Interviews and questionnaires
How do I collect my own data?
Collecting your own empirical data through interviews and questionnaires can add significant value to your assignment. On this page, you can learn some tips on how to methodically and practically plan and conduct interviews and questionnaire surveys, so you can avoid the biggest pitfalls and gather quality data for your academic assignment.
Qualitative and quantitative methods
Which methods should I use?
Qualitative methods
Quantitative methods provide quantifiable data—that is, data measured in units that can be counted, measured, or weighed, and processed statistically. Also referred to as "hard data".
These methods are called descriptive—as they are effective for describing the scope or prevalence of an issue—and with quantitative methods, you can reach more general conclusions, for example about a population group, as your data set will typically include far more subjects than qualitative methods.
For this reason, representativeness is central to quantitative methods, as the ultimate goal is to generalize and make statements about a larger group than the one studied. Therefore, the studied group must be representative of the total population.
Quantitative methods:
- Hard data: numbers, answers, or facts
- Descriptive
- Representative
- Overview
- Closed questions
- Examples: questionnaires and statistics
Quantitative methods
Qualitative methods encompass all other methods where data cannot be quantified in measurable units. Also referred to as "soft data".
In qualitative methods, response categories are not known in advance, so they are more open—or exploratory—in nature. This allows for greater exploration of issues, as, for example, a conversation can evolve along the way and open up issues in a significantly different way than a questionnaire can.
The goal is not to make general statements about a population group and achieve representativeness—but rather to investigate the close and subjective.
Qualitative methods:
- Soft data: text, images, video, etc.
- Exploratory
- Life-oriented
- Depth
- Open-ended questions
- Examples: interviews, focus groups, and observations
Which method should I use?
But how do you decide whether to use quantitative, qualitative, or perhaps mixed data collection for your assignment?
The purpose of data collection is to help you answer your research question. Therefore, the research question is critical to your choice of method.
If, for example, the goal of your assignment is to investigate how often your target group makes vegetarian dinners, a quantitative study might be best suited, as it allows you to make your findings generalizable.
However, if your goal is to investigate what prevents people from making vegetarian food, a qualitative method might be preferable, because you do not initially know the motivations and values involved. An exploratory approach can help unfold the problem field.
It is not an either-or situation: the two types of methods complement each other, as they highlight different aspects.
To conduct a questionnaire survey, you need to have a good understanding of your respondent group in order to define response categories. If your target group is unknown, an interview prior to a questionnaire survey might be a good choice of method. In this way, you can maintain an open and exploratory approach to the problem field in the interview while simultaneously aiming for general insights into your target group in the subsequent questionnaire survey.
Interviews
How do I conduct a good interview?
The most commonly used qualitative method for data collection is interviews.
In interviews, you can delve deeply into a topic and gain insight into an individual's opinions, motivations, and reasoning. In other words, it is the life-oriented aspects being investigated, and the type of data generated is referred to as "soft data." This allows you to take an exploratory approach to a problem by primarily asking open-ended questions and partially letting the informant guide the direction of the conversation.
Interviews can also be used as preparation for a questionnaire survey, especially if it's in an area where you are not an expert yourself. An interview prior to a questionnaire survey will better equip you to ask the right questions.
There are many different types of interviews, such as individual interviews, expert interviews, and focus groups. Regardless of what you choose, it is important to carefully consider who it would make sense to interview, as well as how to identify these people. Perhaps your informants need specific knowledge about a topic, maybe even expert knowledge. Perhaps the target group needs to be defined by a specific interest, education, age, need, or affiliation.
It is up to you to determine this based on the data you need. Your results will be better if you are very clear about who your target group is.
Good interviews, like good questionnaires, require thorough preparation. A significant part of the preparation involves creating a question guide—or interview guide—that serves as a roadmap for the interviewer throughout the interview.
Checklist for interviews
Create a good question guide
- A question guide is a list of the questions/topics you want your respondent to answer. You may prefer to write the questions out fully, while others might prefer only the main topics.
- Create open, semi-structured questions that allow room for dialogue.
- Adjust your questions along the way if you sense that the respondent has understood your question differently than intended.
- Be well-prepared and knowledgeable about the subject area.
- Place the most important questions at the beginning or middle of the interview to ensure you get through them if time runs out.
Align expectations
- Be flexible with time and place
- Send the question guide in advance
- Be transparent about your purpose for the interview
- Be realistic about the time commitment
Prepare thorougly
- Arrive on time and be a good host
- Be prepared
- Give a small token of thanks
- Ensure the technology works
Be "present" during the interview
- Use your body language
- Listen actively
- Use various questioning techniques
Questionnaire surveys
How do I create a good questionnaire survey?
To get off to a good start with questionnaire surveys, here are two videos that can help you avoid common pitfalls and gather better data from your respondents. The first focuses on quantitative data collection, with an emphasis on target groups and selection; the second covers how to formulate good questions.
Part 1: Introduction, target groups, and selection
Tips and tricks for creating a good questionnaire survey.
Learn, among other things, how to incorporate representativeness into your survey design, as well as the considerations you should make regarding data collection.
The above video is in Danish, but English subtitles are available.
Part 2: Questions and response categories
Formulating good questions with the right response categories is essential for creating a successful questionnaire survey.
Watch the video and get started!
The above video is in Danish, but English subtitles are available.
After data collection
What should I do after data collection?
When you have collected data about other people, you should approach it ethically regarding how you use, store, and present the data. You must always ask your informant whether they wish to appear anonymized in your assignment or if you are allowed to use their real name. If individuals or companies can be identified from being mentioned in the interview, strongly consider anonymizing them. If you conduct a questionnaire survey where you collect personal information, you must generally anonymize it—that is, remove names, addresses, etc., before giving others access to it—so the responses cannot be traced back to the respondent.
What conclusions can I draw from my data?
You cannot draw conclusions beyond what your data allows. Every analysis must therefore include a critical assessment of the data you have collected.
To evaluate the collected data, you need to consider it through two concepts: validity and reliability.
Validity (is your data valid and relevant?):
- Can you use the collected data to answer your problem statement?
- Did you ask the right questions, and are you actually getting answers to what you're investigating?
- Are your response categories comprehensive?
Reliability (can you trust the collected data?):
- Are there factors that may have influenced your survey?
- Would you be able to repeat the survey and get the same result?