In its most recent figures on internet use, the Office for National Statistics reported that 6.3% of UK adults had never been online at all. That release covers 2020 and the ONS has not updated the series since. Even then the gap sat almost entirely in one place: 99% of adults aged 16 to 44 were recent internet users, against 54% of those aged 75 and over.
An online survey works as an empirical research method when your research question asks about attitudes, opinions or self-reported behaviour, when your target population is reliably reachable online, and when you want to test a relationship between variables rather than estimate a figure for a whole population. By the end of this article you will have a three-sentence template for the limitations paragraph of your dissertation.
📌 Key takeaways
- 6.3% of UK adults had never used the internet in 2020.
- An open link produces a self-selecting, non-probability sample.
- The MRS Code requires enough technical detail to judge validity.
- Sampling error cannot be calculated for non-probability samples.
- Your methodology chapter needs a limitations paragraph, not an apology.
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What makes an online survey a research method
An online survey is a standardised form of questioning in which the respondent completes the questionnaire on screen, with nobody reading out the questions or writing down the answers. Methods textbooks call this a self-administered survey, and that single feature explains both its strengths and its weaknesses.
The absence of an interviewer buys you consistency. Every respondent sees the same wording, the same order and the same answer options, and no tone of voice nudges a rating in one direction. Leeds Beckett University puts the same point plainly in its guide to research design: all respondents are asked identical questions, so that information can be analysed for patterns and comparisons.
What you lose is control of the setting. You do not know which device someone is using, how distracted they are, or whether the person you meant to reach is the person answering. Misunderstandings stay invisible too: a question that an interviewer would clarify in ten seconds becomes an answer that looks exactly like every other answer in your dataset.
One more thing an online survey does not decide for you is the direction of your research. An online questionnaire is a mode of data collection, not a research tradition. Whether your project is qualitative or quantitative depends on your questions and your planned analysis, not on the tool.
Empirical research methods at a glance
Methods textbooks usually distinguish five empirical research methods: surveys, observation, experiments, content analysis and secondary analysis. The online questionnaire belongs to the first of them.
| Method | What it gives you | Typical form |
|---|---|---|
| Survey | self-reported opinions and behaviour | questionnaire, interview, focus group |
| Observation | actual behaviour rather than self-report | participant or non-participant, overt or covert |
| Experiment | evidence about cause and effect | laboratory experiment, field experiment |
| Content analysis | patterns in texts, images and posts | coding against a category system |
| Secondary analysis | answers from somebody else's dataset | reanalysis of existing studies |
Two distinctions are worth getting right in a viva or a supervision meeting. An experiment is strictly a research design rather than a data collection technique, because the data in an experiment still arrive through a survey, an observation or a measurement. Secondary analysis collects nothing at all; it reworks datasets that other researchers gathered.
Within survey research, the dividing line is the degree of standardisation. A structured questionnaire gives you countable answers from many people, a semi-structured interview gives you few answers in depth, and a focus group lives on what happens between the participants. Experiments add the question of setting: a purpose-built environment makes it a laboratory experiment, the participants' own everyday life makes it a field experiment. For how these fit together in a project, see our articles on data collection and on empirical research.
When an online survey is the right choice
Whether the online mode fits is decided by your research aim, not by your topic. The dividing line runs between two jobs: testing a relationship and estimating a value for a defined population.
In a comparison, random allocation does the work. If you want to know whether version A of an advert is rated more highly than version B, who happens to be in your sample matters far less, as long as the two versions were allocated at random. If you want to say what percentage of UK students do something, you need a selection that mirrors that population, and a shared link will not give you one.
| Your research aim | Online survey | Why |
|---|---|---|
| Test version A against version B | well suited | random allocation carries the comparison |
| Test a relationship between variables | usually suited | unless self-selection is tied to the topic itself |
| Estimate proportions for a population | only with a random sample | no list of all internet users exists |
| Survey every member of one organisation | well suited | if you can access the full mailing list |
| Reach a group with low internet use | not suited | too many people are excluded by the mode |
For most dissertations that is good news. An undergraduate or master's project is not trying to measure the United Kingdom; it is trying to show a relationship, and an online questionnaire does that job cleanly. All your text has to do is say which of the two aims you set yourself.
Coverage: who you cannot reach online in the UK
A coverage problem arises when part of your population, meaning everyone you want to make a statement about, cannot take part at all for technical reasons. Someone who is not online cannot answer, however well your questionnaire is written.
The ONS bulletin Internet users, UK: 2020 shows how unevenly that gap is spread. Almost all adults aged 16 to 44 were recent internet users at 99%, while the figure for adults aged 75 and over was 54%. Regionally, London reached 95% and Northern Ireland 88%.
Two caveats belong with these numbers. The series stops with the 2020 release, so the true gap today is very likely smaller, and the ONS itself advised caution about the oldest age group because fieldwork ran into the early pandemic period. And the survey measures internet access, not whether your particular channel reaches your particular people: an Instagram story reaches your followers, a poster in the department reaches whoever walks past.
⚠️ Warning
The narrower your target group, the less a national average tells you. Check instead whether your specific group is reachable through the channel you have planned, for example shift-working nurses or people over 75. If it is not, run a paper version alongside the online questionnaire and describe both routes in your methodology chapter.
What representativeness in an online survey actually requires is set out in a separate article.
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Self-selection and what the MRS Code expects
Self-selection means the respondents decide for themselves whether to take part, because you shared an open link. In student projects that is the normal case, and it is not a flaw as long as you say so.
The MRS Code of Conduct, operative from 15 May 2023, does not ban self-selection. It imposes a disclosure duty instead. Rules 58 and 59 require that data and reports include enough technical information to allow a reasonable assessment of the validity of results, and the commentary names sampling characteristics and the parameters used when a sample is described as representative.
The Market Research Society is more direct in its January 2026 guidance How to Read Opinion Polls. It warns against the straw poll, which it defines as an unrepresentative poll with little or no value, and separates probability from non-probability samples: in a probability sample every member of the target population has an equal chance of being selected, which is described there as the purest and most robust type of sample. Leeds Beckett adds the practical consequence for a dissertation: with non-probability sampling, the sampling error cannot be measured.
The MRS Code binds MRS members, not students, and your university regulations remain the authority for the formal requirements of your work. As a standard of openness it is still the clearest one available in the UK. For the routes themselves, see our article on finding survey participants; the selection procedures and the question of size are covered in the article on sampling.
Advantages and disadvantages of an online survey
The advantages and disadvantages of an online survey fall into two groups: the practical ones, which decide your timetable, and the methodological ones, which decide how much weight your results can carry. Your methodology chapter is about the second group.
What the method gives you
- Every respondent sees exactly the same questionnaire.
- No interviewer tone or follow-up shifts an answer.
- Sensitive questions attract fewer socially desirable answers.
- Routing and rotation stay invisible to the respondent.
- Answers reach the dataset without transcription errors.
What you accept in return
- Respondents decide for themselves whether to take part.
- Misunderstood questions are never flagged to anyone.
- Faults in the routing go unnoticed during fieldwork.
- Repeat entries are hard to rule out with an open link.
- Without a mailing list there is no real response rate.
Cost, fieldwork time and the effort of building the questionnaire are compared in detail in our article on the online survey and its pros and cons.
How to justify your method in the methodology chapter
A methodology chapter answers four questions in this order: what did you want to know, how did you collect it, whom did you ask, and where do your claims stop. The fourth is the one most often left out, and the one examiners ask about most often.
- State the research aim. Say in one sentence whether you are testing a relationship or estimating a value. That distinction carries the whole justification.
- Name the method and rule out the alternatives. Why a survey rather than observation, why online rather than paper or telephone. Half a sentence per rejected option is enough.
- Describe recruitment and sample. Which channels, which period, how many views, how many usable cases, how many drop-outs. Numbers belong here, not in the conclusion.
- Set out the limitations. A paragraph of its own saying who is missing and what your results therefore cannot show.
💡 Tip
For the limitations paragraph, this template will get you most of the way: “Participation was through an openly shared link on [channel], so the sample is self-selecting. Random selection from the target population was not possible, as no complete list of the target individuals exists. The findings therefore describe the sample surveyed and cannot be generalised to [population].” Three sentences, and the most common criticism is dealt with.
A word on naming your work: in the UK the piece submitted for a master's degree is normally called a dissertation, while a thesis is the doctoral one, which is the opposite of American usage. Where the methodology chapter sits in the overall structure is covered in our article on the empirical research process.
Common mistakes with online surveys as a method
The three most common mistakes with an online survey as a research method happen at the writing stage, not during fieldwork. The questionnaire was fine, the data are in, and the text still claims something the study cannot support.
The first two mistakes share a root: the text promises more than the data can carry. The third is the reverse, where the text says less than the researcher actually thought through.
Mistake 1: calling the sample representative
A large number of responses reduces random variation but corrects no bias. A sample becomes representative through random selection from a defined population, not through size. Matching the age and gender profile creates agreement on those two characteristics and says nothing about any other. Write “the sample surveyed” rather than “students”.
Mistake 2: quoting a response rate that does not exist
A response rate assumes you know how many people were selected and invited. With a mailing list of 200 addresses and 84 replies, the rate is calculable, and the response rate calculator is all you need for that. With a link in a story or a group chat, nobody knows how many people saw it, and any figure would be a guess. Report views, started questionnaires and completed questionnaires instead.
Mistake 3: describing the method instead of justifying it
“An online survey was conducted” is a description, not a justification. The justification comes from the options you turned down: a semi-structured interview would have given deeper answers but not enough cases for the planned group comparison. Two sentences like that show the choice was deliberate, and that is exactly what an examiner is looking for.
Conclusion
An online survey is only as good as the question you ask of it. For comparisons and tests of relationships its sampling problems weigh less heavily; for statements about a whole population it needs a random selection from a defined population, and that is almost never available in a dissertation. Naming that limit yourself does not weaken your work; it makes it checkable.
Where to go next
- Ready to build the questionnaire itself? How to create a questionnaire
- Writing an empirical dissertation right now? Empirical dissertation: how it works
- Already planning the analysis? Methods of analysis at a glance
Method justified, questionnaire still to build?
With empirio.ai, an online survey tool from Germany, you build your questionnaire in a few steps, share it by link or QR code and watch responses come in live, so you can adjust while fieldwork is still running.