How to Write the Problem Statement for a Graduation Thesis

What is a problem statement in a thesis

A problem statement is the opening section that answers one specific question: why is this topic worth researching at this time and in the context you have chosen? The reader does not need to know all of your survey results here. They need to understand the practical context, the problem that exists, what previous studies have not fully explained, and the specific focus of your study.

For a quantitative graduation thesis, the problem statement is usually about 1 to 2 pages, depending on your department's requirements. It may appear in Chapter 1, before the research objectives and research questions. Length matters less than the logic of the argument. A long passage that only describes an industry, company, or market does not yet establish a research problem.

You should distinguish between three concepts. Context is the general situation that leads the reader into the topic. The research problem is something unclear, ineffective, or not yet explained with data. The topic is the specific scope you choose to investigate that problem, such as a customer group, location, industry, or model of variables.

The topic [topic title] may belong to the field of [industry or field]. To review the full scope before writing, you can also see the guide to graduation thesis and the list of graduation thesis topics. These two pages help you avoid writing a problem statement for a topic that is too broad when your actual data can answer only a small part of it.

Standard structure of a problem statement

An easy-to-read problem statement usually moves from broad to narrow. Each paragraph should have its own purpose rather than repeating the same observation with different wording.

The table is a writing framework, not a rigid template. Some departments require the objectives and research questions to appear as separate sections in Chapter 1. In that case, the problem statement only needs to lead into those sections. Do not copy the same wording into all three places.

A strong paragraph often contains an observation, supporting evidence, and a connection to your topic. For example, you might describe a change in digital banking behavior, point out a consequence that deserves attention, and then move to the question of why some users still have not adopted the service. If you do not have reliable data, use cautious wording such as “suggests a need for further examination” instead of claiming a specific percentage.

Steps for writing a problem statement

Step 1: Set one central question

Before opening Word, write one sentence answering this prompt: “What does this study want to know, about whom, and in what context?” For example: “The study aims to identify the factors affecting students’ intention to use e-wallets in Ho Chi Minh City.”

This sentence is not yet a complete paragraph. It is a filter that tells you which sources to keep. If the question includes too many target groups, locations, or outcomes to measure, the topic is too broad. Narrow it first, because writing a problem statement for an unsettled question usually produces a scattered introduction.

Step 2: Write the context from the field to the target group

The first paragraph should introduce the field using information directly related to the dependent variable or behavior you are studying. For example, if the dependent variable is online cosmetics purchase intention, discuss purchasing behavior, the platform experience, or factors affecting the decision rather than telling the entire history of the retail industry.

Check the source for every claim that contains data before including it in the official draft. If you do not yet have a verified source, describe the phenomenon and leave a placeholder for the supporting reference. Do not use a percentage taken from a post with no clear survey method. The committee may immediately ask about the denominator, timing, and target group behind that number.

Step 3: State the evidence of the problem

After presenting the context, answer this question: what is unclear or not working well? The problem may involve low acceptance, a difference between intention and behavior, uneven business results, or known factors that fail to explain a particular target group.

A quantitative research problem must be capable of being converted into measurable variables. “Customers are dissatisfied” can be developed into indicators of service quality, perceived value, and revisit intention. “Businesses need digital transformation” remains too broad if you have not identified which process is changing and which outcome will be measured.

Step 4: Identify the research gap

A research gap does not necessarily mean that nobody has ever studied the topic. You can point to a context that differs from previous studies, a target group that has not been examined, an inconsistent relationship between variables, or an older model that does not fit your question.

Read the objectives, methods, and limitations sections of relevant studies. Record four columns: author and year, target group, variables, and remaining limitation. This keeps you from writing a vague sentence such as “few studies have examined this topic” when many studies already exist.

When presenting the gap, use a level of certainty that matches your evidence. “The studies reviewed have mainly focused on...” is safer than “no study has...” unless you have followed a sufficiently broad search process to prove the latter.

Step 5: Narrow the scope and model

This paragraph moves from the general problem to your specific study. State the target respondents, location, expected period, dependent variable, and group of independent variables. If the model includes a mediator or moderator, include it only when the model and hypotheses have a clear basis.

For example, a study may focus on the effects of perceived usefulness, perceived ease of use, and trust on students’ intention to use an online learning application. This wording tells the reader that you will collect data with a questionnaire and test relationships between the specified variables.

Step 6: End with the objectives and research questions

The general objective should connect directly to the problem you have just described. Specific objectives may then include identifying the factors, assessing the level of influence, testing the hypotheses, and proposing implications that fit the results.

Your research questions must be answerable with your data. Common forms include: “Which factors affect...?”, “How strong is the effect of each factor?”, and “Can the model explain changes in...?” Avoid questions that require an evaluation of the entire market if you surveyed only a convenience sample from one group.

Step 7: Check the logic of the argument

Read the draft again using five questions: What is the context, where is the problem, what gap exists, what is the scope of my study, and which question will the results answer? If a paragraph does not help answer one of these five questions, cut it or move it to the literature review.

You should also compare the terminology across the problem statement, model, questionnaire, and data file. The variable name “continuance intention” should not become “loyalty” at the end if the two concepts are not defined and measured with the same scale.

Usable sentence templates

The sentences below are frameworks that you can replace with real information. Do not keep a template unchanged if it makes your topic sound broader than your actual data.

How to write this in your thesis

You can adapt the following paragraph for your draft: “Based on [evidence of the problem] and the gap related to [missing content], the topic ‘[topic title]’ is conducted to [general objective]. The study focuses on [target group] in [location], thereby assessing the effects of [independent variables] on [dependent variable].”

After filling in the placeholders, check whether every noun in the paragraph appears in your model and questionnaire. If you write “service quality” but the questionnaire measures only “convenience,” the committee has a basis for asking about the inconsistency between the problem and the scale.

A shortened example of a problem statement

Suppose you are studying “Factors affecting students’ intention to use online learning applications in Ho Chi Minh City.” A shortened version could read as follows:

“Online learning applications are becoming a channel that helps students access materials, lectures, and revision activities outside the classroom. However, having an account or having tried an application does not necessarily mean that students intend to continue using it. Some students may find an application accessible but still fail to maintain their use if they do not perceive clear benefits, encounter difficulties while using it, or lack trust in the platform.

Studies of technology acceptance have examined factors such as perceived usefulness and perceived ease of use. However, findings may differ across contexts because of differences in users, application types, and learning conditions. Therefore, the factors affecting intention to use online learning applications need to be tested among students in Ho Chi Minh City.

This study focuses on assessing the effects of perceived usefulness, perceived ease of use, and trust on intention to use. Data will be collected with a questionnaire and analyzed quantitatively to answer the following question: how do these factors affect students’ intention to use online learning applications?”

This is only an introduction and does not replace the literature review or hypotheses. In the next section, you need to define each variable, find sources for the scales, build the model, and explain why each proposed relationship is reasonable. If you use TAM, the foundational source can be cited as (Davis, 1989). If you study behavioral intention through TPB, clearly distinguish attitude, subjective norm, perceived behavioral control, and intention, based on (Ajzen, 1991).

Common problems that make the committee ask follow-up questions

Starting with too much history

You spend a page describing the history of an industry without explaining the research problem. Keep information that connects directly to the target group, variables, and research question.

Using unverifiable data

A large number can make a paragraph appear convincing, but it creates risk if you cannot find the original report. Save the link, report title, year, and sample scope in your source file before adding the number to your thesis.

Writing “no studies have...” too early

An absolute claim often goes beyond the evidence you have. Describe the scope of your review, the target groups, or the contexts that previous studies have focused on, and then state a more specific gap.

Creating a mismatch between the problem statement and the model

The opening paragraph discusses satisfaction, but the model measures purchase intention. Or you mention price, but the questionnaire contains no corresponding indicator. Create a comparison table covering the problem, variables, hypotheses, and measurement items.

Confusing objectives with solutions

The problem statement should lead to the research, not promise in advance that a solution will increase revenue or improve behavior. Quantitative results may support or fail to support the hypotheses, so the opening section should state what you want to test.

Copying a template without changing the scope

The phrase “customers in Vietnam” makes the study much larger than a sample of 200 students from one university. State the actual questionnaire respondents, location, and data collection period.

You should also check for duplication before submitting the draft. You can refer to checking Turnitin to understand the checking process, and review the guide to plagiarism to distinguish valid citation from verbatim copying. If you need to compare the presentation of different types of papers, the pages on research topics and theses can also help you recognize differences in scope and structure.

Frequently asked questions

Is a problem statement the same as stating the reason for choosing a topic?

The two sections are related but not identical. The reason for choosing a topic usually answers why you selected the subject, while the problem statement presents a broader line of reasoning that includes the context, evidence, gap, and research direction.

If your department requires a section called “reason for choosing the topic,” you can use the problem statement as the foundation and then summarize the reason in a short paragraph. Avoid copying the entire section into both places.

How many pages should a problem statement be?

There is no single length that applies to every department. Follow the page range in your university’s graduation thesis guidelines. When no clear requirement exists, about 1 to 2 pages is usually enough to present the problem for a quantitative study with a moderate scope.

Writing more pages does not make the section better if you are only repeating the context. Check whether each paragraph brings the reader closer to the objective, model, and research questions.

Do I need to include data in the problem statement?

You can include data when it clarifies the scale or evidence of the problem and you have a verifiable source. Data should be accompanied by the time, target group, scope, and source. If you have not verified it, use cautious descriptive wording rather than creating a percentage.

The data in the problem statement must also fit the topic. A number about all consumers does not automatically prove a problem among students at one university.

Where can I find a research gap?

Start with the limitations and suggestions for future research in relevant studies. Then compare the target groups, locations, variables, methods, and findings across those studies. The gap should be based on what you have actually reviewed.

Do not write “no studies have...” simply because you have not found a suitable article. A safer approach is to state the contexts that previous studies have focused on and explain what part your topic adds.

Does a quantitative topic need hypotheses in the problem statement?

Usually, you only need to lead to the objectives, research questions, and model direction in the problem statement. Hypotheses should be explained in the theoretical background or research model section, where you have enough space to justify each relationship.

You can mention the names of the variable groups so that the reader understands the scope. You do not need to put all of H1, H2, and H3 into the opening paragraph if your thesis structure has a separate hypothesis section.

Open your draft file and write one central question first. Then complete the seven steps in the framework, compare each variable with the questionnaire, and remove every claim that has no source or does not serve the research question. If you need support with running .sav or .csv data and checking a quantitative model, you can use DoThesis M4 analysis.