Variables in Your D.Min. Research

By this point in the series, you’ve identified a ministry problem, refined it into a research question, and begun thinking about an intervention. You know what you’re going to do. Now comes a question that students often underestimate: What, exactly, are you going to measure?

The answer to that question lives in the concept of variables. This article introduces you to variable thinking in the context of D.Min. research — not to make your project feel more like a laboratory experiment, but to give you the precision you need to design good instruments, collect meaningful data, and write findings that actually answer your research question.

In research, a variable is anything that can change, differ, or be measured across your study population or over time. In a D.Min. project, variables are simply the things you are paying attention to — the things you expect to shift as a result of what you do.

If your project is about increasing prayer participation among congregants, then prayer participation is a variable. It can be higher or lower, more frequent or less frequent, deeper or shallower. Your job as a researcher is to define it precisely enough that you can actually detect whether it changed.

Variables fall into two primary categories that every D.Min. student should understand.

Your independent variable is the intervention — the program, training, initiative, worship practice, or leadership model you design and implement. It is called “independent” because it does not depend on anything else in your study. You control it. You deliver it. It is the cause you are introducing into your ministry context.

In our ongoing example, Pastor Sarah’s independent variable is the eight-week young adult ministry initiative combining weekly Bible study groups and two community service projects. She designed it. She will run it. Its presence or absence is entirely under her control.

When you describe your independent variable in your dissertation, you are essentially describing your intervention in enough detail that another researcher could replicate it.

Your dependent variable is the outcome — the thing you expect to change as a result of the intervention. It is called “dependent” because it depends on what the independent variable does. It is the response you are watching for.

In Sarah’s project, the dependent variables are engagement levels and perceived spiritual growth among young adults aged 18–30. She cannot control these — she can only create conditions that she believes will influence them, and then measure whether they moved.

Here is the key: your dependent variable must be defined specifically enough to be measured. “Spiritual growth” by itself is not measurable. “Participant self-reported spiritual growth as assessed by a pre- and post-initiative survey using a five-point Likert scale” is measurable. The difference between those two statements is the difference between a vague hope and a defensible research design.

Before you finalize your research question and move toward writing your hypothesis, apply this simple two-part test:

1. Can I name my independent variable? — What, specifically, is the intervention? Could I describe it in enough detail that someone else could replicate it?

2. Can I name my dependent variable or variables? — What, specifically, will I measure? How will I know whether it changed?

If you can answer both questions clearly, you are ready to write your hypothesis. If you cannot, keep working on your research question before moving forward. A blurry variable produces a blurry hypothesis, and a blurry hypothesis produces an unfocused dissertation.

D.Min. projects commonly involve more than one dependent variable, and that is perfectly appropriate. Sarah, for instance, has two: engagement levels (which she can measure quantitatively through attendance records and survey data) and perceived spiritual growth (which she will assess qualitatively through interviews and focus groups). The two variables work together to give her a fuller picture of what happened in her project.

However, more is not always better. Each dependent variable requires its own measurement strategy, its own set of instruments, and its own analysis. A project with five or six dependent variables can quickly become unmanageable within the constraints of a D.Min. program. As a general rule, aim for one to three dependent variables that are genuinely central to your research question, and resist the temptation to measure everything that might be interesting.

“Operationalizing” is the researcher’s term for turning an abstract concept into something concrete and measurable. It is one of the most important skills you will develop in this process.

Consider the variable leadership effectiveness. As a concept, almost everyone knows what it means. As a research variable, it means nothing until you define how you will measure it. Will you use a validated leadership assessment instrument? Congregant satisfaction surveys? Attendance trends? Elder board evaluations? The moment you answer that question, you have operationalized your variable.

Here are a few examples of dependent variables and how they might be operationalized in a D.Min. context:

Dependent Variable Possible Operationalization Spiritual growth Pre/post survey using a validated spiritual formation scale Congregational engagement Weekly attendance records and volunteer participation logs Biblical knowledge Pre/post knowledge assessment administered to participants Sense of community Participant interviews coded for belonging and connection themes Leadership confidence Self-assessment survey with Likert-scale items before and after training

Notice that some variables lend themselves to quantitative measurement (numbers, scores, frequencies) and others to qualitative assessment (themes, perceptions, narratives). Many D.Min. projects will include both — which is one reason triangulated data collection, using surveys, interviews, and focus groups together, is so common and so valuable in this kind of research.

Once you have your independent and dependent variables in hand, you may find it useful to think briefly about moderating variables — factors that you are not controlling but that might influence your results. Common moderating variables in ministry research include age, gender, length of church membership, prior ministry experience, and ministry context (urban versus rural, for example).

You are not expected to control for all of these in a D.Min. project, and you do not need to design your study around them. But being aware of them will help you write a more honest findings chapter. If your intervention seemed to work well for long-term members but not for newer attendees, that pattern is worth noting — and it may be a moderating variable at work.

Let’s bring all of this together using Pastor Sarah’s project.

• Independent variable: An eight-week young adult ministry initiative consisting of weekly Bible study groups and two community service projects

• Dependent variable 1: Engagement levels of adults aged 18–30 (operationalized as weekly attendance at church activities, tracked before, during, and after the initiative)

• Dependent variable 2: Perceived spiritual growth among participants (operationalized as self-reported responses on a pre- and post-initiative survey, supplemented by focus group interviews)

• Possible moderating variable: Length of church membership (longer-term members may respond differently than newer attendees)

With these variables clearly named, Sarah is ready to write a hypothesis that is specific, testable, and directly connected to instruments she can actually design. That is exactly what the next article in this series will walk you through.

Variable thinking is the conceptual infrastructure that makes your ministry research credible, replicable, and useful to others. Knowing what you are doing (your independent variable) and what you are measuring (your dependent variables) before you design a single survey question is one of the clearest marks of a well-prepared doctoral student.

Name your variables early. Define them specifically. And keep them central to every methodological decision you make from this point forward.

References

Creswell, J. W., and J. D. Creswell. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches, 5th ed. SAGE Publications, 2018.

Sensing, T. Qualitative Research: A Multi-Methods Approach to Projects for Doctor of Ministry Theses. Wipf and Stock Publishers, 2011.

Vyhmeister, N. J., and T. D. Robertson. Quality Research Papers: For Students of Religion and Theology, 4th ed. Zondervan Academic, 2020.