What is a Research Proposal
A research proposal is a structured document detailing your proposed research plan. It helps assessors determine how feasible your research is and the methodological quality of your study. It can be more of a preliminary outline than a definitive idea, so do not worry. It does not need to be the final product.
Most research proposals follow a similar structure but depending on your discipline and assignment brief, you may be asked to include different components. Here are some common components of a research proposal:
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Introduction
Your introduction is an overview of the research topic and sets the scene for the research proposal. It discusses the broader context of the topic and identifies the rationale for why the research is important. You want to highlight the significance of the research within this section.
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Literature Review
The Literature Review looks at existing evidence/research related to the proposed topic and identifies gaps in the literature where further research is warranted. It could discuss key theories about the topic or methodological approaches used.
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Hypothesis
This part of the proposal should include clearly defined research questions or hypotheses that the study aims to address.
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Aims and Objectives
The aim is the overarching goal or purpose of the study and the objectives are specific and measurable tasks the researcher intends to accomplish to achieve the aim of the research.
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Methodology
The methodology will vary depending on your discipline but some components include the research study design, data collection methods, sampling strategy, sample size, and data analysis techniques.
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Ethical Considerations
Some things to consider include obtaining informed consent, privacy, confidentiality, and data handling, harm to participant or researcher.
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Proposed Timeline
A proposed timeline is often presented as a Gantt Chart in a research proposal. Developing a Gantt chart helps you plan all the activities you need to conduct in order to complete your research.
Templates are available in Microsoft Excel as well as many other platforms.
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Reference List
A reference list is a comprehensive list of all the information sources you have cited in your writing.
This is an essential component of academic work at the postgraduate level.
RefWorks is a reference management software to help you manage information sources. The Library runs regular training workshops for RefWorks and these can be booked via the Library Training Calendar. Write-n-Cite, is the RefWorks add-on for Microsoft Word.
There are different referencing styles used at Ulster University and guidance on how to insert citations in the text of your work and how to prepare a list of references is available via the Library.
Some of the most commonly used referencing styles include:
- APA (American Psychological Association):
- Harvard
- OSCOLA (Law)
- AMA (American Medical Association)
Developing the Research Question and Hypothesis Testing
This is a critical first step in the research process. A well-formulated research question will guide you when making decisions as you develop your research proposal.
As an independent learner, you will need to read beyond textbooks and refer to journal articles which you can access via the Library website.
Once you have identified relevant research articles and the “gap” in the literature, consider some potential research questions.
Depending on your research topic, you could consider using the PICO model as a guide to develop your research question.
PICO Model
Further information on how to use the PICO model is available from the Critical Appraisal Skills Programme (CASP).
Understanding Research Study Designs
The research study design refers to the overall strategy you choose to answer a research question and typically includes the following components.
- Theories or models that underpin the project
- Research question
- Sampling method (recruitment)
- Strategy for collecting data
- Strategy for producing answers (data analysis)
Quantitative Research Design | Qualitative Research Design | Mixed-Methods |
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This is the process of collecting data that is numerical and can be analysed using statistical software packages. Quantitative results are presented in the form of numbers, statistics, graphs and charts. | This involves collecting and analysing non-numerical data such as text or audio. It includes open-ended questions sometimes used in surveys that collect numerical data. | This is an approach where researchers collect and analyse quantitative and qualitative data in the same research study. When interpreting the results, researchers purposefully mix the quantitative and qualitative data, and an interpretation is made with both in mind. |
Research Methodology
The research methodology is the systematic approach or framework that guides the research design process. It includes the sampling method, data collection and analysis methods and the ethical considerations.
Sampling Methods
If your research involves human participants, you will need to decide on a sampling method. This is the technique used to select participants to a research study.
Each sampling method has its strengths and limitations, and when deciding on a sampling method you need to consider the research objectives, the characteristics of your population, as well as time and resource constraints.
Here are some common sampling methods.
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Simple Random Sampling
This approach involves selecting a sample from a population where each individual or object has an equal chance of being chosen.
The researchers will need a list of all the individuals in the target population to select a representative sample.
Free random sampling software is available to facilitate this process.
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Stratified Sampling
In this method, the population is divided into distinct subgroups or strata based on certain characteristics, such as gender or age.
Samples are then selected from each of the subgroups randomly, in proportion to the size of the stratum of the population.
This ensures each subgroup is represented in the sample and allows a more targeted analysis of specific groups within a population.
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Cluster Sampling
In this method, the population is divided into clusters based on a naturally occurring, well-defined division, such as schools or households.
A subset of clusters are then randomly selected and all individuals within the selected cluster are included in the sample.
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Purposive Sampling
This can also be referred to as selective sampling where the researcher intentionally selects participants that meet specific characteristics relevant to the research question.
This method is often used in exploratory research to gain insights into a relatively unknown topic.
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Convenience Sampling
In this method, the researcher recruits participants according to their availability and accessibility such as colleagues, known associates, friends or family.
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snowball sampling
This is a nonprobability sampling technique where research participants are used to recruit additional participants who also meet the inclusion criteria, thus your sample "snowballs".
This is sometimes used when recruiting participant from minority groups or support groups.
Data Collection Methods
The methods change depending on whether you collect quantitative or qualitative data.
Similar to sampling methods, each data collection method has strengths and limitations and when writing your research proposal you need to consider the research objectives, the nature of the research, researcher skills and expertise, and assess the feasibility in terms of time constraints and resources.
Quantitative Techniques | Qualitative Techniques |
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Survey or questionnaire | Interview |
Standardised tests or assessments | Focus group |
Measuring biomarkers | Open-ended survey questions |
Sensor data collection | Life stories |
Secondary data analysis | Secondary data analysis |
Understanding Data
Data comes in many forms, including numbers, characters, text, and images that you arrange in some sort of logical or meaningful way.
When writing the research proposal you need to consider what type of data (quantitative or qualitative) you plan to collect and then how you plan to analyse the data.
If you are to statistically analyse quantitative data, you need to understand there are different types of data.
Types of Data
![A flow diagram to categorise types of data as either categorical (qualitative data) or Numerical (Quantitative data). The categorical data is sub divided into either nominal or ordinal and the numerical data is sub divided into discrete or continuous.](https://www.ulster.ac.uk/__data/assets/image/0009/1628163/varieties/width-2000.png)
Understanding Variables
In the context of research, variables are characteristics that can take on different values. They are things we measure, manipulate, and analyse.
Independent Variable (Exposure) | Dependent Variable (Outcome) |
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A factor that would be associated with the outcome you plan to measure. This can be manipulated or controlled. | The variable you plan to measure to determine whether there was an impact of the exposure on said outcome. This is the variable you would expect to change and would attribute the change to the exposure. |
Other terminology used when dealing with quantitative data includes:
- Moderating variable: A variable that has a contingent effect on the relationship between the independent and dependent variables.
- Covariate: A variable that is related to both the independent (exposure) and dependent (outcome) variables.
Types of Data Analysis
Here are some types of data analysis methods to consider for quantitative and qualitative data.
![Quantitative Analysis image](https://www.ulster.ac.uk/__data/assets/image/0008/842417/varieties/width-800.jpg)
Quantitative Analysis
Many statistical techniques make the assumption that the dependent variable is ‘normally’ distributed.
It is therefore important to consider the distribution of the data before deciding whether to use parametric or non-parametric tests.
- Parametric (normal distribution)
- Non-parametric (non-normal distribution)
![Qualitative Analysis image](https://www.ulster.ac.uk/__data/assets/image/0005/267548/varieties/width-800.jpg)
Qualitative Analysis
This method is used to analyse qualitative data, such as data collected from interviews, focus groups, biographies or documentary archived research.
Here are some common qualitative data analysis methods:
- Thematic analysis
- Content analysis
- Narrative analysis
In Summary
Crafting a well-structured research proposal is essential for outlining your research plan.
Be sure to follow the instructions and guidance provided here and in your module handbook to ensure your proposal meets all the necessary requirements.