How to write a dissertation: a step-by-step guide

A dissertation is easier to write when you know the next step. Difficulties often arise from tackling too many stages at once: choosing the topic as you go, collecting literature without notes, or deciding the structure after writing has begun. This guide takes you from topic selection to the final pre-submission check.

Below you will find a typical dissertation structure, the purpose of each section, an example of turning a broad topic into a testable hypothesis, a phased plan, referencing guidance, an approach to supervisor feedback and a final checklist. Your institution's regulations and template always take precedence over this guide.

What a dissertation should demonstrate

A dissertation demonstrates specific skills: independently addressing a defined topic, finding and critically using relevant literature, applying an appropriate method, writing clearly and following academic rules, particularly referencing.

The usual expectation is well-conducted, clearly explained work showing that you understand what you did and why. The aim is to demonstrate control of the process, from the question through the method to a conclusion that answers it.

Undergraduate and master's dissertations: what differs?

An undergraduate dissertation normally completes a bachelor's degree; a master's dissertation completes postgraduate study. Master's work is usually longer, engages more deeply with literature and more often includes original empirical research. Undergraduate work may instead review existing sources.

Requirements vary between institutions and programmes. Some undergraduate dissertations require research, while some master's dissertations may be theoretical. Length, proposal procedures and deadlines also differ. Start with your programme guidelines and supervisor's advice. This guide applies to both levels; the main differences are scope and depth.

How to choose and narrow your topic

A suitable topic meets four criteria: it interests you; relevant literature is accessible; the necessary data can realistically be collected before your deadline; and it falls within your supervisor's expertise. An apparently original topic with no accessible sources may lack a sound theoretical foundation.

Topics are often too broad rather than fundamentally unsuitable. Narrow the field to a topic, the topic to a problem and the problem to an answerable question. The following example illustrates this process.

Example: from a broad topic to a testable hypothesis

Broad topic: 'Social media and young people.' This leaves the platforms, population and aspect of behaviour undefined.

Narrowed topic: 'The relationship between time spent on social media and study time among final-year secondary-school students.' The population and relationship are now clear.

Aim: 'To examine whether average daily social-media use is associated with average daily study time among final-year secondary-school students.'

Research question: 'Is average daily social-media use associated with average daily study time among final-year secondary-school students?'

Testable hypothesis: 'H1: Average daily social-media use is negatively associated with average daily study time among final-year secondary-school students.'

This hypothesis specifies two measurable variables, a defined population and an expected direction. Data can therefore support or fail to support it. 'Social media is bad for young people' is too vague: it does not identify what is measured, in whom or against which indicator.

Problem, aim, research questions and hypotheses

These four elements form the framework of the dissertation. The problem is the question or gap to be addressed: something insufficiently understood, not working as expected or untested in a particular context. The aim states what the work seeks to establish, using verbs such as examine, identify, analyse or compare. Research questions divide the aim into answerable parts. Hypotheses are research propositions stated in advance so that collected data can support or fail to support them.

Hypotheses are useful when examining relationships, differences or effects and a clear proposition can be tested. They are not required in every quantitative study: descriptive work may use research questions, as often do reviews and qualitative studies. Formal requirements depend on design and programme rules. Statistical testing concerns rejecting or not rejecting a null hypothesis; interpretation explains whether findings support the research proposition.

Consistency is essential: questions follow from the aim, methods enable answers, results address the questions or hypotheses, and conclusions answer what was asked at the outset.

A realistic work plan and timeline

Unrealistic schedules create avoidable stress. Writing is only one stage; topic approval, supervisor responses and data collection also take time. Work backwards from submission, include institutional deadlines and allow contingency for stages involving other people.

The table below illustrates a plan for an empirical dissertation. Adapt stage lengths to your programme, scope and other commitments.

Table 1. Example phased dissertation plan

Stage	Key activities	Expected output	Common risk
1. Topic selection and approval	Discuss with the supervisor, narrow the topic and submit it under programme rules	Approved topic and outline structure	Overly broad topic; delayed approval
2. Literature review	Search databases, read and take notes with complete references	Relevant sources and a theoretical outline	Accumulating sources without selection or notes
3. Methodology	Define sampling, instruments and analysis plan	Methodological framework agreed with the supervisor	An instrument that does not address the research questions
4. Data collection	Conduct surveys, interviews or document collection	An organised, complete dataset	Low response rates; delayed consent
5. Analysis and results presentation	Analyse data and prepare tables and charts	Results chapter	Analysis unsuitable for the data
6. Discussion and conclusion	Interpret findings, compare with literature and synthesise	Complete first draft	Repeating results without interpretation
7. Feedback and revisions	Organise comments and revise using tracked changes	Version agreed with the supervisor	Unplanned changes; overlooked comments
8. Final preparation	Proofreading, reference checks, formatting and technical review	Submission-ready dissertation	Leaving formatting until the final day

Literature-based dissertations may omit primary data collection and analysis, focusing instead on systematic searching, selection and synthesis. Each stage still needs a clear output that shows when it is complete.

A typical dissertation structure

Structure divides the task into sections with specific purposes. Your institution determines the required order and components, but many dissertations follow this framework.

Table 2. Dissertation sections, purposes and questions

Section	Purpose	Question answered
Title page	Identifies the work, author, supervisor and institution	Who wrote it, on what topic, where and when?
Abstract and keywords	A brief overview of the entire work	What is it about and what was found?
Contents	Navigation by chapter and page	Where is each section?
Introduction	Context, problem, aim and structural overview	Why does the topic matter and what is being investigated?
Theory or literature review	Presentation and evaluation of existing knowledge	What is known and what remains unresolved?
Methodology	Description of how the study was conducted	How was it done, and why this way?
Results	Presentation of findings before wider interpretation	What was found?
Discussion	Interpretation and comparison with literature	What do the findings mean and how do they fit existing knowledge?
Conclusion	Synthesis and answers to the aim and questions	What has the work shown and what follows?
References	List of sources used	Which sources underpin the work?
Appendices	Supporting material such as questionnaires, extensive tables or consent forms	What supporting material belongs outside the main text?

Reading order need not be writing order. The introduction and abstract are often easier to finalise after the rest is complete. Check whether your institution also requires an originality declaration, abbreviations, lists of tables and figures or a CV.

Finding, evaluating and organising sources

Start with your university library, subscribed databases, the Croatian journal portal Hrčak and academic search engines such as Google Scholar. Dissertation repositories help illustrate programme expectations, but other students' work should not be the main basis of your theoretical review.

Assess each source's publication venue, author, currency, evidence and relevance. Encyclopaedias and blogs can provide orientation, but academic work should prioritise relevant scholarly and professional sources.

Record full source details with every note from the outset, including page numbers where needed. A table may suffice for a small collection; Zotero or Mendeley can help with larger bibliographies. Reconstructing missing references later is much harder.

Citing and paraphrasing without plagiarism

Every borrowed idea, fact or phrase needs attribution, whether quoted or paraphrased. Format quotations according to the required style. Genuine paraphrasing means understanding and expressing the idea in your own wording and sentence structure; substituting a few synonyms is insufficient.

Similarity tools identify textual overlap with available sources. A percentage alone is not a verdict on plagiarism: results must be interpreted in context, considering quotations, references, match types and institutional rules. Accurate citation and genuine paraphrasing matter regardless of screening tools.

Apply the institution's or supervisor's required citation style consistently in text and references. Check that entries correspond. Also follow rules on reusing your own previously submitted or published work, which may require explicit attribution.

Writing the methodology section

Explain how the research was conducted so readers understand the design, collection and analytical logic. Quantitative studies typically describe design, sampling, instruments, procedures, analysis and ethical issues such as voluntary participation, anonymity and required consent.

Two common errors are designing the instrument before defining precise questions and collecting data without an analysis plan. Link each question or hypothesis to suitable data and an analytical procedure in advance. If you are unsure, our statistical test selection guide takes you through five important research questions.

Results: presenting findings before interpreting them

The results chapter states what was found. Number and title tables and charts according to institutional rules. Guide readers through the findings without repeating every figure. Report the statistical procedure and key indicators supporting conclusions.

Broader interpretation generally belongs in the discussion, allowing readers to consider findings first. If your analysis is complex or you need to turn a dataset into a clear results chapter, explore our support for statistical analysis and interpretation, with clear explanations of each procedure.

Writing the discussion and conclusion

The discussion explains findings in relation to research questions and existing literature, considers expected and unexpected results, and states limitations such as sample size and composition, instrument properties or data coverage. Explicit limitations show you understand the reach of your conclusions.

The conclusion synthesises answers to your aim, questions or hypotheses and may recommend practical action or further research. Do not introduce new data, sources or previously unexamined claims. Compare the introduction and conclusion: the latter should answer what the former promised.

Handling supervisor feedback

Revision rounds are a normal part of many projects. Collect comments in one place, classify them as content, methodology, structure, language or formatting, and address substantive issues first. Ask for clarification or explain your reasoning where needed. Tracked changes help the supervisor review revisions.

For a detailed process and examples, read our article on addressing supervisor comments systematically. For extensive, methodological or urgent feedback, we also offer supervisor and reviewer revision support: organising comments, planning revisions and implementing agreed changes with a clear record.

Language editing, academic editing and technical checks

Completed content still needs language and formatting checks. Review grammar, spelling, terminology and clarity; then structure, transitions, references and unsupported claims. Check margins, spacing, fonts, page numbers, heading levels, table and figure labels, contents and bibliography against the institutional template.

Allow time between the last substantive change and the final read. Do not leave formatting to the last moment, since content changes affect numbering and layout. For demanding language, referencing or formatting needs, consider professional copy-editing and academic editing following institutional guidelines.

Common mistakes that delay completion

Typical problems include reading extensively without notes, writing before agreeing a structure, designing instruments before defining questions, mixing results and discussion, reconstructing references at the end and checking faculty rules only before submission.

Skipped steps often return as extra revisions. Confirm the topic and framework first, organise literature and methodology next, and then begin detailed writing and analysis.

Final checklist before sending work to your supervisor

Use this checklist before review or submission to catch common omissions that cause additional revisions.

Content checks

• The aim, questions and any hypotheses are consistent from introduction to conclusion.
• Every chapter clearly relates to the topic and aim.
• The conclusion directly answers the aim and each question or hypothesis.
• No paragraphs are disconnected from the main argument.

Methodological checks

• Sampling, instruments and collection procedures are clearly described.
• The analysis is specified and aligned with research questions.
• Research limitations are clearly stated.

Sources and referencing checks

• Every borrowed claim, fact and phrase is appropriately sourced.
• All in-text sources appear in the references and vice versa.
• Citation style is consistent throughout.

Language checks

• Spelling and grammar have been checked throughout.
• Terminology is consistent from first chapter to last.
• The entire work has been read after the final change.

Technical checks

• The title page and required sections follow the institutional template.
• Page, table and figure numbering is correct and contents are updated.
• File format and submission method follow official instructions.

When to seek expert academic support

Common questions about undergraduate and master's dissertations

How do I write an undergraduate dissertation?

Choose and narrow the topic, define aims and questions, and plan the stages. Review relevant literature and conduct research where required. Write to an agreed structure, then check references, language and formatting. The introduction and abstract are often easier to finalise last.

How do I write a master's dissertation?

The process is similar, but usually requires greater depth, a broader literature review and more often original research. Your institution defines exact scope, research requirements and proposal procedures.

How long does a dissertation take?

It depends on project type, literature access, research requirements, other commitments and feedback timing. Allow weeks to months as appropriate, planning backwards from submission and including approvals, feedback and revisions.

How many pages should a dissertation have?

Your institution determines length, which varies widely. Undergraduate dissertations may run to several dozen pages and master's work is often longer, but official guidelines govern. Quality depends on a clear, reasoned response to the aim, not page count alone.

How do I choose a dissertation topic?

Find a topic that interests you, has accessible literature, allows feasible data collection and fits your supervisor's expertise. Narrow it to a population, context, variables or answerable question within the required scope.

Does an undergraduate dissertation require empirical research?

Not always. Some programmes permit literature-based work; others require an empirical component. Clarify the rules with your supervisor before submitting the topic.

How do I use sources without plagiarising?

Attribute borrowed ideas, data and wording, including paraphrases. Use your own wording and sentence structure rather than synonym substitutions. Keep complete source details and apply the required citation style from the start.

What should I do with extensive supervisor feedback?

Collect and classify all comments, then address content and methodology before language and formatting. This prevents later substantive changes from undoing earlier editing.

When is statistical analysis needed?

When a project uses quantitative data, such as surveys, measurements or numerical records, to draw conclusions. Select and correctly apply methods suited to the data and questions, then present and interpret results clearly. Purely theoretical or literature-based work does not require statistical analysis.

How are academic support scope and price determined?

They depend on project type, level, stage, the amount and complexity of support and the deadline. Explore an indicative range through the price calculator, then receive a precise quote after material review and before work begins.