Handbook for Doctoral Students in Education/Chapter I Outline
Appearance
There is an infinite number of ways to introduce your dissertation research project. There does not seem to be a common way, however, may elements overlap. Think if it as a set of logical steps explaining what you are planning to do:
- What do you want to study?
- Why do you want to study it? Why is it important?
- How are you going to study it?
These questions can be answered through a series of logical steps, but not all of these steps have to be present in all dissertations
- Introduction/background. How did this study come about? What motivated you to do it? It is fine to list both personal reasons for doing a study and to show the extent of a problem that motivated you to do it. Make it engaging, and captivating, but don’t dwell on your life story; this is not a memoir.
- Problem Statement. It is a statement about what we don’t know, but need to know. There can be two subsets: a practical problem, and a theoretical one. For example, a problem can be that there is no effective strategy for preventing drop-outs among Hispanic boys. A theoretical problem can be that research does not show a comprehensive, multi-factored analysis of the causes of high school drop-out.
- Definition of Terms. Just define your main concepts – these can be either definition drawn from the literature, or your own.
- Purpose. Begin with “The purpose of this study is to…” change, interpret, understand, evaluate, or analyze the problem. Do I need to mention it needs to be directly aligned with the problem?
- Research question. Look at your purpose, and break it down into a set of questions that help achieve it. Do not go beyond 3-4 questions.
- Hypothesis. What are you expecting to find? What assumption are you testing? It is a lot more specific and formal in a quantitative study, and less specific in a qualitative one. Some qualitative researchers, usually of the anthropological bent, avoid the term “hypothesis,” since it refers to a positivist framework. They prefer terms like “hunch” or “conjecture.” However, you need a working theory of what’s going on, which can be proven or disproven. Laying out one or more rival hypotheses is always a great idea. For example, you think that family disengagement is an important factor determining the timing of high school drop-out. And you can find it through in-depth interviews and observations. But it may also be the case that the subjects
- Significance. If you answer the question, what contribution is your study going to make to the field and what sort of practical implications it may have? What is new about your study?
- Conceptual framework. The way you chose to think about the problem – which concepts did you decide to use and why? You can think about the same problem through different theoretical lenses. For example, high school drop-outs can be viewed as an economic problem (then you would use such concepts as human capital, return on investment, etc.), or as a psychological problem (personality traits, social inclusion, etc.). The same problem can be viewed as a pedagogical one, which will lead you think about engagement, curriculum, learning motivation, teaching strategies.
- Design. Give a brief overview of what exactly you are planning to do: sequence of measurements, ways of analysis, etc. A timeline would be great to include - proposed in a proposal, factual in a dissertation.
- Methodology rationale. How can a study like this be possible? Why a study like yours may actually work? Explain in very brief way why you chose the methodology. You will say more about this in a subsequent methods chapter.
- Assumptions/researcher’s stand. Make explicit things that you are not going to test, but which inform your views anyway. This is a more general theory of how things work, as well as your values as a researcher. A more detailed explanation and rationale will be given in Chapter 3.
- Scope and Limitations. There are methodological and conceptual limitations. Methodological ones include limitations of sampling, the method used, various data pollution scenarios, etc. The conceptual limitations are what you are ignoring because of the conceptual framework you use. Make sure to state the degree of generalizability of your future findings.