Time to Hit the Road

Imagine you’re going on a cross-country road trip covering several stops over a couple of weeks. If you’re like most people, you don’t just jump in the car and start driving, assuming you’ll figure things out when you arrive. Instead, you go to travel websites and learn about the local sights, and use a map app and plan your route. You mark where you’re starting, where you’re going, what major stops or checkpoints you’ll hit, and what you need to be aware of along the way.

That’s exactly what Chapter One of a dissertation does.

Chapter One acts as a map for your readers and for yourself. It lays out:

• Where you’re starting → What’s the background or context of the problem? Why is this issue worth studying?
• Where you’re headed → What are your research questions, objectives, or hypotheses? What’s the purpose of this study?
• Why this route → What’s your rationale? Why did you choose this topic and approach, and why does it matter?
• What’s ahead on the road → What key terms or definitions should the reader know? What will the upcoming chapters cover?

Just like a map keeps you on track and helps prevent you from getting lost, Chapter One helps keep your dissertation focused and lays out the course. Without it, you (and your readers) could easily lose sight of where you’re going. But with a strategically informative map, you’re clear about where you’re going, why you’re going there, and how you’ll get there.  It makes the long journey ahead much smoother for you and your readers. Keep in mind, even though you may have done your literature review already, and you are becoming an expert on the subject you’ve chosen to write about, this chapter serves as the first exposure your readers may have to your topic and work. Thus, you should write as though you’re talking to someone who is hearing about it for the first time. Be mindful of this; take the time to set the narrative, and connect your sections to each other as well as to the literature review.

Overview of Key Words and Concepts

This chapter is full of new terms and concepts; in fact, the purpose of this chapter is to introduce you to the parts of Chapter One, so this whole chapter is, in a sense, an overview of the key words and concepts necessary to write Chapter One of your dissertation. However, there is one important key concept to introduce, and that is the difference in focus between a quantitative study and a qualitative one.

Hypotheses and Research Questions

In quantitative research, once you establish your research problem and its significance, you frame your study by formulating one or more hypothesis and matching null hypothesis (Creswell & Creswell, 2018). In qualitative research, you frame what you will study with research questions (Creswell & Poth, 2018). These will be explained in greater detail in this chapter. These elements set the stage for the rest of your dissertation, so it is imperative that they be well framed. Poorly constructed hypotheses and research questions seldom lead to a sound and cohesive research study (Mertens, 2020). In the process of writing your dissertation, even in later chapters, you may find it is necessary to tweak the wording slightly, but the focus of your study must remain untouched unless you are prepared to backtrack and rethink through the literature review process.

Conceptual and Theoretical Frameworks

A conceptual framework refers to the set of concepts, assumptions, beliefs, and theories that support and structure a qualitative research study (Miles, et al., 2014). It is often constructed by the researcher from prior literature, personal experiences, and contextual understanding of the research problem. The conceptual framework maps out how you think the key variables and concepts in a qualitative study relate to each other, and it informs the design, data collection methods, and interpretation of findings. A conceptual framework is rooted in a theoretical perspective, the broad lens through which the author of a dissertation views their study.

In contrast, a theoretical framework is typically drawn from existing, formalized theories or models that offer a lens for understanding the research problem of a quantitative reserach study. While the conceptual framework lays out the “what” in qualitative research (i.e., what constructs you are exploring and how you believe they interact), the theoretical framework explains the “why” by grounding quantitative research in established scholarly theory (Creswell & Creswell, 2018).

It should be noted that these interpretations are commonly adopted or adapted from Miles, Huberman, and Saldaña (2014) and Creswell and Creswell (2018). This table can help you better understand the key differences between theoretical frameworks, theoretical perspectives, and conceptual frameworks.

In qualitative research, think of your theoretical perspective as your research glasses. It represents how you see the world. Your conceptual framework is the map you draw to guide your route. It shows what matters in your study and how those pieces fit together.

In quantitative research, a theoretical framework is a specific prescription lens in your glasses. It sharpens your focus.

While the independent and dependent variables were introduced in the previous chapter, in the quantitative research section below, you will also learn about control variables and extraneous variables, other factors that may need to be taken into account when conducting quantitative research.

Finally, this chapter also introduces limitations and delimitations, two different concepts that are often addressed in one section of Chapter One. Limitations help your reader understand potential outside factors that constrain your study, and delimitations explain limits to the research intentionally placed by the researcher.

The Makeup of Chapter One

Regardless of where you go to school for your doctoral degree, the first chapter of a dissertation research study is structured with some very common components. Although they are not identical from one institution to the next, there will be certain commonalities in language and in how they are organized. Certain elements must be included to provide solid footing for your research study. This chapter will introduce you to the parts of Chapter One in a research study. Due to the differing nature of quantitative research and qualitative research, the parts of Chapter One vary slightly, but significantly. This table shows the recommended outline for Chapter One of a dissertation at Saint Peter’s University. It is possible to vary from this outline, but that should be done in consultation with your mentor and for good reason. Following the table is an explanation of each part of Chapter One depending on which study you’re conducting. Note that some parts are the same, and the text may be repetitive; this is done to improve flow and allow you to focus on one research method or the other. Mixed Methods is not covered separately in this chapter; it naturally will contain elements of both. Creating the design for  a mixed methods research study should include input from your mentor.

Introduction

The introduction to your study provides an overview of the research topic and introduces the general area of study. Many colleges and universities include a section of Chapter One called “Background Information” as well as the introduction. As we are not writing that as a separate section, any background information necessary for the reader to understand the topic should be provided in your introduction.

The introduction provides context. This may be historical, cultural, field specific, or anything else that will help the reader understand the setting for your study. It grabs the reader’s attention by outlining the background, setting the stage for the problem, and explaining why you’ve chosen to write about this topic. Note that the introduction is one section that you will want to revisit when your study has been completed. You may have made changes or adjustments in your approach; you may have learned additional context that will be helpful for your reader to understand before delving into your study. When your paper is nearly complete, re-read your introduction to make sure it still rings true, also identifying new information that could be added as a preview to your study.

Statement of the Problem

The introduction has set the stage and provided the reader with enough context to understand the topic you’ve chosen to write about. The next step is to articulate the specific research problem or issue the study addresses. It explains what gap, inconsistency, or unresolved question exists in the current knowledge or practice and why it needs to be investigated quantitatively. A problem statement can not exist in a vacuum; it absolutely must be grounded in the literature review, and address at least one specifically identified gap in the research.

The following story demonstrates how one fictional student arrived at a problem statement. Your approach should resemble “Jasmine’s” experience.

Significance of the Problem

Once the previous section addresses the question, “What is the problem,” this section answers the question “Why is the problem important?” This section details the potential impact or contribution of the study, showing how the findings could advance knowledge, inform practice, shape policy, or benefit specific groups or fields. Let’s revisit Jasmine. How did she relate the significance of the problem she identified? Notice that not only did Jasmine explain the importance of addressing this problem at her institution, she also set out to explain the value of her study beyond “Midstate University.”

Consider your own problem. It matters to you…it likely matters to the institution and students in your problem. Who else can benefit from the study of your problem?

Purpose of the Study, Research Hypothesis and Null Hypothesis

This may be written as one section, or teased out into separate sections as the writer sees fit–but all must be present in a quantitative study. This section states the overall purpose (what the study seeks to accomplish). Think of your purpose statement as an “elevator speech.” If someone asked you on an elevator what your research study is about, the purpose statement is a short sentence or two that you could say in common language to answer that question. It should be explicitly stated and clear; the wording of this should state “The purpose of this study is to…” with a few sentences of explanation or context.

Once the purpose is identified, you then formally present the research hypothesis (or hypotheses). It is framed as a clear, testable statement predicting the expected relationship or difference between variables. The null hypothesis is also provided, stating that there is no relationship or difference (used for statistical testing). Examples are provided in the infographic (OpenAI, 2025).

Identification of Variables

The concept of variables is introduced in the previous section under Common Quantitative Research Designs. If you have not yet read that chapter, please begin there as a clear understanding of dependent variables and independent variables is necessary before proceeding.

Experimental and Quasi-Experimental Research Variables

When conducting an experimental or quasi-experimental research study, you must identify your independent and dependent variables involved in the study. Additionally, you may also introduce any other control or extraneous variables as well.

As a reminder, an experimental design tests cause-and-effect relationships by investigating an independent variable (the cause, or predictor) and its impact on a dependent variable (the effect, or outcome). The experimental approach is best used when attempting to answer a question framed as “How does X affect Y?” where X represents the independent variable and Y represents the dependent variable.

In addition to these variables, it may also be necessary to identify any control variables or extraneous variables.

A control variable is a factor that a researcher intentionally keeps the same throughout a study so it does not affect the relationship between the independent variable (the cause) and the dependent variable (the effect). Controlling variables helps ensure that any changes in the dependent variable are really due to the independent variable, not some other factor.

For example, imagine you are studying whether the number of hours students sleep affects their test scores. In this case, sleep hours are the independent variable, and test scores are the dependent variable. But other factors like age, prior GPA, or amount of caffeine consumed could also influence test performance. To make your findings more trustworthy, you would need to find a way to control these variables, and document it in your study. This could mean selecting participants of similar age, collecting data only from students with similar GPAs, or asking all participants to avoid caffeine before the test.

When researchers control variables, they are really asking: “What else might explain this result? How can I prevent that from happening?” By thinking this way, you strengthen your study’s internal validity and increase the confidence that your results are due to the variable you intended to study.

An extraneous variable is any other variable that is not intentionally studied but could still affect the dependent variable if not controlled. They are potential sources of error or “noise” that can distort the findings if they’re not identified and managed. As an example, in the same study about the effect of sleep on test scores, if students’ stress levels or caffeine intake affect their test performance but aren’t accounted for, these would be considered extraneous variables.

Correlational Research Variables

If you are conducting a correlational study, you are not looking for a causal relationship, nor are you manipulating one of the variables, so the independent variable and dependent variable are not utilized the way they are in an experimental approach. Instead, you are simply looking for two variables in existing data, and attempting to identify a relationship between the two (Privitera, 2022). They may be referred to as the primary variable of interest (predictor) and the outcome variable (criterion), as described by Creswell and Creswell (2018). The identification of control variables and extraneous variables still applies.

For example, you suspect that there is a correlation (not a causation) between the amount of time students spend on social media (predictor) and their grade point average (criterion). Investigating the existing data, you look for a pattern to confirm or reject your hypothesis; there is no experiment to conduct.

Descriptive Research Variables

Descriptive studies are not looking for cause and effect or even correlation; they are simply designed to identify characteristics or attributes, usually in an emerging body of knowledge. This kind of variable is a descriptive variable or measured variable; they are simply the data you are gathering and reporting. Descriptive research is seldom if ever done for a research dissertation, for a variety of reasons:

• Descriptive designs look for existing patterns in data, but they stop short of examining why those patterns exist.
• Descriptive studies do not usually test or build upon a theory. Doctoral research is expected to engage with a theoretical or conceptual framework, which guides the interpretation of relationships among variables or the meanings of participants’ experiences.
• Because descriptive studies focus on surface-level data (frequencies, percentages, averages), they do not produce the level of analytical depth or interpretation expected of doctoral work.

An example of a descriptive research variable would be describing teachers’ attitudes toward required homework assignments and measuring them numerically with a Likert scale. The teachers’ overall score(s) represent the descriptive variable. However, descriptive research stops short of analyzing the results. Descriptive research can, however, serve as a foundation for later studies. For example, a master’s thesis or institutional survey might describe patterns that later inspire a doctoral study exploring why those patterns occur.

Operational Definitions

This section provides clear, measurable definitions of key variables or terms used in the study, explaining exactly how each will be observed or measured (e.g., “academic achievement” defined as final GPA).

Note that the operational definitions section is different from the Key Terms and Definitions section of a qualitative study; the purpose is not to provide the meaning of terms, but to establish how the variables are identified and measured in the study.

Theoretical Framework

Here, the researcher identifies the specific theory or model that guides the study and helps explain the expected relationships between variables (e.g., social cognitive theory, self-determination theory). A theoretical perspective is the broad philosophical lens or worldview through which an author of a dissertation views their topic of study. It reflects foundational beliefs about what constitutes knowledge and how it can be known (Creswell & Creswell, 2018; Patton, 2015). It provides a foundation for interpreting results.

There are many commonly used theoretical frameworks in education research. For example, if your topic involves behavior change, you might consider Bandura’s Social Cognitive Theory (Bandura, 1986). If your focus is on student motivation and engagement, Self-Determination Theory (Deci & Ryan, 2000) may be more appropriate. Consulting with a research librarian and your mentor are excellent ways to identify a theoretical framework that best fits your study. If you have more than one theoretical framework, you must provide background, an explanation, and a justification for each.

This section of Chapter One should identify the theoretical framework you’ve chosen as the lens to view your study. It should also give background and explanation of the framework, and explain why it was chosen. It is possible to have more than one theoretical framework attached to your study.

The theoretical framework will be revisited in chapter 4 of your study with an explanation as to how your findings connected to your selected theory. Here’s an example illustrating how the theoretical framework connects to the rest of your dissertation. Read about Maya’s experience with forming a theoretical framework before continuing.

The theoretical framework chosen for the study should be justified.

In a dissertation, simply describing the theory is not enough. Your readers expect to see:

• A rationale that ties the study’s context, problem, and research questions directly to the chosen theory.
• A comparison that shows awareness of other relevant frameworks and why they were set aside. Some examples that could have been considered. Mentioning other frameworks demonstrates that you have reviewed the landscape and intentionally chosen the framework that you did.
• A conceptual “fit” that explains how the theory’s components will be applied to interpret the findings.

Let’s see how Maya’s mentor used feedback to help her address these points.

The theoretical framework provides the foundation that connects your study’s problem, purpose, and research questions to a broader body of knowledge, guiding how you design the study, interpret your results, and contribute to theory and practice.

Assumptions

This section outlines the conditions the researcher accepts as true without direct verification, yet are necessary for the study to move forward. Assumptions are not hypotheses to be tested; instead, they are foundational premises that support the research design and methodology. For example, in a survey-based study, the researcher might assume that participants will respond honestly and thoughtfully, and that they will have the ability to recall and report the information requested. In a study using an established instrument from a different context, the researcher assumes the tool has acceptable validity and reliability for the population under investigation, and that it measures the constructs it purports to measure. While any assumptions cannot be proven within the study itself, acknowledging them demonstrates methodological transparency and helps readers understand the context and boundaries of the inquiry (Creswell & Creswell, 2018).

Limitations and Delimitations

Though limitations and delimitations sound similar, they are not the same thing, and should be addressed with at minimum two separate paragraphs. In short, limitations are constraints to a study that a researcher cannot control while delimitations are constraints that the researcher has deliberately chosen.

Limitations

A limitation is a weakness or constraint the researcher cannot control (Patton, 2015; Mertens, 2020). Typically, limitations are inherent in the nature of the research conducted; while a researcher attempts to remove limitations, they exist in every study.

Common limitations in research are:

• Sample-related limitations
  • Small sample size (limits generalizability)
  • Non-random sampling (e.g., convenience sample, purposive sample)
  • Low response rate in surveys
• Measurement limitations
  • Use of self-reported data (risk of bias or inaccurate recall)
  • Limited validity or reliability of untested or self-created instruments or surveys
  • Single measurement point (cross-sectional rather than longitudinal)
• Design limitations
  • Lack of experimental control of variables
  • Short study duration that may not capture long-term effects
  • Limited number of variables analyzed
• Data collection limitations
  • Limited access to relevant populations or settings
  • Language or cultural barriers affecting data interpretation
  • Ethical or logistical constraints (e.g., inability to randomize participants)
• External limitations
  • Context-specific findings (results may not generalize to other settings)
  • Rapidly changing conditions (e.g., during a pandemic or technological shift)
  • Influence of uncontrollable external factors (e.g., school closures, unexpected interruptions)

There’s no hard-and-fast “correct” number of limitations for a dissertation, but in most doctoral studies, you’ll see somewhere between three and seven clearly stated limitations. Generally, that’s enough to demonstrate that the researcher is aware of constraints, but not so many that the study appears fatally flawed. These numbers are just a general guide, not a hard and fast rule:

1–2 limitations

• • Too few, and it may look like you haven’t critically evaluated your design.
  • Risk: Your committee may think you’re ignoring real methodological weaknesses.

3–5 limitations (common range)

• • Balanced and realistic; acknowledges constraints while still showing the study’s value.
  • Typical for both quantitative and qualitative dissertations.

6–7 limitations

• • Still reasonable if your study design is complex or involves multiple phases or data sources.
  • Often appears in mixed methods studies or multi-site research.

More than 7 limitations

• • Acceptable only if many are very minor and do not undermine the study’s validity.
  • If too many are serious (e.g., major sampling, measurement, or analysis constraints), it can weaken confidence in the findings.

The limitations specific to an study should be written in paragraph form, in sentences such as these examples, as opposed to a bulleted or numbered list.

Or

Delimitations

A delimitation is a boundary that the researcher deliberately sets (e.g., focusing only on one population, using only certain variables), helping narrow the study’s scope (Creswell & Poth, 2018). They define what the study will and won’t cover to ensure that the study is both manageable and relevant. Delimitations clarify for the reader the limits of the study’s scope. Delimitations are set to…

• make the project feasible → Time, resources, and scope are limited, so you can’t study everything.
• focus on the most relevant aspects → By narrowing in on certain populations, variables, or methods, you sharpen your research focus.
• align with the research purpose → Your delimitations ensure that the study stays directly aligned with your purpose, research questions, and hypotheses.
• increase clarity and transparency → You show readers you’ve made intentional choices, rather than leaving gaps or exclusions unexplained.

Examples of delimitations might include choosing to study only one sixth grade class of a school with multiple sixth grade classrooms, limiting the study to one district or region when doing a statistical analysis, or studying only specific variables while not addressing others.

There’s no set number of delimitations a dissertation must have, but most studies include between two and five clearly stated delimitations; enough to clarify the study’s boundaries without overcomplicating its scope.

1 delimitation

• • Too few, and it may appear you haven’t intentionally defined the study’s scope
  • Risk: Readers may not understand the intentional boundaries you’ve set to keep the project manageable.

2–4 delimitations (common range)

• • Balanced for most dissertation projects.
  • Demonstrates intentional choices about participants, setting, timeframe, variables, or theoretical focus.

5+ delimitations

• • Acceptable if your study involves multiple dimensions (e.g., multi-site, mixed methods, longitudinal).
  • Ensure they are clearly grouped so readers can easily see the rationale.

It’s not the number of delimitations that matters most, it’s how clearly you explain that these boundaries are intentional choices you made to make the study feasible, focused, and aligned with your research purpose. Unlike limitations, delimitations are within your control and should reflect strategic design decisions.

Summary

This section briefly wraps up Chapter One in a quantitative study, reviewing the key points covered and preparing the reader for the next chapter, typically the literature review. It reinforces the importance of the study and reminds the reader of the study’s direction. And even though chapter two was written first, this summary  introduces the reader to the literature review, as this is the first time that they will read it.

Chapter One in a Qualitative Study

Introduction

The introduction to your study provides an overview of the research topic and introduces the general area of study. Many colleges and universities include a section of Chapter One called “Background Information” as well as the introduction; as Saint Peter’s University does not require that as a separate section, any background information necessary for the reader to understand the topic should be provided in your introduction.

The introduction provides context. This may be historical, cultural, field specific, or anything else that will help the reader understand the setting for your study. It grabs the reader’s attention by outlining the background, setting the stage for the problem, and explaining why you’ve chosen to write about this topic. Note that the introduction is one section that you will want to revisit when your study has been completed. You may have made changes or adjustments in your approach; you may have learned additional context that will be helpful for your reader to understand before delving into your study. When your paper is nearly complete, re-read your introduction to make sure it still rings true, also identifying new information that could be added as a preview to your study.

Statement of the Problem

The introduction has set the stage and provided the reader with enough context to understand the topic you’ve chosen to write about. The next step is to articulate the specific research problem or issue the study addresses. It explains what gap, inconsistency, or unresolved question exists in the current knowledge or practice and why it needs to be investigated qualitatively. The connection between the gap(s) in research found in the literature should not be implied; they must be clearly articulated. This is where the strongest connection is made between your study and past research.

Significance of the Problem

Once the previous section addresses the question, “What is the problem,” this section answers the question “Why is the problem important?” This section details the potential impact or contribution of the study, showing how the findings could advance knowledge, inform practice, shape policy, or benefit specific groups or fields. Let’s circle back to Marcus. How did he relate the significance of the problem he identified? Notice that not only did Marcus identify how it connects to the specific issue at “Metro Community College,” he also connected it to broader connected issues that merit continued study.

Consider your own problem. It matters to you…it likely matters to the institution and the students in your study. Who else can benefit from the study of your problem?

Purpose of the Study

This section states the overall purpose (what the study seeks to accomplish). Think of your purpose statement as an “elevator speech.” If someone asked you on an elevator what your research study is about, the purpose statement is a short sentence that you could say in common language to answer that question. It should be explicitly stated and clear; the wording of this should state “The purpose of this study is to…” with a few sentences of explanation or context.

Research Questions

A research question naturally follows the purpose of the study, and spells out what specifically you are aiming to learn about your research problem with your own research exploration.

In qualitative research, these questions are:

• Open-ended (not yes/no).
• Exploratory; that is, they aim to understand meaning, experience, or process, not test a hypothesis.
• Aligned with one of the qualitative methods introduced in the previous chapter (e.g., case study, phenomenology, ethnography).

Notice: You are not predicting outcomes or measuring variables, you are seeking rich, descriptive insights. When you construct your research study, it will be designed to directly answer these research questions, which in turn will contribute to meeting the purpose of your study.

Think of your research questions in this way:

• Statement of the problem → here’s the gap we don’t understand.
• Purpose of the Study → a statement of what I intend to accomplish with my research.
• Research questions → here’s exactly what I will explore to meet my purpose and help fill that gap.

Crafting strong research questions is often one of the most challenging steps in the dissertation process. The research question is the bridge between the broad problem you want to address and the specific methods you will use to study it. A well-constructed question guides your design, data collection, and analysis; a poorly constructed one can create confusion, weaken your focus, and undermine the study’s credibility. For this reason, your research questions will very likely go through a number of iterations based on conversations with your Dissertation Seminar I professor, mentor, and committee. You may, in fact, tweak wording throughout the dissertation process, but the essence of the question must remain unchanged.

The most common pitfalls of a research question is that they are too broad/vague or too narrow/focused. Let’s look at examples of how each extreme plays out.

Too broad!

A vague question is broad, unfocused, and difficult to answer with the time, resources, and scope available for a dissertation. It may read more like a topic or curiosity than a targeted inquiry.

Too Narrow!

An overly narrow question limits the scope so much that the findings have little broader relevance, or the sample becomes too small to generate meaningful results.

Context is Key! Build a Bridge.

The Research Questions section is not simply a bullet-pointed list of what you plan to ask or study. It’s a bridge between your problem statement, purpose statement, and theoretical/conceptual framework and the methods you will use in the next chapter. This section should provide context, sometimes called the “connective tissue,” that explains how the questions flow logically from the problem, how they align with your framework, and why they are structured as they are.

Without this context, your research questions may appear disconnected or ungrounded. A strong Research Questions section:

1. First, it introduces the rationale. It briefly explains why these specific questions are being asked and how they address the problem.
2. Second, it links directly to theory/framework. It shows how the questions reflect the theoretical or conceptual lens of the study.
3. Finally, it transitions forward, setting up the move into methodology by showing that the questions are both researchable and aligned with the study’s purpose and research methodology.

So if this section is more than just a bulleted list, what does a fully fleshed out version look like? Here’s an example. Notice that there is both connection back and a transition forward, placing the research questions as the bridge between the problem identified and the method of analysis.

As you read this example, ask yourself if you can see the three elements:

1. Is the rationale for the research questions introduced? How does it connect back to the problem and the literature review?
2. Is it clear how it is linked to the framework chosen for the study?
3. Does it transition forward by showing that the questions are both researchable and aligned with the study’s purpose and research methodology?

As you write your research questions sections, contextualizing them in the same manner will make your dissertaiton more cohesive, clearly connecting past research to your own research study.

Definitions of Key Terms

The definition of key terms section provides general conceptual explanations for important terms or concepts in your study, often to clarify meaning for the reader. These are often pulled from literature or theoretical definitions. This section helps orient the reader, especially when terms could be unfamiliar, contested, or have multiple meanings in different contexts. It is important to use established and understood definitions whenever possible to ensure that your research is easily compared to other research studies and generalizable to future research. They should be introduced in an alphabetical list, which will likely continue to grow as your paper develops.

Here are some examples of definitions with citations to show how terminology can be introduced and connected to the field. The corresponding references are provided; in your paper, those references should be included in your references list.

Theoretical Perspective and/or Conceptual Framework

While a quantitative approach is rooted in a theoretical framework, a qualitative study is based on the author’s theoretical perspective. The author may also choose to cast a vision in Chapter One by positing a conceptual framework as well.

Theoretical Perspective

A theoretical perspective is the broad philosophical lens or worldview through which an author of a dissertation views their topic of study. It reflects foundational beliefs about what constitutes knowledge and how it can be known (Creswell & Creswell, 2018; Patton, 2015). Common theoretical perspectives include constructivism, positivism, critical theory, and postmodernism (Mertens, 2020). For example, a constructivist perspective assumes that reality is socially constructed and that meaning is developed through individuals’ interactions with their environments and each other (Creswell & Poth, 2018). In qualitative research, a theoretical perspective is identified in existing research or literature and described in Chapter One. At that point, a conceptual framework may be created by the author to explain their perspective and lens to view the topic based on their research, knowledge, and personal experience. For this and the next section on Conceptual Framework, we will take a look at “Elena’s” journey  in her qualitative study.

Conceptual Framework

In a qualitative study, the conceptual framework serves as the researcher’s own map of how they understand the problem, what they believe are the key constructs involved, and how those constructs relate to each other. It is typically built by the researcher, informed by prior literature, personal insights, observations, the theoretical perspective, and contextual understanding (Miles et al., 2014). While the theoretical perspective provides the broad philosophical lens (such as constructivism or critical theory) through which the researcher approaches the world, the conceptual framework lays out the specific “what:” the particular concepts, assumptions, and proposed relationships that shape the design of the study.

For example, a researcher studying first-generation college students might draw from existing studies on self-efficacy, institutional support, and student persistence to create a conceptual framework showing how these constructs interact. This framework will guide the development of research questions, selection of participants, data collection methods, and interpretation of findings. Importantly, the conceptual framework is unique to the individual study: it reflects the researcher’s synthesis of the relevant ideas, rather than simply applying an established external theory.

As Miles, Huberman, and Saldaña (2014) explain, a strong conceptual framework makes your research more intentional and focused, clarifying your thinking and making your study design coherent. It also provides a valuable guide for your readers, helping them understand the logical connections behind your research choices.

Let’s revisit Elena, and see how she applied a conceptual framework to her study.

Whether you use both a theoretical perspective and a conceptual framework, or just one or the other, is a healthy conversation to have with your Dissertation Seminar I professor and to elaborate upon with your mentor. As you can see, these elements add clarity to your research assumptions (to be addressed next) and methodology.

Assumptions

This section outlines the conditions the researcher accepts as true without direct verification, yet are necessary for the study to move forward. Assumptions are foundational premises that support the research design and methodology. For example, in a survey-based study, the researcher might assume that participants will respond honestly and thoughtfully, and that they will have the ability to recall and report the information requested. In a study using an established instrument from a different context, the researcher assumes the tool has acceptable validity and reliability for the population under investigation, and that it measures the constructs it purports to measure. In qualitative interviews, assumptions might include the belief that participants will feel comfortable sharing their experiences openly or that the researcher can accurately interpret the meaning of their responses. While any assumptions cannot be proven within the study itself, acknowledging them demonstrates methodological transparency and helps readers understand the context and boundaries of the inquiry (Creswell & Creswell, 2018).

Limitations and Delimitations

Though limitations and delimitations sound similar, they are not the same thing, and should be addressed with two separate paragraphs. In short, limitations are constraints to a study that a researcher cannot control while delimitations are constraints that the researcher has deliberately chosen.

Limitations

A limitation is a weakness or constraint the researcher cannot control (Patton, 2015; Mertens, 2020). Typically, limitations are inherent in the nature of the research conducted; while a researcher attempts to remove limitations, they exist in every study.

Common limitations in quantitative research are:

Sample and Context Limitations

• Small or narrowly defined participant group may limit the transferability of findings to other settings.
• Purposeful or convenience sampling may exclude alternative perspectives.
• Limited diversity among participants (e.g., all from one institution or region) may reduce contextual variation.

Researcher and Data Interpretation Limitations

• The researcher’s own background, assumptions, or positionality may influence data collection and interpretation.
• Subjectivity in coding or interpreting qualitative data can affect consistency.
• Researcher–participant relationships may shape participants’ responses (e.g., social desirability or power dynamics).

Data Collection and Scope Limitations

• Data collected from a single site, setting, or case may not capture wider variation.
• Time constraints may prevent prolonged engagement or repeated observations.
• Incomplete or uneven data (e.g., missing interviews, low participation in focus groups) may narrow insights.
• Language or cultural barriers can complicate meaning-making and interpretation.

Analytic and Methodological Limitations

• Use of a single data collection method (e.g., only interviews) may limit depth or triangulation.
• Emergent themes may not fully align with initial research questions or theoretical framework.

External and Contextual Limitations

• Findings may be context-specific and not easily transferable to other populations or settings.
• Changing social, institutional, or policy contexts (e.g., post-pandemic shifts, leadership changes) may influence participants’ perspectives.
• Ethical or logistical constraints (e.g., inability to record sensitive interviews) can limit data richness.

There’s no hard-and-fast “correct” number of limitations for a dissertation, but in most doctoral studies, you’ll see somewhere between three and seven clearly stated limitations, generally enough to demonstrate that the researcher is aware of constraints, but not so many that the study appears fatally flawed. These numbers are just a general guide, not a hard and fast rule:

1–2 limitations

• • Too few, and it may look like you haven’t critically evaluated your design.
  • Risk: Your committee may think you’re ignoring real methodological weaknesses.

3–5 limitations (common range)

• • Balanced and realistic; acknowledges constraints while still showing the study’s value.
  • Typical for both quantitative and qualitative dissertations.

6–7 limitations

• • Still reasonable if your study design is complex or involves multiple phases or data sources.
  • Often appears in mixed methods studies or multi-site research.

More than 7 limitations

• • Acceptable only if many are very minor and do not undermine the study’s validity.
  • If too many are serious (e.g., major sampling, measurement, or analysis constraints), it can weaken confidence in the findings.

The limitations specific to an study should be written in paragraph form, in sentences such as these examples, as opposed to a bulleted or numbered list.

Or

Delimitations

A delimitation is a boundary that the researcher deliberately sets (e.g., focusing only on one population, using only certain variables), helping narrow the study’s scope (Creswell & Poth, 2018). They define what the study will and won’t cover to ensure that the study is both manageable and relevant. Delimitations clarify for the reader the limits of the study’s scope. Delimitations are set to…

• make the project feasible → Time, resources, and scope are limited, so you can’t study everything.
• focus on the most relevant aspects → By narrowing in on certain populations, variables, or methods, you sharpen your research focus.
• align with the research purpose → Your delimitations ensure that the study stays directly aligned with your purpose, research questions, and hypotheses.
• increase clarity and transparency → You show readers you’ve made intentional choices, rather than leaving gaps or exclusions unexplained.

Examples of delimitations might include choosing to study only one sixth grade class of a school with multiple sixth grade classrooms, limiting the study to a focus group of administrators, or studying only specific variables while not addressing others.

There’s no set number of delimitations a dissertation must have, but most studies include between two and five clearly stated delimitations; enough to clarify the study’s boundaries without overcomplicating its scope.

1 delimitation

• • Too few, and it may appear you haven’t intentionally defined the study’s scope
  • Risk: Readers may not understand the intentional boundaries you’ve set to keep the project manageable.

2–4 delimitations (common range)

• • Balanced for most dissertation projects.
  • Demonstrates intentional choices about participants, setting, timeframe, variables, or theoretical focus.

5+ delimitations

• • Acceptable if your study involves multiple dimensions (e.g., multi-site, mixed methods, longitudinal).
  • Ensure they are clearly grouped so readers can easily see the rationale.

It’s not the number of delimitations that matters most, it’s how clearly you explain that these boundaries are intentional choices you made to make the study feasible, focused, and aligned with your research purpose. Unlike limitations, delimitations are within your control and should reflect strategic design decisions.

Summary

This section briefly wraps up Chapter One of your dissertation, reviewing the key points covered and preparing the reader for the next chapter, typically the literature review. It reinforces the importance of the study and reminds the reader of the study’s direction. And even though it was written first, it introduces the reader to the literature review, as this is the first time that they will read it.

Incorporating AI Responsibly: Clarify and Enhance

How to Use AI in Chapter One

There are a number of ways that you can responsibly use AI to aid you in the writing of Chapter One. Here are some suggestions for how it can help you in your understanding of concepts, clarify your vision, and enhance your writing:

Clarifying Concepts and Terminology. There are many complicated terms and concepts in this chapter. In that case, using an AI tool such as ChatGPT can be very helpful by asking questions to help you understand the terms before you attempt to apply them.

Here’s an example of what that might look like.

Getting Feedback on Clarity and Structure. Often, a researcher gets “too close” to their own writing–they wrote it, and have read it so many times that it becomes difficult to view their writing as someone else with fresh eyes might see it. At times like this, AI can be very useful. On a paragraph by paragraph or section by section basis, you can paste your text into an AI tool and ask for feedback. Questions may include:

• Make recommendations to improve my…
  • academic tone
  • organization of my writing
  • clarity
  • grammar and mechanics
• Do my research questions clearly connect to my problem statement?
• Does my introduction adequately provide background for my study?

Making Connections. AI may be able to help you find frameworks and perspectives that connect to your study. It may also be able to assist you in finding similar studies that you can consider for your onw research study.

How NOT to Use AI in Chapter One

• Do not rely on AI for citations or references without verifying. AI can be a helpful tool for starting out on your citations, but it can also produce incorrect, outdated, or fabricated citations. Always verify any source you use–check sources with your research librarian or related databases.

• Do not let AI generate paragraphs or sections of your dissertation. Saint Peter’s University and your committee expect your original voice, critical thinking, and scholarly tone.

• Do not assume AI knows Saint Peter’s expected formatting or requirements. Always refer to your Saint Peter’s University dissertation handbook or mentor for official expectations.

• Do not use AI to “summarize” entire academic articles for citation. It’s acceptable to use AI to summarize an aritcle for your personal review and understanding, aiding you in determining the relevance of the article for your use. Once you suspect the article may be useful, make sure you read the work yourself to ensure accurate representation and citation.

Conversation Topics for Your Mentor

Understanding Theoretical and Conceptual Frameworks

Students should discuss how to select and justify their frameworks, and how those frameworks will guide their design and interpretation of data. Questions to discuss with your mentor might include:

• “What theoretical framework/perspective best suits my study?”
• “Which existing theories or models from the literature might best support my topic?”
• “Should I describe and/or diagram a conceptual framework to explain my vision for my qualitative study?”

Suggested Writing Activities

Framework Mapping

Draw two columns: one labeled Theoretical Framework and the other Theoretical Perspective.

• Under Theoretical Framework, list any formal theories from your literature review that might help explain your research problem.
• Under Theoretical Perspective, list any key concepts, assumptions, or contextual factors that you think influence your study.

Then, write a short paragraph explaining how each might inform your data collection and analysis.

With a clearly defined problem and a plan for your research procedures, you are prepared to move forward into the writing and research phases of your dissertation. As you progress, remember that the dissertation is not a single document written once, but an evolving project. This means you’ll be returning often to your literature review, refining your methods, and revisiting your problem as your understanding deepens.

References

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.

Bass, B. M. (1985). Leadership and performance beyond expectations. Free Press.

Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.

Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). SAGE Publications.

Delgado, R., & Stefancic, J. (2017). Critical race theory: An introduction (3rd ed.). New York University Press.

Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. SAGE Publications.

Mertens, D. M. (2020). Research and evaluation in education and psychology: Integrating diversity with quantitative, qualitative, and mixed methods (5th ed.). SAGE Publications.

Miles, M. B., Huberman, A. M., & Saldaña, J. (2014). Qualitative data analysis: A methods sourcebook (3rd ed.). Sage Publications.

OpenAI. (2025). Infographic: Example purpose, research hypothesis, and null hypothesis in a quantitative study [Infographic]. ChatGPT. https://chat.openai.com

OpenAI. (2025). Conceptual framework for student adaptation experience in immigrant high school students [Diagram]. ChatGPT. https://chat.openai.com/

Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice (4th ed.). SAGE Publications.

Privitera, G. J. (2022). Research methods for the behavioral sciences (4th ed.). SAGE Publications.

Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes (M. Cole, V. John-Steiner, S. Scribner, & E. Souberman, Eds.). Harvard University Press.