It is not always necessary to collect all the data yourself. You may also use existing sources. Think of databases like SCP or CBS, from which you can buy data, but also from your own administration or cash register system. Use existing databases if you want to know more about a particular subject on which national data is collected or if you require quantitative data about your own organization. A lot of data is readily available. Just make clever use of this.
- Formulate a clear purpose and research question and sub-questions that you seek answers to with existing research sources.
- Provide keywords and search terms derived from your purpose and research question. This will give you a clear direction to look for relevant sources.
- Collect current information.
- Make sure the sources are relevant to your problem statement.
- Keep track of which information you get from where, so you and your client can see which sources were used.
- The information provided by existing data sources does not always fully match the problem statement or might be incomplete. In such cases, it is wise to combine existing source research with other research methods.
In literature research, you research readily available data to formulate a problem definition. Some cases have been studied before, and there is no need to reinvent the wheel. By doing literature research, you can gather a lot of information. I will give you eleven tips for doing literature research:
- Much information is already available. Through literature review, you can gather a lot of information about trends, market movements, market structure, and developments without having to do the fieldwork.
- The literature review will form a clear purpose/research question and sub-questions that you want the answers to.
- Provide keywords and search terms derived from your purpose/research question. This will give you a direction to research relevant literature.
- Look for references and source citations to other publications in relevant articles. This will give you what is known as the snowball effect to new information.
- Gather current information.
- Turn the collected literature into one document, adding only the relevant information that answers the research question.
- Keep track of what information you get from where, so you and your client can see which sources were used.
- Mention the sources using the APA rules to avoid plagiarism.
- Important when you are doing desk research is to check the relevance of the data. Does this information answer your problem definition?
- Ensure to have multiple sources. This makes the data more reliable.
- Provide reliable sources, such as (scientific) articles through Google Scholar, published studies on official websites, or sources from the library.
Doing research can benefit you in many ways. You gain insights with which you can make informed decisions and take appropriate actions. Provided you do it right. But if you don't, research will not (or hardly) provide you with what you want and will only cost you unnecessary time. In this blog, I will mention a few pitfalls to watch out for to help you on your way:
- You are researching because you have to. You start a research project because you need the information. For example, to improve your project, provide accountability, feed decision-making, or create support. However, think about what you want to achieve with the research. Do not research because it fits the process or because it is the way it should be done when you don't need that information.
- Asking the wrong research question ultimately prevents you from getting the answers you are looking for. Formulating the right research question is essential to obtaining the information you need. Formulate the research question based on the information you need. The research question often cannot be changed during the research. If you are collecting information, you can not deviate too much from this during the data collection. Pay attention to this when formulating your research question.
- Choosing the wrong research method. The research method you choose depends on the type of information you need. Hence, don't choose a questionnaire if you want to know underlying motivations. Or: don't choose interviews if you want a lot of numbers and percentages from a large group of people.
- Becoming lost in the amount of information. Once you have gathered all the information, the key is not to get lost in the information and get back to your research question. The results of a research study are not a collection of facts but a coherent answer to your question. Therefore, the facts are clustered so that connections are transparent (and thus formulated), and the conclusions are a logical consequence and answer your question.
- Doing nothing with the results. Just doing a survey won't get you there. The results need to be implemented. How you do this depends on the research you have done. Learning moments or action points often emerge logically from a research study. Sit down for this (with colleagues) to formulate an action plan or implementation plan. Formulate concrete agreements with colleagues about what you will do with the information.
Want to read more about how to go through the steps of doing research properly? Then read these previously published blogs:
- How to arrive at the right research question
- How to choose a suitable research method
- How to conduct data collection?
- Tips for analyzing and reporting research
Already I have written several blogs about the use of research methods. But how do you choose a suitable research method for your research? Here are several steps to take.
What information do you already have? And what information do you need to collect?
Think carefully about what information you need to answer your research questions. You may already have information at hand that you can use to answer your research questions. Think, for example, of a data file that you keep with data from participants and the cash register printout of your sold tickets.
Still, you might need more information to answer your research questions.
► Look at the information you already have and can use to answer your research questions. Think about what information you still need and want to collect.
Where can you find the information? Who can help you further?
Once you have an idea of the information you need to answer your research questions, determine where you can find that information. Do you need to conduct interviews to obtain extensive information, or do you want to reach large numbers of respondents with, for instance, a questionnaire? Carefully consider how you will approach the respondents; young people should be approached differently than older people. Or maybe you need to search further in the literature to find the correct information.
► Therefore, clearly define what information you want to find, which persons can help you with the information, and how you will approach them.
Which tool will you use for which research question?
Once you have a clear idea of what information you want to collect and who you will consult, you can establish what you can combine. Which subjects will recur in the interview, and what will you pay attention to when making your observations.
► Make a diagram showing what information you want to collect, from whom, and in what way.
Each research question requires its own way of researching. For some research questions, the answer is best found by doing qualitative research. For other inquiries, quantitative research is more appropriate. But what exactly do qualitative and quantitative research entail? In this blog, I will explain this to you.
Qualitative research is aimed at obtaining information about what matters and why. It provides in-depth information by examining the underlying motivations, opinions, wishes, and needs of the research group.
The following methods are appropriate for qualitative research:
- Individual in-depth interview or a Duo interview;
- Group discussion;
- Mystery guests.
Quantitative research focuses on quantity. It gives you numerical results about a specific group. To speak of representative research, you need a minimum number of participants within your target group who give their opinion. For this, you can draw a sample. When this sample has a specific size and characteristics (depending on the research question), statements can be generalized to the entire target group.
For quantitative research, a (digital) questionnaire/survey is primarily used as a method. The answers from the questionnaire are then processed in a data processing program (e.g., Excel or SPSS), after which you can conduct analysis and calculation. Percentages and numbers usually describe the results.
In my next blog, I will explain for which answers it is best to do qualitative research and when, on the contrary, it is wiser to choose quantitative research.
A questionnaire is a commonly used research method to measure the effects of an activity, project, or program. The question is whether a questionnaire is always an appropriate method. Do you want to make statements about the entire target group and collect a lot of data? Then it is a smart method. Do you want insight into the underlying motivations and opinions of your target group? Then a questionnaire is a less wise choice. Why is a questionnaire a good method, and why a less good method? Here you will find the pros and cons explained:
- It allows you to survey a large group of people. This is necessary if you want the results of your research to be representative of the entire research group. You can then make statements like: '80% of the visitors say they learned something from the activity'.
- An interviewer or observer cannot influence answers; this ensures objectivity.
- The way of asking questions is standardized, ensuring unambiguous answers.
- In-depth statistical analyses can be made, for example, to subgroups or to establish correlations.
- You have little influence on the response rate, often resulting in a relatively low response rate with this method.
- The respondent cannot tell his story freely; the answers are primarily pre-programmed.
- Respondents tend to answer socially appropriately, even when it is anonymous.
- Underlying motivations are difficult to ascertain with a questionnaire, making the questions and answers superficial. There is no option for follow-up questions.
- Respondents cannot complete the questionnaire. If they quit at the halfway point, it is of little use.
- You can ask a limited number of questions, as response rates drop the more extended the questionnaire is.
In conclusion, questionnaires can be a valuable research tool when applied correctly and when the research objectives align with the method's strengths. They are particularly useful for gathering data from a large and diverse audience, enabling researchers to make generalizations and perform in-depth statistical analyses. However, the limitations of questionnaires, such as potential response bias, inability to probe underlying motivations, and low response rates, should be carefully considered. Depending on the research goals, it may be necessary to complement questionnaire data with other research methods, such as interviews or focus groups, to gain a more comprehensive understanding of the target group's opinions and motivations
Be creative when choosing your research methods. There are many ways to collect your data. And you can make all sorts of combinations. Think beyond the standard research methods.
By adapting standard methods, you can make it easy for respondents; this will increase your response rate. People will enjoy participating in your research. For example, tear-off cards are very short questionnaires. And short interviews are questionnaires with many open questions. A brief conversation in which a respondent can tell their story over a cup of coffee is a nicer experience than filling out a questionnaire.
Using panels makes good use of people who want to participate in your research, and they are often rewarded for doing so. You pay per respondent, and the panel administrator is happy to help you assess representativeness. You can often select your target group very precisely based on all kinds of background characteristics.
Combining methods gives depth to the information collected. For example, you can interpret the results of a questionnaire in group discussions. Alternatively, you can compile a questionnaire based on a literature review. Or first, analyze existing data files and then ask what is missing in a questionnaire. That way, you don't have to ask several things in your questionnaire, and you can go in-depth about the subject matter in your questionnaire.
You can make respondents keep a logbook and combine this with tracking. This way, you can see what the respondents do, and the respondent also describes it. Please keep the privacy laws in mind.
Combinations I like to use are observations and short conversations based on a questionnaire. Based on what you have observed, you ask some questions. For example, why someone did what they did or how they experienced it.
After formulating your goals, designing the research instrument, and collecting information, it is time to analyze and report the data. Some things to keep in mind when analyzing and reporting your research:
- Analysis and reporting go hand in hand in practice, while they are actually two different steps that can be done separately. By performing the steps at the same time, you keep the overview and save time.
- Before you start the analysis, it is good to check whether the fieldwork was carried out and recorded correctly. You check whether you have a sufficient response rate (especially for quantitative research), the representativeness of your data and whether you were able to collect adequate information (especially for qualitative research)
- Describe your research group. Especially in quantitative research, you may be asked questions about how you arrived at your conclusions and data.
- The core of the analysis and reporting is answering your sub-questions. Therefore, always consider whether the information also answers the sub-question and whether it adds anything.
- In qualitative research, you're going to group the answers by topic and sub-question. In quantitative methods, you will look at percentages, mean scores, and correlation with a data processing program like excel or spss.
- Determine the suitable form for your report. Consider the report's purpose (to inform, persuade, provoke action, etc.) and who the target group is.
- Make connections between the details and conclusions in your report. Which answers to sub-questions enhance each other? Where do you see links throughout the study? Pull the paragraphs and chapters together with these connections and conclusions.
Questionnaires often use scales to measure respondents' opinions but also to look at what they did. However, you can also use scales in observations, logs, tear-off cards, and interviews.
Which scales are there?
There are several different scales you can use, and they all give slightly different information.
- 2-point scale: yes/no
- 3-point scale: a lot/little/not at all or yes/neutral/no or
- 4-point scale: totally disagree/disagree/agree/ totally agree
- 5-point scale: totally disagree/disagree/no opinion/agree/fully agree or 5 stars (from very dissatisfied to very satisfied)
- 10-point scale: a report mark from 1 to 10
Which scale do you choose?
- With the 2-point scale, respondents must fill in extremes; it is either yes or no. This scale gives a very clear picture, and there is no middle ground. Sometimes respondents find this difficult, as people prefer to keep a low profile or add more nuance. Only use this scale when it's about a straightforward yes or no, like with questions about behavior: you have or have not visited a museum.
- The 3-point scale allows respondents to choose extremes but also to answer neutrally. However, when often responding neutrally, this does not yield much for the survey. Also, use this scale especially when asking about behavior: How often do you drink coffee? Not - sometimes - every day
- With the 4-point scale, there is no room for neutral answers, and respondents have to make a choice. It does allow for some nuance, which respondents like. This scale is used when you ask for an opinion, and you want them to choose.
- Another option when asking for opinion or attitude is the 5-point scale. Respondents like this scale because it allows for nuance and provides a middle ground if they cannot or do not want to choose. You can broaden a scale to 7, but that gives the illusion of more distinction, while you can't interpret that. Since this scale is very frequently used, respondents and readers of your research will understand this scale. The five-point scale allows you to present a range of statements that collectively measure something. This gives you a good idea of the opinion or attitude of respondents about a particular subject. When putting together the theories, you need to pay attention to the validity and coherence of your theories.
- The 10-point scale has a broad division between very bad and excellent and everything in between. Everyone is familiar with report cards; however, the disadvantage is that there are some differences in interpretation in the details. Everyone agrees that up to 5 is insufficient, but what is the difference between an 8 and a 9? In addition, some people never give a 10 because perfect does not exist, while others give a 10 if they think it is very good. So this scale gives respondents a lot of room to add nuance, but it is difficult to define. Only use this scale if you want to compare your score with other scores or with scores from previous measurements. In that case, ask for a general grade and express the different parts on a different scale.
The validity of a study explains the extent to which the questions asked measure what they are supposed to measure. In other words, are the questions asked unambiguous. Could the respondent have interpreted the question differently than you had intended it? And regarding the questionnaire as a whole: do the questions asked in the questionnaire answer the research question.
By challenging a questionnaire, you can find out if it is valid. You can do this by presenting the questionnaire to a test person and having them think out loud while completing it. Another possibility is to present the questionnaire to a test group and have them ask questions as soon as a question is unclear. It is essential that your test persons/group resemble your research population. So if you want to present the questionnaire to young people aged 15 to 18, your test persons/group should consist of young people aged 15 to 18.
After this test, especially with a test group, analyze the answers and ask for advice from a fellow researcher. Are the answers consistent? Is the logic within the questionnaire correct? Are the results consistent with similar studies?
It is more important to test, adapt, and retest with newly developed research instruments. Especially if you want to measure more abstract concepts such as attitude or development, extensive testing is needed to get a valid questionnaire.
When using an existing questionnaire, you should take a moment to see if it has already been tested for comprehension and consistency.
In addition to validity, the concept of reliability is often discussed when conducting research. Want to know more about this? Also read my blog about reliability.