THE TOP 10 TIPS for WRITe your PRIMARY RESEARCH

1. CLARIFICATION OF RESEARCH QUESTIONS

In the initial stages of writing your dissertation, the objectives and research questions may appear vague and open-ended. When you begin your primary research, however, you should start by defining your primary questions, or you risk losing your entire concentration. Make sure you write your questions in a precise manner. Write them down, and remember them all the way to the front.

2.   STUDIES THAT ARE COMPARABLE

Find studies published that have similar goals and scope to your own to discover some potential models or models for your own strategy. In many cases, this may trigger warnings of unanticipated obstacles and challenges that are better managed if they are established prior to the time.

3.   ALTERNATIVE METHODS

There's always a factor of choice among competing research methods. Analysing the implications and nature of each methodology is an entire task and must be done carefully. Make a list of alternatives and evaluate the benefits and risks of each.

4.   ETHICAL QUESTIONS

Certain areas of study are more ethically laden than others. However, most projects require at the very least a few minor ethical decisions. Security of data and confidentiality are only two typical issues that need to be addressed in a direct manner.

5.   TIME PLANNING

Primary research is an extended process that could get out of hand in the event that no constraints are put in place. A realistic and flexible plan of time is a great device to ensure you are on the right track when it comes to addressing your research needs.

6.   LESS IS NOT MORE

You can trim down and alter large amounts of data if you realise that you don't have enough space to integrate it all, but not in reverse. Be sure your research is sufficiently extensive that you don't end up in the unfortunate situation of trying to increase the size of the data analysis section of your book.

7.   THE SYSTEMATIC COLLECTION OF DATA AND STUDY

Certain research projects can yield so much data that the absence of a well-organized approach could result in a disaster. Be serious about filing. Preserve digital and paper copies and do not depend solely on memory to differentiate between different data sets.

8.   QUANTITATIVE DATA COLLECTION

When collecting quantitative data, it is important to be aware of the application of different statistical measures to the data you're collecting. Concerns about precision, accuracy, and reliability are all addressed in this article and will be a major factor in how you approach conducting your research in quantitative terms.

9.   QUALITATIVE DATA COLLECTION

The main concern with qualitative research centres around the question of how much information from small sample sizes can be generalised. But any limitations in terms of quantity are compensated by the depth of information and the narrative. Design topics for interviews and discussions that do more than scratch the surface.

10.  DEVELOPMENT

It is crucial to remain focused on the primary research questions. Be aware that it is beneficial to follow your intuition when your research is beginning to gain momentum in a certain direction. Be sure to stay away from the goals you have set and be aware of the issues that may be outside the main concentration.

DISSERTATION TUTOR

A dissertation tutor can be an invaluable resource when it comes to understanding the systematic collection of data and study for your research. They can work with you to develop a comprehensive research plan that outlines the specific methods you will use to collect data, such as surveys, interviews, or experiments. Additionally, they can help you identify the most appropriate methods for analysing your data, such as statistical software or content analysis. A dissertation tutor can also assist you in identifying potential pitfalls and ethical considerations, such as ensuring participant anonymity and obtaining informed consent. By working with a dissertation tutor, you can develop a more systematic approach to your research, ensuring that your data collection and analysis are rigorous and thorough.