Who can help me collect data for my dissertation?

Your ethics approval is through, and now someone has to design the instrument, find real respondents, and clean what comes back. A researcher in your field builds the questionnaire or interview guide, runs recruitment within your approved protocol, and hands you a dataset you can defend.

Direct answer: Someone who can help you collect data is a researcher who has done fieldwork in your discipline, not a general data-entry service, because designing a sample and a question set that measures what your research question actually asks takes methods training. You can run collection yourself with your supervisor's guidance once your ethics application is approved, and many programmes expect you to. A university research office can sometimes point you toward existing datasets that already cover your population. Or you can commission Data Collection Support from MAAS EdTech, where a researcher in your field designs the questionnaire or interview guide, builds a sampling plan, recruits real respondents within the protocol your ethics board approved, or sources a secondary dataset, and cleans the data before handing it to you. Whichever route you take, collection cannot start before your institution's ethics approval is granted, and no researcher, including MAAS, should begin fieldwork without it.

Why does data collection stall so many dissertations?

Collection is where a dissertation timeline most often loses months, even when every earlier chapter is finished on schedule.

• Ethics approval takes longer than planned. A form returned for revision can add weeks that were not built into the original timeline.
• Recruitment is slower than the literature makes it look. Low-incentive surveys can sit open for weeks with too few responses.
• A sampling plan written after the fact does not hold up. An answer decided after the data came in reads as an afterthought when a supervisor asks why the sample was drawn that way.
• Raw responses need cleaning before they mean anything. Incomplete entries, duplicates and inconsistent coding have to be resolved first.

What is MAAS Data Collection Support?

The stage between an approved ethics application and a dataset ready for analysis: instrument design, sampling plan, real responses or a secondary dataset, then cleaning. No target grade, quoted by scope; MAAS EdTech does not fabricate data or fill in responses to reach a target sample size.

Who is Data Collection Support for?

Students and researchers whose question and ethics approval are settled and who now need the instrument built and the data gathered, the design steps Crotty (1998) places at the methods layer.

• Dissertation and thesis students with an approved ethics application who now need the questionnaire or interview guide built
• Researchers who need a sampling plan they can defend when asked why the sample was drawn that way
• Students who need a secondary dataset sourced because primary collection is not feasible
• Anyone with raw survey or interview data that needs cleaning before analysis

This is not for you if your ethics approval has not yet been granted. If your ethics form itself is not yet written, an expert can guide you through preparing it, which adds 5% to the base price, quoted separately.

What do you get?

An instrument, a sampling plan, a dataset built from real responses, and the documentation that shows how it was gathered.

Instrument design

• A questionnaire or interview guide built from your research question, checked against the target population it measures, so what counts as a good response is clear before recruitment starts
• A pilot round where useful, to catch confusing items before full recruitment

Sampling and recruitment

• A sampling plan written before recruitment starts, with the reasoning documented for your methodology chapter, the layer Crotty (1998) and Staller (2013) place sampling decisions at
• Recruitment follows the protocol your ethics board approved. Where that protocol names only you as the researcher, the expert prepares the invitation, instrument and sampling plan, and you send them out and collect responses yourself
• A secondary dataset sourced and matched to your research question, when primary collection is not the right route

Data cleaning

• Incomplete and duplicate entries flagged and resolved by a documented rule, not removed at random
• Coding checked for consistency against a documented rule
• A file handed back in the format your analysis stage needs

How strict are ethics timelines in practice?

Ethics rules are set programme by programme, so check your handbook for when the ethics form is due and how it counts towards the methodology chapter before any primary or secondary data is touched.

Whichever route your data takes, primary collection, a case study applying an existing framework, or secondary dataset reanalysis, it has to match the epistemological stance argued earlier in the methodology chapter (Crotty, 1998).

Where does an instrument and a sampling plan actually sit in your methodology?

Crotty (1998) separates the research process into four nested layers: epistemology, theoretical perspective, methodology, and methods, placing statistical analysis, interviews, questionnaires and case studies at the methods layer, the layer a sampling plan and a data collection instrument belong to. Staller (2013), summarising Crotty (1998), situates survey research, ethnography, grounded theory and action research one layer up, at methodology. Not every author agrees on where each technique sits: Creswell and Creswell (2023) group quantitative, qualitative and mixed methods at the methodology layer instead of splitting them across layers, and McCarthy (2012) notes that Crotty treats a case study as a method while other authors treat it as a research strategy. Saunders, Lewis and Thornhill (2012) warn that many texts use "methodology" and "methods" interchangeably regardless of which convention they claim to follow, so keeping a sampling plan clearly at the methods layer is easier for a supervisor to follow.

Why does a documented sampling plan hold up better under questioning?

A supervisor asking why a sample was drawn a particular way is comparing your choice against what a defensible sample in your field looks like, so a sampling plan written down before recruitment starts holds up better than one reconstructed afterward. A documented sampling rationale states that reasoning before anyone else has to ask for it.

How it works

Collection runs in three stages, the instrument first, then fieldwork, then cleaning.

What happens to the data after analysis, and who collects it?

Nothing further, unless you ask for it. Once your dataset moves into SPSS, R, or Python analysis, you keep the raw file, the syntax, and every output, so you can explain how each result was reached. Your researcher works in your discipline, because a sampling frame that fits a marketing survey does not fit a clinical interview study. Level, field and country are visible on the experts page, and how engagements have run on success stories.

What decides your quote?

Two prices sit at the base, and everything else moves the number from there.

• Data collection (Collect Data) starts at 2,205,000 VND per item, exclusive of 8% VAT. Roughly £63 or $85 at the exchange rate on 22/09/2026, for reference only.
• Questionnaire or interview guide design (Questionnaire) starts at 2,205,000 VND per item, exclusive of 8% VAT, at the same reference rate.
• Sample size and method move the figure from there, since a 100-response survey and a 30-transcript interview study are different amounts of work.
• Turnaround matters because recruitment runs on real people's schedules, not on a rush fee alone.

Send your approved ethics protocol and your research question, and a figure comes back. Seeing the number commits you to nothing.

Have an approved ethics protocol and need the data gathered? support@maasedtech.com or +84 979 422 393 (WhatsApp).

Not ready to book a call? Send your protocol on WhatsApp or Messenger and ask for a figure.

Frequently asked questions

Data Collection Support designs your questionnaire or interview guide, builds a sampling plan, gathers real responses within your approved protocol or sources a secondary dataset, and cleans the data before handing it to you. It sets no target grade and starts only once your ethics approval is granted.

Does collection start before my ethics approval comes through?
No. Fieldwork cannot begin before your institution's ethics board approves the protocol, for MAAS or for any researcher. If you still need to prepare the form, expert guidance on it can be quoted alongside collection.

Will any of the data be invented or filled in to hit a target sample size?
No. Every response comes from a real participant or a sourced secondary dataset, and MAAS EdTech does not fabricate responses to reach a number.

Will MAAS change your expert if the first one is not a good fit for your field?
Yes. If the researcher does not suit your discipline or your population, MAAS EdTech arranges a change of expert.

What do I need to send to get a quote?
Your approved ethics protocol, your research question, your target population, and whether you already have a draft instrument or need one built from scratch.

Can you analyse the data once it is collected?
Yes, as a separate step. SPSS, R, or Python analysis runs on your dataset and returns the file, the syntax, and the output you need to defend the chapter.

References

Creswell, J. W., & Creswell, J. D. (2023). Research design: Qualitative, quantitative, and mixed methods approaches (6th ed.). SAGE.

Crotty, M. (1998). The foundations of social research: Meaning and perspective in the research process. SAGE.

McCarthy, J. (2012). Reflections on business research (RIBM Working Paper Series). Manchester Metropolitan University. https://mmu-eprints-repo-prod.mmu-eprints.cdl.cosector.com/593399/1/JeffMcCarthy-ReflectionsOnBusiness-Research-RIBM-Mar2012.pdf

Saunders, M., Lewis, P., & Thornhill, A. (2012). Research methods for business students (6th ed.). Pearson.

Staller, K. M. (2013). Epistemological boot camp: The politics of science and what every qualitative researcher needs to know to survive. Qualitative Social Work, 12(4), 395–413. https://doi.org/10.1177/1473325012450483