2. American women
Question: | How often do British university students use Facebook each week? |
Variable: | Weekly Facebook usage |
Group: | British university students |
Question: | How often do male and female British university students upload photos and comment on other users' photos on Facebook each week? |
Variable: | 1. Weekly photo uploads on Facebook 2. Weekly comments on other users? photos on Facebook |
Group: | 1. Male, British university students 2. Female, British university students |
Question: | What are the most important factors that influence the career choices of Australian university students? |
Variable: | Factors influencing career choices |
Group: | Australian university students |
In each of these example descriptive research questions, we are quantifying the variables we are interested in. However, the units that we used to quantify these variables will differ depending on what is being measured. For example, in the questions above, we are interested in frequencies (also known as counts ), such as the number of calories, photos uploaded, or comments on other users? photos. In the case of the final question, What are the most important factors that influence the career choices of Australian university students? , we are interested in the number of times each factor (e.g., salary and benefits, career prospects, physical working conditions, etc.) was ranked on a scale of 1 to 10 (with 1 = least important and 10 = most important). We may then choose to examine this data by presenting the frequencies , as well as using a measure of central tendency and a measure of spread [see the section on Data Analysis to learn more about these and other statistical tests].
However, it is also common when using descriptive research questions to measure percentages and proportions , so we have included some example descriptive research questions below that illustrate this.
Question: | What percentage of American men and women exceed their daily calorific allowance? |
Variable: | Daily calorific intake |
Group: | 1. American men 2. American women |
Question: | What proportion of British male and female university students use the top 5 social networks? |
Variable: | Use of top 5 social networks (i.e. Facebook, MySpace, Twitter, LinkedIn, and Classmates) |
Group: | 1. Male, British university students 2. Female, British university students |
In terms of the first descriptive research question about daily calorific intake , we are not necessarily interested in frequencies , or using a measure of central tendency or measure of spread , but instead want understand what percentage of American men and women exceed their daily calorific allowance . In this respect, this descriptive research question differs from the earlier question that asked: How many calories do American men and women consume per day? Whilst this question simply wants to measure the total number of calories (i.e., the How many calories part that starts the question); in this case, the question aims to measure excess ; that is, what percentage of these two groups (i.e., American men and American women) exceed their daily calorific allowance, which is different for males (around 2500 calories per day) and females (around 2000 calories per day).
If you are performing a piece of descriptive , quantitative research for your dissertation, you are likely to need to set quite a number of descriptive research questions . However, if you are using an experimental or quasi-experimental research design , or a more involved relationship-based research design , you are more likely to use just one or two descriptive research questions as a means to providing background to the topic you are studying, helping to give additional context for comparative research questions and/or relationship-based research questions that follow.
Comparative research questions aim to examine the differences between two or more groups on one or more dependent variables (although often just a single dependent variable). Such questions typically start by asking "What is the difference in?" a particular dependent variable (e.g., daily calorific intake) between two or more groups (e.g., American men and American women). Examples of comparative research questions include:
Question: | What is the difference in the daily calorific intake of American men and women? |
Dependent variable: | Daily calorific intake |
Groups: | 1. American men 2. American women |
Question: | What is the difference in the weekly photo uploads on Facebook between British male and female university students? |
Dependent variable: | Weekly photo uploads on Facebook |
Groups: | 1. Male, British university students 2. Female, British university students |
Question: | What are the differences in usage behaviour on Facebook between British male and female university students? |
Dependent variable: | Usage behaviour on Facebook (e.g. logins, weekly photo uploads, status changes, commenting on other users' photos, app usage, etc.) |
Group: | 1. Male, British university students 2. Female, British university students |
Question: | What are the differences in perceptions towards Internet banking security between adolescents and pensioners? |
Dependent variable: | Perceptions towards Internet banking security |
Groups: | 1. Adolescents 2. Pensioners |
Question: | What are the differences in attitudes towards music piracy when pirated music is freely distributed or purchased? |
Dependent variable: | Attitudes towards music piracy |
Groups: | 1. Freely distributed pirated music 2. Purchased pirated music |
Groups reflect different categories of the independent variable you are measuring (e.g., American men and women = "gender"; Australian undergraduate and graduate students = "educational level"; pirated music that is freely distributed and pirated music that is purchased = "method of illegal music acquisition").
Comparative research questions also differ in terms of their relative complexity , by which we are referring to how many items/measures make up the dependent variable or how many dependent variables are investigated. Indeed, the examples highlight the difference between very simple comparative research questions where the dependent variable involves just a single measure/item (e.g., daily calorific intake) and potentially more complex questions where the dependent variable is made up of multiple items (e.g., Facebook usage behaviour including a wide range of items, such as logins, weekly photo uploads, status changes, etc.); or where each of these items should be written out as dependent variables.
Overall, whilst the dependent variable(s) highlight what you are interested in studying (e.g., attitudes towards music piracy, perceptions towards Internet banking security), comparative research questions are particularly appropriate if your dissertation aims to examine the differences between two or more groups (e.g., men and women, adolescents and pensioners, managers and non-managers, etc.).
Whilst we refer to this type of quantitative research question as a relationship-based research question, the word relationship should be treated simply as a useful way of describing the fact that these types of quantitative research question are interested in the causal relationships , associations , trends and/or interactions amongst two or more variables on one or more groups. We have to be careful when using the word relationship because in statistics, it refers to a particular type of research design, namely experimental research designs where it is possible to measure the cause and effect between two or more variables; that is, it is possible to say that variable A (e.g., study time) was responsible for an increase in variable B (e.g., exam scores). However, at the undergraduate and even master's level, dissertations rarely involve experimental research designs , but rather quasi-experimental and relationship-based research designs [see the section on Quantitative research designs ]. This means that you cannot often find causal relationships between variables, but only associations or trends .
However, when we write a relationship-based research question , we do not have to make this distinction between causal relationships, associations, trends and interactions (i.e., it is just something that you should keep in the back of your mind). Instead, we typically start a relationship-based quantitative research question, "What is the relationship?" , usually followed by the words, "between or amongst" , then list the independent variables (e.g., gender) and dependent variables (e.g., attitudes towards music piracy), "amongst or between" the group(s) you are focusing on. Examples of relationship-based research questions are:
Question: | What is the relationship between gender and attitudes towards music piracy amongst adolescents? |
Dependent variable: | Attitudes towards music piracy |
Independent variable: | Gender |
Group: | Adolescents |
Question: | What is the relationship between study time and exam scores amongst university students? |
Dependent variable: | Exam scores |
Independent variable: | Study time |
Group: | University students |
Question: | What is the relationship amongst career prospects, salary and benefits, and physical working conditions on job satisfaction between managers and non-managers? |
Dependent variable: | Job satisfaction |
Independent variable: | 1. Career prospects 2. Salary and benefits 3. Physical working conditions |
Group: | 1. Managers 2. Non-managers |
As the examples above highlight, relationship-based research questions are appropriate to set when we are interested in the relationship, association, trend, or interaction between one or more dependent (e.g., exam scores) and independent (e.g., study time) variables, whether on one or more groups (e.g., university students).
The quantitative research design that we select subsequently determines whether we look for relationships , associations , trends or interactions . To learn how to structure (i.e., write out) each of these three types of quantitative research question (i.e., descriptive, comparative, relationship-based research questions), see the article: How to structure quantitative research questions .
Formulating a quantitative research question can often be a difficult task. When composing a research question, a researcher needs to determine if they want to describe data, compare differences among groups, assess a relationship, or determine if a set of variables predict another variable. The type of question the researcher asks will help to determine the type of statistical analysis that needs to be conducted. It is also important to consider what specific variables need to be assessed when writing a research question. The researcher must be certain all variables are quantifiable, or measurable. Measuring variables can be as simple as having participants report their age or as involved as having participants answer survey questions that make up a reliable instrument. Some examples of different types of research questions are presented below:
Aligning theoretical framework, gathering articles, synthesizing gaps, articulating a clear methodology and data plan, and writing about the theoretical and practical implications of your research are part of our comprehensive dissertation editing services.
Descriptive:
Describe the teachers’ perceptions of the newly implemented reading assessment program.
The goal of a descriptive research question is to describe the data. The researcher cannot infer any conclusions from this type of analysis; it simply presents data. Descriptive questions do not have corresponding null and alternative hypotheses because the researcher is not making inferences. Descriptive studies can be conducted on categorical or continuous data.
Comparative:
Are there differences in students’ grades by gender (male vs. female)?
Are there differences in job level (entry vs. mid vs. executive) by gender (male vs. female)?
Comparative questions can be assessed using a continuous variable and a categorical grouping variable, as well as with two categorical grouping variables. They type of analysis will vary depending on the types of data.
Relationship:
Is there a relationship between age and fitness level?
Is there a relationship between ice cream sales and temperature at noon?
Questions that assess relationships do not require a definitive independent and dependent variable, but two variables are required; they can be considered variables of interest as opposed to independent and dependent variables. Data used for this type of analysis can be dichotomous, ordinal, or continuous. They type of analysis will vary depending on the types of data.
Predictive:
Do age, gender, and education predict income?
Does a pitcher’s ERA predict the number of wins the team has?
Predictive questions have a definitive independent and dependent variable. Typically, the independent variable should be continuous or dichotomous, but nominal and ordinal variables can be used. When nominal and ordinal variables are used as predictors, they must be dummy coded. Like the independent variable, the dependent variable is typically continuous or dichotomous, but can also be ordinal or nominal. The type of analysis that is appropriate will vary based upon the type of data.
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Part 2: Conceptualizing your research project
Chapter outline.
Content warning: examples in this chapter include references to sexual violence, sexism, substance use disorders, homelessness, domestic violence, the child welfare system, cissexism and heterosexism, and truancy and school discipline.
Learning objectives.
Learners will be able to…
Writing a good research question is an art and a science. It is a science because you have to make sure it is clear, concise, and well-developed. It is an art because often your language needs “wordsmithing” to perfect and clarify the meaning. This is an exciting part of the research process; however, it can also be one of the most stressful.
Creating a good research question begins by identifying a topic you are interested in studying. At this point, you already have a working question. You’ve been applying it to the exercises in each chapter, and after reading more about your topic in the scholarly literature, you’ve probably gone back and revised your working question a few times. We’re going to continue that process in more detail in this chapter. Keep in mind that writing research questions is an iterative process, with revisions happening week after week until you are ready to start your project.
When it comes to research questions, social science is best equipped to answer empirical questions —those that can be answered by real experience in the real world—as opposed to ethical questions —questions about which people have moral opinions and that may not be answerable in reference to the real world. While social workers have explicit ethical obligations (e.g., service, social justice), research projects ask empirical questions to help actualize and support the work of upholding those ethical principles.
In order to help you better understand the difference between ethical and empirical questions, let’s consider a topic about which people have moral opinions. How about SpongeBob SquarePants? [1] In early 2005, members of the conservative Christian group Focus on the Family (2005) [2] denounced this seemingly innocuous cartoon character as “morally offensive” because they perceived his character to be one that promotes a “pro-gay agenda.” Focus on the Family supported their claim that SpongeBob is immoral by citing his appearance in a children’s video designed to promote tolerance of all family forms (BBC News, 2005). [3] They also cited SpongeBob’s regular hand-holding with his male sidekick Patrick as further evidence of his immorality.
So, can we now conclude that SpongeBob SquarePants is immoral? Not so fast. While your mother or a newspaper or television reporter may provide an answer, a social science researcher cannot. Questions of morality are ethical, not empirical. Of course, this doesn’t mean that social science researchers cannot study opinions about or social meanings surrounding SpongeBob SquarePants (Carter, 2010). [4] We study humans after all, and as you will discover in the following chapters of this textbook, we are trained to utilize a variety of scientific data-collection techniques to understand patterns of human beliefs and behaviors. Using these techniques, we could find out how many people in the United States find SpongeBob morally reprehensible, but we could never learn, empirically, whether SpongeBob is in fact morally reprehensible.
Let’s consider an example from a recent MSW research class I taught. A student group wanted to research the penalties for sexual assault. Their original research question was: “How can prison sentences for sexual assault be so much lower than the penalty for drug possession?” Outside of the research context, that is a darn good question! It speaks to how the War on Drugs and the patriarchy have distorted the criminal justice system towards policing of drug crimes over gender-based violence.
Unfortunately, it is an ethical question, not an empirical one. To answer that question, you would have to draw on philosophy and morality, answering what it is about human nature and society that allows such unjust outcomes. However, you could not answer that question by gathering data about people in the real world. If I asked people that question, they would likely give me their opinions about drugs, gender-based violence, and the criminal justice system. But I wouldn’t get the real answer about why our society tolerates such an imbalance in punishment.
As the students worked on the project through the semester, they continued to focus on the topic of sexual assault in the criminal justice system. Their research question became more empirical because they read more empirical articles about their topic. One option that they considered was to evaluate intervention programs for perpetrators of sexual assault to see if they reduced the likelihood of committing sexual assault again. Another option they considered was seeing if counties or states with higher than average jail sentences for sexual assault perpetrators had lower rates of re-offense for sexual assault. These projects addressed the ethical question of punishing perpetrators of sexual violence but did so in a way that gathered and analyzed empirical real-world data. Our job as social work researchers is to gather social facts about social work issues, not to judge or determine morality.
Now that you’ve made sure your working question is empirical, you need to revise that working question into a formal research question. So, what makes a good research question? First, it is generally written in the form of a question. To say that your research question is “the opioid epidemic” or “animal assisted therapy” or “oppression” would not be correct. You need to frame your topic as a question, not a statement. A good research question is also one that is well-focused. A well-focused question helps you tune out irrelevant information and not try to answer everything about the world all at once. You could be the most eloquent writer in your class, or even in the world, but if the research question about which you are writing is unclear, your work will ultimately lack direction.
In addition to being written in the form of a question and being well-focused, a good research question is one that cannot be answered with a simple yes or no. For example, if your interest is in gender norms, you could ask, “Does gender affect a person’s performance of household tasks?” but you will have nothing left to say once you discover your yes or no answer. Instead, why not ask, about the relationship between gender and household tasks. Alternatively, maybe we are interested in how or to what extent gender affects a person’s contributions to housework in a marriage? By tweaking your question in this small way, you suddenly have a much more fascinating question and more to say as you attempt to answer it.
A good research question should also have more than one plausible answer. In the example above, the student who studied the relationship between gender and household tasks had a specific interest in the impact of gender, but she also knew that preferences might be impacted by other factors. For example, she knew from her own experience that her more traditional and socially conservative friends were more likely to see household tasks as part of the female domain, and were less likely to expect their male partners to contribute to those tasks. Thinking through the possible relationships between gender, culture, and household tasks led that student to realize that there were many plausible answers to her questions about how gender affects a person’s contribution to household tasks. Because gender doesn’t exist in a vacuum, she wisely felt that she needed to consider other characteristics that work together with gender to shape people’s behaviors, likes, and dislikes. By doing this, the student considered the third feature of a good research question–she thought about relationships between several concepts. While she began with an interest in a single concept—household tasks—by asking herself what other concepts (such as gender or political orientation) might be related to her original interest, she was able to form a question that considered the relationships among those concepts.
This student had one final component to consider. Social work research questions must contain a target population. Her study would be very different if she were to conduct it on older adults or immigrants who just arrived in a new country. The target population is the group of people whose needs your study addresses. Maybe the student noticed issues with household tasks as part of her social work practice with first-generation immigrants, and so she made it her target population. Maybe she wants to address the needs of another community. Whatever the case, the target population should be chosen while keeping in mind social work’s responsibility to work on behalf of marginalized and oppressed groups.
In sum, a good research question generally has the following features:
Okay, it’s time to write out your first draft of a research question.
Brainstorm whether your research question might be better suited to quantitative or qualitative methods.
The type of research you are conducting will impact the research question that you ask. Probably the easiest questions to think of are quantitative descriptive questions. For example, “What is the average student debt load of MSW students?” is a descriptive question—and an important one. We aren’t trying to build a causal relationship here. We’re simply trying to describe how much debt MSW students carry. Quantitative descriptive questions like this one are helpful in social work practice as part of community scans, in which human service agencies survey the various needs of the community they serve. If the scan reveals that the community requires more services related to housing, child care, or day treatment for people with disabilities, a nonprofit office can use the community scan to create new programs that meet a defined community need.
Quantitative descriptive questions will often ask for percentage, count the number of instances of a phenomenon, or determine an average. Descriptive questions may only include one variable, such as ours about student debt load, or they may include multiple variables. Because these are descriptive questions, our purpose is not to investigate causal relationships between variables. To do that, we need to use a quantitative explanatory question.
Most studies you read in the academic literature will be quantitative and explanatory. Why is that? If you recall from Chapter 2 , explanatory research tries to build nomothetic causal relationships. They are generalizable across space and time, so they are applicable to a wide audience. The editorial board of a journal wants to make sure their content will be useful to as many people as possible, so it’s not surprising that quantitative research dominates the academic literature.
Structurally, quantitative explanatory questions must contain an independent variable and dependent variable. Questions should ask about the relationship between these variables. The standard format I was taught in graduate school for an explanatory quantitative research question is: “What is the relationship between [independent variable] and [dependent variable] for [target population]?” You should play with the wording for your research question, revising that standard format to match what you really want to know about your topic.
Let’s take a look at a few more examples of possible research questions and consider the relative strengths and weaknesses of each. Table 9.1 does just that. While reading the table, keep in mind that I have only noted what I view to be the most relevant strengths and weaknesses of each question. Certainly each question may have additional strengths and weaknesses not noted in the table. Each of these questions is drawn from student projects in my research methods classes and reflects the work of many students on their research question over many weeks.
What are the internal and external effects/problems associated with children witnessing domestic violence? | Written as a question | Not clearly focused | How does witnessing domestic violence impact a child’s romantic relationships in adulthood? |
Considers relationships among multiple concepts | Not specific and clear about the concepts it addresses | ||
Contains a population | |||
What causes foster children who are transitioning to adulthood to become homeless, jobless, pregnant, unhealthy, etc.? | Considers relationships among multiple concepts | Concepts are not specific and clear | What is the relationship between sexual orientation or gender identity and homelessness for late adolescents in foster care? |
Contains a population | |||
Not written as a yes/no question | |||
How does income inequality predict ambivalence in the Stereo Content Model using major U.S. cities as target populations? | Written as a question | Unclear wording | How does income inequality affect ambivalence in high-density urban areas? |
Considers relationships among multiple concepts | Population is unclear | ||
Why are mental health rates higher in white foster children than African Americans and other races? | Written as a question | Concepts are not clear | How does race impact rates of mental health diagnosis for children in foster care? |
Not written as a yes/no question | Does not contain a target population |
A good research question should also be specific and clear about the concepts it addresses. A student investigating gender and household tasks knows what they mean by “household tasks.” You likely also have an impression of what “household tasks” means. But are your definition and the student’s definition the same? A participant in their study may think that managing finances and performing home maintenance are household tasks, but the researcher may be interested in other tasks like childcare or cleaning. The only way to ensure your study stays focused and clear is to be specific about what you mean by a concept. The student in our example could pick a specific household task that was interesting to them or that the literature indicated was important—for example, childcare. Or, the student could have a broader view of household tasks, one that encompasses childcare, food preparation, financial management, home repair, and care for relatives. Any option is probably okay, as long as the researcher is clear on what they mean by “household tasks.” Clarifying these distinctions is important as we look ahead to specifying how your variables will be measured in Chapter 11 .
Table 9.2 contains some “watch words” that indicate you may need to be more specific about the concepts in your research question.
Factors, Causes, Effects, Outcomes | What causes or effects are you interested in? What causes and effects are important, based on the literature in your topic area? Try to choose one or a handful you consider to be the most important. |
Effective, Effectiveness, Useful, Efficient | Effective at doing what? Effectiveness is meaningless on its own. What outcome should the program or intervention have? Reduced symptoms of a mental health issue? Better socialization? |
Etc., and so forth | Don’t assume that your reader understands what you mean by “and so forth.” Remember that focusing on two or a small handful concepts is necessary. Your study cannot address everything about a social problem, though the results will likely have implications on other aspects of the social world. |
It can be challenging to be this specific in social work research, particularly when you are just starting out your project and still reading the literature. If you’ve only read one or two articles on your topic, it can be hard to know what you are interested in studying. Broad questions like “What are the causes of chronic homelessness, and what can be done to prevent it?” are common at the beginning stages of a research project as working questions. However, moving from working questions to research questions in your research proposal requires that you examine the literature on the topic and refine your question over time to be more specific and clear. Perhaps you want to study the effect of a specific anti-homelessness program that you found in the literature. Maybe there is a particular model to fighting homelessness, like Housing First or transitional housing, that you want to investigate further. You may want to focus on a potential cause of homelessness such as LGBTQ+ discrimination that you find interesting or relevant to your practice. As you can see, the possibilities for making your question more specific are almost infinite.
In exploratory research, the researcher doesn’t quite know the lay of the land yet. If someone is proposing to conduct an exploratory quantitative project, the watch words highlighted in Table 9.2 are not problematic at all. In fact, questions such as “What factors influence the removal of children in child welfare cases?” are good because they will explore a variety of factors or causes. In this question, the independent variable is less clearly written, but the dependent variable, family preservation outcomes, is quite clearly written. The inverse can also be true. If we were to ask, “What outcomes are associated with family preservation services in child welfare?”, we would have a clear independent variable, family preservation services, but an unclear dependent variable, outcomes. Because we are only conducting exploratory research on a topic, we may not have an idea of what concepts may comprise our “outcomes” or “factors.” Only after interacting with our participants will we be able to understand which concepts are important.
Remember that exploratory research is appropriate only when the researcher does not know much about topic because there is very little scholarly research. In our examples above, there is extensive literature on the outcomes in family reunification programs and risk factors for child removal in child welfare. Make sure you’ve done a thorough literature review to ensure there is little relevant research to guide you towards a more explanatory question.
Preferably, you should be creating an explanatory research question for quantitative research.
Qualitative research questions differ from quantitative research questions. Because qualitative research questions seek to explore or describe phenomena, not provide a neat nomothetic explanation, they are often more general and openly worded. They may include only one concept, though many include more than one. Instead of asking how one variable causes changes in another, we are instead trying to understand the experiences , understandings , and meanings that people have about the concepts in our research question. These keywords often make an appearance in qualitative research questions.
Let’s work through an example from our last section. In Table 9.1, a student asked, “What is the relationship between sexual orientation or gender identity and homelessness for late adolescents in foster care?” In this question, it is pretty clear that the student believes that adolescents in foster care who identify as LGBTQ+ may be at greater risk for homelessness. This is a nomothetic causal relationship—LGBTQ+ status causes changes in homelessness.
However, what if the student were less interested in predicting homelessness based on LGBTQ+ status and more interested in understanding the stories of foster care youth who identify as LGBTQ+ and may be at risk for homelessness? In that case, the researcher would be building an idiographic causal explanation . The youths whom the researcher interviews may share stories of how their foster families, caseworkers, and others treated them. They may share stories about how they thought of their own sexuality or gender identity and how it changed over time. They may have different ideas about what it means to transition out of foster care.
Because qualitative questions usually center on idiographic causal relationships, they look different than quantitative questions. Table 9.3 below takes the final research questions from Table 9.1 and adapts them for qualitative research. The guidelines for research questions previously described in this chapter still apply, but there are some new elements to qualitative research questions that are not present in quantitative questions.
How does witnessing domestic violence impact a child’s romantic relationships in adulthood? | How do people who witness domestic violence understand its effects on their current relationships? |
What is the relationship between sexual orientation or gender identity and homelessness for late adolescents in foster care? | What is the experience of identifying as LGBTQ+ in the foster care system? |
How does income inequality affect ambivalence in high-density urban areas? | What does racial ambivalence mean to residents of an urban neighborhood with high income inequality? |
How does race impact rates of mental health diagnosis for children in foster care? | How do African-Americans experience seeking help for mental health concerns? |
Qualitative research questions have one final feature that distinguishes them from quantitative research questions: they can change over the course of a study. Qualitative research is a reflexive process, one in which the researcher adapts their approach based on what participants say and do. The researcher must constantly evaluate whether their question is important and relevant to the participants. As the researcher gains information from participants, it is normal for the focus of the inquiry to shift.
For example, a qualitative researcher may want to study how a new truancy rule impacts youth at risk of expulsion. However, after interviewing some of the youth in their community, a researcher might find that the rule is actually irrelevant to their behavior and thoughts. Instead, their participants will direct the discussion to their frustration with the school administrators or the lack of job opportunities in the area. This is a natural part of qualitative research, and it is normal for research questions and hypothesis to evolve based on information gleaned from participants.
However, this reflexivity and openness unacceptable in quantitative research for good reasons. Researchers using quantitative methods are testing a hypothesis, and if they could revise that hypothesis to match what they found, they could never be wrong! Indeed, an important component of open science and reproducability is the preregistration of a researcher’s hypotheses and data analysis plan in a central repository that can be verified and replicated by reviewers and other researchers. This interactive graphic from 538 shows how an unscrupulous research could come up with a hypothesis and theoretical explanation after collecting data by hunting for a combination of factors that results in a statistically significant relationship. This is an excellent example of how the positivist assumptions behind quantitative research and intepretivist assumptions behind qualitative research result in different approaches to social science.
As you are getting ready to finalize your research question and move into designing your research study, it is important to check whether your research question is feasible for you to answer and what importance your results will have in the community, among your participants, and in the scientific literature
Key questions to consider when evaluating your question’s feasibility include:
Key questions to consider when evaluating the importance of your question include:
This chapter described how to create a good quantitative and qualitative research question. In Parts 3 and 4 of this textbook, we will detail some of the basic designs like surveys and interviews that social scientists use to answer their research questions. But which design should you choose?
As with most things, it all depends on your research question. If your research question involves, for example, testing a new intervention, you will likely want to use an experimental design. On the other hand, if you want to know the lived experience of people in a public housing building, you probably want to use an interview or focus group design.
We will learn more about each one of these designs in the remainder of this textbook. We will also learn about using data that already exists, studying an individual client inside clinical practice, and evaluating programs, which are other examples of designs. Below is a list of designs we will cover in this textbook:
The design of your research study determines what you and your participants will do. In an experiment, for example, the researcher will introduce a stimulus or treatment to participants and measure their responses. In contrast, a content analysis may not have participants at all, and the researcher may simply read the marketing materials for a corporation or look at a politician’s speeches to conduct the data analysis for the study.
I imagine that a content analysis probably seems easier to accomplish than an experiment. However, as a researcher, you have to choose a research design that makes sense for your question and that is feasible to complete with the resources you have. All research projects require some resources to accomplish. Make sure your design is one you can carry out with the resources (time, money, staff, etc.) that you have.
There are so many different designs that exist in the social science literature that it would be impossible to include them all in this textbook. The purpose of the subsequent chapters is to help you understand the basic designs upon which these more advanced designs are built. As you learn more about research design, you will likely find yourself revising your research question to make sure it fits with the design. At the same time, your research question as it exists now should influence the design you end up choosing. There is no set order in which these should happen. Instead, your research project should be guided by whether you can feasibly carry it out and contribute new and important knowledge to the world.
research questions that can be answered by systematically observing the real world
unsuitable research questions which are not answerable by systematic observation of the real world but instead rely on moral or philosophical opinions
the group of people whose needs your study addresses
attempts to explain or describe your phenomenon exhaustively, based on the subjective understandings of your participants
"Assuming that the null hypothesis is true and the study is repeated an infinite number times by drawing random samples from the same populations(s), less than 5% of these results will be more extreme than the current result" (Cassidy et al., 2019, p. 233).
whether you can practically and ethically complete the research project you propose
the impact your study will have on participants, communities, scientific knowledge, and social justice
Graduate research methods in social work Copyright © 2021 by Matthew DeCarlo, Cory Cummings, Kate Agnelli is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.
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The choice of research topic is a vital step in the process of any academic task completion. Whether you’re working on a small essay or a large dissertation, your topic will make it fail or fly. The best way to cope with the naming task and proceed to the writing part is to use our free online tool for title generation. Its benefits are indisputable.
Using our research question generator tool, you won’t need to crack your brains over this part of the writing assignment anymore. All you need to do is:
The results will be preliminary; you should use them as an initial reference point and refine them further for a workable, correctly formulated research question.
Depending on your type of study (quantitative vs. qualitative), you might need to formulate different research question types. For instance, a typical quantitative research project would need a quantitative research question, which can be created with the following formula:
Variable(s) + object that possesses that variable + socio-demographic characteristics
You can choose among three quantitative research question types: descriptive, comparative, and relationship-based. Let's consider each type in more detail to clarify the practical side of question formulation.
Descriptive
As its name suggests, a descriptive research question inquires about the number, frequency, or intensity of something and aims to describe a quantitative issue. Some examples include:
Comparative
Comparative research questions presuppose comparing and contrasting things within a research study. You should pick two or more objects, select a criterion for comparison, and discuss it in detail. Here are good examples:
Relationship-based
Relationship-based research is a bit more complex, so you'll need extra work to formulate a good research question. Here, you should single out:
Let’s illustrate how it works:
In a nutshell, a research question is the one you set to answer by performing a specific academic study. Thus, for instance, if your research question is, “How did global warming affect bird migration in California?," you will study bird migration patterns concerning global warming dynamics.
You should think about the population affected by your topic, the specific aspect of your concern, and the timing/historical period you want to study. It’s also necessary to specify the location – a specific country, company, industry sector, the whole world, etc.
A great, effective research question should answer the "who, what, when, where" questions. In other words, you should define the subject of interest, the issue of your concern related to that subject, the timeframe, and the location of your study.
If you don’t know how to write a compelling research question, use our automated tool to complete the task in seconds. You only need to insert your subject of interest, and smart algorithms will do the rest, presenting a set of workable, interesting question suggestions.
Thanks to survey research, we can learn what a group of people thinks and feels. It’s useful for making good decisions.
In this article, we’ll show you how to do survey research step-by-step. You’ll also learn why survey research is important and who can benefit from it.
Let’s get started:
Survey research is all about gathering data from a specific group to get insights into different topics. It’s a go-to method for understanding opinions, behaviors, and traits in a target population. You’ll see it used in many fields like market research, public health, and social sciences.
This approach is popular because professionals can figure out what people think, how they act, and what makes them tick. Whether you’re trying to gauge customer satisfaction , public health trends, or social attitudes, surveys are a handy tool.
It’s a straightforward way to get the information you need to make decisions and understand your audience better.
Survey research is unique because it’s systematic . Researchers use popular methods for survey research like online, phone, and in-person surveys to reach their audience.
A good survey has a mix of question types, including open-ended ones, to get a wide range of answers.
Surveys can focus on the whole population or just a sample. Getting a representative sample is key for accurate results. Researchers then analyze the data to find useful insights. This helps them understand trends and behaviors in the group they studied.
Survey research has many perks for businesses and researchers. One big advantage is its flexibility in how surveys are done. From phone surveys to mobile surveys, and mixed-mode surveys that combine different techniques, there are many ways to reach people and gather data effectively.
Businesses can get a competitive edge with survey research. For instance, panel surveys collect data from a specific group over time, helping track changes in consumer behavior and preferences. This ongoing data collection can inform product development, marketing strategies, and customer service improvements.
Researchers also gain from survey research’s ability to provide comprehensive data. Census surveys aim to gather info from the entire population and are invaluable for large-scale studies. Survey research centers, like those at universities or places like Sage Publications, often use these methods for extensive projects that add to academic knowledge and have practical applications.
Conducting survey research is easier than it sounds.
Check out our detailed step-by-step guide describing each step in an easily understandable format:
Before starting your survey research, be sure to pinpoint the survey’s purpose. Are you looking to gather consumer feedback , understand employee satisfaction, or explore market trends? Clarifying the objective helps focus the entire project.
Next, identify the key characteristics of your target audience. Who are you trying to reach? Age, gender, location, and occupation can all be relevant factors. Knowing your audience is great for tailoring your questions and survey approach.
Surveys come in various forms, each suitable for different research needs. Some common survey methods include online surveys, telephone surveys, postal surveys, and person surveys.
Census surveys aim to gather data from the entire population, while sample surveys focus on a subset. Each has its pros and cons, depending on the research scope and resources.
Online surveys : convenient and cost-effective for reaching a large audience.
Telephone surveys : useful for detailed responses but can be time-consuming.
Postal surveys : traditional method, still valuable for certain demographics.
Person surveys : face-to-face interaction can yield in-depth insights.
Mobile surveys : great for quick feedback on the go.
Mixed-mode surveys : combining different methods can improve response rates and data quality.
Well-crafted questions are the backbone of survey research. Aim for clarity and brevity to avoid confusing respondents.
Incorporate both open-ended questions for detailed feedback and closed-ended questions for quantitative analysis. This mix lets you cover different aspects of the research topic.
Avoid leading questions that can bias survey responses. Group similar questions to maintain a logical flow. Pre-test the survey with a small group to catch any issues.
Determine if you need data from the entire population or a specific target group. This decision influences your sampling strategy.
A representative sample reflects the broader population. Avoiding bias in survey research is key to obtaining valid results.
Random sampling : each individual has an equal chance of being selected.
Stratified sampling : divides the population into subgroups and samples each proportionally.
Make surveys user-friendly with a clean layout and easy navigation. Personalize invitations to boost participation.
Use a script for phone surveys to maintain consistency. For postal surveys, include a return envelope to encourage responses.
Survey software can streamline the data collection process, track response rates, and manage survey distribution.
Follow up with non-respondents to improve response rates. Use multiple reminders if necessary.
Data analysis should focus on identifying trends and patterns. Software tools can assist in visualizing the data and spotting correlations.
Use charts, graphs, and tables to present data visually. This makes complex information more digestible.
Visual aids help highlight key findings and support your conclusions.
Summarize the findings, highlight applications of survey research, and suggest practical steps based on the data.
Check this out: online survey examples and templates
Survey research comes in two flavors: qualitative and quantitative .
Qualitative research digs into the reasons and motivations behind what people do. It uses open-ended questions, letting respondents share detailed, narrative responses. This approach gives deep, nuanced insights but usually involves a smaller group of people.
Quantitative research, on the other hand, deals with numbers. It uses structured surveys with closed-ended questions to collect data that can be crunched statistically. This method works with larger groups and provides generalizable results. It’s great for measuring how common certain behaviors or opinions are in a population.
Survey research is important because it lets us see the complexities of human behavior.
As a result of collecting and analyzing responses from a target population, researchers can uncover patterns, preferences, and motivations.
This understanding is essential for fields ranging from marketing to public policy, as it shapes strategies and decisions.
Survey research is a great way to get actionable insights. By gathering data directly from people, researchers can make decisions based on real-world information.
For example, using quantitative methods, businesses can spot market trends, customer preferences, and areas for improvement. These insights aren’t just theoretical – they lead to practical steps that can improve products, services, and strategies.
Market research firms live and breathe data. They use survey research to understand consumer behavior and preferences.
By gathering insights through various methods, such as online surveys and phone surveys, these firms help businesses tailor their products and marketing strategies.
You get to know your customers better, making it easier to meet their needs and stay ahead of the competition.
Schools, colleges, and universities rely on survey research to improve educational outcomes. They collect feedback from students, parents, and staff to identify areas for improvement.
Whether it’s course content, teaching methods, or campus facilities, surveys let educational institutions enhance the learning experience.
Plus, they can use the data to secure funding and support from stakeholders.
Healthcare organizations benefit from survey research too. Collecting patient feedback lets them improve care quality and patient satisfaction.
Surveys identify issues in service delivery, patient safety, and overall healthcare experience.
Whether it’s a hospital, clinic, or a public health department, using survey research leads to better healthcare outcomes for everyone involved.
Government agencies use surveys to gather public opinion on various policies and programs. They aim to understand the needs and preferences of citizens to make informed decisions.
From local governments to federal agencies, survey research aids in crafting policies that truly reflect public interest.
It’s a way for you to have your voice heard on matters that affect your community and daily life.
Non-profits leverage survey research to evaluate the impact of their programs and services.
They gather insights from beneficiaries, donors, and volunteers to make their efforts align with their mission. Whether it’s a charity, foundation, or advocacy group, surveys help non-profits maximize their impact and make a difference.
It’s all about understanding how to serve better and drive positive change in society.
If you’re looking to conduct your first survey research, SurveyLab is here to save the day with comprehensive survey services.
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Published by Alvin Nicolas at August 19th, 2024 , Revised On August 19, 2024
Before you start your research, the first thing you need to identify is the research method . Depending on different factors, you will either choose a quantitative or qualitative study.
Qualitative research is a great tool that helps understand the depth and richness of human opinions and experiences. Unlike quantitative research, which focuses on numerical data , qualitative research allows exploring and interpreting the experiences of the subject. Questionnaires, although mostly associated with quantitative research, can also be a valuable instrument in qualitative studies. Let’s explore what qualitative research questionnaires are and how you can create one.
Qualitative research questionnaires are a structured or semi-structured set of questions designed to gather detailed, open-ended participant responses. It allows you to uncover underlying reasons and opinions and provides insights into a particular phenomenon.
While quantitative questionnaires often have closed-ended questions and numerical responses, a qualitative questionnaire encourages participants to express themselves freely. Before you design your questionnaire, you should know exactly what you need so you can keep your questions specific enough for the participants to understand.
For example:
Now that you are familiar with what qualitative research questions are, let’s look at the different types of questions you can use in your survey .
These are used to explore and describe a phenomenon in detail. It helps answer the “what” part of the research, and the questions are mostly foundational.
Example: How do students experience online learning?
This type allows you to compare and contrast different groups or situations. You can explore the differences and similarities to highlight the impact of specific variables.
Example: How do the study habits of first-year and fourth-year university students differ?
These questions help you understand the meanings people attach to experiences or phenomena by answering the “how” and “why”.
Example: What does “success” mean to entrepreneurs?
You can use these to assess the quality or value of something. These allow you to understand the outcomes of various situations.
Example: How effective is the new customer service training program?
To understand how something happens or develops over time, researchers often use process-oriented questions.
Example: How do individuals develop their career goals?
These allow you to discover new perspectives on a topic. However, you have to be careful that there must be no preconceived notions or research biases to it.
Example: What are the emerging trends in the mobile gaming industry?
For your study to be successful, it is important to consider designing a questionnaire for qualitative research critically, as it will shape your research and data collection. Here is an easy guide to writing your qualitative research questions perfectly.
Many students start their research without clear goals, and they have to make substantial changes to their study in the middle of the research. This wastes time and resources.
Before you start crafting your questions, it is important to know your research objectives. You should know what you aim to discover through your research, or what specific knowledge gaps you are going to fill. With the help of a well-defined research focus, you can develop relevant and meaningful information.
There are mostly open-ended questionnaires in qualitative research. They begin with words like “how,” “what,” and “why.” However, the structure of your research questions depends on your research design . You have to consider using broad, overarching questions to explore the main research focus, and then add some specific probes to further research the particular aspects of the topic.
The more clear and concise your research questions are, the more effective and free from ambiguity they will be. Do not use complex terminology that might confuse participants. Try using simple and direct language that accurately conveys your intended meaning.
Here is a table to explain the wrong and right ways of writing your qualitative research questions.
How would you characterise your attitude towards e-commerce transactions? | How do you feel about online shopping? |
Could you elucidate on the obstacles encountered in your professional role? | What challenges do you face in your job? |
What is your evaluation of the innovative product aesthetic? | What do you think about the new product design? |
Can you elaborate on the influence of social networking platforms on your interpersonal connections? | How has social media impacted your relationships? |
Once you have developed some questions, check if they align with your research objectives. You must ensure that each question contributes to your overall research questions. After this, you can eliminate any questions that do not serve a clear purpose in your study.
While it is tempting to cover multiple aspects of a topic in one question, it is best to focus on a single theme per question. This helps to elicit focused responses from participants. Moreover, you have to avoid combining unrelated concepts into a single question.
If your main research question is complicated, you can create sub-questions with a “ladder structure”. These allow you to understand the attributes, consequences, and core values of your research. For example, let’s say your main broad research question is:
The intermediate questions may be:
It is important to consider your research objectives, target population, resources and needed depth of research when selecting a survey method. The main types of qualitative surveys are discussed below.
Face-to-face surveys involve direct interaction between the researcher and the participant. This method allows observers to capture non-verbal cues, body language, and facial expressions, and helps adapt questions based on participant responses. They also let you clarify any misunderstandings. Moreover, there is a higher response rate because of personal interaction.
Example: A researcher conducting a study on consumer experiences with a new product might visit participants’ homes to conduct a detailed interview.
These type of qualitative research survey questionnaires provide a less intrusive method for collecting qualitative data. The benefits of telephone surveys include, that it allows you to collect data from a wider population. Moreover, it is generally less expensive than face-to-face interviews and interviews can be conducted efficiently.
Example: A market research firm might conduct telephone surveys to understand customer satisfaction with a telecommunication service.
Online survey questionnaires are a convenient and cost-effective way to gather qualitative data. You can reach a wide audience quickly, and participants may feel more comfortable sharing sensitive information because of anonymity. Additionally, there are no travel or printing expenses.
Example: A university might use online surveys to explore students’ perceptions of online learning experiences.
Questionnaires are undoubtedly a great data collection tool. However, it comes with its fair share of advantages and disadvantages. Let’s discuss the benefits of questionnaires in qualitative research and their cons as well.
Can be inexpensive to distribute and collect | Can suffer from low response rates |
Allow researchers to reach a wide audience | There is a lack of control over the environment |
Consistent across participants | Once the questionnaire is distributed, it cannot be modified |
Anonymity helps make participants feel more comfortable | Participants may not fully understand questions |
Open-ended questions provide rich, detailed responses | Open-ended questions may not capture the right answers |
Here is a concise qualitative research questionnaire sample for research papers to give you a better idea of its format and how it is presented.
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A survey research questionnaire can have both qualitative and quantitative questions. The qualitative questions are mostly open-ended, and quantitative questions take the form of yes/no, or Likert scale rating.
Yes, survey questionnaires can be used in qualitative research for data collection. However, instead of a Likert scale or rating, you can post open-ended questions to your respondents. The participants can provide detailed responses to the questions asked.
In qualitative research, questionnaires allow you to collect qualitative data. The open-ended and unstructured questions help respondents present their ideas freely and provide insights.
Content analysis is used to identify specific words, patterns, concepts, themes, phrases, or sentences within the content in the recorded communication.
In correlational research, a researcher measures the relationship between two or more variables or sets of scores without having control over the variables.
Inductive and deductive reasoning takes into account assumptions and incidents. Here is all you need to know about inductive vs deductive reasoning.
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Once you've read our guide on how to write a research question, you can use these examples to craft your own. ... Note that the design of your research question can depend on what method you are pursuing. Here are a few options for qualitative, quantitative, and statistical research questions.
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Framing the research question is the first step in any research project, and you can learn how to write a research question that is focused, achievable, and answerable! Check this detailed article to know what a research question is, the different types, and a step-by-step process to formulate effective research questions, with examples.
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Read the complete guide to writing a research question, including the characteristics of a good research question, examples, and steps to create strong research questions.
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Why is a research question essential to the research process? Research questions help writers focus their research by providing a path through the research and writing process. The specificity of a well-developed research question helps writers avoid the "all-about" paper and work toward supporting a specific, arguable thesis.
It provides any reader procedures in making research questions that are cursorily discussed in graduate school, especially during thesis writing. The author hopes that this module will facilitate ...
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Research Questions: Types & Examples Depending on your type of study (quantitative vs. qualitative), you might need to formulate different research question types. For instance, a typical quantitative research project would need a quantitative research question, which can be created with the following formula:
Quantitative research, on the other hand, deals with numbers. It uses structured surveys with closed-ended questions to collect data that can be crunched statistically. This method works with larger groups and provides generalizable results. It's great for measuring how common certain behaviors or opinions are in a population.
Questionnaires, although mostly associated with quantitative research, can also be a valuable instrument in qualitative studies. Let's explore what qualitative research questionnaires are and how you can create one. ... Here is an easy guide to writing your qualitative research questions perfectly. Tip 1: Understand Your Research Goals.
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