Proofreading by a UK PhD

Many students read 10, 20, or even 30 journal papers but still don’t know how to turn that reading into a proper literature review.

In this video, I share my 5-question strategy for reading a journal paper critically:

Why was the paper written?
What problem did the paper try to solve?
Was the problem solved or not?
What were the limitations?
What can your study do better?

I also show how to use one important Scopus and Web of Science paper to identify the Critical Literature Review, build a clearer Problem Statement, understand the research gap, and convert reading into a proper literature review write-up.

This method is important not only for Chapter 2 Literature Review, but also for building a stronger Chapter 1 Introduction, designing the Conceptual Framework, choosing the right Research Methodology, justifying Chapter 3 Methodology, preparing Chapter 4 Data Analysis using tools such as Smart PLS, SPSS, NVivo, and Atlas Ti, strengthening Chapter 5 Conclusion, and preparing better for Viva.

Whether your study is Quantitative or Qualitative, you must know how to read journal papers critically before writing your thesis.

If you are struggling with your thesis or dissertation, comment your topic and one important reference paper. I may use it for the next example.

PhD Timeline to graduate-on-time!

2nd year: Finish ethics and pilot, data collection, and data analysis.

3rd year: Finish chapter 4 data analysis and chapter 5 conclusion, and add the final touch-up to your thesis, final proofreading, VIVA, and finish corrections from VIVA.

Follow this timeline to graduate-on-time, or if you can do some parts slightly faster, you can graduate before time!

Chapter 1 Introduction tutorial: why your proposal still looks weak even after using AI

A weak Chapter 1 Introduction can destroy the direction of your whole study. If the opening is unclear, your Chapter 2 Literature Review becomes unfocused, your Chapter 3 Methodology becomes hard to justify, your Chapter 4 Data Analysis feels disconnected, and your Chapter 5 Conclusion becomes less convincing.

AI can generate words.
But it cannot fully understand your context, your research gap, and the real flow of your study.

If your Chapter 1 is wrong, your whole thesis can look weak in front of the examiner.

Watch this video before AI destroys the foundation of your proposal.