- The means adopted for the collection and generation of data
- The tools and techniques used for data collection.
Be Aware of what is expected in your discipline of study: The requirements are different in each of the academic study discipline. A scholar of philosophy may not need a much extended chapter of research methodology, but at the same time the scientific disciplines call for a detailed explanation of the chapter. As a researcher you must be well aware about the expectation that have been kept from your area of study.
Define the technical jargons well: There is typical terminology used in research methodology that is specific to the area of study. These words may not be used in day to day language and hence the chances are that the reader might not be aware of the jargons. With some investment of time and effort, these terms can be defined in the chapter, so that the reader finds it easier to comprehend.
Keep away from inconsistencies: The best way to keep away from inconsistencies is to talk about only that needs to be spoken about. If you have thorough knowledge about the concepts of your subject area, give focussed and limited information in a graduating flow. This would keep the inconsistencies away.
Define your data collection technique well explained: Do not be vague throughout your research methodology chapter. With good knowledge and conceptual clarity you would know that your research falls in which category. The three main categories being, qualitative, quantitative, and case study. Whatever be the category of your research, in clear language, and terminology give your data collection techniques, so that there isn’t any ambiguity in the mind of the reader as well.
Choose suitable data analysis tools: The collected data needs to go through some statistical tests and analysis. The data analysis techniques are again of two main categories, inductive and deductive. If the data is of many types, than more than one type of technique may also be needed in one project. But do not adopt multiple philosophies as that does not tend to help at all.
Give an account of your analysis: A clear explicit and concise explanation of your data analysis technique should be included in the chapter. This description of how you actually analysed your data can also be illustrated with relevant examples.
Make it interesting and revealing: Your thesis as a whole should be interesting and revealing so that in each chapter here is something new for the reader to know and there is curiosity and an element of surprise to move to the next chapter as well.