There is great concern that scholars are unsure of the differences between research methodology and research methods. This blog post will help you differentiate between the two and offer easy-to-use sources, so your research paper, thesis, or dissertation stands out from the crowd as one that has both a well-written research methodology section and a well-written research methods section.

What is Research Methodology?

Research methodology is a broad view of the different strategies of inquiry available (qualitative, quantitative, or mixed-methods). The scholar will define each with textbook descriptions and narrow down the optimal choice with a rationale of why they chose a particular research methodology. 

A good research methodology section in your paper will document each possible option, define them from various textbooks, and explain why one was selected and why the others were not selected for your particular study. 

The Creswell book includes great content about various methodologies and methods. If your school does not use the Creswell book, keep reading. I will have more recommendations here in this blog post. Cozby and Bates is also another recommendation.

Research Methodology: What is Quantitative Research?

The quantitative inquiry will include a discussion of experimental and non-experimental designs. When talking about these different types of designs, also include a look at comparative, quasi-experimental, exploratory, explanatory, causal, descriptive, and correlational studies. As with the previous paragraph, define these different designs and explain why you selected the one you did for your study.

Research Methodology: What is Qualitative Research?

Qualitative Research will include a discussion of broad qualitative research methodologies such as ethnography, phenomenological, grounded theory, narrative, and case study. Please keep in mind that some will say phenomenological is a methodology and case study is a method. 

It will depend on how you are using this in your own study. See the Yin book on Case Study Research and the Moustakas book on Phenomenological Research Methods for more information if you are considering case study and/or phenomenological.

Research Methodology: What are Mixed Methods?

Mixed methods will include content about concurrent, sequential, or transformative. Some use phrases such as combined, convergence, integrated, and multi-method. In short, the mixed methods study includes both qualitative and quantitative. Therefore, review the above two paragraphs and include information for both in your paper.

When talking about research methodology, I also usually include conversations about cross-sectional versus longitudinal. Field-based versus lab-based is also a good discussion to have in the methodology section. Again, use a textbook definition of each and explain why you are doing the type of study you are doing.

What are Research Methods?

Research methods, techniques, or procedures include questions, data collection, data analysis, interpretation, write-up, validation, and more. I call this the recipe for the study. While the methodology is broad, the methods section is at the micro-level, explaining how you will do the study you plan to do.

Research Methods: What are Quantitative Methods?

Quantitative methods are predetermined. They will need to be discussed in the research proposal. They may include instrument-based (survey, questionnaire, index, etc.) questions. They can also include performance data such as key performance indicators (KPIs). 

Quantitative data can be primary or secondary data. Primary is where the researcher collects the data themselves. Secondary (also called archival) is where the researcher collects data from an established secondary source. Using a quantitative book such as Hair et al., Pallant, or Tabachnick and Fidell will offer guidance in the step-by-step approach for the quantitative methods section.

Research Methods: What is Qualitative Data?

Qualitative data includes a variety of options such as interviews, observations, documents, and audio-visual files. Mooh et al. (2016) conducted a study to see what methods and methodology were included in 146 projects. The top qualitative methods were semi-structured interviews, focus groups, open interviews, participant observations, questionnaires, workshops, structured interviews, document analysis, ethnographic interviews, group interviews, life history, meetings, narrative elicitation, surveys, field studies, and open interviews, and scoping. 

Once the data collection method is described, the methods section should also include a discussion about reliability and validity. Using a qualitative book such as Patton, Yin, or Saldana will help with the step-by-step approach needed for qualitative inquiry. If you are doing a hermeneutical or exegetical study, please see Henson, Robbins, or Osborne for more details.

In summary, this blog helps you to know the difference between research methodology and research methods. They should both be included in your paper. The Methods section, or Chapter 3, as many refer to this should be textbook-heavy. It should include a well-written definition for each keyword and then an explanation of why you chose what you chose. Your manuscript will stand out from the crowd because you are including accurate language in both sections. This is also a good chance for you to use these two sections as teachable moments. Writing them in such a way that you are learning enough to teach other people is the way you become the expert. Keep up the good work!

Cronbach’s Alpha, Coefficient Alpha, Internal Consistency, and Reliability Scores

When I first started hearing about Cronbach’s alpha, coefficient alpha, internal consistency, and reliability scores, I became more confused with each empirical article using different names and wondering if they were talking about the same thing.

In a study to get to the bottom of the situation, I found that they were talking about the same test. Cronbach’s test for internal consistency is the most popular test for scale reliability; however, the naming conventions are all over the place. In this blog post, I urge that we agree to use one name going forward to reduce confusion and demonstrate our understanding of this concept. Coefficient α seems to be the best option.

By the way, alpha should be abbreviated with “α” instead of writing out the word.

What’s the origin of the Coefficient Alpha?

Cronbach introduced the reliability test in 1951. He never intended his name to be used with the test results, as it has been done for decades. In a paper written by Cronbach and Shavelson, he explained that it was an embarrassment that the formula adopted his name, becoming known as Cronbach’s alpha (2004, p. 397).

What is the Coefficient Alpha?

The test itself, whatever it is called, is the most common reliability test for internal consistency; however, there are important factors to know about this test. First, it is a unidimensional test. This means that if you are testing the reliability of an instrument that has four subscales (dimensions), the alpha should be computed for each of the dimensions separately, not for the entire survey.

What are some examples of the Coefficient Alpha?

An example is the Leader-Member Exchange (LMX) instrument by Liden and Maslyn (1998). The overall survey measures LMX. However, the questions that make up each dimension are used to compute the coefficient α. The LMX has the following four dimensions: affect, loyalty, professional respect, and contribution. In their original 1998 study, Liden and Maslyn reported the coefficient alpha as .92 for effect, .90 for loyalty, .78 for professional respect, and .60 for contribution.

They retested with another sample of participants and found the reliability of the data to be .90 for effect, .89 for loyalty, 74 for professional respect, and .57 for contribution. They performed one more test with a different group of participants and found the coefficient alphas as .83 for effect, .79 for professional respect, .66 for loyalty, and .56 for contribution.

Another important factor for the coefficient α is the generally accepted threshold. This, too, has been confusing over the years and likely misinterpreted. We seem to all agree that the range is .00 to 1.0. However, many textbooks say the minimum threshold is .70, meaning if the coefficient α is at or above .70, the data is reliable.

In the example above by Liden and Maslan, many of the scores were below .70. However, the original text by Nunnally actually implies that .70 is “miserably low,” and depending on the purpose of the data, .90 may not be high enough (1975, p. 10).

In my quest to find the answers, I wrote a book chapter titled Clearly Communicating Conceptions of Validity and Reliability (Dean, 2021). I found that a satisfactory level of reliability depends on how it is being used. Nunnally wrote that for modest reliability, “.70 or higher will suffice,” yet for the purpose of applied settings, a score of “.80 is not nearly high enough;” however, “a reliability of .90 is the minimum that should be tolerated, and a reliability of .95 should be considered the desirable standard” (Nunnally, 1978, pp. 245-246). In other words, it is time to raise the standards for reliability.

The Data is Reliable vs The Instrument is Reliable

The final misconception of coefficient alpha is the common phrase where someone says the instrument is valid and reliable. The coefficient alpha is not measuring the reliability of the instrument itself. It measures the data gathered from the instrument. It is more accurate to say the data is reliable instead of saying the instrument is reliable.

References

Cronbach, L. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297-334.

Cronbach, L. J., & Shavelson, R. J. (2004). My current thoughts on coefficient alpha and successor procedures. Educational and Psychological Measurement, 64(3), 391-418. https://doi.org/10.1177/0013164404266386

Dean, D. (2021). Clearly Communicating Conceptions of Validity and Reliability (M. Bocarnea, B. Winston, & D. Dean, Eds.). In Advancements in organizational data collection and measurements: Strategies for addressing attitudes, beliefs, and behaviors. Hershey, PA: Business Science Reference.

Liden, R. C., & Maslyn, J. M. (1998). Multidimensionality of Leader-Member Exchange: An empirical assessment through scale development. Journal of Management, 24(1), 43-72.

Nunnally, J. (1975). Psychometric theory. 25 years ago and now. Educational Researcher, 4(10), 7-21. https://doi.org/10.2307/1175619

Nunnally J. (1978) An Overview of Psychological Measurement. In: Wolman B.B. (eds) Clinical Diagnosis of Mental Disorders. Springer, Boston, MA. https://doi.org/10.1007/978-1-4684-2490-4_4

Can APA be in first person vs. second person vs. third person? The style and tone of your dissertation will depend greatly on your point of view. You may want to make this decision with your dissertation chair as some prefer the first person while others prefer the third person. Also, deciding on this direction early in the dissertation writing process will help to avoid rewriting sections of the paper later. It is much easier to start with the correct point of view rather than going back to try and change all of the occurrences of the third person to the first person later.

Can APA Be In First Person?

Writing in the first person is recommended by APA to avoid ambiguity. First-person writing includes words such as “I,” “me,” “we,” and “us.” When writing a paper by yourself, it may be appropriate to use words such as “I,” whereas writing a paper with more than one author would enable you to write with words such as “we.” Be careful not to use “we” if you are the only author. This causes me to question if you have a mouse in your pocket. APA 7 prefers for authors to not refer to themselves in the third person. Instead of saying “the author did research,” you will simply say, “I did research.”

Can APA Be In Second Person?

Second-person writing includes words such as “you” and “your.” It is best to avoid the second-person point of view in scholarly writing entirely. This may go back to the psychological teaching of using “I statements” instead of “you statements” for best effect. When a person uses “you” instead of “I,” it seems to provoke a defensive stance from the recipient as if they are being accused of something or they are having a finger pointed at them. Therefore, it is best to avoid writing and speaking with “you” statements.

Can APA be In Third Person?

Third-person writing uses words such as the researcher, the scholar, or the writer (instead of I). Historically, many of us were taught to use the third person for formal writing. However, a shift in this decision was made at some point in time, and APA 7 clearly encourages writers to use the first-person point of view instead of the third person. Using third-person writing can get complicated and confusing in a dissertation because there are so many mentions of other authors that the reader becomes unsure if the text is talking about the dissertation student or the empirical author. Again, please speak with your dissertation Chair to see which direction they want you to head in.

If you want expert advice on how to write your dissertation, schedule a free strategy call today!

The last thing we want to do is program the Variable View in SPSS wrong. Especially after spending months or even years on writing the research proposal, defending the proposal, applying and getting human subjects research approval, and setting up the survey. The Variable View in SPSS is not intuitive. This blog post will give you easy instruction to complete this seemingly menial, but highly important task.

Once the data is imported into SPSS, the Variable View tab needs to be fixed. This tab should show each name of your dataset, the type of data, the width of data, decimals, etc. At first glance, many may assume it is correct as is; however, there is a 99.9% chance that the Variable View needs your attention.

Name

First, make sure each row of data has been transferred into SPSS. I call this the gut check. Just make sure everything looks the way you would expect. The name of each column should be listed as a row in Variable View. Feel free to revise the names in the Name column so they are logically named and not too long as these names will show up in the SPSS output.

Type

The type of data is important. The options include numeric, comma, dot, etc. Typically, we need the data to be numeric, although there may be string data if you asked an open-ended question. String data will not show up as an option in SPSS analysis commands because SPSS needs to compute numbers, not alpha characters.

To fix this, a numerical code will need to be created. Dummy codes, as some call this, basically assign a numerical value to the category. For example, instead of listing male and female, code the two options as 0 and 1. To clean up SPSS, I will sometimes remove the data that I will not use during the analysis. However, if in doubt of knowing if it should stay there or not, just leave it.

Width

The width column is basically how long the data will be. It is similar to the length in Microsoft Excel. If your data is 01-99, the default width should be 2. It does not hurt to have this number bigger than needed, but you won’t want it smaller. I don’t usually need to touch this field in the Variable View.

Decimal

The decimal column is for aesthetics. As a general rule, two numbers after the decimal is usually sufficient. If you want to round to the nearest whole number, place a zero in this field. As an FYI, the width of data for APA tables may follow this rule of thumb: whole numbers (no decimal), average/mean (1 decimal), p-values (3-decimals).

Label

The label column is more of a notes field. I don’t usually use this, but for some researchers, it may be helpful. This is completely up to you. It will not show on your SPSS output, so feel free to use whatever you want in the label field or to ignore it entirely.

Values

Values and measure are the last two columns that I want to include in this blog post. Values will need to be revised to match your survey. If you used 1 for male and 2 for female in your survey, this would need to match in SPSS. If you used a Likert scale, add the value labels as indicated on the original survey. For example, 1 = greatly inhibits, 2 = somewhat inhibits, 3 = slightly inhibits, etc. It is important to make sure this information matches how the survey was set up.

Measure

The last column that could throw a wrench in your plans is measure. The following three options are available in SPSS: Nominal, Ordinal, and Scale.

Notice how certain datasets could be scale, ordinal, or nominal depending on how it is presented. For example, age from 0 – 120 would be scale, but if I categorize the ages into groups of 0-10, 11-20, 21-30, 31-40, etc. then it would be considered nominal. One way to think of these options is in a hierarchy. Scale is the highest level of the hierarchy.

It is possible to change scale data to ordinal or nominal, but not possible to change ordinal or nominal data into scale. The second level in the hierarchy is ordinal. It is possible to change ordinal data into nominal, but it is not possible to move ordinal data into scale.

Finally, nominal data is just that. It cannot be changed to ordinal or scale. Think about the measure options as a hierarchy with one being Scale, two being Ordinal, and three being nominal. It is mathematically possible to move the scale to ordinal or nominal, but it is not possible to move nominal to ordinal or scale.

Scale

Is your data continuous such as age or income? Scale might be the best option if your data could be placed on a measurement stick such as a ruler, thermometer, or a scale to measure weight.

One might assume that scale is used for Likert-type scales, but that is not correct. Scale is used for a measurement of 0-1000, as an example. This may also include test scores for ACT, GED, GRE, or SAT. The possible option may only be 1 – 36, but it would still be treated the same as if the possible outcome was 1-100 or an infinite number beyond 1000.

Ordinal

When your data is categorized with some type of natural order or rank order, choose ordinal. This may include ranking data as mild, medium, or hot. It could also include Likert-type scales such as measuring levels of satisfaction from 1 = highly dissatisfied to 5 = highly satisfied or measuring cultural differences with 1 = greatly inhibits, 2 = somewhat inhibits, 3 = slightly inhibits, etc. Ordinal data could also include a grading system such as A, B, C, etc.

Nominal

Categorical variables cannot be added, subtracted, divided, or multiplied. When your data is categorized but has no specific rank order, select nominal. This could include the department a person works in, gender, mode of transportation, region, or religious affiliation.

Conclusion

In closing, the Variable View in SPSS is something that deserves attention. This seemingly boring task, especially defining the measures, could have an unintended impact on your results. If in doubt, reach out to your methodologist for help or reach out to us and schedule a strategy call!

To abbreviate or not to abbreviate – that is the question!

Have you found yourself writing your dissertation and you question if you should use a country name or some variation of an abbreviation? This blog post will help.

As an editor and professor, I read lots of dissertations and I find that it is common for there to be inconsistency with how students write out country names or use abbreviations in general. This blog post will focus on the abbreviation of countries, when to use periods with an abbreviation, and when to use abbreviations in general.

As a general rule, most abbreviations need to be introduced with the full spelling of each word first. For example, the American Psychological Association (APA) is the writing style of choice. Notice how APA is spelled out first. This should be the process with most abbreviations.

Commonly used abbreviations may not need to be written out. If the abbreviation is listed as a word in Merriam-Webster’s Collegiate Dictionary then it will not need to be written out prior to using it as an abbreviation. Examples of such abbreviations include APA, FBI, HTML, NASA, NBA, NFL, and PDF.

When writing your dissertation in APA 7, the rule of thumb is to spell out the full name of the country if it is used as a noun. For example, the United Kingdom or the United States of America. Below is an example:

Smith (2022) conducted a study of 331 healthcare workers in the United States of America (noun). She acquired their names and contact information from the U.S. (adjective) Database of Doctors.

An author can abbreviate the country name if it is used as an adjective. For example, the U.S. stock report or the U.K. education system. In the example above, I use the U.S. Database of Doctors.

Notice that when abbreviating a country, the abbreviation includes periods unless it is the heading or on the title page. It is best to avoid using abbreviations if at all possible in a heading or on the title page.

Using periods in the abbreviation of a country is counterintuitive as many other abbreviations do not use periods with APA style. If the abbreviation is in all capital letters, such as CIA, NYT, or TOC, the periods are not needed.

If the abbreviation is for measurements, the periods are not needed unless it is for inches. For example measurements of length would be ft or mi for feet or mile. The abbreviation for inch actually uses one period to avoid confusion (in.). Measurements of time would be abbreviated hr or min for hour or minute.

Other abbreviations should be used only if they assist the reader with clarity or if the abbreviation is easily recognized. It is usually easier to read a chapter if the words are spelled out. For example, transformational leadership theory includes the following four domains: idealized influence, inspirational motivation, intellectual stimulation, and individual consideration. Many authors will abbreviate each domain as II, IM, IS, and IC. While this is convenient on one hand, it can also cause challenges with readability on the other hand.

The problem usually enters the paper as the abbreviations are not used consistently. As a general rule, if an abbreviation is used, it should be used at least three times. Otherwise, it is not really adding any value to the paper. Another rule of thumb is that if an abbreviation is used, it should be reintroduced periodically, yet consistently. In the example of transformational leadership domains, I would advise against using the abbreviations; however, if an author wants to use them I suggest introducing the abbreviations the first time the words are used and then using the abbreviations for the rest of the section (think Microsoft style 2^nd heading). When the next section is presented, I would spell out the abbreviation again the first time in that heading and then use the abbreviations consistently throughout that section. This reminds the reader periodically of the full name without them having to search for it.

Overall, my advice is to avoid abbreviations unless they are absolutely necessary or they increase the readability of the document. If an abbreviation is used, make sure they are used properly and consistently. One final thought on readability is to use the Microsoft readability feature. To do this with your Word document open, select Home > Editor > Document Stats > OK. The readability scores will include Flesh Reading Ease and Flesch-Kincaid Grade Level. I have seen recommendations for dissertations to be at or below the 8/9 grade level. Check with your school to see if they have such a requirement.

Please contact us if have any questions about writing your dissertation!

Learning how to develop research questions is a big step in designing your research study and forces you to think about what you want to know as you gather data from your participants. No longer is the topic you’ve selected just a hypothetical issue you’re interested in addressing; once you have written the research questions, you realize that you must explain to the reader exactly what it is that you want to know at the end of your research. However, I often talk with dissertation writers who are confused with the difference between research questions and interview questions. Or, I will be reviewing draft interview questions for a client and come across questions that are much more suited for interview questions.

What, then, is the difference between research questions and interview questions? In short, research questions are questions you want to answer by completing your study. Interview questions are questions you ask of your participants to help you address your research questions. Sounds like circular logic, doesn’t it? Let’s dig a little deeper.

The need for interview questions is self-evident: you have participants and so you need to ask them questions in a qualitative study in order to collect data. So, why do you need research questions? Research questions are the pillars of your study: those key concepts you want to explore so that you can address the gap you have identified. See the image below:

Image description: Identification of the problem or gap leads to the creation of the purpose of your study. You’ve identified the purpose – the statement that explains what your study will do. The purpose statement is then further refined by the use of research questions.

Examples of research questions

What can we do to learn how to develop research questions? Writing the research questions is dependent upon several things: (1) the problem or gap you have identified, (2) the purpose of your study, (3) the qualitative approach you are using, and, sometimes (4) your theoretical framework. Let’s look at an example:

My problem statement is:

Instructional barriers exist for nursing educators in teaching with full body patient simulators remotely when instruction on campus is limited due to the global pandemic.

The gap I’ve identified is:

While there is extensive literature on the use of full body patient simulators in on-campus nursing instruction(citation of several sources would be listed here in a real example), there is a lack of research on how nursing educators can modify this instruction when learning is remote.

The purpose statement is:

The purpose of this qualitative descriptive study is to explore how nursing educators describe their strategies in teaching with full body patient simulators in remote delivery for ASN nursing students at a community college.

The theoretical framework I’ve chosen is:

Self-efficacy theory by Albert Bandur

In the above, I have addressed all four elements that I’ll need for creating my research questions, including #3, the qualitative approach. I’ve sneaked that into my purpose statement by writing, “this qualitative descriptive study.” Given that we know these four things, now we can begin writing our research questions.

How many research questions should you create?

I’m a fan of “less is more” when it comes to research questions, but again, the four elements above will dictate how many you need. Another factor – possibly a fifth one to consider – is how many does your dissertation chair want you to have? That will always be a consideration.

However, remember this: the number of research questions you have will determine how you divide up your data and report on it in chapter four. Thus, if you have four research questions, then you will have to divide up the reporting of your data into four discrete parts with each research question as a heading. If you have two research questions, you will divide the reporting of your data into two discrete parts.

Further warning, though: I’ve worked with many dissertation writers who believe more research questions are better, and then end up having to figure out how to split their data in a way that the answers to each research question is unique from the rest. Making it not sound redundant is challenging.

Pulling it together

Given the pieces of the puzzle I’ve listed above, let’s draft some research questions.

How do nursing educators describe their experiences in teaching ASN nursing students using full body patient simulators in a remote environment?

Note my setup of the question – how do they describe their experiences? That addresses my descriptive approach. This question is almost a rephrasing of the purpose statement as a question.

How do nursing educators describe the mastery experiences that influenced their strategies used in teaching with full-body patient simulators in a remote environment?

Here I’ve used describe again, and now I’m bringing in one of the tenets of self-efficacy theory that I will be using in my study – mastery experiences.

How do nursing educators describe the social models that influenced their strategies used in teaching with full-body patient simulators in a remote environment?

This question is similar to the one above it, but uses a different tenet of self-efficacy theory.

Here I will stop with my questions. In this made-up research study, I am only going to use two of the tenets of self-efficacy theory and I’ve created research questions around them.

Looking over my three questions, I see that two are different enough from each other – addressing mastery experiences and another addressing social models – to gather unique data to result in clearly discrete parts in my write-up in chapter 4. The first question is broader and gives room for me to create interview questions that perhaps align with the themes in the literature.

In the next post, I will show you how to develop your interview questions for your research to ensure that they are an outgrowth of your research questions and written in a way that will engage your participants, generating good data for your study. So, did you learn how to develop research questions? Let us know where you are in developing your research questions in the comments below.

The Problem Is Not the Purpose

This is the second of a two-part series (see the first article here). When working with new dissertation writers on developing their problem statements, I often ask them to complete an alignment exercise that has them write out their topic, the problem statement, and the purpose statement. New researchers may find this task difficult if they have not carefully considered what the societal, real-world problem is that needs to be addressed. In its place, I often see purpose statements of what they will do in their study based on the topic about which they are interested in writing.

Remember: the problem statement does not tell us what the study is going to do. It does not tell us what needs to be done. It is so tempting to jump to the purpose of the study or even the solution to fix the problem, but here you must stay focused: what is the problem you will address? Stay on that and don’t get ahead of yourself. Support it with literature…really dig in, and get very comfortable talking about and writing about the problem as it exists in the present.

Here’s an example of what I often see, based on my fictional paragraph on hierarchical employee structures:

The problem is that this study seeks to understand how employees in Fortune 500 companies perceive their opportunities for initiative in their work.

That sentence might seem glaringly obvious as (1) not a problem statement, and (2) vague because you’ve read up to this point, but I see this all the time from new writers. When you don’t know exactly what the problem is that you are addressing then it becomes really easy to slip in to telling the reader what you are going to study, instead. Remember: read the literature and let it guide you into understanding what the nature of the problem is within your topic.

The Problem Statement Section Is Short, Concise, and Robust

On average, the problem statement is two paragraphs. It is not long or filled with fluff. Think of it like a recipe: direct, concise, yet including all the ingredients. While I’ve seen problem statements as short as one paragraph or as long as four, the most common is a two-paragraph structure.

As a reminder: here is the first paragraph of our fictional problem statement section:

The problem is that the hierarchical employee structures within Fortune 500 companies diminish employee initiative. According to Johnson (2019), such structures inhibit decision-making, which leaves employees unsure if what they are doing is in line with departmental or corporate goals. In addition, Williams (2020) indicated that bloated management teams serve to protect management rather than employees who may be taking risks in proposing new methods, products, or ideas. Allen (2020) further explained that without changes by Fortune 500 companies in how they structure their employee hierarchy, corporate competitiveness will decrease as fewer new ideas and stale but safe products decrease consumer interest.

The first paragraph, like my fictional account above, is about the societal or “real-world” problem. The second paragraph is what I call the literature problem: i.e., there is a problem, and researchers have not adequately explored it (or examined it at all). While in the first paragraph your goal is to prove to us that the problem is real, current, and well-supported by evidence, your goal in the second paragraph is to convince us that the problem is worth studying. Not all problems are worth studying.

So how do you convince us that the problem is worth studying (and worth our time to continue reading about in your proposal)? The literature tells you it is. Thus, in this second paragraph you have to do two things:

1. Tell us what is known, and
2. Tell us what is not known but is worth knowing.

Here’s how this goes using my fictional problem statement:

While there is an abundance of research on the disadvantages of hierarchical corporate systems within Fortune 500 companies (Brown, 2017; Costas, 2017; Harris & Robinson, 2019; Washington et al., 2016; Wright & Eddington, 2021), there is a dearth of research on how employees navigate these systems when trying to present new ideas or share creative initiatives.

In one sentence, I’ve told you what is known and I have cited some of that “abundance of research” I alluded to, and I’ve told you what is not known (which I have not cited because there is a gap in the literature).

But we’re not quite done with paragraph 2. Now we need to prove that studying the problem is a worthwhile endeavor. Again, we turn to the literature:

Johnson (2019) conducted a quantitative study on the effect of hierarchical systems on management decision making, but recommended that future research explore the perceptions of employees in dealing with indecisive or contradictory management goals in taking initiative. Hernandez and Evans (2021) noted that a limitation of their research was a focus only on management bloat as it affected corporate competitiveness but did not specifically focus on the perceptions of non-management employees in the hierarchical structure. Further, Williams (2020) suggested that future research uncover the perceptions of employees who want to take risks but are reluctant to do so given the management focus on appeasing their managers and limiting all risk.

Thus, what we have done here is tell the reader what other researchers say must be covered. Why is this important and why can’t you – the dissertation researcher – just tell us this from your own, anecdotal evidence? After all, perhaps you’ve explored the topic you’ve chosen because you are immersed in it. If you’re the non-management employee working in a Fortune 500 Company you might see this every day and have strong feelings about the issue.

The reality is that you don’t yet have the authority yet to tell the reader what needs to be examined. You will get there, and in chapter 5 you get the chance to tell us what remains to be studied and should be studied based on the data you collected and analyzed. But in chapter 1 and this problem statement section, you are still exploring the issue, and you have to rely on researchers who have gone before you.

The Answers Are in the Literature

By now, you may be seeing a trend in what I’m saying: the answers to the questions you have about the problem you want to address are found in the literature. In truth, the answers to almost all of your questions about writing the dissertation are found in reading research studies – a lot of research studies.

You not only uncover the problem that needs to be examined in your study by reading the literature, but you can see how other authors have structured their problem statements and their problem statement sections. How do they go about supporting the existence of the problem they wish to study? How do they structure their sentences to be short, concise, and yet “full of all the ingredients” like a recipe is structured?

Another tip for acing your problem statement section when submitting it to your chair is to have read 5 or 10 problem statement sections in recent dissertations from the department or college at your university. Using Proquest’s Dissertation and Theses database enables you to look at published dissertations from your school, and possibly even your department or from committees in which your chair served. Doing this allows you to (1) see the structure that your university (and department) require, and (2) understand the quality of work that earned approval from the committee.

It’s the Underpinning of Your Entire Study

Overall, the goal of your problem statement section is to give us the ingredients of the problem and help us understand why it needs to be studied. The two-paragraph section should be short, well-supported, and devoid of fluff. The problem statement section sets up the rationale for your study, which leads directly into the purpose of your study that tells us what your study will do, how it will do it, and from whom you will collect the data.

If your problem statement goes beyond what I have outlined here, it likely means that you haven’t yet nailed down what you will study with the needed specificity. Remember: the answers you seek are in the literature. Other studies will help you see what remains to be explored. Keep reading, keep taking notes, and keep journaling. These practices will guide you in choosing the best problem statement for your study.

Writing the problem statement and the section in which it resides may not be what the new dissertation writer thinks of when they begin the journey of designing their research study. New dissertation writers are often frustrated with their progress, and invariably it has something to do with not having a clear problem statement or not having one at all. Unlike a typical graduate-level research paper, the problem statement is founded on a real issue that needs to be studied and is not just a topic of interest that you may have.

The problem statement is the underpinning of your entire dissertation. That may sound a bit hyperbolic, but it is the reality. While some universities do not even require dissertation writers to identify their problem statement but instead prefer they explain the purpose and design of their study, I still recommend to writers that they create this problem statement as it will guide them in writing every other section of their proposal.

The problem statement not only tells the reader what the problem is, but it helps us to understand why we should care. You are telling the reader that an urgency exists to conduct the study because the problem has been identified and you – the researcher – are going to tell us how you will explore the issue and what purpose it will serve.

The Problem Statement Is a Real Problem

By the time you get to the dissertation phase, you probably have a good idea of the topic of interest you want to explore. You may even know how you want to design your study and the population from which you want to gather data. However, this may be getting ahead of yourself. Is your topic built upon a problem you’ve identified? Is it a real problem in the world? Is your problem more than just a gap in the literature?

The first step in identifying the problem statement is to review the literature on your topic of interest and see what other researchers are saying still needs to be examined. You will want to take notes on the limitations of their own studies and their recommendations for future research because they are giving you a roadmap for your study! In reviewing 20 or so articles for your initial exploration of a topic of interest, you might find three or four that point you in the direction that is similar to the topic you were considering.

In all likelihood, they are going to give you much more specific recommendations than you were considering, which will help you narrow down your ideas. Save those recommendations and limitations you noted. You will want to use them in the problem statement section.

The next step in your dissertation is to ensure that the problem you choose to study is unique. There is little use in studying a problem that a hundred other researchers before you have studied. A quick exploration in Google Scholar can help you see the state of the literature on the problem you want to address. If you see other studies on the same problem, then you need to find an angle of the problem that has not been explored.

For example, are the other studies quantitative but you want do a qualitative exploration of the problem? Was the latest study conducted 10 years ago and a more recent study is needed? Were the studies you found all carried out in Europe and Asia but you want to see what the data would say when collected in the United States? Any decision you make regarding the choice of your topic should have a rationale, so be sure to take notes on the other studies and explain why yours still makes sense.

Finally, the problem in your dissertation doesn’t necessarily have to be a negative thing. A problem could be that we don’t know how something might work that could benefit society, or we don’t know how a particular population feels about an experience they shared that impacts our understanding of the event, or we don’t know what strategies might work best in a particular scenario. Here’s an example:

The problem is that it is not known how elementary specials teachers perceive the inclusion of STEM curriculum in non-general education classes.

It is not necessarily a bad thing that STEM curriculum is infused in arts classes, for example. The problem is that no one has bothered to ask the art and music teachers about it, and they just might have some good ideas for improving its inclusion! This is an especially salient problem statement if the population being researched is not achieving STEM goals and the dissertation researcher determines to collect data that might inform a better understanding of poor performance.

The Problem Is Supported by the Literature

After taking the steps outlined above, your next steps are these. You will need to prove, with several citations, that the problem exists, and that if it is not studied, there will be negative consequences. Also remember that you are proving the existence of the problem you mention in the opening statement. You do not add more problems in this paragraph. Here is a fictional example of what I mean:

The problem is that the hierarchical employee structures within Fortune 500 companies diminish employee initiative. According to Smith (2020), hierarchical systems result in bloated costs to the corporation. In addition, Jones (2021) noted that hierarchical systems result in less efficiency and create lengthier work projects. Finally, Gutierrez (2021) indicated that without a corporate reorganization away from the strict hierarchical model used by Fortune 500 companies, companies will increase their chances of poor management decisions that are costly.

In the paragraph above, the first sentence is the problem statement regarding management that stifles employee initiative. However, what do the sentences that follow it discuss? Bloated costs, less efficiency, longer time to complete projects, and poor management decisions. It’s true that all of these might be associated with strict hierarchical systems, but they do not support the statement about hierarchical systems stifling employee initiative.

Let’s revise this:

The problem is that the hierarchical employee structures within Fortune 500 companies diminish employee initiative. According to Johnson (2019), such structures inhibit decision-making, which leaves employees unsure if what they are doing is in line with departmental or corporate goals. In addition, Williams (2020) indicated that bloated management teams serve to protect management rather than employees who may be taking risks in proposing new methods, products, or ideas. Allen (2020) further explained that without changes by Fortune 500 companies in how they structure their employee hierarchy, corporate competitiveness will decrease as fewer new ideas and stale but safe products decrease consumer interest.

See the difference? We now have a first paragraph that (1) tells us what the specific problem is, and (2) directly supports the existence and reality of the problem with recent literature. We have proved that our study is based on a recent, real-world problem that other researchers have noted exists and has consequences. From this paragraph we have also established that our problem is specific.

In part 2 of this exploration on how to write the Problem Statement for your dissertation, we will discuss what goes in the second paragraph of this section as well as what the problem statement is…and is not.