Research Resources for Students

Research projects ask you to make a chain of decisions, and each one depends on the one before. Your question shapes your method, your method shapes your sample and data, and your data shapes what you can honestly claim at the end.

This page explains those decisions in plain terms. It is a starting point, not a replacement for your module handbook or your supervisor. Where your department has its own rules, theirs come first.

Where to start

If you are at the beginning of a project, these resources fit together in roughly this order:

• Shape your idea with the research question builder, and browse writing topics if you are still choosing an area.
• Organise your reading with the literature review matrix and the guide to writing a literature review.
• Plan your proposal with the guide to research proposals.
• Map your chapters with the thesis chapter planner and the guide to thesis chapters.
• For shorter projects, see the guides to research papers and lab reports.

Choosing qualitative, quantitative or mixed methods

The right method is the one that can answer your question. Students sometimes choose a method first because it feels familiar or easier, and then struggle to make the question fit.

Mixed methods is not simply "doing a survey and some interviews". You need a reason for combining them, for example using interviews to explain patterns found in survey data, and you need to say how the two parts connect.

Research questions and hypotheses

A research question states what you want to find out. A hypothesis is a testable prediction about the answer, usually used in quantitative and experimental research.

• Qualitative studies normally use open research questions and no hypotheses.
• Quantitative studies often state hypotheses, sometimes paired with a null hypothesis, especially in psychology, health and the natural sciences.
• Some disciplines and departments prefer research objectives instead. Check what your handbook asks for.

A good question is focused, researchable with the time and data you have, and connected to a gap in the literature. "What affects student wellbeing?" is too broad for most dissertations. "How do final-year nursing students at one university describe the effect of clinical placements on their wellbeing?" sets a clear scope (illustrative example).

The research question builder walks you through narrowing a topic step by step.

Sampling basics

Your sample is the set of people, documents, organisations or cases you collect data from.

Probability and non-probability sampling

• Probability sampling gives every member of a population a known chance of being selected, for example simple random or stratified sampling. It supports generalising findings to the wider population.
• Non-probability sampling selects participants by other means, for example purposive sampling (choosing people with specific experience), convenience sampling or snowball sampling. It is common in qualitative research, where the aim is depth rather than statistical generalisation.

Whatever you choose, explain why it suits your question and acknowledge its limits. Convenience samples of classmates are common in student projects, and that is acceptable if you are honest about what it means for your conclusions.

How big should your sample be?

There is no single correct number. Sample size depends on your design: statistical analyses depend on the tests you plan to run and the effect you expect, while qualitative studies are often judged on whether the data is rich enough to answer the question.

Be cautious about rules of thumb you find online. Ask your supervisor, follow your department's guidance and, for quantitative work, use your university's statistics support or recommended methods textbooks to justify your figure.

Data collection methods

Pilot your instrument before full data collection. Even asking two or three people to complete a draft survey or answer interview questions will reveal unclear wording.

Research ethics approval

Most universities require ethics review before you collect data from people. The details vary by institution and discipline, but the process usually asks you to show that:

• participants are informed about the study and freely consent to take part;
• they can withdraw, and you explain how and until when;
• data is stored securely and handled in line with data protection law;
• risks to participants, and to you, are identified and reduced;
• vulnerable groups, sensitive topics or covert methods are given extra justification.

Start this early. Approval can take longer than students expect, and collecting data before approval may mean you cannot use it. Your university's ethics committee pages and your supervisor are the authorities here, and any template they provide should be used exactly.

Judging the quality of a study

Validity and reliability

In quantitative research, quality is usually discussed in terms of validity (are you measuring what you claim to measure, and are your conclusions justified?) and reliability (would the measurement produce consistent results if repeated?).

Trustworthiness

Qualitative researchers often use the idea of trustworthiness instead, commonly broken down into credibility, transferability, dependability and confirmability. In practice, this means showing your reasoning clearly: how you analysed the data, how you checked your interpretations and how your own position might have influenced the study.

Whichever framework applies, your methodology chapter should name the main limitations and explain what you did about them. Examiners tend to respect honest limitations more than claims of a flawless design.

Presenting and interpreting data

Tables or charts?

• Use a table when readers need exact values or need to compare several variables precisely.
• Use a chart when the pattern matters more than the precise figures, such as a trend over time or a comparison between groups.
• Do not show the same data twice in both formats unless your guidelines ask for it.
• Number and title every table and figure, label axes and units, and refer to each one in the text.

For qualitative data, themes are usually presented in prose with short, carefully chosen quotations, sometimes supported by a summary table of themes.

Describe first, then interpret

Report what the data shows before explaining what it means. In many structures, results and discussion are separate chapters. Even when combined, keep the difference clear in your sentences.

Do not overclaim

Correlation does not show causation. A small or convenience sample does not represent a whole population. A theme raised by several interviewees is not proof of a universal experience. Use careful language such as "suggests", "is associated with" and "in this sample", and match the strength of your claims to the strength of your evidence.

Thesis planning milestones

Long projects go wrong when they are planned as one big task. Breaking the work into milestones lets you and your supervisor see progress and problems early. A typical sequence looks like this:

1. Agree your topic and draft research question with your supervisor.
2. Complete an initial literature search and organise it in a matrix.
3. Submit your proposal and, where needed, your ethics application.
4. Draft the literature review while you wait for approval.
5. Collect your data, keeping notes on decisions and problems.
6. Analyse the data and draft your results.
7. Write the discussion and conclusion, then revise the introduction to match.
8. Edit, check referencing and format to your university's requirements.

Build in time for supervisor feedback between stages. The thesis chapter planner helps you set word counts and milestones for each chapter.

Frequently asked questions

Do I need a hypothesis for my dissertation?

Not always. Hypotheses are common in quantitative and experimental studies, while qualitative and many mixed-methods projects use research questions or objectives instead. Follow your department's guidance and your supervisor's advice on which format they expect.

Can I change my research question after starting?

Questions are often refined as you read and plan, and that is normal. Larger changes, especially after ethics approval or data collection, should be discussed with your supervisor, because they may affect your approval and methods.

Can AcademicDude help with my research design?

Yes, in the form of guidance. We can talk through your question, method, sampling and chapter structure and give feedback on your drafts, while you make the decisions and write the work yourself. See thesis and dissertation guidance and research paper and project guidance.