Lead Lecturers

What is academic writing?

Academic writing:

• is a formal way to write in academia

• is well structured both at paragraph level and overall 'paper' level

• uses more formal vocabulary, grammar and sentence structure

• uses references from academic literature to support the points being made

• is not a casual way to communicate and differs greatly from casual 'everyday' writing

• is a serious and professional way to communicate with your academic peers and university teaching staff.

• Avoid writing in the first person ('I', 'we', 'us', 'our' etc.) unless writing a reflection, or the Methodology section of a report.

• Avoid the use of questions; academic writing should 'inform' rather than 'question'.

• Avoid using emotive language, e.g. It is a shame that the government is really resistant to addressing these dire circumstances.

• Avoid vague vocabulary such as 'a lot’, 'good/bad’, 'get/give', 'things', etc.; use a thesaurus to find a specific, unambiguous alternative.

• Do not use contractions, e.g. isn't, won't, don't, can't, etc.

• Do not use colloquialisms, slang or jargon.

• Do not write only of your opinions; academic writing needs interpretation and research to underpin your thoughts or perspectives.

• Avoid gender-specific language when it is inappropriate. For example, instead of referring to 'man' or mankind' to refer to humanity as a whole, use terms such as 'humankind' or 'people'.

• Avoid gender-specific language when it is irrelevant or unnecessary. For example, instead of referring to a 'competent female manager', simply refer to the 'competent manager', unless it is essential for the reader to understand that the manager is a woman.

• Avoid using pronouns such as 'he' or 'she' unless you are sure of the person’s gender; consider alternatives, such as alternating which pronoun you use, or replacing these pronouns with 'they' or 'who'. For example, instead of stating, 'If a person is excluded, he should formally complain', try, 'A person who is excluded should formally complain'.

• Avoid language that may imply a negative attitude to someone based on their race, religion, skin colour, ability or sexuality.

• Focus on the whole person, rather than their attributes, unless their attributes are relevant and significant to the text that you are writing.

• Be very clear about the specific purpose of the writing task – what have you been asked to do?

• Seek clarification if in doubt.

• Ensure that you are following the instructions of the task strictly and carefully.

• See the section on 'Easy steps to writing an essay' for more information on how to interpret an assignment question.

• The most obvious audience for your assignment is 'your lecturer/tutor' who is also the 'marker'. Do not leave out any basic or essential information because you think it is too obvious for them. Your lecturer/tutor expects you to show that you know the material and the subject matter and that you are able to perform the task at hand.

• Imagine that you are writing to someone in order to teach the person about the topic. Consequently, you need to be explicit and clear.

• See the writing section of this website to develop your skills in paragraph writing and meaningful sentences.

• nature and purpose of the task

• lecturer’s requirements

• assignment type – e.g. case study, report, reflective journal, literature review.  Each assignment type has different requirements in regards to the structure and appropriate language

The following examples show that effective academic writing is more formal, professional and authoritative in tone. For example:

Casual writing = Kids' education these days isn't as good as in the old days, is it?

Academic Writing = It can be argued that children's education is not currently as effective as it has been in the past.

TIPS:

Effective academic writing uses inclusive language without bias.

TIPS:

The right tone in your writing depends on your understanding of the topic

When you think about the future of the business world, what comes to mind? Chances are, you may think of artificial intelligence running much of the busy work that companies have. It is a concept that is not too far off, but it may be machine learning which dominates the business landscape instead of AI. While similar, machine learning and artificial intelligence are still quite different, with machine learning involving machines learning specific functions over time. The algorithms used are designed to improve with each successive iteration, getting smarter as more time passes. We do not have to stretch our minds too far to see the future in action. Real-world applications of machine learning solutions are already prevalent in business.

Why is Machine Learning Important?

Businesses have always sought ways to make their operations more efficient and effective, thereby cutting costs and increasing profits. Machine learning is simply the latest technological tool to be used to those ends. This is compounded by how important collecting and analyzing data has become in today’s business world. To stay competitive, companies have needed to use the best machine learning software to utilize that data properly. With the many different types of machine learning out there, nearly every industry can benefit from this technology.

Machine Learning Examples in Real Life

It is easy to say that companies should adopt machine learning solutions for their businesses, but some might not understand what machine learning can do. So it is essential to look at each machine learning application for the real world to see how best to apply it for your operations. Many of these solutions have been in place at companies for years now.

One of the most common examples is machine learning algorithms’ ability to identify market trends and perform market analysis. This has been especially helpful for companies in the financial industry, but since every business needs to be on top of market news, it can be used almost anywhere. Machine learning works in this category by analyzing vast amounts of data to identify specific patterns indicating what markets will do soon. Some of these signals can be slight, possibly so small that a human observer would miss them. However, with enough data points, machine learning can pinpoint them and give companies valuable information on what the market will do in the days, weeks, months, and even years ahead. Best of all, this type of analysis can be done in real-time. With this information at hand, companies will always be prepared for what is to come.

Of course, one of the keys to company success stems from providing the customer with a high-quality experience. Machine learning can help in this regard as well. One area, in particular, comes from giving customers accurate product recommendations. You have likely come across this feature when shopping on Amazon or watching movies on Netflix. Machine learning helps in this process by taking a customer’s past actions and behaviours and determining what kind of products they would be most interested in based on this data. This is especially helpful for eCommerce companies, who rely on repeat business and customers purchasing multiple items. If a customer knows that a company has a good idea of what they like, they are more likely to stick around.

Improving the customer experience with machine learning can go even further than that. With machine learning algorithms, businesses can improve customer retention. Companies are collecting a great deal of data on their customers, and it’s through analyzing customer behaviour that machine learning can pick up on specific “warning signs” that a customer might soon leave. If companies know a customer is on the verge of leaving, they can take further steps to keep them around. Even in this approach, machine learning can make a difference by basically identifying the next best course of action in retaining the customer.

While much of the focus on machine learning is on improving customer relations, there are aspects and work processes within the organization that can be improved. Take hiring practices, for example. A typical job opening at a large organization could get dozens, even hundreds of applicants, and sifting through them all can consume a lot of time and resources. That’s where machine learning can step in and direct companies to the best applicants. Machine learning algorithms, based upon past and current successful employee data, can determine which of the applicants would have the best chances at being successful at the job. This can narrow down the field to something much more manageable. Machine learning can also eliminate potential biases that can come up in hiring practices, which would lead to a much fairer process on the whole.

Machine learning can also play a role in helping organizations improve their overall logistics. The supply chain can get quite complicated, especially when a business doesn’t have control over every step of the process. If something goes wrong, it can cripple a company temporarily. Machine learning algorithms, in this case, can be used to predict when things might go wrong, such as an accident at a factory. If something unfortunate does happen, machine learning can also be applied to finding solutions to mitigate the damage and keep businesses up and running despite the setbacks.

Medical and insurance companies are seeing the benefits of utilizing machine learning in their practices. This can also benefit the health of patients and customers through the use of health monitoring. Through various wearable devices, organizations can now collect data on a person’s health, anything from their heart rate to how many steps they walk each day. Based off of this information, the health industry can get a better understanding of how healthy someone is. Machine learning algorithms can even detect if future health problems may arise or predict if something bad might happen soon.

Another machine learning application in the financial world includes risk assessment, a significant area for investments. By analyzing market data, machine learning algorithms can get a good idea of what moves will most likely see a return on investment. At the same time, they can help companies steer clear of investments that carry too much risk, even if, on the surface, they seem safe and secure.

The Future of Machine Learning

As impressive as machine learning capabilities are today, the possibilities of what it can do in the future are making many of the top machine learning companies excited. Security is one area that holds much promise. While strides have been made in spam reduction, realm time machine learning advances make improvements to cyber-security likely. In this way, potential malware attacks can be sniffed out and taken care of before they have the chance to do widespread damage.

Expect further advances in image and voice recognition, which is already seeing some impressive leaps thanks to virtual assistants' proliferation. It could be that one day soon, nearly every device we have will respond with remarkable accuracy to voice prompts.

Machine learning, in general, will also get better over time, as is its nature. Many of the examples given above will only become more efficient as machine learning algorithms become more ingrained in business practices. While some machine learning problems still need work, these real-life examples show that machine learning promise isn’t all hype — it stands to transform businesses completely.

The following are the top 31 academic research project defence questions you may encounter during an academic research project defence. Please use this guide to assess yourself to see if you are ready for your research defence. Observe these questions and the recommended steps to answering them. We went through the record of past academic research project defence questions. I am also advising that you go further and ask past students about some of their academic research project defence questions they encountered during their defence. Just make sure you do not restrict yourself to only these questions.

Question 1: What is Your Research About?

That this is the first academic research project defence question you are asked does not mean you should take it lightly. Every academic research project defence question is geared towards testing how well you understand your research study area. Here they will ask you to explain to them in a few sentences what your research is all about. Is the question basic, right? This is a part of the academic research project defence process that gets most students choking for words. At any rate, the questions are simple, and as a student either BSc or MSc or DBA or PhD, as a student during your academic research project defence, the least that is expected of you is for you to know what your research is all about.

To answer this academic research project defence question, you have to know everything about your research project, from the first chapter to the last. To answer this question, all you have to do is to give them a summary of the research. At this stage, your abstract is your friend. Yes! Before going for your academic research project defence as an undergraduate or postgraduate, you must have mastered your abstract's content. You should, at this time, be able to pour out the content of your abstract to them boldly. And this is one reason why I have always advised that your abstract should never be taken for granted while writing your research. It is the work's synopsis, and a better understanding of your abstract is all you need to get past this often embarrassing question.

Question 2: Why did you decide to undertake this specific research?

Watch out! Take your next step carefully. This particular academic research project defence question can be too complicated, and it goes a long way to persuade the board that you have done a relevant study. The question could also come in a more direct form and they could ask you, “What is the research problem”

This is how you should answer this question. You may choose to expound on the issue(s) examined in the study. Your decision to tackle this problem turns into your inspiration. Try not to state monetary reasons or the need to graduate as inspiration, as you may effortlessly go off point. This questions could give birth to the following questions, so prepare for them:

Questions 3: What are the motivations for your research?

Question 2 and 3 may look similar, but answering them may reveal a slight difference. You could be motivated by solving an existing problem to embark on this research. You could be inspired by the need to contribute to the body of knowledge in the field. You could also be motivated by professional curiosity.

Question 4: Why is the problem you have tackled worth tackling:

not all research-able problems are worth tackling with a full academic study, and please note. You should be able to identify the issue being tackled as relevant enough to warrant an academic investigation into its resolution.

Question 5: What are the main aims, questions, hypotheses?

Do not worry too much about this particular academic research project defence question if you are an undergraduate. This question may only come up during a PHD level defence. 

Question 6: How will this study contribute to the body of knowledge?

This is one question that has not changed over the years. At this point, you are required to justify how your study will add to the existing body of knowledge. This is the part where your method, contextual analysis or any special model or conceptual framework utilized as a part of the investigation should be used to defend it.

Question 7: What is the significance of the study?

Much the same as expressing how your study will contribute to the existing body of knowledge, you should explain the significance of your research. To answer this question, you should explain how your study will help the Government to approach the creation and development of policies, how it will help different students who may wish to conduct research on the topic and how organizations and the general public will profit from your study.

Question 8: Did you bridge any gap from your study?

You must use your academic research project to solve an existing problem; now, what is the problem, at this stage you must define the issues that your research was conducted to approach, you must identify existing knowledge gaps in your research are for example, research on automated teller machine usage in Singapore, from this example the knowledge gap could be the fact that up until your research no scholar or academician have attempted to provide us with the necessary facts behind the use of Automated teller Machines in Singapore and because of this financial institution and the Government do not have the necessary scholastic contribution to their decision making process on this issue. If you follow this example, you have already identified a knowledge gap

Question 9: What limitations did you encounter?

This is another straightforward, however precarious, inquiry. To answer this question, you should be watchful with words as you may trap yourself. Be sufficiently ready not to offer out yourself. Try not to talk about the limitations in your data analysis procedures, as this may infer that your examination might be one-sided or not well researched. Use specific and more obvious limitations like the issues you encountered joining addresses and task instead of restricting your investigation.

Question 10: What are the principal findings of this research project?

Briefly explain the outcome of your study. Please, it is imperative at this stage that you link the result of your research to your research question to avoid veering out of point. Connect your findings to your research goals/questions. This will make the board to be carried along effectively.

Question 11: How do your findings compare with other research in this field?

List out your findings and list out the findings of other projects in the same field, and highlight the gaps that your research serves to fill. Explain how the findings of other researchers only do to complement but not to invalidate your research.

Question 12: Comment on and Justify Your Research methodology.

To get past this part of your academic research defence, you must have a sound knowledge of your Chapter 3. Explain your research methodology to them and the reason behind your choice of that method. At this point, your ability to justify your sample size and technique will be highly rewarded here.

Question 13: Why choose this method?

You should be able to at this stage explain the reasons behind your choice of method. If you are going to defend your research, you will protect your research methodology, which is not as difficult as it may seem. Just quotes studies where this method have been used in the past to support the reason behind your choice of method.

Question 14: In light of your discoveries/findings, what are your recommendations?

Recommendations are indispensable in each study. It would be best if you made recommendations. But if you have survived the academic research defence process up to the point where you are asked this question, you will not have any problem when you are asked to reveal your recommendations.

Question 15: where did you go wrong?

Again, you must avoid exposing your weak point. You can point out obvious mistakes like grammatical errors and typographies but do not ever pick a hole in your method or statistics. Avoid exposing the weak points in your research.

Question 16: Based on your findings, what areas will you suggest for future research?

When you are asked this particular academic research project defence question, you should try to make suggestions for future researchers. For example, if I researched the challenges of automated teller machine usage in Singapore, the right area for prospective study may be in electronic banking or point of sales systems. The best way to get past this is to identify the knowledge gaps still existing within the area of your study. These knowledge gaps should already be evident to you during the research process.

Question 17: What is the practicability of your research?

This question is always easy for science students and engineering students, but for the social scientists or management science students, it may be a bit tricky because their research is mostly in the form of abstracts. However, you should try your best to be realistic here. Relate your study to current trends in your environment, office, economy, Government, schools, church etc. The use of relevant examples and illustrations will score you a good point here.

Question 18: How would you summarize your study to a practitioner in a few sentences?

Here you may want to start using technical terminologies and words related to your research like you would do if you were in front of an expert in that field. Just summarize the technical importance of your research. Your capacity to pass on specialized data from the investigation will score you great focuses here.

Question 19: What would you change if you were to conduct the study again?

Sometimes such academic research project defence question are asked to trap you into exposing the weaknesses in your research; the question is meant to point you towards the weaknesses in your research so please just do the same thing I asked you to do in question 6.

Question 20: What is your measurement Instrument?

This academic research project defence question is simply an inquiry about your data collection method for the study. Here you state if questionnaires were distributed or data was gotten from secondary sources. For more information on measurement instruments

Question 21: What are your research variables?

Here you will need to convince the board members that you know what you are talking about. You need to explain your independent and dependent variable(s) to convince them that you are on point. Your variables are present in your project topic. You need to identify these variables and know their definitions as well to ace your defence.

Question 22: What are your research questions?

This should not pose any challenge, as your research questions are clearly stated in chapter one.

In answering the above question, you should also watch out for this other question:

• How did your research questions emerge?
• Why are your research questions interesting or important?

Question 23: What do you plan to do with your research project after Graduation?

If you intend to publish your research or make some parts of it available to an online journal, then this is the part where you would mention that. Suggesting that you want to make your research available online for future researchers or as a part of an online publication is always a very impressive idea.

Question 24: What source of data was employed for the study?

At this point you have to state the source(s) you got data from. In general you have to state whether data was gotten from primary or secondary source or both. You can further convince the committee members by discoursing on literature reviewed for the study-both theoretical and empirical.

Question 25: What theories or theoretical framework is your study based on?

Never you go for your research project defence without a  knowledge of  at least two relevant theories that relate to your study. For example, the “impact of motivation on employee productivity” will be based on Maslow’s Theory and other theories of motivation. If you cannot find relevant theories to back up your study, consult your supervisor for help or send us a mail let us connect you with a research expert.

Question 26: How would you relate your findings to existing theories on the study?

Now, this particular academic research project defence question. It is wise to read about how your research relates with existing theories in your study. You should know existing theories on the subject matter as well as empirical studies too. Your ability to link your findings to previous research studies (Whether they agree or not) will go a long way in validating your study.

Question 27: How has your thinking changed as a result of your project?

They want to know what your initial opinion about the study was and they are watching to see if your opinion have changed during the course of the study. You have to be very careful in answering this questions because you must give tangible reasons for any change in opinion and if care is not taking you may make your research seem obsolete by saying your opinion about the research changed during the course of the study. be very careful when answering such academic research project defense question that may invalidate your research.

Question 28: What recommendations do you have for future research?

this academic research project defense question is tasking you to Identify areas that you think may need more research.  This is easily done by identifying issues around you that are not yet researched and highlighting them out as filled with prospects for future research.

Question 29: What is the scope of the study?

State the delimitation of the study in brief. This could be date or geography or both.

Question 30: What question(s) do you have for the committee?

Not a likely academic research project defense question in our Nigerian context. This is an opportunity to interact with your committee members and ask some constructive questions. Do not ask silly or too difficult questions as the goal should be to make the committee members feel as the “judges”. It will also go a long way in showing that you are a brilliant and confident.

Question 31: Do you have any closing statements/comments?

When you are finally asked if you have any closing question, you can now be rest assured that there may not be any further questions so you can relax and use this opportunity to thank members of your committee for their time and questions. Tell them you appreciate all the valuable lessons you have learnt from them overtime and that you will implement all the important suggestions made and make all necessary corrections.

This single act alone would make your internal and external supervisor to see you as somebody who is willing to learn and who is ready to take corrections.

Formula of Pearson Product Moment Correlation