Forming a good question is often the most difficult part of the planning process. This is because the exact language of the question frames the rest of the project. Most researchers do this step repeatedly as they change their question in light of previous research and other constraints.

• Find a subject that is interesting to you.
• It should be feasible within your resource constraints, such as time and money.
• It should lead to new and distinctive insights.

The 'literature review' section in academic research demonstrated that researchers have thoroughly and systematically reviewed relevant findings of previous studies on the topic.

• Your research project should include something similar to a 'literature review.'
• Write at least six bullet points describing the major findings on your topic by other people.
• Using this, you should be able to point out where you could provide new and required insights.

Two basic rhetorical positions can help you frame the novelty-and-importance argument in academic research.

• Build on or extend a set of existing ideas. 'Person A has argued that X is true. This implies Y, which has not yet been tested. My project will test Y. If I find evidence to support it, it will change the way we view X.'
• Argue that there is a gap in existing knowledge, either because previous research reached conflicting conclusions or failed to consider something important.

The overall goal is to show that your research will be part of a larger conversation: How your project flows from what's already known, how it advances, extends, or challenges the existing knowledge.

At some point, you'll need to consider which data source and analytical strategy are most likely to give the answers you need.

• Consider whether your question would be best addressed by qualitative data (interviews, observations, or historical records), quantitative data (surveys or census records) or a combination of both.
• You might need to collect your own data, or it might be available in an existing database.

The point is to plan research, not to conduct it. The purpose of this step is to think through a feasible approach to answering your research question. You might reevaluate and revise while planning your project as new and unexpected avenues are revealed.

A systematic approach will establish the building blocks of your research project.

• Clearly describe the question you've chosen to study.
• Summarise the state of the art in knowledge about the question, and where your project could provide novel insight.
• Identify the best strategy for collecting and analysing relevant data.

Ask yourself:

1. What will be the general topic of your paper?
2. What will be the specific topic of your paper?

Write down your answers in bullet points accepting that you'll probably change your answers as you read other studies on your topic.

These questions should drive your analysis.

• Your question(s) should be phrased in a way that you can't answer 'yes' or 'no.'
• It should have multiple plausible answers.
• It should be framed in terms of How? or What?, instead of asking Why?

Your background information should come from scholarly books and journals, or reputable mass media sources. Use search engines such as JSTOR and Google Scholar.

Create an annotated bibliography by providing at least ten sources relevant to your topic.

• Name of author(s).
• Publication date.
• Title of book, chapter, or article.
• If it is a chapter or article, write the journal's title or book where they appear.
• A brief description of this work, including the main findings and methods.
• A summary of how this work contributes to your project.
• A brief description of the implications of this work.
• Identify and gap or controversy in knowledge this work points up, and how your project could address the problem.

Write a short statement of about 250 words about the kind of data that would help address your research and how you'd analyse it.

• What are the main concepts or variables in your project? Include brief definitions.
• Do any data sources exist on those concepts, if not, would you need to collect data?
• _Of the analytical strategies you could apply to your data, which would be the most appro_priate and the most feasible?