1. Background/literature review
An effective literature review is one that shows how your research question(s) is situated in the relevant literature in your field, not one that demonstrates that you have read a lot of that literature. So, don’t include lots of literature on related topics that are not specifically relevant to what your study will focus on.
2. Research questions
Research questions may be exploratory, confirmatory, or explanatory, or may not tidily correspond to any of these categories. Regardless of which of these they are, they need to be clearly and explicitly stated. And make sure that they are actually questions .
Design science proposals, rather than stating research questions, should state clearly the artefact to be designed.
3. Data collection strategies You need to be very clear in describing the data/evidence that you are using. Justify your case selection and/or sampling strategies. Which data collection tools do you propose to use ? Again you should try to justify the choices that you make, within the practical limitations of your project and time frame. What are the strengths and weaknesses of the choices that you have made?
4. Data analysis strategies Given the decisions you have made about your topic, research questions and data sources – what are the most appropriate forms of analysis? Here you should discuss the analytic method and how it helps answer the question. Note that software is not a method: we do not care if you use Nvivo or Stata, we do care if you use thematic analysis or logistic
regression.
5. Anticipated outcomes of the study What insights do you expect to be drawn from your anticipated findings? How will they complement the academic literature you have read about the topic you are studying? What are the consequences or lessons might be for practice, policy or public life?
