey.

Simple random sampling is a type of probability sampling in which the researcher randomly selects a subset of participants from a population . Each member of the population has an equal chance of being selected. Data are then collected from as large a percentage as possible of this random subset.

Sampling bias occurs when some members of a population are systematically more likely to be selected in a sample than others.

In multistage sampling , or multistage cluster sampling, you draw a sample from a population using smaller and smaller groups at each stage.

This method is often used to collect data from a large, geographically spread group of people in national surveys, for example. You take advantage of hierarchical groupings (e.g., from county to city to neighbourhood) to create a sample that’s less expensive and time-consuming to collect data from.

In non-probability sampling , the sample is selected based on non-random criteria, and not every member of the population has a chance of being included.

Common non-probability sampling methods include convenience sampling , voluntary response sampling, purposive sampling , snowball sampling , and quota sampling .

Probability sampling means that every member of the target population has a known chance of being included in the sample.

Probability sampling methods include simple random sampling , systematic sampling , stratified sampling , and cluster sampling .

Samples are used to make inferences about populations . Samples are easier to collect data from because they are practical, cost-effective, convenient, and manageable.

While a between-subjects design has fewer threats to internal validity , it also requires more participants for high statistical power than a within-subjects design .

Advantages:

• Prevents carryover effects of learning and fatigue.
• Shorter study duration.

Disadvantages:

• Needs larger samples for high power.
• Uses more resources to recruit participants, administer sessions, cover costs, etc.
• Individual differences may be an alternative explanation for results.

In a factorial design, multiple independent variables are tested.

If you test two variables, each level of one independent variable is combined with each level of the other independent variable to create different conditions.

Yes. Between-subjects and within-subjects designs can be combined in a single study when you have two or more independent variables (a factorial design). In a mixed factorial design, one variable is altered between subjects and another is altered within subjects.

Within-subjects designs have many potential threats to internal validity , but they are also very statistically powerful .

• Only requires small samples
• Statistically powerful
• Removes the effects of individual differences on the outcomes
• Internal validity threats reduce the likelihood of establishing a direct relationship between variables
• Time-related effects, such as growth, can influence the outcomes
• Carryover effects mean that the specific order of different treatments affect the outcomes

Quasi-experimental design is most useful in situations where it would be unethical or impractical to run a true experiment .

Quasi-experiments have lower internal validity than true experiments, but they often have higher external validity  as they can use real-world interventions instead of artificial laboratory settings.

In experimental research, random assignment is a way of placing participants from your sample into different groups using randomisation. With this method, every member of the sample has a known or equal chance of being placed in a control group or an experimental group.

A quasi-experiment is a type of research design that attempts to establish a cause-and-effect relationship. The main difference between this and a true experiment is that the groups are not randomly assigned.

In a between-subjects design , every participant experiences only one condition, and researchers assess group differences between participants in various conditions.

In a within-subjects design , each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.

The word ‘between’ means that you’re comparing different conditions between groups, while the word ‘within’ means you’re comparing different conditions within the same group.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

Triangulation can help:

• Reduce bias that comes from using a single method, theory, or investigator
• Enhance validity by approaching the same topic with different tools
• Establish credibility by giving you a complete picture of the research problem

But triangulation can also pose problems:

• It’s time-consuming and labour-intensive, often involving an interdisciplinary team.
• Your results may be inconsistent or even contradictory.

There are four main types of triangulation :

• Data triangulation : Using data from different times, spaces, and people
• Investigator triangulation : Involving multiple researchers in collecting or analysing data
• Theory triangulation : Using varying theoretical perspectives in your research
• Methodological triangulation : Using different methodologies to approach the same topic

Experimental designs are a set of procedures that you plan in order to examine the relationship between variables that interest you.

To design a successful experiment, first identify:

• A testable hypothesis
• One or more independent variables that you will manipulate
• One or more dependent variables that you will measure

When designing the experiment, first decide:

• How your variable(s) will be manipulated
• How you will control for any potential confounding or lurking variables
• How many subjects you will include
• How you will assign treatments to your subjects

Exploratory research explores the main aspects of a new or barely researched question.

Explanatory research explains the causes and effects of an already widely researched question.

The key difference between observational studies and experiments is that, done correctly, an observational study will never influence the responses or behaviours of participants. Experimental designs will have a treatment condition applied to at least a portion of participants.

An observational study could be a good fit for your research if your research question is based on things you observe. If you have ethical, logistical, or practical concerns that make an experimental design challenging, consider an observational study. Remember that in an observational study, it is critical that there be no interference or manipulation of the research subjects. Since it’s not an experiment, there are no control or treatment groups either.

These are four of the most common mixed methods designs :

• Convergent parallel: Quantitative and qualitative data are collected at the same time and analysed separately. After both analyses are complete, compare your results to draw overall conclusions. 
• Embedded: Quantitative and qualitative data are collected at the same time, but within a larger quantitative or qualitative design. One type of data is secondary to the other.
• Explanatory sequential: Quantitative data is collected and analysed first, followed by qualitative data. You can use this design if you think your qualitative data will explain and contextualise your quantitative findings.
• Exploratory sequential: Qualitative data is collected and analysed first, followed by quantitative data. You can use this design if you think the quantitative data will confirm or validate your qualitative findings.

Triangulation in research means using multiple datasets, methods, theories and/or investigators to address a research question. It’s a research strategy that can help you enhance the validity and credibility of your findings.

Triangulation is mainly used in qualitative research , but it’s also commonly applied in quantitative research . Mixed methods research always uses triangulation.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

There are five common approaches to qualitative research :

• Grounded theory involves collecting data in order to develop new theories.
• Ethnography involves immersing yourself in a group or organisation to understand its culture.
• Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
• Phenomenological research involves investigating phenomena through people’s lived experiences.
• Action research links theory and practice in several cycles to drive innovative changes.

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organise your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyse data (e.g. experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
• If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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Academic Research in Education

• How to Find Books, Articles and eBooks
• Books, eBooks, & Multimedia
• Evaluating Information
• Deciding on a Topic
• Creating a Thesis Statement
• The Literature Review
• Scope of Research

Defining the Scope of your Project

What is scope.

• Choosing a Design
• Citing Sources & Avoiding Plagiarism
• Contact Library

Post-Grad Collective [PGC]. (2017, February 13). Thesis Writing-Narrow the Scope   [Video file]. Retrieved from https://www.youtube.com/watch?v=IlCO5yRB9No&feature=youtu.be

Learn to cite a YouTube Video! 

The scope of your project sets clear parameters for your research. 

A scope statement will give basic information about the depth and breadth of the project. It tells your reader exactly what you want to find out , how you will conduct your study, the reports and deliverables  that will be part of the outcome of the study, and the responsibilities of the researchers involved in the study. The extent of the scope will be a part of acknowledging any biases in the research project. 

Defining the scope of a project: 

• focuses your research goals
• clarifies the expectations for your research project
•  helps you determine potential biases in your research methodology by acknowledging the limits of your research study 
• identifies the limitations of your research 
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Setting Limits and Focusing Your Study: Exploring scope and delimitation

As a researcher, it can be easy to get lost in the vast expanse of information and data available. Thus, when starting a research project, one of the most important things to consider is the scope and delimitation of the study. Setting limits and focusing your study is essential to ensure that the research project is manageable, relevant, and able to produce useful results. In this article, we will explore the importance of setting limits and focusing your study through an in-depth analysis of scope and delimitation.

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Table of Contents

Scope and Delimitation – Definition and difference

Scope refers to the range of the research project and the study limitations set in place to define the boundaries of the project and delimitation refers to the specific aspects of the research project that the study will focus on.

In simpler words, scope is the breadth of your study, while delimitation is the depth of your study.

Scope and delimitation are both essential components of a research project, and they are often confused with one another. The scope defines the parameters of the study, while delimitation sets the boundaries within those parameters. The scope and delimitation of a study are usually established early on in the research process and guide the rest of the project.

Types of Scope and Delimitation

Significance of Scope and Delimitation

Setting limits and focusing your study through scope and delimitation is crucial for the following reasons:

• It allows researchers to define the research project’s boundaries, enabling them to focus on specific aspects of the project. This focus makes it easier to gather relevant data and avoid unnecessary information that might complicate the study’s results.
• Setting limits and focusing your study through scope and delimitation enables the researcher to stay within the parameters of the project’s resources.
• A well-defined scope and delimitation ensure that the research project can be completed within the available resources, such as time and budget, while still achieving the project’s objectives.

5 Steps to Setting Limits and Defining the Scope and Delimitation of Your Study

There are a few steps that you can take to set limits and focus your study.

1. Identify your research question or topic

The first step is to identify what you are interested in learning about. The research question should be specific, measurable, achievable, relevant, and time-bound (SMART). Once you have a research question or topic, you can start to narrow your focus.

2. Consider the key terms or concepts related to your topic

What are the important terms or concepts that you need to understand in order to answer your research question? Consider all available resources, such as time, budget, and data availability, when setting scope and delimitation.

The scope and delimitation should be established within the parameters of the available resources. Once you have identified the key terms or concepts, you can start to develop a glossary or list of definitions.

3. Consider the different perspectives on your topic

There are often different perspectives on any given topic. Get feedback on the proposed scope and delimitation. Advisors can provide guidance on the feasibility of the study and offer suggestions for improvement.

It is important to consider all of the different perspectives in order to get a well-rounded understanding of your topic.

4. Narrow your focus

Be specific and concise when setting scope and delimitation. The parameters of the study should be clearly defined to avoid ambiguity and ensure that the study is focused on relevant aspects of the research question.

This means deciding which aspects of your topic you will focus on and which aspects you will eliminate.

5. Develop the final research plan

Revisit and revise the scope and delimitation as needed. As the research project progresses, the scope and delimitation may need to be adjusted to ensure that the study remains focused on the research question and can produce useful results. This plan should include your research goals, methods, and timeline.

Examples of Scope and Delimitation

To better understand scope and delimitation, let us consider two examples of research questions and how scope and delimitation would apply to them.

Research question: What are the effects of social media on mental health?

Scope: The scope of the study will focus on the impact of social media on the mental health of young adults aged 18-24 in the United States.

Delimitation: The study will specifically examine the following aspects of social media: frequency of use, types of social media platforms used, and the impact of social media on self-esteem and body image.

Research question: What are the factors that influence employee job satisfaction in the healthcare industry?

Scope: The scope of the study will focus on employee job satisfaction in the healthcare industry in the United States.

Delimitation: The study will specifically examine the following factors that influence employee job satisfaction: salary, work-life balance, job security, and opportunities for career growth.

Setting limits and defining the scope and delimitation of a research study is essential to conducting effective research. By doing so, researchers can ensure that their study is focused, manageable, and feasible within the given time frame and resources. It can also help to identify areas that require further study, providing a foundation for future research.

So, the next time you embark on a research project, don’t forget to set clear limits and define the scope and delimitation of your study. It may seem like a tedious task, but it can ultimately lead to more meaningful and impactful research. And if you still can’t find a solution, reach out to Enago Academy using #AskEnago and tag @EnagoAcademy on Twitter , Facebook , and Quora .

Frequently Asked Questions

The scope in research refers to the boundaries and extent of a study, defining its specific objectives, target population, variables, methods, and limitations, which helps researchers focus and provide a clear understanding of what will be investigated.

Delimitation in research defines the specific boundaries and limitations of a study, such as geographical, temporal, or conceptual constraints, outlining what will be excluded or not within the scope of investigation, providing clarity and ensuring the study remains focused and manageable.

To write a scope; 1. Clearly define research objectives. 2. Identify specific research questions. 3. Determine the target population for the study. 4. Outline the variables to be investigated. 5. Establish limitations and constraints. 6. Set boundaries and extent of the investigation. 7. Ensure focus, clarity, and manageability. 8. Provide context for the research project.

To write delimitations; 1. Identify geographical boundaries or constraints. 2. Define the specific time period or timeframe of the study. 3. Specify the sample size or selection criteria. 4. Clarify any demographic limitations (e.g., age, gender, occupation). 5. Address any limitations related to data collection methods. 6. Consider limitations regarding the availability of resources or data. 7. Exclude specific variables or factors from the scope of the study. 8. Clearly state any conceptual boundaries or theoretical frameworks. 9. Acknowledge any potential biases or constraints in the research design. 10. Ensure that the delimitations provide a clear focus and scope for the study.

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How to write the scope of the study?

The scope of the study refers to the elements that will be covered in a research project. It defines the boundaries of the research. The scope is always decided in the preliminary stages of a study. Deciding it in the later stages creates a lot of ambiguity regarding the research goals. The main purpose of the scope of the study is that explains the extent to which the research area will be explored and thus specifies the parameters that will be observed within the study. In other words, it enables the researcher to define what the study will cover and the elements that it will not. Defining the scope helps the researcher acquire a high level of research and writing capability.

Goals of establishing the scope of the study

The following steps can help the researcher to effectively define the goals of establishing a scope of the study.

Identification of the project or research needs

The first step is to identify the research needs. This helps them set a benchmark from the first step. Identification of the ‘what’ and ‘why’ enables the researcher to clearly set the research goals and objectives and the manner in which they will be performed.

Confirmation of the goals and objectives of the research

The goals and objectives defined in the project scope should be aligned with the SMART (Specific, Measurable, Achievable, Realistic and Timeframe) guidelines, which are:

• Specific- this involves a clear specification of what the researcher wants to achieve. It involves specifying what, why and how things will be done. This reduces the chances of ambiguities and any misunderstanding in the future.
• Measurable- Goals should be measurable and dynamic so that constant feedback can be generated for improvement.
• Achievable- Research goals should be achievable with the resources that are available.
• Realistic- Goals should be easier to deliver so that complications that can hamper the quality of the research can be avoided. Other considerations to be kept in mind are the budget and timeline.  
• Time frame- lastly, the researcher should estimate whether the set goals can be achieved within the given time frame or not.

Expectations and Acceptance

The researcher should take into account the expectations of the research and how well the findings of the researcher will be accepted by the reader. For instance, will the findings of your study help in policymaking or not?

Identification of the constraints

there are always certain roadblocks in conducting research, such as environmental conditions, technological inefficiency and lack of resources. Identifying these limitations and their possible solutions in advance help achieve goals better.

Identifying the necessary changes

After the preliminary goals are set, the researcher must carry out some part of the research so that necessary changes that lead to waste of time and resources at later stages are reduced. For example, while conducting an interview, if the researcher believes that the sample size decided is too large or too small according to the scope of the study, then the researcher can make the necessary changes in that order to avoid wastage of time and resources.

Guidelines for writing the scope of the study

The major things that the researcher should keep in mind while writing the scope of the study are as follows.

• Time period: While writing the scope of the study the researcher should first mention or state categorically the time periods the study will cover. Generally, the researchers combine the scope of the study with the limitation of the study. These things are quite interwoven. The main difference between the two is that limitations further cover the points like monetary constraints or non-cooperation from the side of the target audience.
• Geography: In addition to this another major point that the researcher should keep in mind is that the scope of the study should state the specific aspect of the data that needs to be collected like the geographic locations and the variables.
• Research population: Another major aspect that should be involved while writing the scope of the study is the sample size or the population that the researcher has selected for the study. The sampling plan must clearly indicate the sample universe, target population, profile and sample size with justification.
• Theories: The researcher should state the academic theories that are being applied to the data collected so that the reader better knows the lens of the analysis. This is presented in the ‘theoretical framework’ section.
• Purpose: The scope of the study must indicate the purpose behind it. It must briefly define the larger picture, i.e. the overall goal the researcher is trying to achieve.  
• Limitations: It is impossible to avoid roadblocks in research. Every research is restricted in scope and is subjected to certain limitations. By acknowledging these limitations and how they are restricting the study makes its findings even more credible.

Consider the topic ‘Analysis of the role of social media on the educational development in India from 2000-2015’. The scope of the study for this research topic should include several roles within the mentioned time period. Further, it should also cover the mass media types that have been used in the analysis of the study also including the location and the sample size as well.

Scope of the study

With the increase in the number of social media users and its use in everyday communication at the individual and organizational levels, there has been a corresponding increase in its incorporation in educational development and especially in a country like India. In view of this situation, the present study analyzes the role of social media on the educational development of students. To this end, the study will also cover the changes in the usage of social media in the educational field over the time period ranging from 2000-2015. The scope of the study is restricted to select social media platforms, specifically Facebook, Twitter and YouTube. The empirical study in this research is restricted to five universities located across India, wherein the opinions of 30 teachers were studied in interview sessions. Further, the study also involves an analysis of students’ perspectives on the role of social media in education from the same university. Therefore the scope of this study is limited to India, and more specifically to those offering Arts and Science-related courses.

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How Do I Scope, Shape and Configure My Research Project?

• First Online: 28 June 2019

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• Gael McDonald 4  

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In this chapter, we show that in order to make your research feasible and realistically achievable, you need to make scoping and shaping choices, pertaining to the nature of the research activities that you will use to gather the evidence you need and configuring choices, pertaining to the patterns and connections between those research activities. Such choices move you toward the ‘pointy end’ of research where you assemble the evidence you need to address your research questions/hypotheses. Appropriately scoping, shaping and configuring research will typically require adaptations and trade-offs in response to impediments or constraints you experience or can foresee down the track in order to achieve project feasibility. We also argue that you may, in addition, need to build up some type of conceptual framework to help guide your scoping, shaping and configuring activities.

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Alfawaz, A. (2015). Recruitment and selection practices for female administrative officers in Saudi public sector universities. Unpublished Ph.D. thesis, UNE Business School, University of New England, Armidale, NSW

Google Scholar  

Anderson, B. F., Deane, D. H., Hammond, K. R., McClelland, G. H., & Shanteau, J. C. (1981). Concepts in judgement and decision making: Definitions, sources, interrelations, comments . New York: Praeger Publishers.

Azorín, J. M., & Cameron, R. (2010). The application of mixed methods in organisational research: A literature review. Electronic Journal of Business Research Methods, 8 (2), 95–105.

Braund, M. (2001). Understanding public perceptions of police in the ACT through observations of police-public turf interactions and surveys of the public . Unpublished Ph.D. thesis, Department of Marketing and Management, University of New England, Armidale, NSW.

Cavana, R. Y., Delahaye, B. L., & Sekaran, U. (2001). Applied business research: Qualitative and quantitative approaches . Milton, QLD, Australia: Wiley.

Charmaz, K. (2014). Constructing grounded theory (2nd ed.). Los Angeles: Sage Publications.

Cooksey, R. W. (2014). Illustrating statistical procedures: Finding meaning in quantitative data (2nd ed.). Prahran, VIC: Tilde University Press.

Creswell, J. W., & Plano Clark, L. (2011). Designing and conducting mixed methods research (2nd ed.). Los Angeles: Sage Publications.

Creswell, J. W., & Plano Clark, L. (2018). Designing and conducting mixed methods research (3rd ed.). Thousand Oaks: Sage Publications.

Cryer, J. D., & Chan, K.-S. (2008). Time series analysis: With applications in R . New York: Springer.

Book   Google Scholar  

Fieger, P. (2015). Efficiency and effectiveness in the Australian Technical and Further Education system. unpublished Ed.D. portfolio, UNE Business School, University of New England, NSW.

Fisher, C. (2007). Researching and writing a dissertation: A guidebook for business students (2nd ed.). Essex, UK: Pearson Education.

Flick, U. (2018). Triangulation. In N. K. Denzin & Y. S. Lincoln (Eds.), The Sage handbook of qualitative research (5th ed., pp. 444–461). Los Angeles: Sage Publications.

Glaser, B. (1992). The basics of grounded theory analysis . Mill Valley, CA: Sociology Press.

Glass, G. V., Willson, V. L., & Gottman, J. N. M. (2008). Design and analysis of time-series experiments . Charlotte, NC: Information Age Publishing.

Gregson, W. (2016). Harnessing sources of innovation, useful knowledge and leadership within a complex public sector agency network: A reflective practice perspective. Unpublished Ph.D.I portfolio, UNE Business School, University of New England, Armidale, NSW.

Harrison, J. (2003). Information scope in small service firms: A comparison of universalistic, contingency and configurational theoretical approaches. Unpublished Ph.D. thesis, University of New England, Armidale, NSW.

Henryks, J. (2009). Organic foods, choice and consumer context: An exploration of switching behavior . Unpublished Ph.D. thesis, School of Business, Economics and Public Policy, University of New England, Armidale, NSW.

Jick, T. D. (1979). Mixing qualitative and quantitative methods: Triangulation in action. Administrative Science Quarterly, 24 (4), 602–611.

Article   Google Scholar  

Johnson, R. B., & Onwuegbuzie, A. (2004). Mixed methods research: A research paradigm whose time has come. Educational Researcher, 33 (7), 14–26.

Kaptchuk, T. J. (2001). The double-blind, randomized, placebo-controlled trial: gold standard or golden calf? Journal of Clinical Epidemiology, 54 (6), 541–549.

Kincheloe, J. L. (2005). On to the next level: Continuing the conceptualization of the bricolage. Qualitative Inquiry, 11 (3), 323–350.

Maxwell, J. A. (2005). Qualitative research design: An interactive approach (2nd ed.). London: Sage Publications.

Miles, M. B., Huberman, A. M., & Saldana, J. (2014). Qualitative data analysis: An expanded sourcebook (3rd ed.). Los Angeles: Sage Publications.

Morse, J. M., Stern, P. N., Corbin, J., Bowers, B., Charmaz, K., & Clarke, A. E. (2009). Developing grounded theory: The second generation . Walnut Creek, CA: Left Coast Press.

Muchiri, M. (2006). Transformational leader behaviours, social processes of leadership and substitutes for leadership and their relationships with employee commitment, organisational efficacy and citizenship behaviours. Unpublished Ph.D. thesis, New England Business School, University of New England, Armidale, NSW.

Patton, M. Q. (2011). Developmental evaluation: Applying complexity concepts to enhance innovation and use . New York: The Guilford Press.

Ross, E. (1999). Academics’ perceptions of university culture and the factors that facilitate or inhibit commitment to it . Unpublished Ph.D. thesis, Department of Marketing and Management, University of New England, Armidale, NSW.

Sandall, J. (2006). Navigating pathways through complex systems of interacting problems: Strategic management of native vegetation policy. Unpublished Ph.D. thesis, New England Business School, University of New England, Armidale, NSW.

Smyth, R., & Maxwell, T. W. (2008). The research matrix: An approach to supervision of higher degree research . Milperra, NSW: Higher Education Research and Development Society of Australia.

Spector, P. E. (2006). Method variance in organizational research truth or urban legend? Organizational Research Methods, 9 (2), 221–232.

Strauss, A., & Corbin, J. (1990). The basics of qualitative research: Grounded theory procedures and techniques . London: Sage Publications.

Tashakkori, A., & Teddlie, C. (Eds.). (2010). Sage handbook of mixed methods in social & behavioral research (2nd ed.). Thousand Oaks, CA: Sage Publications.

Teddlie, C., & Tashakkori, A. (2011). Mixed methods research: Contemporary issues in an emerging field. In N. K. Denzin & Y. S. Lincoln (Eds.), The Sage handbook of qualitative research (pp. 285–299). Thousand Oaks, CA: Sage Publications.

Wolodko, K. (2017). The emergence of group dynamics from contextualised social processes: A complexity-oriented grounded-theory approach. Unpublished Ph.D. thesis, UNE Business School, University of New England, Armidale, NSW.

Yin, R. K. (2014). Case study research: Design and methods (5th ed.). Los Angeles: Sage Publications.

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Cooksey, R., McDonald, G. (2019). How Do I Scope, Shape and Configure My Research Project?. In: Surviving and Thriving in Postgraduate Research. Springer, Singapore. https://doi.org/10.1007/978-981-13-7747-1_12

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How to Write Limitations of the Study (with examples)

This blog emphasizes the importance of recognizing and effectively writing about limitations in research. It discusses the types of limitations, their significance, and provides guidelines for writing about them, highlighting their role in advancing scholarly research.

Updated on August 24, 2023

No matter how well thought out, every research endeavor encounters challenges. There is simply no way to predict all possible variances throughout the process.

These uncharted boundaries and abrupt constraints are known as limitations in research . Identifying and acknowledging limitations is crucial for conducting rigorous studies. Limitations provide context and shed light on gaps in the prevailing inquiry and literature.

This article explores the importance of recognizing limitations and discusses how to write them effectively. By interpreting limitations in research and considering prevalent examples, we aim to reframe the perception from shameful mistakes to respectable revelations.

What are limitations in research?

In the clearest terms, research limitations are the practical or theoretical shortcomings of a study that are often outside of the researcher’s control . While these weaknesses limit the generalizability of a study’s conclusions, they also present a foundation for future research.

Sometimes limitations arise from tangible circumstances like time and funding constraints, or equipment and participant availability. Other times the rationale is more obscure and buried within the research design. Common types of limitations and their ramifications include:

• Theoretical: limits the scope, depth, or applicability of a study.
• Methodological: limits the quality, quantity, or diversity of the data.
• Empirical: limits the representativeness, validity, or reliability of the data.
• Analytical: limits the accuracy, completeness, or significance of the findings.
• Ethical: limits the access, consent, or confidentiality of the data.

Regardless of how, when, or why they arise, limitations are a natural part of the research process and should never be ignored . Like all other aspects, they are vital in their own purpose.

Why is identifying limitations important?

Whether to seek acceptance or avoid struggle, humans often instinctively hide flaws and mistakes. Merging this thought process into research by attempting to hide limitations, however, is a bad idea. It has the potential to negate the validity of outcomes and damage the reputation of scholars.

By identifying and addressing limitations throughout a project, researchers strengthen their arguments and curtail the chance of peer censure based on overlooked mistakes. Pointing out these flaws shows an understanding of variable limits and a scrupulous research process.

Showing awareness of and taking responsibility for a project’s boundaries and challenges validates the integrity and transparency of a researcher. It further demonstrates the researchers understand the applicable literature and have thoroughly evaluated their chosen research methods.

Presenting limitations also benefits the readers by providing context for research findings. It guides them to interpret the project’s conclusions only within the scope of very specific conditions. By allowing for an appropriate generalization of the findings that is accurately confined by research boundaries and is not too broad, limitations boost a study’s credibility .

Limitations are true assets to the research process. They highlight opportunities for future research. When researchers identify the limitations of their particular approach to a study question, they enable precise transferability and improve chances for reproducibility. 

Simply stating a project’s limitations is not adequate for spurring further research, though. To spark the interest of other researchers, these acknowledgements must come with thorough explanations regarding how the limitations affected the current study and how they can potentially be overcome with amended methods.

How to write limitations

Typically, the information about a study’s limitations is situated either at the beginning of the discussion section to provide context for readers or at the conclusion of the discussion section to acknowledge the need for further research. However, it varies depending upon the target journal or publication guidelines. 

Don’t hide your limitations

It is also important to not bury a limitation in the body of the paper unless it has a unique connection to a topic in that section. If so, it needs to be reiterated with the other limitations or at the conclusion of the discussion section. Wherever it is included in the manuscript, ensure that the limitations section is prominently positioned and clearly introduced.

While maintaining transparency by disclosing limitations means taking a comprehensive approach, it is not necessary to discuss everything that could have potentially gone wrong during the research study. If there is no commitment to investigation in the introduction, it is unnecessary to consider the issue a limitation to the research. Wholly consider the term ‘limitations’ and ask, “Did it significantly change or limit the possible outcomes?” Then, qualify the occurrence as either a limitation to include in the current manuscript or as an idea to note for other projects. 

Writing limitations

Once the limitations are concretely identified and it is decided where they will be included in the paper, researchers are ready for the writing task. Including only what is pertinent, keeping explanations detailed but concise, and employing the following guidelines is key for crafting valuable limitations:

1) Identify and describe the limitations : Clearly introduce the limitation by classifying its form and specifying its origin. For example:

• An unintentional bias encountered during data collection
• An intentional use of unplanned post-hoc data analysis

2) Explain the implications : Describe how the limitation potentially influences the study’s findings and how the validity and generalizability are subsequently impacted. Provide examples and evidence to support claims of the limitations’ effects without making excuses or exaggerating their impact. Overall, be transparent and objective in presenting the limitations, without undermining the significance of the research. 

3) Provide alternative approaches for future studies : Offer specific suggestions for potential improvements or avenues for further investigation. Demonstrate a proactive approach by encouraging future research that addresses the identified gaps and, therefore, expands the knowledge base.

Whether presenting limitations as an individual section within the manuscript or as a subtopic in the discussion area, authors should use clear headings and straightforward language to facilitate readability. There is no need to complicate limitations with jargon, computations, or complex datasets.

Examples of common limitations

Limitations are generally grouped into two categories , methodology and research process .

Methodology limitations

Methodology may include limitations due to:

• Sample size
• Lack of available or reliable data
• Lack of prior research studies on the topic
• Measure used to collect the data
• Self-reported data

The researcher is addressing how the large sample size requires a reassessment of the measures used to collect and analyze the data.

Research process limitations

Limitations during the research process may arise from:

• Access to information
• Longitudinal effects
• Cultural and other biases
• Language fluency
• Time constraints

The author is pointing out that the model’s estimates are based on potentially biased observational studies.

Final thoughts

Successfully proving theories and touting great achievements are only two very narrow goals of scholarly research. The true passion and greatest efforts of researchers comes more in the form of confronting assumptions and exploring the obscure.

In many ways, recognizing and sharing the limitations of a research study both allows for and encourages this type of discovery that continuously pushes research forward. By using limitations to provide a transparent account of the project's boundaries and to contextualize the findings, researchers pave the way for even more robust and impactful research in the future.

Charla Viera, MS

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Research Aims, Objectives & Questions

The “Golden Thread” Explained Simply (+ Examples)

By: David Phair (PhD) and Alexandra Shaeffer (PhD) | June 2022

The research aims , objectives and research questions (collectively called the “golden thread”) are arguably the most important thing you need to get right when you’re crafting a research proposal , dissertation or thesis . We receive questions almost every day about this “holy trinity” of research and there’s certainly a lot of confusion out there, so we’ve crafted this post to help you navigate your way through the fog.

Overview: The Golden Thread

• What is the golden thread
• What are research aims ( examples )
• What are research objectives ( examples )
• What are research questions ( examples )
• The importance of alignment in the golden thread

What is the “golden thread”?  

The golden thread simply refers to the collective research aims , research objectives , and research questions for any given project (i.e., a dissertation, thesis, or research paper ). These three elements are bundled together because it’s extremely important that they align with each other, and that the entire research project aligns with them.

Importantly, the golden thread needs to weave its way through the entirety of any research project , from start to end. In other words, it needs to be very clearly defined right at the beginning of the project (the topic ideation and proposal stage) and it needs to inform almost every decision throughout the rest of the project. For example, your research design and methodology will be heavily influenced by the golden thread (we’ll explain this in more detail later), as well as your literature review.

The research aims, objectives and research questions (the golden thread) define the focus and scope ( the delimitations ) of your research project. In other words, they help ringfence your dissertation or thesis to a relatively narrow domain, so that you can “go deep” and really dig into a specific problem or opportunity. They also help keep you on track , as they act as a litmus test for relevance. In other words, if you’re ever unsure whether to include something in your document, simply ask yourself the question, “does this contribute toward my research aims, objectives or questions?”. If it doesn’t, chances are you can drop it.

Alright, enough of the fluffy, conceptual stuff. Let’s get down to business and look at what exactly the research aims, objectives and questions are and outline a few examples to bring these concepts to life.

Research Aims: What are they?

Simply put, the research aim(s) is a statement that reflects the broad overarching goal (s) of the research project. Research aims are fairly high-level (low resolution) as they outline the general direction of the research and what it’s trying to achieve .

Research Aims: Examples  

True to the name, research aims usually start with the wording “this research aims to…”, “this research seeks to…”, and so on. For example:

“This research aims to explore employee experiences of digital transformation in retail HR.”   “This study sets out to assess the interaction between student support and self-care on well-being in engineering graduate students”  

As you can see, these research aims provide a high-level description of what the study is about and what it seeks to achieve. They’re not hyper-specific or action-oriented, but they’re clear about what the study’s focus is and what is being investigated.

Need a helping hand?

Research Objectives: What are they?

The research objectives take the research aims and make them more practical and actionable . In other words, the research objectives showcase the steps that the researcher will take to achieve the research aims.

The research objectives need to be far more specific (higher resolution) and actionable than the research aims. In fact, it’s always a good idea to craft your research objectives using the “SMART” criteria. In other words, they should be specific, measurable, achievable, relevant and time-bound”.

Research Objectives: Examples  

Let’s look at two examples of research objectives. We’ll stick with the topic and research aims we mentioned previously.  

For the digital transformation topic:

To observe the retail HR employees throughout the digital transformation. To assess employee perceptions of digital transformation in retail HR. To identify the barriers and facilitators of digital transformation in retail HR.

And for the student wellness topic:

To determine whether student self-care predicts the well-being score of engineering graduate students. To determine whether student support predicts the well-being score of engineering students. To assess the interaction between student self-care and student support when predicting well-being in engineering graduate students.

  As you can see, these research objectives clearly align with the previously mentioned research aims and effectively translate the low-resolution aims into (comparatively) higher-resolution objectives and action points . They give the research project a clear focus and present something that resembles a research-based “to-do” list.

Research Questions: What are they?

Finally, we arrive at the all-important research questions. The research questions are, as the name suggests, the key questions that your study will seek to answer . Simply put, they are the core purpose of your dissertation, thesis, or research project. You’ll present them at the beginning of your document (either in the introduction chapter or literature review chapter) and you’ll answer them at the end of your document (typically in the discussion and conclusion chapters).  

The research questions will be the driving force throughout the research process. For example, in the literature review chapter, you’ll assess the relevance of any given resource based on whether it helps you move towards answering your research questions. Similarly, your methodology and research design will be heavily influenced by the nature of your research questions. For instance, research questions that are exploratory in nature will usually make use of a qualitative approach, whereas questions that relate to measurement or relationship testing will make use of a quantitative approach.  

Let’s look at some examples of research questions to make this more tangible.

Research Questions: Examples  

Again, we’ll stick with the research aims and research objectives we mentioned previously.  

For the digital transformation topic (which would be qualitative in nature):

How do employees perceive digital transformation in retail HR? What are the barriers and facilitators of digital transformation in retail HR?  

And for the student wellness topic (which would be quantitative in nature):

Does student self-care predict the well-being scores of engineering graduate students? Does student support predict the well-being scores of engineering students? Do student self-care and student support interact when predicting well-being in engineering graduate students?  

You’ll probably notice that there’s quite a formulaic approach to this. In other words, the research questions are basically the research objectives “converted” into question format. While that is true most of the time, it’s not always the case. For example, the first research objective for the digital transformation topic was more or less a step on the path toward the other objectives, and as such, it didn’t warrant its own research question.  

So, don’t rush your research questions and sloppily reword your objectives as questions. Carefully think about what exactly you’re trying to achieve (i.e. your research aim) and the objectives you’ve set out, then craft a set of well-aligned research questions . Also, keep in mind that this can be a somewhat iterative process , where you go back and tweak research objectives and aims to ensure tight alignment throughout the golden thread.

The importance of strong alignment 

Alignment is the keyword here and we have to stress its importance . Simply put, you need to make sure that there is a very tight alignment between all three pieces of the golden thread. If your research aims and research questions don’t align, for example, your project will be pulling in different directions and will lack focus . This is a common problem students face and can cause many headaches (and tears), so be warned.

Take the time to carefully craft your research aims, objectives and research questions before you run off down the research path. Ideally, get your research supervisor/advisor to review and comment on your golden thread before you invest significant time into your project, and certainly before you start collecting data .  

Recap: The golden thread

In this post, we unpacked the golden thread of research, consisting of the research aims , research objectives and research questions . You can jump back to any section using the links below.

As always, feel free to leave a comment below – we always love to hear from you. Also, if you’re interested in 1-on-1 support, take a look at our private coaching service here.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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39 Comments

Thank you very much for your great effort put. As an Undergraduate taking Demographic Research & Methodology, I’ve been trying so hard to understand clearly what is a Research Question, Research Aim and the Objectives in a research and the relationship between them etc. But as for now I’m thankful that you’ve solved my problem.

Well appreciated. This has helped me greatly in doing my dissertation.

An so delighted with this wonderful information thank you a lot.

so impressive i have benefited a lot looking forward to learn more on research.

I am very happy to have carefully gone through this well researched article.

Infact,I used to be phobia about anything research, because of my poor understanding of the concepts.

Now,I get to know that my research question is the same as my research objective(s) rephrased in question format.

I please I would need a follow up on the subject,as I intends to join the team of researchers. Thanks once again.

Thanks so much. This was really helpful.

I know you pepole have tried to break things into more understandable and easy format. And God bless you. Keep it up

i found this document so useful towards my study in research methods. thanks so much.

This is my 2nd read topic in your course and I should commend the simplified explanations of each part. I’m beginning to understand and absorb the use of each part of a dissertation/thesis. I’ll keep on reading your free course and might be able to avail the training course! Kudos!

Thank you! Better put that my lecture and helped to easily understand the basics which I feel often get brushed over when beginning dissertation work.

This is quite helpful. I like how the Golden thread has been explained and the needed alignment.

This is quite helpful. I really appreciate!

The article made it simple for researcher students to differentiate between three concepts.

Very innovative and educational in approach to conducting research.

I am very impressed with all these terminology, as I am a fresh student for post graduate, I am highly guided and I promised to continue making consultation when the need arise. Thanks a lot.

A very helpful piece. thanks, I really appreciate it .

Very well explained, and it might be helpful to many people like me.

Wish i had found this (and other) resource(s) at the beginning of my PhD journey… not in my writing up year… 😩 Anyways… just a quick question as i’m having some issues ordering my “golden thread”…. does it matter in what order you mention them? i.e., is it always first aims, then objectives, and finally the questions? or can you first mention the research questions and then the aims and objectives?

Thank you for a very simple explanation that builds upon the concepts in a very logical manner. Just prior to this, I read the research hypothesis article, which was equally very good. This met my primary objective.

My secondary objective was to understand the difference between research questions and research hypothesis, and in which context to use which one. However, I am still not clear on this. Can you kindly please guide?

In research, a research question is a clear and specific inquiry that the researcher wants to answer, while a research hypothesis is a tentative statement or prediction about the relationship between variables or the expected outcome of the study. Research questions are broader and guide the overall study, while hypotheses are specific and testable statements used in quantitative research. Research questions identify the problem, while hypotheses provide a focus for testing in the study.

Exactly what I need in this research journey, I look forward to more of your coaching videos.

This helped a lot. Thanks so much for the effort put into explaining it.

What data source in writing dissertation/Thesis requires?

What is data source covers when writing dessertation/thesis

This is quite useful thanks

I’m excited and thankful. I got so much value which will help me progress in my thesis.

where are the locations of the reserch statement, research objective and research question in a reserach paper? Can you write an ouline that defines their places in the researh paper?

Very helpful and important tips on Aims, Objectives and Questions.

Thank you so much for making research aim, research objectives and research question so clear. This will be helpful to me as i continue with my thesis.

Thanks much for this content. I learned a lot. And I am inspired to learn more. I am still struggling with my preparation for dissertation outline/proposal. But I consistently follow contents and tutorials and the new FB of GRAD Coach. Hope to really become confident in writing my dissertation and successfully defend it.

As a researcher and lecturer, I find splitting research goals into research aims, objectives, and questions is unnecessarily bureaucratic and confusing for students. For most biomedical research projects, including ‘real research’, 1-3 research questions will suffice (numbers may differ by discipline).

Awesome! Very important resources and presented in an informative way to easily understand the golden thread. Indeed, thank you so much.

Well explained

The blog article on research aims, objectives, and questions by Grad Coach is a clear and insightful guide that aligns with my experiences in academic research. The article effectively breaks down the often complex concepts of research aims and objectives, providing a straightforward and accessible explanation. Drawing from my own research endeavors, I appreciate the practical tips offered, such as the need for specificity and clarity when formulating research questions. The article serves as a valuable resource for students and researchers, offering a concise roadmap for crafting well-defined research goals and objectives. Whether you’re a novice or an experienced researcher, this article provides practical insights that contribute to the foundational aspects of a successful research endeavor.

A great thanks for you. it is really amazing explanation. I grasp a lot and one step up to research knowledge.

I really found these tips helpful. Thank you very much Grad Coach.

I found this article helpful. Thanks for sharing this.

thank you so much, the explanation and examples are really helpful

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Focus: Education — Career Advice

How to write your first research paper.

Writing a research manuscript is an intimidating process for many novice writers in the sciences. One of the stumbling blocks is the beginning of the process and creating the first draft. This paper presents guidelines on how to initiate the writing process and draft each section of a research manuscript. The paper discusses seven rules that allow the writer to prepare a well-structured and comprehensive manuscript for a publication submission. In addition, the author lists different strategies for successful revision. Each of those strategies represents a step in the revision process and should help the writer improve the quality of the manuscript. The paper could be considered a brief manual for publication.

It is late at night. You have been struggling with your project for a year. You generated an enormous amount of interesting data. Your pipette feels like an extension of your hand, and running western blots has become part of your daily routine, similar to brushing your teeth. Your colleagues think you are ready to write a paper, and your lab mates tease you about your “slow” writing progress. Yet days pass, and you cannot force yourself to sit down to write. You have not written anything for a while (lab reports do not count), and you feel you have lost your stamina. How does the writing process work? How can you fit your writing into a daily schedule packed with experiments? What section should you start with? What distinguishes a good research paper from a bad one? How should you revise your paper? These and many other questions buzz in your head and keep you stressed. As a result, you procrastinate. In this paper, I will discuss the issues related to the writing process of a scientific paper. Specifically, I will focus on the best approaches to start a scientific paper, tips for writing each section, and the best revision strategies.

1. Schedule your writing time in Outlook

Whether you have written 100 papers or you are struggling with your first, starting the process is the most difficult part unless you have a rigid writing schedule. Writing is hard. It is a very difficult process of intense concentration and brain work. As stated in Hayes’ framework for the study of writing: “It is a generative activity requiring motivation, and it is an intellectual activity requiring cognitive processes and memory” [ 1 ]. In his book How to Write a Lot: A Practical Guide to Productive Academic Writing , Paul Silvia says that for some, “it’s easier to embalm the dead than to write an article about it” [ 2 ]. Just as with any type of hard work, you will not succeed unless you practice regularly. If you have not done physical exercises for a year, only regular workouts can get you into good shape again. The same kind of regular exercises, or I call them “writing sessions,” are required to be a productive author. Choose from 1- to 2-hour blocks in your daily work schedule and consider them as non-cancellable appointments. When figuring out which blocks of time will be set for writing, you should select the time that works best for this type of work. For many people, mornings are more productive. One Yale University graduate student spent a semester writing from 8 a.m. to 9 a.m. when her lab was empty. At the end of the semester, she was amazed at how much she accomplished without even interrupting her regular lab hours. In addition, doing the hardest task first thing in the morning contributes to the sense of accomplishment during the rest of the day. This positive feeling spills over into our work and life and has a very positive effect on our overall attitude.

Rule 1: Create regular time blocks for writing as appointments in your calendar and keep these appointments.

2. start with an outline.

Now that you have scheduled time, you need to decide how to start writing. The best strategy is to start with an outline. This will not be an outline that you are used to, with Roman numerals for each section and neat parallel listing of topic sentences and supporting points. This outline will be similar to a template for your paper. Initially, the outline will form a structure for your paper; it will help generate ideas and formulate hypotheses. Following the advice of George M. Whitesides, “. . . start with a blank piece of paper, and write down, in any order, all important ideas that occur to you concerning the paper” [ 3 ]. Use Table 1 as a starting point for your outline. Include your visuals (figures, tables, formulas, equations, and algorithms), and list your findings. These will constitute the first level of your outline, which will eventually expand as you elaborate.

The next stage is to add context and structure. Here you will group all your ideas into sections: Introduction, Methods, Results, and Discussion/Conclusion ( Table 2 ). This step will help add coherence to your work and sift your ideas.

Now that you have expanded your outline, you are ready for the next step: discussing the ideas for your paper with your colleagues and mentor. Many universities have a writing center where graduate students can schedule individual consultations and receive assistance with their paper drafts. Getting feedback during early stages of your draft can save a lot of time. Talking through ideas allows people to conceptualize and organize thoughts to find their direction without wasting time on unnecessary writing. Outlining is the most effective way of communicating your ideas and exchanging thoughts. Moreover, it is also the best stage to decide to which publication you will submit the paper. Many people come up with three choices and discuss them with their mentors and colleagues. Having a list of journal priorities can help you quickly resubmit your paper if your paper is rejected.

Rule 2: Create a detailed outline and discuss it with your mentor and peers.

3. continue with drafts.

After you get enough feedback and decide on the journal you will submit to, the process of real writing begins. Copy your outline into a separate file and expand on each of the points, adding data and elaborating on the details. When you create the first draft, do not succumb to the temptation of editing. Do not slow down to choose a better word or better phrase; do not halt to improve your sentence structure. Pour your ideas into the paper and leave revision and editing for later. As Paul Silvia explains, “Revising while you generate text is like drinking decaffeinated coffee in the early morning: noble idea, wrong time” [ 2 ].

Many students complain that they are not productive writers because they experience writer’s block. Staring at an empty screen is frustrating, but your screen is not really empty: You have a template of your article, and all you need to do is fill in the blanks. Indeed, writer’s block is a logical fallacy for a scientist ― it is just an excuse to procrastinate. When scientists start writing a research paper, they already have their files with data, lab notes with materials and experimental designs, some visuals, and tables with results. All they need to do is scrutinize these pieces and put them together into a comprehensive paper.

3.1. Starting with Materials and Methods

If you still struggle with starting a paper, then write the Materials and Methods section first. Since you have all your notes, it should not be problematic for you to describe the experimental design and procedures. Your most important goal in this section is to be as explicit as possible by providing enough detail and references. In the end, the purpose of this section is to allow other researchers to evaluate and repeat your work. So do not run into the same problems as the writers of the sentences in (1):

1a. Bacteria were pelleted by centrifugation. 1b. To isolate T cells, lymph nodes were collected.

As you can see, crucial pieces of information are missing: the speed of centrifuging your bacteria, the time, and the temperature in (1a); the source of lymph nodes for collection in (b). The sentences can be improved when information is added, as in (2a) and (2b), respectfully:

2a. Bacteria were pelleted by centrifugation at 3000g for 15 min at 25°C. 2b. To isolate T cells, mediastinal and mesenteric lymph nodes from Balb/c mice were collected at day 7 after immunization with ovabumin.

If your method has previously been published and is well-known, then you should provide only the literature reference, as in (3a). If your method is unpublished, then you need to make sure you provide all essential details, as in (3b).

3a. Stem cells were isolated, according to Johnson [23]. 3b. Stem cells were isolated using biotinylated carbon nanotubes coated with anti-CD34 antibodies.

Furthermore, cohesion and fluency are crucial in this section. One of the malpractices resulting in disrupted fluency is switching from passive voice to active and vice versa within the same paragraph, as shown in (4). This switching misleads and distracts the reader.

4. Behavioral computer-based experiments of Study 1 were programmed by using E-Prime. We took ratings of enjoyment, mood, and arousal as the patients listened to preferred pleasant music and unpreferred music by using Visual Analogue Scales (SI Methods). The preferred and unpreferred status of the music was operationalized along a continuum of pleasantness [ 4 ].

The problem with (4) is that the reader has to switch from the point of view of the experiment (passive voice) to the point of view of the experimenter (active voice). This switch causes confusion about the performer of the actions in the first and the third sentences. To improve the coherence and fluency of the paragraph above, you should be consistent in choosing the point of view: first person “we” or passive voice [ 5 ]. Let’s consider two revised examples in (5).

5a. We programmed behavioral computer-based experiments of Study 1 by using E-Prime. We took ratings of enjoyment, mood, and arousal by using Visual Analogue Scales (SI Methods) as the patients listened to preferred pleasant music and unpreferred music. We operationalized the preferred and unpreferred status of the music along a continuum of pleasantness. 5b. Behavioral computer-based experiments of Study 1 were programmed by using E-Prime. Ratings of enjoyment, mood, and arousal were taken as the patients listened to preferred pleasant music and unpreferred music by using Visual Analogue Scales (SI Methods). The preferred and unpreferred status of the music was operationalized along a continuum of pleasantness.

If you choose the point of view of the experimenter, then you may end up with repetitive “we did this” sentences. For many readers, paragraphs with sentences all beginning with “we” may also sound disruptive. So if you choose active sentences, you need to keep the number of “we” subjects to a minimum and vary the beginnings of the sentences [ 6 ].

Interestingly, recent studies have reported that the Materials and Methods section is the only section in research papers in which passive voice predominantly overrides the use of the active voice [ 5 , 7 , 8 , 9 ]. For example, Martínez shows a significant drop in active voice use in the Methods sections based on the corpus of 1 million words of experimental full text research articles in the biological sciences [ 7 ]. According to the author, the active voice patterned with “we” is used only as a tool to reveal personal responsibility for the procedural decisions in designing and performing experimental work. This means that while all other sections of the research paper use active voice, passive voice is still the most predominant in Materials and Methods sections.

Writing Materials and Methods sections is a meticulous and time consuming task requiring extreme accuracy and clarity. This is why when you complete your draft, you should ask for as much feedback from your colleagues as possible. Numerous readers of this section will help you identify the missing links and improve the technical style of this section.

Rule 3: Be meticulous and accurate in describing the Materials and Methods. Do not change the point of view within one paragraph.

3.2. writing results section.

For many authors, writing the Results section is more intimidating than writing the Materials and Methods section . If people are interested in your paper, they are interested in your results. That is why it is vital to use all your writing skills to objectively present your key findings in an orderly and logical sequence using illustrative materials and text.

Your Results should be organized into different segments or subsections where each one presents the purpose of the experiment, your experimental approach, data including text and visuals (tables, figures, schematics, algorithms, and formulas), and data commentary. For most journals, your data commentary will include a meaningful summary of the data presented in the visuals and an explanation of the most significant findings. This data presentation should not repeat the data in the visuals, but rather highlight the most important points. In the “standard” research paper approach, your Results section should exclude data interpretation, leaving it for the Discussion section. However, interpretations gradually and secretly creep into research papers: “Reducing the data, generalizing from the data, and highlighting scientific cases are all highly interpretive processes. It should be clear by now that we do not let the data speak for themselves in research reports; in summarizing our results, we interpret them for the reader” [ 10 ]. As a result, many journals including the Journal of Experimental Medicine and the Journal of Clinical Investigation use joint Results/Discussion sections, where results are immediately followed by interpretations.

Another important aspect of this section is to create a comprehensive and supported argument or a well-researched case. This means that you should be selective in presenting data and choose only those experimental details that are essential for your reader to understand your findings. You might have conducted an experiment 20 times and collected numerous records, but this does not mean that you should present all those records in your paper. You need to distinguish your results from your data and be able to discard excessive experimental details that could distract and confuse the reader. However, creating a picture or an argument should not be confused with data manipulation or falsification, which is a willful distortion of data and results. If some of your findings contradict your ideas, you have to mention this and find a plausible explanation for the contradiction.

In addition, your text should not include irrelevant and peripheral information, including overview sentences, as in (6).

6. To show our results, we first introduce all components of experimental system and then describe the outcome of infections.

Indeed, wordiness convolutes your sentences and conceals your ideas from readers. One common source of wordiness is unnecessary intensifiers. Adverbial intensifiers such as “clearly,” “essential,” “quite,” “basically,” “rather,” “fairly,” “really,” and “virtually” not only add verbosity to your sentences, but also lower your results’ credibility. They appeal to the reader’s emotions but lower objectivity, as in the common examples in (7):

7a. Table 3 clearly shows that … 7b. It is obvious from figure 4 that …

Another source of wordiness is nominalizations, i.e., nouns derived from verbs and adjectives paired with weak verbs including “be,” “have,” “do,” “make,” “cause,” “provide,” and “get” and constructions such as “there is/are.”

8a. We tested the hypothesis that there is a disruption of membrane asymmetry. 8b. In this paper we provide an argument that stem cells repopulate injured organs.

In the sentences above, the abstract nominalizations “disruption” and “argument” do not contribute to the clarity of the sentences, but rather clutter them with useless vocabulary that distracts from the meaning. To improve your sentences, avoid unnecessary nominalizations and change passive verbs and constructions into active and direct sentences.

9a. We tested the hypothesis that the membrane asymmetry is disrupted. 9b. In this paper we argue that stem cells repopulate injured organs.

Your Results section is the heart of your paper, representing a year or more of your daily research. So lead your reader through your story by writing direct, concise, and clear sentences.

Rule 4: Be clear, concise, and objective in describing your Results.

3.3. now it is time for your introduction.

Now that you are almost half through drafting your research paper, it is time to update your outline. While describing your Methods and Results, many of you diverged from the original outline and re-focused your ideas. So before you move on to create your Introduction, re-read your Methods and Results sections and change your outline to match your research focus. The updated outline will help you review the general picture of your paper, the topic, the main idea, and the purpose, which are all important for writing your introduction.

The best way to structure your introduction is to follow the three-move approach shown in Table 3 .

Adapted from Swales and Feak [ 11 ].

The moves and information from your outline can help to create your Introduction efficiently and without missing steps. These moves are traffic signs that lead the reader through the road of your ideas. Each move plays an important role in your paper and should be presented with deep thought and care. When you establish the territory, you place your research in context and highlight the importance of your research topic. By finding the niche, you outline the scope of your research problem and enter the scientific dialogue. The final move, “occupying the niche,” is where you explain your research in a nutshell and highlight your paper’s significance. The three moves allow your readers to evaluate their interest in your paper and play a significant role in the paper review process, determining your paper reviewers.

Some academic writers assume that the reader “should follow the paper” to find the answers about your methodology and your findings. As a result, many novice writers do not present their experimental approach and the major findings, wrongly believing that the reader will locate the necessary information later while reading the subsequent sections [ 5 ]. However, this “suspense” approach is not appropriate for scientific writing. To interest the reader, scientific authors should be direct and straightforward and present informative one-sentence summaries of the results and the approach.

Another problem is that writers understate the significance of the Introduction. Many new researchers mistakenly think that all their readers understand the importance of the research question and omit this part. However, this assumption is faulty because the purpose of the section is not to evaluate the importance of the research question in general. The goal is to present the importance of your research contribution and your findings. Therefore, you should be explicit and clear in describing the benefit of the paper.

The Introduction should not be long. Indeed, for most journals, this is a very brief section of about 250 to 600 words, but it might be the most difficult section due to its importance.

Rule 5: Interest your reader in the Introduction section by signalling all its elements and stating the novelty of the work.

3.4. discussion of the results.

For many scientists, writing a Discussion section is as scary as starting a paper. Most of the fear comes from the variation in the section. Since every paper has its unique results and findings, the Discussion section differs in its length, shape, and structure. However, some general principles of writing this section still exist. Knowing these rules, or “moves,” can change your attitude about this section and help you create a comprehensive interpretation of your results.

The purpose of the Discussion section is to place your findings in the research context and “to explain the meaning of the findings and why they are important, without appearing arrogant, condescending, or patronizing” [ 11 ]. The structure of the first two moves is almost a mirror reflection of the one in the Introduction. In the Introduction, you zoom in from general to specific and from the background to your research question; in the Discussion section, you zoom out from the summary of your findings to the research context, as shown in Table 4 .

Adapted from Swales and Feak and Hess [ 11 , 12 ].

The biggest challenge for many writers is the opening paragraph of the Discussion section. Following the moves in Table 1 , the best choice is to start with the study’s major findings that provide the answer to the research question in your Introduction. The most common starting phrases are “Our findings demonstrate . . .,” or “In this study, we have shown that . . .,” or “Our results suggest . . .” In some cases, however, reminding the reader about the research question or even providing a brief context and then stating the answer would make more sense. This is important in those cases where the researcher presents a number of findings or where more than one research question was presented. Your summary of the study’s major findings should be followed by your presentation of the importance of these findings. One of the most frequent mistakes of the novice writer is to assume the importance of his findings. Even if the importance is clear to you, it may not be obvious to your reader. Digesting the findings and their importance to your reader is as crucial as stating your research question.

Another useful strategy is to be proactive in the first move by predicting and commenting on the alternative explanations of the results. Addressing potential doubts will save you from painful comments about the wrong interpretation of your results and will present you as a thoughtful and considerate researcher. Moreover, the evaluation of the alternative explanations might help you create a logical step to the next move of the discussion section: the research context.

The goal of the research context move is to show how your findings fit into the general picture of the current research and how you contribute to the existing knowledge on the topic. This is also the place to discuss any discrepancies and unexpected findings that may otherwise distort the general picture of your paper. Moreover, outlining the scope of your research by showing the limitations, weaknesses, and assumptions is essential and adds modesty to your image as a scientist. However, make sure that you do not end your paper with the problems that override your findings. Try to suggest feasible explanations and solutions.

If your submission does not require a separate Conclusion section, then adding another paragraph about the “take-home message” is a must. This should be a general statement reiterating your answer to the research question and adding its scientific implications, practical application, or advice.

Just as in all other sections of your paper, the clear and precise language and concise comprehensive sentences are vital. However, in addition to that, your writing should convey confidence and authority. The easiest way to illustrate your tone is to use the active voice and the first person pronouns. Accompanied by clarity and succinctness, these tools are the best to convince your readers of your point and your ideas.

Rule 6: Present the principles, relationships, and generalizations in a concise and convincing tone.

4. choosing the best working revision strategies.

Now that you have created the first draft, your attitude toward your writing should have improved. Moreover, you should feel more confident that you are able to accomplish your project and submit your paper within a reasonable timeframe. You also have worked out your writing schedule and followed it precisely. Do not stop ― you are only at the midpoint from your destination. Just as the best and most precious diamond is no more than an unattractive stone recognized only by trained professionals, your ideas and your results may go unnoticed if they are not polished and brushed. Despite your attempts to present your ideas in a logical and comprehensive way, first drafts are frequently a mess. Use the advice of Paul Silvia: “Your first drafts should sound like they were hastily translated from Icelandic by a non-native speaker” [ 2 ]. The degree of your success will depend on how you are able to revise and edit your paper.

The revision can be done at the macrostructure and the microstructure levels [ 13 ]. The macrostructure revision includes the revision of the organization, content, and flow. The microstructure level includes individual words, sentence structure, grammar, punctuation, and spelling.

The best way to approach the macrostructure revision is through the outline of the ideas in your paper. The last time you updated your outline was before writing the Introduction and the Discussion. Now that you have the beginning and the conclusion, you can take a bird’s-eye view of the whole paper. The outline will allow you to see if the ideas of your paper are coherently structured, if your results are logically built, and if the discussion is linked to the research question in the Introduction. You will be able to see if something is missing in any of the sections or if you need to rearrange your information to make your point.

The next step is to revise each of the sections starting from the beginning. Ideally, you should limit yourself to working on small sections of about five pages at a time [ 14 ]. After these short sections, your eyes get used to your writing and your efficiency in spotting problems decreases. When reading for content and organization, you should control your urge to edit your paper for sentence structure and grammar and focus only on the flow of your ideas and logic of your presentation. Experienced researchers tend to make almost three times the number of changes to meaning than novice writers [ 15 , 16 ]. Revising is a difficult but useful skill, which academic writers obtain with years of practice.

In contrast to the macrostructure revision, which is a linear process and is done usually through a detailed outline and by sections, microstructure revision is a non-linear process. While the goal of the macrostructure revision is to analyze your ideas and their logic, the goal of the microstructure editing is to scrutinize the form of your ideas: your paragraphs, sentences, and words. You do not need and are not recommended to follow the order of the paper to perform this type of revision. You can start from the end or from different sections. You can even revise by reading sentences backward, sentence by sentence and word by word.

One of the microstructure revision strategies frequently used during writing center consultations is to read the paper aloud [ 17 ]. You may read aloud to yourself, to a tape recorder, or to a colleague or friend. When reading and listening to your paper, you are more likely to notice the places where the fluency is disrupted and where you stumble because of a very long and unclear sentence or a wrong connector.

Another revision strategy is to learn your common errors and to do a targeted search for them [ 13 ]. All writers have a set of problems that are specific to them, i.e., their writing idiosyncrasies. Remembering these problems is as important for an academic writer as remembering your friends’ birthdays. Create a list of these idiosyncrasies and run a search for these problems using your word processor. If your problem is demonstrative pronouns without summary words, then search for “this/these/those” in your text and check if you used the word appropriately. If you have a problem with intensifiers, then search for “really” or “very” and delete them from the text. The same targeted search can be done to eliminate wordiness. Searching for “there is/are” or “and” can help you avoid the bulky sentences.

The final strategy is working with a hard copy and a pencil. Print a double space copy with font size 14 and re-read your paper in several steps. Try reading your paper line by line with the rest of the text covered with a piece of paper. When you are forced to see only a small portion of your writing, you are less likely to get distracted and are more likely to notice problems. You will end up spotting more unnecessary words, wrongly worded phrases, or unparallel constructions.

After you apply all these strategies, you are ready to share your writing with your friends, colleagues, and a writing advisor in the writing center. Get as much feedback as you can, especially from non-specialists in your field. Patiently listen to what others say to you ― you are not expected to defend your writing or explain what you wanted to say. You may decide what you want to change and how after you receive the feedback and sort it in your head. Even though some researchers make the revision an endless process and can hardly stop after a 14th draft; having from five to seven drafts of your paper is a norm in the sciences. If you can’t stop revising, then set a deadline for yourself and stick to it. Deadlines always help.

Rule 7: Revise your paper at the macrostructure and the microstructure level using different strategies and techniques. Receive feedback and revise again.

5. it is time to submit.

It is late at night again. You are still in your lab finishing revisions and getting ready to submit your paper. You feel happy ― you have finally finished a year’s worth of work. You will submit your paper tomorrow, and regardless of the outcome, you know that you can do it. If one journal does not take your paper, you will take advantage of the feedback and resubmit again. You will have a publication, and this is the most important achievement.

What is even more important is that you have your scheduled writing time that you are going to keep for your future publications, for reading and taking notes, for writing grants, and for reviewing papers. You are not going to lose stamina this time, and you will become a productive scientist. But for now, let’s celebrate the end of the paper.

• Hayes JR. In: The Science of Writing: Theories, Methods, Individual Differences, and Applications. Levy CM, Ransdell SE, editors. Mahwah, NJ: Lawrence Erlbaum; 1996. A new framework for understanding cognition and affect in writing; pp. 1–28. [ Google Scholar ]
• Silvia PJ. How to Write a Lot. Washington, DC: American Psychological Association; 2007. [ Google Scholar ]
• Whitesides GM. Whitesides’ Group: Writing a Paper. Adv Mater. 2004; 16 (15):1375–1377. [ Google Scholar ]
• Soto D, Funes MJ, Guzmán-García A, Warbrick T, Rotshtein T, Humphreys GW. Pleasant music overcomes the loss of awareness in patients with visual neglect. Proc Natl Acad Sci USA. 2009; 106 (14):6011–6016. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hofmann AH. Scientific Writing and Communication. Papers, Proposals, and Presentations. New York: Oxford University Press; 2010. [ Google Scholar ]
• Zeiger M. Essentials of Writing Biomedical Research Papers. 2nd edition. San Francisco, CA: McGraw-Hill Companies, Inc.; 2000. [ Google Scholar ]
• Martínez I. Native and non-native writers’ use of first person pronouns in the different sections of biology research articles in English. Journal of Second Language Writing. 2005; 14 (3):174–190. [ Google Scholar ]
• Rodman L. The Active Voice In Scientific Articles: Frequency And Discourse Functions. Journal Of Technical Writing And Communication. 1994; 24 (3):309–331. [ Google Scholar ]
• Tarone LE, Dwyer S, Gillette S, Icke V. On the use of the passive in two astrophysics journal papers with extensions to other languages and other fields. English for Specific Purposes. 1998; 17 :113–132. [ Google Scholar ]
• Penrose AM, Katz SB. Writing in the sciences: Exploring conventions of scientific discourse. New York: St. Martin’s Press; 1998. [ Google Scholar ]
• Swales JM, Feak CB. Academic Writing for Graduate Students. 2nd edition. Ann Arbor: University of Michigan Press; 2004. [ Google Scholar ]
• Hess DR. How to Write an Effective Discussion. Respiratory Care. 2004; 29 (10):1238–1241. [ PubMed ] [ Google Scholar ]
• Belcher WL. Writing Your Journal Article in 12 Weeks: a guide to academic publishing success. Thousand Oaks, CA: SAGE Publications; 2009. [ Google Scholar ]
• Single PB. Demystifying Dissertation Writing: A Streamlined Process of Choice of Topic to Final Text. Virginia: Stylus Publishing LLC; 2010. [ Google Scholar ]
• Faigley L, Witte SP. Analyzing revision. Composition and Communication. 1981; 32 :400–414. [ Google Scholar ]
• Flower LS, Hayes JR, Carey L, Schriver KS, Stratman J. Detection, diagnosis, and the strategies of revision. College Composition and Communication. 1986; 37 (1):16–55. [ Google Scholar ]
• Young BR. In: A Tutor’s Guide: Helping Writers One to One. Rafoth B, editor. Portsmouth, NH: Boynton/Cook Publishers; 2005. Can You Proofread This? pp. 140–158. [ Google Scholar ]

How To Write Scope and Delimitation of a Research Paper (With Examples)

An effective research paper or thesis has a well-written Scope and Delimitation.  This portion specifies your study’s coverage and boundaries.

Not yet sure about how to write your research’s Scope and Delimitation? Fret not, as we’ll guide you through the entire writing process through this article.

Related: How To Write Significance of the Study (With Examples)

Table of Contents

What is the scope and delimitation of a research paper.

The “Scope and Delimitation” section states the concepts and variables your study covered. It tells readers which things you have included and excluded in your analysis.

This portion tells two things: 1

• The study’s “Scope” – concepts and variables you have explored in your research and;
• The study’s “Delimitation” – the “boundaries” of your study’s scope. It sets apart the things included in your analysis from those excluded.

For example, your scope might be the effectiveness of plant leaves in lowering blood sugar levels. You can “delimit” your study only to the effect of gabi leaves on the blood glucose of Swiss mice.

Where Should I Put the Scope and Delimitation?

This portion is in Chapter 1, usually after the “Background of the Study.”

Why Should I Write the Scope and Delimitation of My Research Paper?

There’s a lot to discover in a research paper or thesis. However, your resources and time dedicated to it are scarce. Thus, given these constraints, you have to narrow down your study. You do this in the Scope and Delimitation.

Suppose you’re studying the correlation between the quantity of organic fertilizer and plant growth . Experimenting with several types of plants is impossible because of several limitations. So, you’ve decided to use one plant type only. 

Informing your readers about this decision is a must. So, you have to state it in your Scope and Delimitation. It also acts as a “disclaimer” that your results are inapplicable to the entire plant kingdom.

What Is the Difference Between Delimitation and Limitation?

People often use the terms “Delimitation” and “Limitation” interchangeably. However, these words differ 2 .

Delimitation refers to factors you set to limit your analysis. It delineates those that are included in your research and those that are excluded. Remember, delimitations are within your control. 

Meanwhile, limitations are factors beyond your control that may affect your research’s results.  You can think of limitations as the “weaknesses” of your study. 

Let’s go back to our previous example. Due to some constraints, you’ve only decided to examine one plant type: dandelions. This is an example of a delimitation since it limits your analysis to dandelions only and not other plant types. Note that the number of plant types used is within your control. 

Meanwhile, your study cannot state that a higher quantity of organic fertilizer is the sole reason for plant growth. That’s because your research’s focus is only on correlation. Since this is already beyond your control, then this is a limitation. 

How To Write Scope and Delimitation: Step-by-Step Guide

To write your research’s Scope and Delimitation section, follow these steps:

1. Review Your Study’s Objectives and Problem Statement

Your study’s coverage relies on its objectives. Thus, you can only write this section if you know what you’re researching. Furthermore, ensure that you understand the problems you ought to answer. 

Once you understand the abovementioned things, you may start writing your study’s Scope and Delimitation.

2. State the Key Information To Explain Your Study’s Coverage and Boundaries

a. The Main Objective of the Research

This refers to the concept that you’re focusing on in your research. Some examples are the following:

• level of awareness or satisfaction of a particular group of people
• correlation between two variables
• effectiveness of a new product
• comparison between two methods/approaches
• lived experiences of several individuals

It’s helpful to consult your study’s Objectives or Statement of the Problem section to determine your research’s primary goal.

b. Independent and Dependent Variables Included

Your study’s independent variable is the variable that you manipulate. Meanwhile, the dependent variable is the variable whose result depends upon the independent variable. Both of these variables must be clear and specific when indicated. 

Suppose you study the relationship between social media usage and students’ language skills. These are the possible variables for the study:

• Independent Variable: Number of hours per day spent on using Facebook
• Dependent Variable: Grade 10 students’ scores in Quarterly Examination in English. 

Note how specific the variables stated above are. For the independent variable, we narrow it down to Facebook only. Since there are many ways to assess “language skills,” we zero in on the students’ English exam scores as our dependent variable. 

c. Subject of the Study

This refers to your study’s respondents or participants. 

In our previous example, the research participants are Grade 10 students. However, there are a lot of Grade 10 students in the Philippines. Thus, we have to select from a specific school only—for instance, Grade 10 students from a national high school in Manila. 

d. Timeframe and Location of the Study

Specify the month(s), quarter(s), or year(s) as the duration of your study. Also, indicate where you will gather the data required for your research. 

e. Brief Description of the Study’s Research Design and Methodology

You may also include whether your research is quantitative or qualitative, the sampling method (cluster, stratified, purposive) applied, and how you conducted the experiment.

Using our previous example, the Grade 10 students can be selected using stratified sampling. Afterward, the researchers may obtain their English quarterly exam scores from their respective teachers. You can add these things to your study’s Scope and Delimitation. 

3. Indicate Which Variables or Factors Are Not Covered by Your Research

Although you’ve already set your study’s coverage and boundaries in Step 2, you may also explicitly mention things you’ve excluded from your research. 

Returning to our previous example, you can state that your assessment will not include the vocabulary and oral aspects of the English proficiency skill. 

Examples of Scope and Delimitation of a Research Paper

1. scope and delimitation examples for quantitative research.

a. Example 1

Research Title

    A Study on the Relationship of the Extent of Facebook Usage on the English Proficiency Level of Grade 10 Students of Matagumpay High School

Scope and Delimitation

(Main Objective)

This study assessed the correlation between the respondents’ duration of Facebook usage and their English proficiency level. 

(Variables used)

The researchers used the number of hours per day of using Facebook and the activities usually performed on the platform to assess the respondents’ extent of Facebook usage. Meanwhile, the respondents’ English proficiency level is limited to their quarterly English exam scores. 

(Subject of the study)

A sample of fifty (50) Grade 10 students of Matagumpay High School served as the study’s respondents. 

(Timeframe and location)

This study was conducted during the Second Semester of the School Year 2018 – 2019 on the premises of Matagumpay High School in Metro Manila. 

(Methodology)

The respondents are selected by performing stratified random sampling to ensure that there will be ten respondents from five Grade 10 classes of the school mentioned above. The researchers administered a 20-item questionnaire to assess the extent of Facebook usage of the selected respondents. Meanwhile, the data for the respondents’ quarterly exam scores were acquired from their English teachers. The collected data are handled with the utmost confidentiality. Spearman’s Rank Order Correlation was applied to quantitatively assess the correlation between the variables.

(Exclusions)

This study didn’t assess other aspects of the respondents’ English proficiency, such as English vocabulary and oral skills. 

Note: The words inside the parentheses in the example above are guides only. They are not included in the actual text.

b. Example 2

  Level of Satisfaction of Grade 11 Students on the Implementation of the Online Learning Setup of Matagumpay High School for SY 2020 – 2021

This study aims to identify students’ satisfaction levels with implementing online learning setups during the height of the COVID-19 pandemic.

Students’ satisfaction was assessed according to teachers’ pedagogy, school policies, and learning materials used in the online learning setup. The respondents included sixty (60) Grade 11 students of Matagumpay High School who were randomly picked. The researchers conducted the study from October 2020 to February 2021. 

Online platforms such as email and social media applications were used to reach the respondents. The researchers administered a 15-item online questionnaire to measure the respondents’ satisfaction levels. Each response was assessed using a Likert Scale to provide a descriptive interpretation of their answers. A weighted mean was applied to determine the respondents’ general satisfaction. 

This study did not cover other factors related to the online learning setup, such as the learning platform used, the schedule of synchronous learning, and channels for information dissemination.

2. Scope and Delimitation Examples for Qualitative Research

  Lived Experiences of Public Utility Vehicle (PUV) Drivers of Antipolo City Amidst the Continuous June 2022 Oil Price Hikes

This research focused on the presentation and discussion of the lived experiences of PUV drivers during the constant oil price hike in June 2022.

The respondents involved are five (5) jeepney drivers from Antipolo City who agreed to be interviewed. The researchers assessed their experiences in terms of the following: (1) daily net income; (2) duration and extent of working; (3) alternative employment opportunity considerations; and (4) mental and emotional status. The respondents were interviewed daily at their stations on June 6 – 10, 2022. 

In-depth one-on-one interviews were used for data collection.  Afterward, the respondents’ first-hand experiences were drafted and annotated with the researchers’ insights. 

The researchers excluded some factors in determining the respondents’ experiences, such as physical and health conditions and current family relationship status. 

 A Study on the Perception of the Residents of Mayamot, Antipolo City on the Political and Socioeconomic Conditions During the Post-EDSA Period (1986 – 1996)

This research aims to discuss the perception of Filipinos regarding the political and socioeconomic economic conditions during the post-EDSA period, specifically during the years 1986 – 1996. 

Ten (10) residents of Mayamot, Antipolo City, who belonged to Generation X (currently 40 – 62 years old), were purposively selected as the study’s respondents. The researchers asked them about their perception of the following aspects during the period mentioned above (1) performance of national and local government; (2) bureaucracy and government services; (3) personal economic and financial status; and (4) wage purchasing power. 

The researchers conducted face-to-face interviews in the respondents’ residences during the second semester of AY 2018 – 2019. The responses were written and corroborated with the literature on the post-EDSA period. 

The following factors were not included in the research analysis: political conflicts and turmoils, the status of the legislative and judicial departments, and other macroeconomic indicators. 

Tips and Warnings

1. use the “5ws and 1h” as your guide in understanding your study’s coverage.

• Why did you write your study?  
• What variables are included?
• Who are your study’s subject
• Where did you conduct the study?
• When did your study start and end?
• How did you conduct the study?

2. Use key phrases when writing your research’s scope

• This study aims to … 
• This study primarily focuses on …
• This study deals with … 
• This study will cover …
• This study will be confined…

3. Use key phrases when writing factors beyond your research’s delimitations

• The researcher(s) decided to exclude …
• This study did not cover….
• This study excluded … 
• These variables/factors were excluded from the study…

4. Don’t forget to ask for help

Your research adviser can assist you in selecting specific concepts and variables suitable to your study. Make sure to consult him/her regularly. 

5. Make it brief

No need to make this section wordy. You’re good to go if you meet the “5Ws and 1Hs”. 

Frequently Asked Questions

1. what are scope and delimitation in tagalog.

In a Filipino research ( pananaliksik ), Scope and Delimitation is called “ Saklaw at Delimitasyon”. 

Here’s an example of Scope and Delimitation in Filipino:

Pamagat ng Pananaliksik

Epekto Ng Paggamit Ng Mga Digital Learning Tools Sa Pag-Aaral Ng Mga Mag-Aaral Ng Mataas Na Paaralan Ng Matagumpay Sa General Mathematics

Sakop at Delimitasyon ng Pag-aaral

Nakatuon ang pananaliksik na ito sa epekto ng paggamit ng mga digital learning aids sa pag-aaral ng mga mag-aaral.

Ang mga digital learning tools na kinonsidera sa pag-aaral na ito ay Google Classroom, Edmodo, Kahoot, at mga piling bidyo mula YouTube. Samantala, ang epekto sa pag-aaral ng mga mag-aaral ng mga nabanggit na digital learning tools ay natukoy sa pamamagitan ng kanilang (1) mga pananaw hinggil sa benepisyo nito sa kanilang pag-aaral sa General Mathematics at (2) kanilang average grade sa asignaturang ito.

Dalawampu’t-limang (25) mag-aaral mula sa Senior High School ng Mataas na Paaralan ng Matagumpay ang pinili para sa pananaliksik na ito. Sila ay na-interbyu at binigyan ng questionnaire noong Enero 2022 sa nasabing paaralan. Sinuri ang resulta ng pananaliksik sa pamamagitan ng mga instrumentong estadistikal na weighted mean at Analysis of Variance (ANOVA). Hindi saklaw ng pananaliksik na ito ang ibang mga aspeto hinggil sa epekto ng online learning aids sa pag-aaral gaya ng lebel ng pag-unawa sa aralin at kakayahang iugnay ito sa araw-araw na buhay. 

2. The Scope and Delimitation should consist of how many paragraphs?

Three or more paragraphs will suffice for your study’s Scope and Delimitation. Here’s our suggestion on what you should write for each paragraph:

Paragraph 1: Introduction (state research objective) Paragraph 2: Coverage and boundaries of the research (you may divide this section into 2-3 paragraphs) Paragraph 3 : Factors excluded from the study

• University of St. La Salle. Unit 3: Lesson 3 Setting the Scope and Limitation of a Qualitative Research [Ebook] (p. 12). Retrieved from https://www.studocu.com/ph/document/university-of-st-la-salle/senior-high-school/final-sg-pr1-11-12-unit-3-lesson-3-setting-the-scope-and-limitation-of-a-qualitative-research/24341582
• Theofanidis, D., & Fountouki, A. (2018). Limitations and Delimitations in the Research Process. Perioperative Nursing (GORNA), 7(3), 155–162. doi: 10.5281/zenodo.2552022

Written by Jewel Kyle Fabula

in Career and Education , Juander How

Jewel Kyle Fabula

Jewel Kyle Fabula is a Bachelor of Science in Economics student at the University of the Philippines Diliman. His passion for learning mathematics developed as he competed in some mathematics competitions during his Junior High School years. He loves cats, playing video games, and listening to music.

Browse all articles written by Jewel Kyle Fabula

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Time is an important element of any research design, and here I want to introduce one of the most fundamental distinctions in research design nomenclature: cross-sectional versus longitudinal studies. A cross-sectional study is one that takes place at a single point in time. In effect, we are taking a ‘slice’ or cross-section of whatever it is we’re observing or measuring. A longitudinal study is one that takes place over time – we have at least two (and often more) waves of measurement in a longitudinal design.

A further distinction is made between two types of longitudinal designs: repeated measures and time series . There is no universally agreed upon rule for distinguishing these two terms, but in general, if you have two or a few waves of measurement, you are using a repeated measures design. If you have many waves of measurement over time, you have a time series . How many is ‘many’? Usually, we wouldn’t use the term time series unless we had at least twenty waves of measurement, and often far more. Sometimes the way we distinguish these is with the analysis methods we would use. Time series analysis requires that you have at least twenty or so observations. Repeated measures analyses (like repeated measures ANOVA) aren’t often used with as many as twenty waves of measurement.

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