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Hello Albert Many thanks for this paper! Overall, you have captured the main aspects of your research quite well. The literature review is generally well written. I have made a number of comments in the text and I encourage you to respond to them in cooperation with your supervisor. Overall, the paper needs tightening in the areas I have identified in my comments in the text. It’s been a pleasure to work with you!

Yusaf Akbar, Jan 4 at 2:12am Dear Albert, Thank you for submitting your Academic Writing Assignment. Mastering the skills for writing for an academic audience, whether via traditional or contemporary methods of constructing and presenting your arguments, will help you to improve your ability to think more critically about your research as well as communicate with colleagues and industry experts at a more sophisticated level.

The lessons, knowledge, and practice you have gained from this course will be used again and again as you continue to research, discover, and present new insights and opportunities for improvement within your field.

My goal is to provide feedback on your submission, specific to your quantitative analysis section, to help you strengthen the way in which you present your data insights and how to best use them within your paper. Data insights on their own are meaningless if you can’t communicate their importance and impact – you will need to learn to be one part artist and one part analyst!

Conceptual Model and Hypothesis:

 I would have appreciated the inclusion of a conceptual model within your paper, not just the appendix. You’d be amazed at the value add of including visuals (models, graphs, charts, etc) within your paper – it can allow you to convey a great deal of information in a very succinct and clear way and allow you more room to expand upon analyses and discussion.
I’m curious if you considered using Ethnic status of an employee as an additional mediator/moderator within your conceptual model? There might be value in examining how this variables plays on the construct of mentoring. Data Set: • Perhaps I read past this, but it wasn’t clear how you developed, or where you found, the scales for CAO. Were the items all developed from the “mentoring function scale”? My understanding is that you leveraged the previous scale to develop your items for measuring EMNS. A few sentences to further clarify the genesis of your scales and their validation status would have been valuable.
Why didn’t you include CAO as a variable within your correlation analyses? • Did you run any type of factor analysis to ensure all variables were useful? • There is a disconnect between your conceptual model and the regression analyses you ran. While I understand exactly what you were doing and why, it would be valuable to create continuity in your presentation to alleviate the disconnect.

Data Presentation:

As mentioned above, try to bring in more of your data via charts, etc, as this will improve readability and reduce the need for your audience to scroll between the appendix and their related sections of the paper.
Purely stylistic, but anytime you have a numeric value above ten (10), type out the number with numerals not text, it is easier to read and keys the reader into something that is most likely very important.
The regressions you ran need some review and refinement to better match your conceptual model. Your first regression leverages education level, ethnic background and age; however, only ethnic status is an IV in your model, why did you add these additional components? If you are asserting that these three components together create an aggregate variable upon which you want to test then that needs to be clearer (if I read past this and missed it I apologize!) Overall, nicely done Albert.

Your analysis demonstrated a good foundation for quantitative analysis. While there are some minor tweaks I would encourage this is something your supervisor can speak to better. Additionally, as you move forward with SEM I think you will be surprised by the potential insights you are able to generate, especially if you reconsider how you are leveraging the variable of ethnic status, and the component aspects of mentorship. Both of which are prime candidates for SEM analysis.

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