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In Part I, I discussed all the gobbledegook (technical term) that goes into the front matter of your dissertation proposal. In Part II, I describe the elements of the first chapter of a typical three-chapter proposal. I know what you’re thinking: What could be more fun?

The dissertation proposal: Chapter 1

Chapter 1 is the introduction to your study—you already know that much, I bet. A typical Chapter 1 contains the background, problem, purpose, research questions, maybe the significance of the study, a brief overview of your research plan, and a list of definitions of key terms.

Whew! A lot of stuff goes in Chapter 1. That makes sense. It’s an overview of your entire proposal, after all. What can go wrong? Plenty.

For best results, write Chapter 1 after you have written Chapters 2 and 3. Does anyone actually do that? I am positive many dissertations do not, judging by how what they write in Chapter 3 fails to align with what they wrote in Chapter 1. It’s like dissertation amnesia sets in somewhere in the middle of Chapter 2. Suddenly they forget they were planning a qualitative study and start waxing eloquently on the challenges of using probability methods to choose a sample size. Hooboy. Amnesia!

What elements belong in Chapter 1? Let’s briefly talk about each one, just to make sure we are on the same page.

Introduction. The first section if Chapter 1 is the introduction (duh), although according to APA style, we omit the “Introduction” heading, because I guess everyone knows the first paragraphs of a chapter constitute the introduction to the chapter. Thus, adding the heading is unnecessary. I can’t tell you how many times I’ve written that exact message in a comment box in someone’s dissertation—I can tell you, it’s a lot. This very common error is attributable to failure to read that pesky style manual. Come on, social science dissertators! Read your style manual.

The introduction to the chapter is not an overview of the study; it’s an introduction to the topic. I recommend writing the Background and Problem Statements before you write this section. The introduction is the setup. If you “preview” the main points that lead to the problem your study will address, your readers will be deeply comforted. Your reviewers will feel reassured (and more likely to approve your proposal) if your preview aligns with your background and problem statement sections.

Background. Often, the next section will have a subheading, “Background.” Write Chapter 2 first (Chapter 2 is usually your literature review); then you can copy and paste a few of the highlights here. I mean, copy a few sentences, the pithy ones that neatly summarize the situation. Don’t copy entire paragraphs! Reviewers really dislike reading the same material twice. Except for the elements that have to be consistent between chapters, I mean. Like your problem statement, your purpose statement, and your research questions. Gah! Did I just make things more confusing?

Problem statement. The problem statement should be one concise (250-300 word) paragraph stating explicitly the problem your study will address. Don’t pussyfoot around, don’t make your readers try to guess the problem from your eloquent pleading. Just say it: “The problem addressed in this study is…” Some institutions will have you state the general problem (the broad problem) and then state the specific problem YOUR study will address. For example, “The general problem addressed in this study is that dissertators cry a lot during the proposal-writing process. The specific problem addressed in this study is whether dissertators’ moods (measured on the Dissertator Mood Scale) correlate with how many times they submitted their proposals before receiving approval.”

Purpose statement. The purpose statement should clearly flow from the problem statement. Some experts recommend using the exact wording from the problem statement in the first line of the purpose statement (or as close as possible). For example, “The purpose of this study is to determine to what extent dissertators’ moods (measured on the Dissertator Mood Scale) correlate with how many times they submitted their proposals before receiving approval.”

The rest of the purpose statement should contain descriptions of the study’s implementation: the population and sample, the sample size, the recruiting method, the data collection and analysis methods, and the geographical area. Just lay it all out there. Quite often, the purpose statement is one paragraph, but generally does not exceed one page in length.

Theoretical (or conceptual) framework. For all you folks aiming at earning a Ph.D., this section is vitally important. To earn your degree, you must extend theory, not just apply it. If you are seeking some other type of doctorate, like a D.B.A. or Ed.D., you may not have to extend theory, but you still need some sort of explanation of what worldview you are using to organize your study.

That is why I am astounded that dissertators sometimes leave the theoretical framework section out entirely. Without some sort of theoretical or conceptual framework, your study has no bones. What would happen if your skeleton suddenly disappeared? Right. Like that. Not good.

What theory could explain why dissertators get more and more depressed as they keep submitting their proposals and receiving rejections? (I feel I can speak on this topic, having been one of those demoralized dissertators.) Maybe it’s because of attribution theory, or motivation theory, or even discomfort theory. If you have done your homework (read many articles and dissertations), then you know the theories that are relevant to your topic. You can try to debunk them, extend them, confirm them… you can even make up one of your own! But you Ph.D. wannabes gotta have a theory.

Some of you qualitative folks might not use an actual theory. Instead, your institution may require you to propose a “conceptual framework.” This kind of framework might not rise to the level of being an actual identifiable theory (although it might someday, thanks to your research), but it should offer the reader some explanation of why you think the phenomenon is happening. Are dissertators just a bunch of whiners? Could be. More likely, dissertators get discouraged when they don’t achieve their desired outcome. That could be your conceptual framework. Your research will explore, expand, confirm, or disconfirm that statement.

Research questions. Now that you know the problem, the purpose, and the theoretical framework you will use, you can write your research questions to align with those elements. Your goal is to make sure these elements are all aligned—that is, that they make sense in relation to one another, creating a logical flow, from problem, to purpose, to questions. The problem is XYZ, so my purpose will be to investigate XYZ, and therefore, my research questions will be logically aimed at resolving XYZ.

Right. Clear as mud? Well, aligning the elements of the proposal is by far the hardest part of the project. Don’t freak out—we all have to go through it. However, once you get all the pieces lined up, everything will suddenly fall into place. It’s a great feeling.

Nature of study. The nature of the study section might be a few paragraphs or several pages describing in more detail how you plan to implement your study. Specifically. I mean, truly nuts-and-bolts specific. It’s a distillation of Chapter 3—write Chapter 3 first, so you can pluck statements to describe the population and sample and explain how you plan to recruit participants. Describe your data collection and analysis plans in some detail, more than you wrote in your Purpose Statement, but much less material than you will write for Chapter 3. Don’t let this section be more detailed than your discussion in Chapter 3! That happens. Don’t do it.

Significance of study. The significance of your study rests on how well you can justify its approval. What will happen if we don’t get the benefit of the results of your study? Who will be harmed? What happens if you conduct your study? Who will be helped?

Social science dissertators seem to like to wax maudlin in their problem and purpose statements. That means they use frothy overly dramatic arguments to convince the reader that the problem they have identified is worth studying. I’m sorry to tell you, the frothy emotional appeal is not a sound justification for your study. Your best bet is to cite some previous experts in the field who recommended some future researcher (you, for instance) should study dissertators’ moods. If credible, peer-reviewed researchers say something needs to be studied, then you can feel confident you have a solid justification for your study.

Definitions of key terms. Usually, Chapter 1 closes with a list of definitions, arranged in alphabetical order, with citations. Don’t overdo it. You won’t need definitions of terms like dissertation, quantitative, or survey. Mostly, you should aim to define a key term the first time you mention it. Most of your readers won’t go back to your list of definitions to look something up—they’ll just flail along hoping it will all soon make sense. That is not what you want. Make it easy on your reader and provide all the help you can as they are reading, so they never have to stop and wonder, what the heck does that word mean?

Oh, yeah, one more thing. Whatever terms you decide to use, use them consistently throughout your paper. This isn’t creative writing, people. Take pity on your readers (and reviewers). Be consistent.

Next time, I’ll write about Chapter 2, traditionally the review of your literature. What could possibly go wrong? A few things. Stay tuned.

 

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If you haven’t felt like cheating at least once in your life, you aren’t human.

I sometimes see evidence of cheating in the papers I edit. Cheating can come in many forms, for example, surveying or interviewing only people you know or can conveniently reach, or fudging the data to support your foregone conclusions (falsifying or fabricating data). The most common form of cheating I see is plagiarism, which I will address in my next blog post. Today I ponder why dissertators may feel tempted to cheat.

I can say without any doubt that I am completely human. I cheated in second grade when I erased my arithmetic errors and tried desperately to fill in the correct answers without my teacher seeing. I’m sure she saw it all. I dreaded the public humiliation of being wrong even more than I dreaded getting caught. What a dilemma for a 7-year-old!

Research has rules. Following the rules associated with scholarly integrity are similar to following the rules of any other field. Driving has rules and consequences if you break the rules. Scholarly research and writing is no different. Temptation to cheat can happen to anyone, anytime. Most of us don’t know what heinousness we are capable of until we are pushed into a corner with our backs against the wall. Picture someone deprived of sleep, subsisting on sugar and carbs, with burgeoning flu symptoms and a deadline to submit at midnight Eastern time. That person is at great risk of cutting corners, if not outright cheating.

All about plagiarism for dissertators whose backs are against the wall

Reasons why we feel tempted to cheat

People cheat, or think about cheating, in their academic writing and research for a variety of reasons. Cheating can take the form of buying essays, plagiarizing others’ words, falsifying or fabricating data, even outright lying about our study results. Cheating happens, in graduate school (Google cheating in graduate school and prepare to be shocked) as well as after graduate school. The big drivers behind cheating are fear, laziness, a sense of entitlement, a desire to beat the system, and unrealistic assumptions.

Fear

We fear that we will fail, that our work won’t be good enough, that we aren’t smart enough … or we fear that we might actually succeed and have to live up to some vague standard of perfection. We fear we will miss a deadline or be criticized; we fear that everyone will realize we aren’t really cut out for doctoral-level work. We fear that the world will discover we are frauds, that we can’t spell, that we are too stupid to learn statistics, that we’ll never understand how to write in English. Fear, fear, fear, a whole lot of vague fear. If the thought of cheating gives you a sense of relief, as if you just dodged a bullet, or eases the pressure in your chest so you can finally breathe, then you know fear is your enemy.

Laziness

Maybe you aren’t scared, maybe you are just lazy. You may once have had good intentions, but now that the assignment is due, you shrug and submit your half-baked paper, because you can’t be bothered to find those missing sources or add those missing citations. All that detail work is not really your scene. If anyone notices, you can always fix it later. The thought of following every darn detail and nailing it to the paper seems like an unnecessary amount of grunt work, best left to eggheads. You tell yourself you aren’t really a cheater, per se—you are just pragmatic and efficient.

Sense of entitlement

You may have signed up for this doctoral program with no intention of actually doing all the work necessary to earn it. You’ve coasted by on your good writing skills until now, why would graduate school be any different? Adding citations is good for other dissertators, but you should be exempt from that rule and from all the other silly research rules that seem like they don’t apply to your unique and special situation and status. You wouldn’t use the word cheating to describe what you are tempted to do, but whatever—you are fine with making up your own rules. The problem is, you don’t learn from your mistakes. You repeatedly make the same errors, because you don’t take direction.

Desire to beat the system

Getting one over on the system can be a sport for some of us. Are you pumped up and excited at the prospect of testing the limits of what you can get away with? You may have quickly discovered during your coursework that your mentors weren’t all that nitpicky—they didn’t call you on every missing citation. It’s easy to assume you were winning and that you would keep on winning when you presented your research plan. A vague proposal is okay with you—you will pull the rabbit out of the hat at the last minute, figure it out on the fly, make it by the seat of your pants, pull yourself up by your bootstraps, crunch a few numbers, and slide into home victorious. A little fudge here, a little nudge there … it’s all part of the game, right?

Unrealistic assumptions

You may have enrolled in your doctoral program with the assumption that it would be as easy to earn as your Master’s degree was. You may have recently come to the conclusion that you are in over your head with this doctoral research project. Your struggle to get your proposal approved could be an indication that you aren’t ready for doctoral-level work, but you are in too deep to back out now. You feel the only good option is to cheat and hope you don’t get caught.

Consequences of cheating

Can you relate to any of these temptations to cheat? If at least one doesn’t make you feel a bit queasy, you aren’t awake right now: Your eyes are traveling the text but the conductor is sacked out in the caboose, if you know what I mean. Maybe you need to take a break and think about your academic career. Because that is what you risk when you give in to the temptation to cheat in your research and writing.

You aren’t the only one who has something to lose when you cheat. Think about the people who haven’t been helped and may have been harmed or killed because unethical researchers falsified data, leading to inaccurate conclusions.

Please don’t lie to yourself. You may think it won’t happen to you, but pressure can blow our ethical boundaries to smithereens. It can happen to anyone. It has happened to many: Wikipedia shows a list of research cheaters here.

The most common form of cheating is plagiarism. Next week I will discuss plagiarism, because I consider it a scourge, a veritable plague upon dissertator land.

For more insight into cheating and plagiarism, and for help getting your proposal approved, check out my book.

Dissertators often struggle with theory. Virtually all dissertators must grapple with theory when they propose their research projects to their graduate school reviewers. Many whose proposals I’ve edited seem to think they can just ignore theory altogether. They seem to have a hard time choosing a theory, applying a theory… or even understanding why they need a theory in the first place.

The two fundamental theoretical approaches—deductive and inductive reasoning—offer dissertators two viewpoints to help them organize their thinking when they plan their projects.

Deductive reasoning

Deductive reasoning starts with a general theory about how something works. We collect observations to confirm the theory. It’s a birds-eye view of your topic.

For example, we can start with a theory, like this:

PROPOSED THEORY: Dissertators who don’t get enough sleep are cranky and dissatisfied with their doctoral experience.

Using that theory, we write a statement (hypothesis) that we can test: “Getting at least 8 hours of sleep a night significantly reduces dissertator dissatisfaction.” Then we collect observations of dissertators who get 8 hours of sleep per night and compare them to the data for dissertators who don’t. I bet the theory is confirmed: Dissertators who don’t get enough sleep act a lot like cranky teenagers who don’t want to go to school.

What can go wrong? The main drawback with research approaches that use deductive reasoning is the fact that the entire research project depends on the validity of the original theory or premise. The premise is assumed to be true. If the premise is incorrect, your conclusions may be valid, based on your theory, but only for that sample. Generalizing or transferring your conclusions to some other population or setting may be impossible.

For example, you might assume that toy preferences among six-year-olds are determined by gender.

PROPOSED THEORY: Girls prefer dolls and boys prefer toy trucks.

If you think this, you wouldn’t be alone: the toy industry has assumed this theory for years. Children may not know much about theory, but they know what they like. With two brothers, I had many opportunities to enjoy toy trucks, racing cars, little green army men, and cap guns. However, I also had my share of Barbies and troll dolls. Preferences vary by child, but overall, apparently, there is evidence to confirm the theory that children’s toy preferences are gender-typed from an early age. See here and here. But not all researchers have agreed: see here.

Your study of 50 six-year-olds may confirm or disconfirm this theory, thus adding to the body of knowledge on the topic and helping parents feel a little less guilty about watching their little girls grab for Barbies and their little boys grab for Legos.

For more on deductive reasoning, visit one of my favorite websites, changing minds.

Inductive reasoning

Inductive reasoning works from the specific and generates a theory from the observations. We observe some phenomenon, analyze the observation data, draw some inferences about it (our theory), and then collect more data to (we hope) confirm our conclusions.

1. Observe
2. Analyze
3. Infer
4. Confirm

Instead of starting with a theory, we collect observations of a phenomenon and build a theory from the ground up. That’s why grounded theory approaches used in qualitative research are considered inductive.

For example, you notice dissertators in the School of Education seem to sit around the library and cry a lot. You wonder what’s up. You talk to 10 dissertators from different programs and find some similarities and differences in their responses. Based on these patterns, you formulate a tentative hypothesis:

PROPOSED THEORY: Education dissertators worry more about everything, compared to dissertators in the business or computer departments, who usually worry about nothing.

Your data led you to generate this proposed theory. Thus, out of your data comes a broad theory about the tenderhearted education dissertator. You didn’t start with a theory: you got down and dirty with the data and the theory emerged from the patterns and themes you extracted from your data.

What can go wrong? The main issue with inductive reasoning approaches is that data collection can be an open-ended process. This is primarily a concern among qualitative dissertators. You can’t know ahead of time how big your sample needs to be, because you plan to collect data until you reach data saturation—that point at which new data generate no new insights.

That might sound like fun to you, but it’s a red flag for your Chair, Committee, and grad school reviewers. They are nervous enough letting a novice researcher collect data from human subjects: They know what can happen when overly enthusiastic interviewers go off the rails. What do I mean? Think about it: Pumped up (desperate) dissertators may badger, cajole, and otherwise manipulate their subjects into talking, thus injecting bias in their data, and setting up potential IRB issues for the institution that gave these dissertators permission to conduct research. That is why the idea of giving you a blank check to talk to an unknown number of people makes IRB reviewers shiver in their boots.

For more on inductive reasoning, visit changing minds.

Which approach should you use?

Most dissertators’ projects fall into the category of deductive reasoning. They start with a theory, collect some data, and see how their findings confirm or disconfirm the theory. This time-tested approach is safe and familiar, has lots of support in the literature, and your reviewers know and understand it. You are more likely to get your dissertation proposal approved if you use a deductive reasoning approach.

However, for all you off-the-beaten-path dissertators, if you can convince your Chair and Committee members that you can implement it successfully, the inductive approach is for you.

Misusing theory (or not using theory at all) is one of the reasons you might fail to get your dissertation proposal approved. If you need some help with your proposal, check out my book, available now through Amazon in both print and Kindle formats.