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Design: Selection of Data Collection Methods

Elise paradis , phd, bridget o'brien , phd, laura nimmon , phd, glen bandiera , md, maria athina (tina) martimianakis , phd.

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Elise Paradis, PhD, is Assistant Professor, Leslie Dan Faculty of Pharmacy and Department of Anesthesia, Faculty of Medicine, University of Toronto, Ontario, Canada, and a Scientist, Wilson Centre; Bridget C. O'Brien, PhD, is Associate Professor, Department of Medicine, University of California, San Francisco; Laura Nimmon, PhD, is a Scientist, Centre for Health Education Scholarship, and Assistant Professor, Department of Occupational Science and Occupational Therapy, Faculty of Medicine, University of British Columbia, Vancouver, Canada; Glen Bandiera, MD, is Chief of Emergency Medicine, St. Michael's Hospital, Associate Dean, Postgraduate Medical Education, and Professor, Department of Medicine, University of Toronto; and Maria Athina (Tina) Martimianakis, PhD, is Assistant Professor, Department of Paediatrics, University of Toronto, and a Scientist, Wilson Centre.

Corresponding author: Elise Paradis, PhD, University of Toronto, Leslie Dan Faculty of Pharmacy and Department of Anesthesia, Faculty of Medicine, 144 College Street, Toronto, ON M5S 3M2 Canada, 416.946.7022, [email protected]

Editor's Note: The online version of this article contains resources for further reading and a table of strengths and limitations of qualitative data collection methods.

The Challenge

Imagine that residents in your program have been less than complimentary about interprofessional rounds (IPRs). The program director asks you to determine what residents are learning about in collaboration with other health professionals during IPRs. If you construct a survey asking Likert-type questions such as “How much are you learning?” you likely will not gather the information you need to answer this question. You understand that qualitative data deal with words rather than numbers and could provide the needed answers. How do you collect “good” words? Should you use open-ended questions in a survey format? Should you conduct interviews, focus groups, or conduct direct observation? What should you consider when making these decisions?

Introduction

Qualitative research is often employed when there is a problem and no clear solutions exist, as in the case above that elicits the following questions: Why are residents complaining about rounds? How could we make rounds better? In this context, collecting “good” information or words (qualitative data) is intended to produce information that helps you to answer your research questions, capture the phenomenon of interest, and account for context and the rich texture of the human experience. You may also aim to challenge previous thinking and invite further inquiry.

Coherence or alignment between all aspects of the research project is essential. In this Rip Out we focus on data collection, but in qualitative research, the entire project must be considered. 1 , 2 Careful design of the data collection phase requires the following: deciding who will do what, where, when, and how at the different stages of the research process; acknowledging the role of the researcher as an instrument of data collection; and carefully considering the context studied and the participants and informants involved in the research.

Types of Data Collection Methods

Data collection methods are important, because how the information collected is used and what explanations it can generate are determined by the methodology and analytical approach applied by the researcher. 1 , 2 Five key data collection methods are presented here, with their strengths and limitations described in the online supplemental material.

Questions added to surveys to obtain qualitative data typically are open-ended with a free-text format. Surveys are ideal for documenting perceptions, attitudes, beliefs, or knowledge within a clear, predetermined sample of individuals. “Good” open-ended questions should be specific enough to yield coherent responses across respondents, yet broad enough to invite a spectrum of answers. Examples for this scenario include: What is the function of IPRs? What is the educational value of IPRs, according to residents? Qualitative survey data can be analyzed using a range of techniques.

Interviews are used to gather information from individuals 1-on-1, using a series of predetermined questions or a set of interest areas. Interviews are often recorded and transcribed. They can be structured or unstructured; they can either follow a tightly written script that mimics a survey or be inspired by a loose set of questions that invite interviewees to express themselves more freely. Interviewers need to actively listen and question, probe, and prompt further to collect richer data. Interviews are ideal when used to document participants' accounts, perceptions of, or stories about attitudes toward and responses to certain situations or phenomena. Interview data are often used to generate themes , theories , and models . Many research questions that can be answered with surveys can also be answered through interviews, but interviews will generally yield richer, more in-depth data than surveys. Interviews do, however, require more time and resources to conduct and analyze. Importantly, because interviewers are the instruments of data collection, interviewers should be trained to collect comparable data. The number of interviews required depends on the research question and the overarching methodology used. Examples of these questions include: How do residents experience IPRs? What do residents' stories about IPRs tell us about interprofessional care hierarchies?

Focus groups are used to gather information in a group setting, either through predetermined interview questions that the moderator asks of participants in turn or through a script to stimulate group conversations. Ideally, they are used when the sum of a group of people's experiences may offer more than a single individual's experiences in understanding social phenomena. Focus groups also allow researchers to capture participants' reactions to the comments and perspectives shared by other participants, and are thus a way to capture similarities and differences in viewpoints. The number of focus groups required will vary based on the questions asked and the number of different stakeholders involved, such as residents, nurses, social workers, pharmacists, and patients. The optimal number of participants per focus group, to generate rich discussion while enabling all members to speak, is 8 to 10 people. 3 Examples of questions include: How would residents, nurses, and pharmacists redesign or improve IPRs to maximize engagement, participation, and use of time? How do suggestions compare across professional groups?

Observations are used to gather information in situ using the senses: vision, hearing, touch, and smell. Observations allow us to investigate and document what people do —their everyday behavior—and to try to understand why they do it, rather than focus on their own perceptions or recollections. Observations are ideal when used to document, explore, and understand, as they occur, activities, actions, relationships, culture, or taken-for-granted ways of doing things. As with the previous methods, the number of observations required will depend on the research question and overarching research approach used. Examples of research questions include: How do residents use their time during IPRs? How do they relate to other health care providers? What kind of language and body language are used to describe patients and their families during IPRs?

Textual or content analysis is ideal when used to investigate changes in official, institutional, or organizational views on a specific topic or area to document the context of certain practices or to investigate the experiences and perspectives of a group of individuals who have, for example, engaged in written reflection. Textual analysis can be used as the main method in a research project or to contextualize findings from another method. The choice and number of documents has to be guided by the research question, but can include newspaper or research articles, governmental reports, organization policies and protocols, letters, records, films, photographs, art, meeting notes, or checklists. The development of a coding grid or scheme for analysis will be guided by the research question and will be iteratively applied to selected documents. Examples of research questions include: How do our local policies and protocols for IPRs reflect or contrast with the broader discourses of interprofessional collaboration? What are the perceived successful features of IPRs in the literature? What are the key features of residents' reflections on their interprofessional experiences during IPRs?

How You Can Start TODAY

Review medical education journals to find qualitative research in your area of interest and focus on the methods used as well as the findings.

When you have chosen a method, read several different sources on it.

From your readings, identify potential colleagues with expertise in your choice of qualitative method as well as others in your discipline who would like to learn more and organize potential working groups to discuss challenges that arise in your work.

What You Can Do LONG TERM

Either locally or nationally, build a community of like-minded scholars to expand your qualitative expertise.

Use a range of methods to develop a broad program of qualitative research.

Supplementary Material

• 1. Teherani A, Martimianakis T, Stenfors-Hayes T, Wadhwa A, Varpio L. Choosing a qualitative research approach. J Grad Med Educ . 2015; 7 4: 669– 670. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 2. Wright S, O'Brien BC, Nimmon L, Law M, Mylopoulos M. Research design considerations. J Grad Med Educ . 2016; 8 1: 97– 98. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 3. Stalmeijer RE, McNaughton N, Van Mook WN. Using focus groups in medical education research: AMEE Guide No. 91. Med Teach . 2014; 36 11: 923– 939. [ DOI ] [ PubMed ] [ Google Scholar ]

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How to collect data for your thesis

Collecting theoretical data

Search for theses on your topic, use content-sharing platforms, collecting empirical data, qualitative vs. quantitative data, frequently asked questions about gathering data for your thesis, related articles.

After choosing a topic for your thesis , you’ll need to start gathering data. In this article, we focus on how to effectively collect theoretical and empirical data.

Empirical data : unique research that may be quantitative, qualitative, or mixed.

Theoretical data : secondary, scholarly sources like books and journal articles that provide theoretical context for your research.

Thesis : the culminating, multi-chapter project for a bachelor’s, master’s, or doctoral degree.

Qualitative data : info that cannot be measured, like observations and interviews .

Quantitative data : info that can be measured and written with numbers.

At this point in your academic life, you are already acquainted with the ways of finding potential references. Some obvious sources of theoretical material are:

• edited volumes
• conference proceedings
• online databases like Google Scholar , ERIC , or Scopus

You can also take a look at the top list of academic search engines .

Looking at other theses on your topic can help you see what approaches have been taken and what aspects other writers have focused on. Pay close attention to the list of references and follow the bread-crumbs back to the original theories and specialized authors.

Another method for gathering theoretical data is to read through content-sharing platforms. Many people share their papers and writings on these sites. You can either hunt sources, get some inspiration for your own work or even learn new angles of your topic. 

Some popular content sharing sites are:

With these sites, you have to check the credibility of the sources. You can usually rely on the content, but we recommend double-checking just to be sure. Take a look at our guide on what are credible sources?

The more you know, the better. The guide, " How to undertake a literature search and review for dissertations and final year projects ," will give you all the tools needed for finding literature .

In order to successfully collect empirical data, you have to choose first what type of data you want as an outcome. There are essentially two options, qualitative or quantitative data. Many people mistake one term with the other, so it’s important to understand the differences between qualitative and quantitative research .

Boiled down, qualitative data means words and quantitative means numbers. Both types are considered primary sources . Whichever one adapts best to your research will define the type of methodology to carry out, so choose wisely.

In the end, having in mind what type of outcome you intend and how much time you count on will lead you to choose the best type of empirical data for your research. For a detailed description of each methodology type mentioned above, read more about collecting data .

Once you gather enough theoretical and empirical data, you will need to start writing. But before the actual writing part, you have to structure your thesis to avoid getting lost in the sea of information. Take a look at our guide on how to structure your thesis for some tips and tricks.

The key to knowing what type of data you should collect for your thesis is knowing in advance the type of outcome you intend to have, and the amount of time you count with.

Some obvious sources of theoretical material are journals, libraries and online databases like Google Scholar , ERIC or Scopus , or take a look at the top list of academic search engines . You can also search for theses on your topic or read content sharing platforms, like Medium , Issuu , or Slideshare .

To gather empirical data, you have to choose first what type of data you want. There are two options, qualitative or quantitative data. You can gather data through observations, interviews, focus groups, or with surveys, tests, and existing databases.

Qualitative data means words, information that cannot be measured. It may involve multimedia material or non-textual data. This type of data claims to be detailed, nuanced and contextual.

Quantitative data means numbers, information that can be measured and written with numbers. This type of data claims to be credible, scientific and exact.

Dissertation Preparation

• Creating a Research Plan

Collecting Data

• Writing a Dissertation
• Function of Structures
• Detailed Structures
• Developing an Argument
• Finding Dissertations
• Additional Sources
• Citation Management

For most research projects the data collection phase feels like the most important part. However, you should avoid jumping straight into this phase until you have adequately defined your research problem and the extent and limitations of your research. If you are too hasty you risk collecting data that you will not be able to use.

• Consider how you are going to store and retrieve your data. You should set up a system that allows you to:
• record data accurately as you collect it;
• retrieve data quickly and efficiently;
• analyze and compare the data you collect; and
• create appropriate outputs for your dissertation e.g. tables and graphs, if appropriate.

Pilot Studies

A pilot study involves preliminary data collection, using your planned methods, but with a very small sample. It aims to test out your approach and identify any details that need to be addressed before the main data collection goes ahead.  For example, you could get a small group to fill in your questionnaire, perform a single experiment, or analyze a single novel or document.

• When you complete your pilot study you should be cautious about reading too much into the results that you have generated (although these can sometimes be interesting). The real value of your pilot study is what it tells you about your method.
• Was it easier or harder than you thought it was going to be?
• Did it take longer than you thought it was going to?
• Did participants, chemicals, and processes behave in the way you expected?
• What impact did it have on you as a researcher?

Spend time reflecting on the implications that your pilot study might have for your research project, and make the necessary adjustment to your plan. Even if you do not have the time or opportunity to run a formal pilot study, you should try and reflect on your methods after you have started to generate some data.

Dealing with Problems

Once you start to generate data you may find that the research project is not developing as you had hoped. Do not be upset that you have encountered a problem. Research is, by its nature, unpredictable. Analyze the situation. Think about what the problem is and how it arose. Is it possible that going back a few steps may resolve it? Or is it something more fundamental? If so, estimate how significant the problem is to answering your research question, and try to calculate what it will take to resolve the situation. Changing the title is not normally the answer, although modification of some kind may be useful.

If a problem is intractable you should arrange to meet your supervisor as soon as possible. Give him or her a detailed analysis of the problem, and always value their recommendations. The chances are they have been through a similar experience and can give you valuable advice. Never try to ignore a problem, or hope that it will go away. Also don’t think that by seeking help you are failing as a researcher.

Finally, it is worth remembering that every problem you encounter, and successfully solve, is potentially useful information in writing up your research. So don’t be tempted to skirt around any problems you encountered when you come to write-up. Rather, flag up these problems and show your examiners how you overcame them.

Reporting the Research

As you conduct research, you are likely to realize that the topic that you have focused on is more complex than you realized when you first defined your research question. The research is still valid even though you are now aware of the greater size and complexity of the problem. A crucial skill of the researcher is to define clearly the boundaries of their research and to stick to them. You may need to refer to wider concerns; to a related field of literature; or to alternative methodology; but you must not be diverted into spending too much time investigating relevant, related, but distinctly separate fields.

Starting to write up your research can be intimidating, but it is essential that you ensure that you have enough time not only to write up your research but also to review it critically, then spend time editing and improving it. The following tips should help you to make the transition from research to writing:

• In your research plan, you need to specify a time when you are going to stop researching and start writing. You should aim to stick to this plan unless you have a very clear reason why you need to continue your research longer.
• Take a break from your project. When you return, look dispassionately at what you have already achieved and ask yourself the question: ‘Do I need to do more research?’
• Speak to your supervisor about your progress. Ask them whether you still need to collect more data.

Remember that you can not achieve everything in your dissertation. A section where you discuss ‘Further Work’ at the end of your dissertation will show that you are thinking about the implications your work has for the academic community.

• << Previous: Creating a Research Plan
• Next: Writing a Dissertation >>

Data Collection Methods

Data collection is a process of collecting information from all the relevant sources to find answers to the research problem, test the hypothesis (if you are following deductive approach ) and evaluate the outcomes. Data collection methods can be divided into two categories: secondary methods of data collection and primary methods of data collection.

Secondary Data Collection Methods

Secondary data is a type of data that has already been published in books, newspapers, magazines, journals, online portals etc.  There is an abundance of data available in these sources about your research area in business studies, almost regardless of the nature of the research area. Therefore, application of appropriate set of criteria to select secondary data to be used in the study plays an important role in terms of increasing the levels of research validity and reliability.

These criteria include, but not limited to date of publication, credential of the author, reliability of the source, quality of discussions, depth of analyses, the extent of contribution of the text to the development of the research area etc. Secondary data collection is discussed in greater depth in Literature Review chapter.

Secondary data collection methods offer a range of advantages such as saving time, effort and expenses. However they have a major disadvantage. Specifically, secondary research does not make contribution to the expansion of the literature by producing fresh (new) data.

Primary Data Collection Methods

Primary data is the type of data that has not been around before. Primary data is unique findings of your research. Primary data collection and analysis typically requires more time and effort to conduct compared to the secondary data research. Primary data collection methods can be divided into two groups: quantitative and qualitative.

Quantitative data collection methods are based on mathematical calculations in various formats. Methods of quantitative data collection and analysis include questionnaires with closed-ended questions, methods of correlation and regression, mean, mode and median and others.

Quantitative methods are cheaper to apply and they can be applied within shorter duration of time compared to qualitative methods. Moreover, due to a high level of standardisation of quantitative methods, it is easy to make comparisons of findings.

Qualitative research methods , on the contrary, do not involve numbers or mathematical calculations. Qualitative research is closely associated with words, sounds, feeling, emotions, colours and other elements that are non-quantifiable.

Qualitative studies aim to ensure greater level of depth of understanding and qualitative data collection methods include interviews, questionnaires with open-ended questions, focus groups, observation, game or role-playing, case studies etc.

Your choice between quantitative or qualitative methods of data collection depends on the area of your research and the nature of research aims and objectives.

My e-book, The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance offers practical assistance to complete a dissertation with minimum or no stress. The e-book covers all stages of writing a dissertation starting from the selection to the research area to submitting the completed version of the work within the deadline.

John Dudovskiy

• Introduction for Types of Dissertations
• Overview of the Dissertation
• Self-Assessment Exercise
• What is a Dissertation Committee
• Different Types of Dissertations
• Introduction for Overview of the Dissertation Process
• Responsibilities: the Chair, the Team and You
• Sorting Exercise
• Stages of a Dissertation
• Managing Your Time
• Create Your Own Timeline
• Working with a Writing Partner
• Key Deadlines
• Self Assessment Exercise
• Additional Resources
• Purpose and Goals
• Read and Evaluate Chapter 1 Exemplars
• Draft an Introduction of the Study
• Outline the Background of the Problem
• Draft your Statement of the Problem
• Draft your Purpose of the Study
• Draft your Significance of the Study
• List the Possible Limitations and Delimitations
• Explicate the Definition of Terms
• Outline the Organization of the Study
• Recommended Resources and Readings
• Purpose of the Literature Review
• What is the Literature?
• Article Summary Table
• Writing a Short Literature Review
• Outline for Literature Review
• Synthesizing the Literature Review
• Purpose of the Methodology Chapter
• Topics to Include
• Preparing to Write the Methodology Chapter
• Confidentiality
• Building the Components for Chapter Three
• Preparing for Your Qualifying Exam (aka Proposal Defense)
• What is Needed for Your Proposal Defense?
• Submitting Your Best Draft
• Preparing Your Abstract for IRB
• Use of Self-Assessment
• Preparing Your PowerPoint
• During Your Proposal Defense
• After Your Proposal Defense
• Pre-observation – Issues to consider
• During Observations
• Wrapping Up
• Recommended Resources and Readings (Qualitative)
• Quantitative Data Collection
• Recommended Resources and Readings (Quantitative)
• Qualitative: Before you Start
• Qualitative: During Analysis
• Qualitative: After Analysis
• Qualitative: Recommended Resources and Readings
• Quantitative: Deciding on the Right Analysis
• Quantitative: Data Management and Cleaning
• Quantitative: Keep Track of your Analysis
• The Purpose of Chapter 4
• The Elements of Chapter 4
• Presenting Results (Quantitative)
• Presenting Findings (Qualitative)
• Chapter 4 Considerations
• The Purpose of Chapter 5
• Preparing Your Abstract for the Graduate School
• Draft the Introduction for Chapter 5
• Draft the Summary of Findings
• Draft Implications for Practice
• Draft your Recommendations for Research
• Draft your Conclusions
• What is Needed
• What Happens During the Final Defense?
• What Happens After the Final Defense?
• Surveys, tests, or questionnaires – administered in groups, one-on-one, by mail, or online;
• Reviews of records or documents using a rubric; or
• Observations.
• Accuracy/trustworthiness of data collected (i.e., respondent can openly answer; limited researcher bias)
• Amount of data that can be collected easily
• Degree of sampling bias (i.e., ability to draw a representative sample)
• Cost and effort required
• Speed (i.e., time it takes to complete data collection)
• Administrative issues (i.e., management, auditing, data entry)
• Depth of information that can be obtained

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• Knowledge Base
• Methodology
• Data Collection Methods | Step-by-Step Guide & Examples

Data Collection Methods | Step-by-Step Guide & Examples

Published on 4 May 2022 by Pritha Bhandari .

Data collection is a systematic process of gathering observations or measurements. Whether you are performing research for business, governmental, or academic purposes, data collection allows you to gain first-hand knowledge and original insights into your research problem .

While methods and aims may differ between fields, the overall process of data collection remains largely the same. Before you begin collecting data, you need to consider:

• The  aim of the research
• The type of data that you will collect
• The methods and procedures you will use to collect, store, and process the data

To collect high-quality data that is relevant to your purposes, follow these four steps.

Table of contents

Step 1: define the aim of your research, step 2: choose your data collection method, step 3: plan your data collection procedures, step 4: collect the data, frequently asked questions about data collection.

Before you start the process of data collection, you need to identify exactly what you want to achieve. You can start by writing a problem statement : what is the practical or scientific issue that you want to address, and why does it matter?

Next, formulate one or more research questions that precisely define what you want to find out. Depending on your research questions, you might need to collect quantitative or qualitative data :

• Quantitative data is expressed in numbers and graphs and is analysed through statistical methods .
• Qualitative data is expressed in words and analysed through interpretations and categorisations.

If your aim is to test a hypothesis , measure something precisely, or gain large-scale statistical insights, collect quantitative data. If your aim is to explore ideas, understand experiences, or gain detailed insights into a specific context, collect qualitative data.

If you have several aims, you can use a mixed methods approach that collects both types of data.

• Your first aim is to assess whether there are significant differences in perceptions of managers across different departments and office locations.
• Your second aim is to gather meaningful feedback from employees to explore new ideas for how managers can improve.

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Based on the data you want to collect, decide which method is best suited for your research.

• Experimental research is primarily a quantitative method.
• Interviews , focus groups , and ethnographies are qualitative methods.
• Surveys , observations, archival research, and secondary data collection can be quantitative or qualitative methods.

Carefully consider what method you will use to gather data that helps you directly answer your research questions.

When you know which method(s) you are using, you need to plan exactly how you will implement them. What procedures will you follow to make accurate observations or measurements of the variables you are interested in?

For instance, if you’re conducting surveys or interviews, decide what form the questions will take; if you’re conducting an experiment, make decisions about your experimental design .

Operationalisation

Sometimes your variables can be measured directly: for example, you can collect data on the average age of employees simply by asking for dates of birth. However, often you’ll be interested in collecting data on more abstract concepts or variables that can’t be directly observed.

Operationalisation means turning abstract conceptual ideas into measurable observations. When planning how you will collect data, you need to translate the conceptual definition of what you want to study into the operational definition of what you will actually measure.

• You ask managers to rate their own leadership skills on 5-point scales assessing the ability to delegate, decisiveness, and dependability.
• You ask their direct employees to provide anonymous feedback on the managers regarding the same topics.

You may need to develop a sampling plan to obtain data systematically. This involves defining a population , the group you want to draw conclusions about, and a sample, the group you will actually collect data from.

Your sampling method will determine how you recruit participants or obtain measurements for your study. To decide on a sampling method you will need to consider factors like the required sample size, accessibility of the sample, and time frame of the data collection.

Standardising procedures

If multiple researchers are involved, write a detailed manual to standardise data collection procedures in your study.

This means laying out specific step-by-step instructions so that everyone in your research team collects data in a consistent way – for example, by conducting experiments under the same conditions and using objective criteria to record and categorise observations.

This helps ensure the reliability of your data, and you can also use it to replicate the study in the future.

Creating a data management plan

Before beginning data collection, you should also decide how you will organise and store your data.

• If you are collecting data from people, you will likely need to anonymise and safeguard the data to prevent leaks of sensitive information (e.g. names or identity numbers).
• If you are collecting data via interviews or pencil-and-paper formats, you will need to perform transcriptions or data entry in systematic ways to minimise distortion.
• You can prevent loss of data by having an organisation system that is routinely backed up.

Finally, you can implement your chosen methods to measure or observe the variables you are interested in.

The closed-ended questions ask participants to rate their manager’s leadership skills on scales from 1 to 5. The data produced is numerical and can be statistically analysed for averages and patterns.

To ensure that high-quality data is recorded in a systematic way, here are some best practices:

• Record all relevant information as and when you obtain data. For example, note down whether or how lab equipment is recalibrated during an experimental study.
• Double-check manual data entry for errors.
• If you collect quantitative data, you can assess the reliability and validity to get an indication of your data quality.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organisations.

When conducting research, collecting original data has significant advantages:

• You can tailor data collection to your specific research aims (e.g., understanding the needs of your consumers or user testing your website).
• You can control and standardise the process for high reliability and validity (e.g., choosing appropriate measurements and sampling methods ).

However, there are also some drawbacks: data collection can be time-consuming, labour-intensive, and expensive. In some cases, it’s more efficient to use secondary data that has already been collected by someone else, but the data might be less reliable.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

Reliability and validity are both about how well a method measures something:

• Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
• Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research , you also have to consider the internal and external validity of your experiment.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

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CHAPTER 3 - RESEARCH METHODOLOGY: Data collection method and Research tools

As it is indicated in the title, this chapter includes the research methodology of the dissertation. In more details, in this part the author outlines the research strategy, the research method, the research approach, the methods of data collection, the selection of the sample, the research process, the type of data analysis, the ethical considerations and the research limitations of the project. The research held with respect to this dissertation was an applied one, but not new. Rather, numerous pieces of previous academic research exist regarding the role of DMOs in promoting and managing tourist destinations, not only for Athens in specific, but also for other tourist destinations in Greece and other places of the world. As such, the proposed research took the form of a new research but on an existing research subject. In order to satisfy the objectives of the dissertation, a qualitative research was held. The main characteristic of qualitative research is that it is mostly appropriate for small samples, while its outcomes are not measurable and quantifiable (see table 3.1). Its basic advantage, which also constitutes its basic difference with quantitative research, is that it offers a complete description and analysis of a research subject, without limiting the scope of the research and the nature of participant’s responses (Collis & Hussey, 2003).

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How to Analyse Secondary Data for a Dissertation

Secondary data refers to data that has already been collected by another researcher. For researchers (and students!) with limited time and resources, secondary data, whether qualitative or quantitative can be a highly viable source of data.  In addition, with the advances in technology and access to peer reviewed journals and studies provided by the internet, it is increasingly popular as a form of data collection.  The question that frequently arises amongst students however, is: how is secondary data best analysed?

The process of data analysis in secondary research

Secondary analysis (i.e., the use of existing data) is a systematic methodological approach that has some clear steps that need to be followed for the process to be effective.  In simple terms there are three steps:

• Step One: Development of Research Questions
• Step Two: Identification of dataset
• Step Three: Evaluation of the dataset.

Let’s look at each of these in more detail:

Step One: Development of research questions

Using secondary data means you need to apply theoretical knowledge and conceptual skills to be able to use the dataset to answer research questions.  Clearly therefore, the first step is thus to clearly define and develop your research questions so that you know the areas of interest that you need to explore for location of the most appropriate secondary data.

Step Two: Identification of Dataset

This stage should start with identification, through investigation, of what is currently known in the subject area and where there are gaps, and thus what data is available to address these gaps.  Sources can be academic from prior studies that have used quantitative or qualitative data, and which can then be gathered together and collated to produce a new secondary dataset.  In addition, other more informal or “grey” literature can also be incorporated, including consumer report, commercial studies or similar.  One of the values of using secondary research is that original survey works often do not use all the data collected which means this unused information can be applied to different settings or perspectives.

Key point: Effective use of secondary data means identifying how the data can be used to deliver meaningful and relevant answers to the research questions.  In other words that the data used is a good fit for the study and research questions.

Step Three: Evaluation of the dataset for effectiveness/fit

A good tip is to use a reflective approach for data evaluation.  In other words, for each piece of secondary data to be utilised, it is sensible to identify the purpose of the work, the credentials of the authors (i.e., credibility, what data is provided in the original work and how long ago it was collected).  In addition, the methods used and the level of consistency that exists compared to other works. This is important because understanding the primary method of data collection will impact on the overall evaluation and analysis when it is used as secondary source. In essence, if there is no understanding of the coding used in qualitative data analysis to identify key themes then there will be a mismatch with interpretations when the data is used for secondary purposes.  Furthermore, having multiple sources which draw similar conclusions ensures a higher level of validity than relying on only one or two secondary sources.

A useful framework provides a flow chart of decision making, as shown in the figure below.

Following this process ensures that only those that are most appropriate for your research questions are included in the final dataset, but also demonstrates to your readers that you have been thorough in identifying the right works to use.

Writing up the Analysis

Once you have your dataset, writing up the analysis will depend on the process used.  If the data is qualitative in nature, then you should follow the following process.

Pre-Planning

• Read and re-read all sources, identifying initial observations, correlations, and relationships between themes and how they apply to your research questions.
• Once initial themes are identified, it is sensible to explore further and identify sub-themes which lead on from the core themes and correlations in the dataset, which encourages identification of new insights and contributes to the originality of your own work.

Structure of the Analysis Presentation

Introduction.

The introduction should commence with an overview of all your sources. It is good practice to present these in a table, listed chronologically so that your work has an orderly and consistent flow. The introduction should also incorporate a brief (2-3 sentences) overview of the key outcomes and results identified.

The body text for secondary data, irrespective of whether quantitative or qualitative data is used, should be broken up into sub-sections for each argument or theme presented. In the case of qualitative data, depending on whether content, narrative or discourse analysis is used, this means presenting the key papers in the area, their conclusions and how these answer, or not, your research questions. Each source should be clearly cited and referenced at the end of the work. In the case of qualitative data, any figures or tables should be reproduced with the correct citations to their original source. In both cases, it is good practice to give a main heading of a key theme, with sub-headings for each of the sub themes identified in the analysis.

Do not use direct quotes from secondary data unless they are:

• properly referenced, and
• are key to underlining a point or conclusion that you have drawn from the data.

All results sections, regardless of whether primary or secondary data has been used should refer back to the research questions and prior works. This is because, regardless of whether the results back up or contradict previous research, including previous works shows a wider level of reading and understanding of the topic being researched and gives a greater depth to your own work.

Summary of results

The summary of the results section of a secondary data dissertation should deliver a summing up of key findings, and if appropriate a conceptual framework that clearly illustrates the findings of the work. This shows that you have understood your secondary data, how it has answered your research questions, and furthermore that your interpretation has led to some firm outcomes.

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Dissertation Methodology – Structure, Example and Writing Guide

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Dissertation Methodology

In any research, the methodology chapter is one of the key components of your dissertation. It provides a detailed description of the methods you used to conduct your research and helps readers understand how you obtained your data and how you plan to analyze it. This section is crucial for replicating the study and validating its results.

Here are the basic elements that are typically included in a dissertation methodology:

• Introduction : This section should explain the importance and goals of your research .
• Research Design : Outline your research approach and why it’s appropriate for your study. You might be conducting an experimental research, a qualitative research, a quantitative research, or a mixed-methods research.
• Data Collection : This section should detail the methods you used to collect your data. Did you use surveys, interviews, observations, etc.? Why did you choose these methods? You should also include who your participants were, how you recruited them, and any ethical considerations.
• Data Analysis : Explain how you intend to analyze the data you collected. This could include statistical analysis, thematic analysis, content analysis, etc., depending on the nature of your study.
• Reliability and Validity : Discuss how you’ve ensured the reliability and validity of your study. For instance, you could discuss measures taken to reduce bias, how you ensured that your measures accurately capture what they were intended to, or how you will handle any limitations in your study.
• Ethical Considerations : This is where you state how you have considered ethical issues related to your research, how you have protected the participants’ rights, and how you have complied with the relevant ethical guidelines.
• Limitations : Acknowledge any limitations of your methodology, including any biases and constraints that might have affected your study.
• Summary : Recap the key points of your methodology chapter, highlighting the overall approach and rationalization of your research.

Types of Dissertation Methodology

The type of methodology you choose for your dissertation will depend on the nature of your research question and the field you’re working in. Here are some of the most common types of methodologies used in dissertations:

Experimental Research

This involves creating an experiment that will test your hypothesis. You’ll need to design an experiment, manipulate variables, collect data, and analyze that data to draw conclusions. This is commonly used in fields like psychology, biology, and physics.

Survey Research

This type of research involves gathering data from a large number of participants using tools like questionnaires or surveys. It can be used to collect a large amount of data and is often used in fields like sociology, marketing, and public health.

Qualitative Research

This type of research is used to explore complex phenomena that can’t be easily quantified. Methods include interviews, focus groups, and observations. This methodology is common in fields like anthropology, sociology, and education.

Quantitative Research

Quantitative research uses numerical data to answer research questions. This can include statistical, mathematical, or computational techniques. It’s common in fields like economics, psychology, and health sciences.

Case Study Research

This type of research involves in-depth investigation of a particular case, such as an individual, group, or event. This methodology is often used in psychology, social sciences, and business.

Mixed Methods Research

This combines qualitative and quantitative research methods in a single study. It’s used to answer more complex research questions and is becoming more popular in fields like social sciences, health sciences, and education.

Action Research

This type of research involves taking action and then reflecting upon the results. This cycle of action-reflection-action continues throughout the study. It’s often used in fields like education and organizational development.

Longitudinal Research

This type of research involves studying the same group of individuals over an extended period of time. This could involve surveys, observations, or experiments. It’s common in fields like psychology, sociology, and medicine.

Ethnographic Research

This type of research involves the in-depth study of people and cultures. Researchers immerse themselves in the culture they’re studying to collect data. This is often used in fields like anthropology and social sciences.

Structure of Dissertation Methodology

The structure of a dissertation methodology can vary depending on your field of study, the nature of your research, and the guidelines of your institution. However, a standard structure typically includes the following elements:

• Introduction : Briefly introduce your overall approach to the research. Explain what you plan to explore and why it’s important.
• Research Design/Approach : Describe your overall research design. This can be qualitative, quantitative, or mixed methods. Explain the rationale behind your chosen design and why it is suitable for your research questions or hypotheses.
• Data Collection Methods : Detail the methods you used to collect your data. You should include what type of data you collected, how you collected it, and why you chose this method. If relevant, you can also include information about your sample population, such as how many people participated, how they were chosen, and any relevant demographic information.
• Data Analysis Methods : Explain how you plan to analyze your collected data. This will depend on the nature of your data. For example, if you collected quantitative data, you might discuss statistical analysis techniques. If you collected qualitative data, you might discuss coding strategies, thematic analysis, or narrative analysis.
• Reliability and Validity : Discuss how you’ve ensured the reliability and validity of your research. This might include steps you took to reduce bias or increase the accuracy of your measurements.
• Ethical Considerations : If relevant, discuss any ethical issues associated with your research. This might include how you obtained informed consent from participants, how you ensured participants’ privacy and confidentiality, or any potential conflicts of interest.
• Limitations : Acknowledge any limitations in your research methodology. This could include potential sources of bias, difficulties with data collection, or limitations in your analysis methods.
• Summary/Conclusion : Briefly summarize the key points of your methodology, emphasizing how it helps answer your research questions or hypotheses.

How to Write Dissertation Methodology

Writing a dissertation methodology requires you to be clear and precise about the way you’ve carried out your research. It’s an opportunity to convince your readers of the appropriateness and reliability of your approach to your research question. Here is a basic guideline on how to write your methodology section:

1. Introduction

Start your methodology section by restating your research question(s) or objective(s). This ensures your methodology directly ties into the aim of your research.

2. Approach

Identify your overall approach: qualitative, quantitative, or mixed methods. Explain why you have chosen this approach.

• Qualitative methods are typically used for exploratory research and involve collecting non-numerical data. This might involve interviews, observations, or analysis of texts.
• Quantitative methods are used for research that relies on numerical data. This might involve surveys, experiments, or statistical analysis.
• Mixed methods use a combination of both qualitative and quantitative research methods.

3. Research Design

Describe the overall design of your research. This could involve explaining the type of study (e.g., case study, ethnography, experimental research, etc.), how you’ve defined and measured your variables, and any control measures you’ve implemented.

4. Data Collection

Explain in detail how you collected your data.

• If you’ve used qualitative methods, you might detail how you selected participants for interviews or focus groups, how you conducted observations, or how you analyzed existing texts.
• If you’ve used quantitative methods, you might detail how you designed your survey or experiment, how you collected responses, and how you ensured your data is reliable and valid.

5. Data Analysis

Describe how you analyzed your data.

• If you’re doing qualitative research, this might involve thematic analysis, discourse analysis, or grounded theory.
• If you’re doing quantitative research, you might be conducting statistical tests, regression analysis, or factor analysis.

Discuss any ethical issues related to your research. This might involve explaining how you obtained informed consent, how you’re protecting participants’ privacy, or how you’re managing any potential harms to participants.

7. Reliability and Validity

Discuss the steps you’ve taken to ensure the reliability and validity of your data.

• Reliability refers to the consistency of your measurements, and you might discuss how you’ve piloted your instruments or used standardized measures.
• Validity refers to the accuracy of your measurements, and you might discuss how you’ve ensured your measures reflect the concepts they’re supposed to measure.

8. Limitations

Every study has its limitations. Discuss the potential weaknesses of your chosen methods and explain any obstacles you faced in your research.

9. Conclusion

Summarize the key points of your methodology, emphasizing how it helps to address your research question or objective.

Example of Dissertation Methodology

An Example of Dissertation Methodology is as follows:

Chapter 3: Methodology

• Introduction

This chapter details the methodology adopted in this research. The study aimed to explore the relationship between stress and productivity in the workplace. A mixed-methods research design was used to collect and analyze data.

Research Design

This study adopted a mixed-methods approach, combining quantitative surveys with qualitative interviews to provide a comprehensive understanding of the research problem. The rationale for this approach is that while quantitative data can provide a broad overview of the relationships between variables, qualitative data can provide deeper insights into the nuances of these relationships.

Data Collection Methods

Quantitative Data Collection : An online self-report questionnaire was used to collect data from participants. The questionnaire consisted of two standardized scales: the Perceived Stress Scale (PSS) to measure stress levels and the Individual Work Productivity Questionnaire (IWPQ) to measure productivity. The sample consisted of 200 office workers randomly selected from various companies in the city.

Qualitative Data Collection : Semi-structured interviews were conducted with 20 participants chosen from the initial sample. The interview guide included questions about participants’ experiences with stress and how they perceived its impact on their productivity.

Data Analysis Methods

Quantitative Data Analysis : Descriptive and inferential statistics were used to analyze the survey data. Pearson’s correlation was used to examine the relationship between stress and productivity.

Qualitative Data Analysis : Interviews were transcribed and subjected to thematic analysis using NVivo software. This process allowed for identifying and analyzing patterns and themes regarding the impact of stress on productivity.

Reliability and Validity

To ensure reliability and validity, standardized measures with good psychometric properties were used. In qualitative data analysis, triangulation was employed by having two researchers independently analyze the data and then compare findings.

Ethical Considerations

All participants provided informed consent prior to their involvement in the study. They were informed about the purpose of the study, their rights as participants, and the confidentiality of their responses.

Limitations

The main limitation of this study is its reliance on self-report measures, which can be subject to biases such as social desirability bias. Moreover, the sample was drawn from a single city, which may limit the generalizability of the findings.

Where to Write Dissertation Methodology

In a dissertation or thesis, the Methodology section usually follows the Literature Review. This placement allows the Methodology to build upon the theoretical framework and existing research outlined in the Literature Review, and precedes the Results or Findings section. Here’s a basic outline of how most dissertations are structured:

• Acknowledgements
• Literature Review (or it may be interspersed throughout the dissertation)
• Methodology
• Results/Findings
• References/Bibliography

In the Methodology chapter, you will discuss the research design, data collection methods, data analysis methods, and any ethical considerations pertaining to your study. This allows your readers to understand how your research was conducted and how you arrived at your results.

Advantages of Dissertation Methodology

The dissertation methodology section plays an important role in a dissertation for several reasons. Here are some of the advantages of having a well-crafted methodology section in your dissertation:

• Clarifies Your Research Approach : The methodology section explains how you plan to tackle your research question, providing a clear plan for data collection and analysis.
• Enables Replication : A detailed methodology allows other researchers to replicate your study. Replication is an important aspect of scientific research because it provides validation of the study’s results.
• Demonstrates Rigor : A well-written methodology shows that you’ve thought critically about your research methods and have chosen the most appropriate ones for your research question. This adds credibility to your study.
• Enhances Transparency : Detailing your methods allows readers to understand the steps you took in your research. This increases the transparency of your study and allows readers to evaluate potential biases or limitations.
• Helps in Addressing Research Limitations : In your methodology section, you can acknowledge and explain the limitations of your research. This is important as it shows you understand that no research method is perfect and there are always potential weaknesses.
• Facilitates Peer Review : A detailed methodology helps peer reviewers assess the soundness of your research design. This is an important part of the publication process if you aim to publish your dissertation in a peer-reviewed journal.
• Establishes the Validity and Reliability : Your methodology section should also include a discussion of the steps you took to ensure the validity and reliability of your measurements, which is crucial for establishing the overall quality of your research.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Methods of Data Collection – Guide with Tips

Published by Carmen Troy at August 14th, 2021 , Revised On October 26, 2023

A key aspect of the  dissertation writing process  is to choose a method of data collection that would be recognised as independent and reliable in your field of study.

A well-rounded data collection method helps you communicate to the readers exactly how you would go about testing the research  hypothesis  or addressing the  research questions  – usually set out in the  dissertation introduction chapter .

So what are the different methods of data collection you can use in your dissertation?

When choosing a dissertation method of data collection, there are certain elements you would need to keep in mind including the chosen topic, the established research aim and objectives, formulated  research questions , and time and monetary limitations.

With several data collection methods to choose from, students often get confused about the most appropriate for their own research.

Here is a complete guide on the two research designs you can choose from in your dissertation –  primary research and secondary research . The different research approaches within each of these two categories are explained below in detail.

Primary Research Strategy

Primary research involves data collection directly from participants. This data collection method is often chosen when the research is based on a certain area, a specific organisation, or a country.

Because the dissertation requires specific  results  and information, the primary research strategy is chosen to gather the required information and formulate results according to the research questions. There are various methods for conducting primary research:

Interviews are face-to-face discussions conducted directly with the participant(s). The matters raised during interviews are audio/video recorded or manually written down for subsequent analysis.

Participants are asked to fill out and sign a consent form before conducting the interviews. All questions asked during the interview are related to the research only.

Participants have the complete right to remain anonymous or reveal personal details if appropriate. Interviews are one of the most commonly used data collection strategies for dissertations employed by researchers.

Interviews are a flexible type of research. There are three types of interviews, depending on the extent to which they are structured – structured interviews , semi-structured interviews , and informal/unstructured interviews .

• The researcher collects responses based on a set of established questions with little to no room for deviation from the pre-determined structure with structured interviews.
• Unstructured interviews do not require the researcher to have a set of pre-agreed questions for the interview. The scope of this type of interview includes comprehensive areas of discussion. Responses are gathered by employing techniques such as probing and prompting.
• Semi-structured interviews offer a balance between a formal interview’s focus and the flexibility of an unstructured interview.
• In either case, the participant is informed beforehand of the nature of the interview they will be involved in.
• While there is no strict rule concerning the number of participants an interview can involve, it would make sense to keep the group to 5-6 people. On the other hand, you can interview only one subject if that is more appropriate to your needs.

With the advent of technology, and to save time, many researchers now conduct online interviews and/or telephonic interviews. The timings and schedule are set before the day of the interview, and the participant is informed of the details via email. This helps in saving valuable time for the researcher, as well as the participant.

Not sure whether you should use primary or secondary research for your dissertation? Here is an article that provides all the information you need to  decide whether you should choose primary or secondary research .

Surveys  are another popular primary data collection method. The participants for this type of  research design  are chosen through a sampling method based on a selected population.

The researcher prepares a survey that consists of questions relating to  the topic of research . These  survey questions can be either open or close-ended .

Close-ended questions require the participant to choose from the multiple choices provided. If you are conducting a survey, you may decide not to meet the respondents due to financial or time constraints because surveys can be filled online or over a telephonic session.

On the other hand, open-ended questions do not have any options, and the respondent has the liberty to answer according to their own perception and understanding. For these types of surveys, meeting the participant in person would be the more fitting option.

Dissertations with close-ended questions are classified as quantitative research strategy dissertations. The data collected from these surveys are  analysed through statistical tools  such as SPSS or Excel.

Diverse tests are applied to the data depending on the research questions, aim, and objectives to reach a conclusion. For open-ended questions, qualitative analysis  is conducted by thematic analysis and coding techniques.

• Surveys are frequently conducted in market research, social sciences, and commercial settings.
• Surveys can also be useful across a wide range of disciplines from business to anthropology.

Our writers have years of experience in dissertation research. Whether you need help with the full dissertation paper or just a part of it, ResearchProspect writers can help you achieve your desired grade.

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• Great Research/Sources
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If not, we can help. Our panel of experts makes sure to keep the 3 pillars of Research Methodology strong, and that too with zero plagiarism.

Questionnaires

Questionnaires are similar to closed-ended surveys. They contain standard questions and are distributed amongst a set of participants. A lot of researchers follow the Likert scale when using questionnaires.

This scale includes 5 options ranging from “strongly agree” to “strongly disagree”. The questionnaire consists of statements to which the respondents have to respond based on the specified options.

These responses are then  analysed with the help of SPSS or another analytical tool  by running analytical tests to create trend graphs and charts according to each statement’s responses.

Observation

This type of dissertation research design is usually used when the behaviour of a group of people or an individual is to be studied. The researcher observes the participants figure out how they behave in certain conditions.

There are two types of observations – overt and covert. Overt observation is usually adopted when observing individuals. Participants are aware that they are being observed, and they also sign a written consent form.

On the other hand, covert observation refers to observation without consent. The participant is not aware that researchers are studying them, and no formal consent forms are required to be signed.

Focus Groups

This dissertation data collection method involves collecting data from a small group of people, usually limited to 8-10. The whole idea of focus groups is to bring together experts on the topic that is being investigated.

The researcher must play the role of a moderator to stimulate discussion between the focus group members. However, a focus group data collection strategy is viral among businesses and organisations who want to learn more about a certain niche market to identify a new group of potential consumers.

What data collection best suits your research?

• Find out by hiring an expert from ResearchProspect today!
• Despite how challenging the subject may be, we are here to help you.

Secondary Research Strategy

Secondary research is the other research approach for dissertations, and it is usually chosen for its cost-effectiveness. Secondary research refers to the study and analysis of already published material on the subject.

This means that when a research topic is finalised, the  research question  is formulated and aims and objectives set up; the researcher starts to look for research and studies conducted in the past on the same topic. Reviewing and analysing those studies helps understand the topic more effectively and relate previous results and conclusions.

Researchers carried out secondary research when there was limited or no access to the participants relating to the thesis problem , even though there could be other reasons to choose a secondary data collection strategy, such as time constraints and the high cost of conducting primary research.

When using previous research, you should always be aware that it might have been carried out in a different setting with different aims and objectives. Thus, they cannot exactly match the outcome  of your dissertation.

Basing your  findings  solely on one study will undermine the reliability of your work. Do your research, understand  your topic  and look for other researchers’ views in your field of study. This will give you an idea as to how the topic has been studied in the past.

Reviewing and analysing different perspectives on the same topic will help you improve your understanding, and you’ll be able to think critically about everything you read.

A thorough critical analysis will help you present the previous research and studies to add weight to your research work.

Results and  discussion  of secondary research are based on the findings mentioned in the previous studies and what you learned while reviewing and analysing them. There is absolutely nothing wrong if your findings are different from others who investigated the same topic.

The sources for this type of research include existing literature and research material (usually extracted from government bodies, libraries, books, journals, or credible websites).

If you are still unsure about the different research strategies you can use in your dissertation, you might want to get some help from our writers who will offer free advice regarding which method of research you should base your dissertation on.

Would you like some help with your dissertation methodology? We have academic experts for all academic subjects, who can assist you no matter how urgent or complex your needs may be.

Research prospect can help you with irrespective of the dissertation’s length; it can be partial or full. Please  fill out our simple order form  to place your order for the dissertation chapter –  methodology . Or find out more about our  dissertation writing services .

Frequently Asked Questions

What are the different methods of data collection.

Different methods of data collection include:

• Surveys/questionnaires: Gather standardized responses.
• Interviews: Obtain in-depth qualitative insights.
• Observations: Study behaviour in natural settings.
• Experiments: Manipulate variables to analyze outcomes.
• Secondary sources: Utilize existing data or documents.
• Case studies: Investigate a single subject deeply.

What is data collection?

Data collection is the systematic process of gathering and measuring information on variables of interest in an established systematic fashion, enabling one to answer relevant questions and evaluate outcomes. This process can be conducted through various methods such as surveys, observations, experiments, and digital analytics.

What methods of data collection are there?

Data collection methods include surveys, interviews, observations, experiments, case studies, focus groups, and document reviews. Additionally, digital methods encompass web analytics, social media monitoring, and data mining. The appropriate method depends on the research question, population studied, available resources, and desired data quality.

Which example illustrates the idea of collecting data?

A researcher distributes online questionnaires to study the impact of remote work on employee productivity. Respondents rate their efficiency, work-life balance, and job satisfaction. The collected data is then analysed to determine correlations and trends, providing insights into the effectiveness and challenges of remote work environments. This illustrates data collection.

What is qualitative data?

Qualitative data is non-numerical information that describes attributes, characteristics, or properties of an object or phenomenon. It provides insights into patterns, concepts, emotions, and contexts. Examples include interview transcripts, observational notes, and open-ended survey responses. This data type emphasises understanding depth, meaning, and complexity rather than quantification.

How to collect data?

• Define the research question or objective.
• Determine the data type (qualitative or quantitative).
• Select an appropriate collection method (surveys, interviews, observations, experiments).
• Design tools (e.g., questionnaires).
• Conduct the data-gathering process.
• Store and organise data securely.
• Review and clean data for accuracy.

You May Also Like

What are the different types of research you can use in your dissertation? Here are some guidelines to help you choose a research strategy that would make your research more credible.

Want to start your quantitative research? Learn what a quantitative research questionnaire is and how to write excellent research questions.

Action research for my dissertation?, A brief overview of action research as a responsive, action-oriented, participative and reflective research technique.

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You are here » Home » Comunicação e informação » Notícias » Project begins data collection on the triple border between Brazil, Peru and Colombia

Project begins data collection on the triple border between Brazil, Peru and Colombia

Júlio Pedrosa (Fiocruz Amazônia)

The project aims to implement open and replicable multimodal information ecosystems on the health of populations in Brazil's border areas with French Guiana and Colombia and Peru (Photo: Julio Pedrosa)

The Mosaic Project was selected by the European Union's Horizon Europe program for funding from 2024 to 2027. It is the first European call for research proposals to be supported by the International Platform for Science, Technology and Innovation in Health (Pictis), the result of a cooperation agreement signed by Fiocruz with the University of Aveiro in Portugal. The group was welcomed by the director of Fiocruz Amazônia, Stefanie Lopes, who highlighted the innovative nature of the project's approach to health and surveillance actions in border regions and the importance of the joint participation of the institutions.

“Mosaic is a project that brings together fields of Fiocruz's work in health surveillance, in local communities, understanding the main diseases that circulate in the project's intervention regions, and bringing solutions for new monitoring and surveillance systems and health training systems within this larger context, under the auspices of the European Union,” said Carlos Eduardo Andrade Lima da Rocha, advisor to the IOC/Fiocruz Vice Directorate of IDP, who accompanied the group on the mission. Lima da Rocha highlights the strategic role of the Platform in enabling Fiocruz researchers to participate in the program.

Fiocruz's International Platform for Science, Technology and Innovation in Health (Pictis) is aimed at consolidating an international health research center with Fiocruz and the University of Aveiro in Portugal as its leading institutions. It manages and participates in teaching, research, development and innovation activities in health, with the aim of generating new products, processes and services, as well as participating in the transfer and dissemination of new knowledge and technologies for the well-being of society.

Paulo Peiter, a researcher at the IOC/Fiocruz Parasitic Diseases Laboratory and the One Health/Global Health Sector Laboratory of the International Platform for Science, Technology and Innovation in Health, highlighted the importance of the partnership between the researchers taking part in the project and the engagement of populations in the cross-border community health surveillance initiative. “We are starting a new challenge, which is to go into the field here in the Amazon, in a very particular moment in a scenario of historic drought, a context related to the project's aim of working on the issue of climate change and how it is affecting the daily lives of populations, talking with and understanding how they perceive these needs,” explained Peiter, who is leading the work package under the responsibility of the IOC/Fiocruz, via Pictis.

Researchers Sérgio Luz Bessa, José Joaquín Carvajal Cortes and Alessandra Nava, from the Center for Pathogens, Reservoirs and Vectors in the Amazon - PreV Amazonia, of the Laboratory for the Ecology of Communicable Diseases in the Amazon (EDTA), are working on the project for Fiocruz Amazônia. Mosaic further includes the African Conservation Center, from Kenya; the University of Warszawski, from Poland; the University of Lisbon, from Portugal; the Cayenne Hospital Center, from French Guiana; the National Research Institute for Agriculture, Food and the Environment, the Center for International Cooperation in Agronomic Research for Development; and the Universities of Perpignan, D'Aix Marseille and D'Artois, from France, the University of Brasilia (UnB), the Pan American Health Organization (PAHO) and the National University of Colombia.

“Mosaic's trajectory has been closely monitored by relevant bodies within the European Union and in Brazil, such as the Ministry of Foreign Affairs and the European Union Delegation in Brasilia, as well as other Fiocruz bodies, in this important stage of building a strategic alliance between ILMD, IOC, ICICTI and ENSP and the other partners that make up this consortium,” says Pictis' scientific coordinator, José Cordeiro, noting that Mosaic's first mission to Kenya was successful and well conducted by all partners.

Triple Border

In the Triple Border, the group met with researchers and local actors at the National University of Colombia, sharing experiences in health surveillance, climate change and successful projects in health and in improving living conditions, involving the communities living in the cross-border territory. On the second day, the team worked in the field at the Upetana Primary Care Unit in Tabatinga, which belongs to the Alto Rio Solimões Special Indigenous Health District (DSEI), where there was a round table discussion with the Mosaic Project researchers and the Tikuna midwives and a presentation of the local social cartography by the DSEI technicians, who belong to the Kokama ethnic group and are graduates of the Vigifront Program. The activities further involved visits to the Border Laboratory (Lafron), in Tabatinga, and to the Sinchi Institute - Instituto Amazónico de Investigaciones Cientificas, in Leticia, a city in Colombia on the border with Brazil.

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