How to Write an Academic Journal Article

1. Introduction: Hi friends, welcome to this course on how to write an academic journal article. I'm Dr. Lyndon Walker, and I will be guiding you through this course. So anyone can write an academic journal article. And I've put anyone in quotes because there are, there are some qualifies to that. So when I say anyone, you don't need to be a university lecturer. You don't need to have a PhD, but you do need to produce work. That is all the quality that one of these people would produce. So that possibly eliminate some people. But for you, if you brought and motivated and you can write well and you can do appropriate analysis, then it's completely reasonable that you could publish your own academic journal article. It's not just for literature is a new university people. So in this course we're going to run through the various steps. In some ways it's going to be like a research methods course, but condensed down to a much shorter time. There is a little bit of assumed knowledge hand. So I have another course which is how to read an academic journal article that talks a lot about how to find academic journal articles, what they are, how they're structured, and how you would go about reading them if you haven't already done this course. And I'm not familiar with academic articles. I would certainly suggest standing there. I will fill in some of the gaps, but it will be helpful for you. So a little bit about me. I have a PhD which was awarded joint me in statistics and sociology. I've undergrad honors and master's degrees that were across statistics and finance. And I have a graduate diploma in higher education. So I've been around academia for quite a long time, probably about 15 years as a full-time academic and various different roles. And during that time I've published around about 25 articles depending on how you count them. Some of these have been Conference pipe as books, book chapters, but also an academic journal articles. I've also been a reviewer for journals. So I have been a peer reviewer. I've looked at and evaluated the work of to decide whether it should be published. So today I will be sharing my knowledge, my experience from both my own writing, but also as a reviewer when I've looked at other people's work to determine whether it should be published or not. So I, what does an academic journal article? Well, basically it's a piece of scholarly research which has undergone a peer review process. So this means that other experts in the field who review for this general have looked at it and they won't know who you are. You I don't know who dyads, what double-blind peer review means. But they will have looked at work and decided that they think that it is of sufficient quality that it can be published in this particular journal. So looking at the structure of this course, we're going to start by looking at research questions. So you're thinking about writing an article. How do you structure what it is that you actually want to write about? So we'll look at research questions, objectives, hypotheses, really just kinda figuring out what you might write about. The next step will be how to do a literature review. So how do you go about sourcing and reading the other articles in your area so that you have a good set of knowledge and you will be able to talk about this in your own ADA. Cool. The next thing we will look at will be weird to publish. So I put this quite early in the course because I think it's a helpful thing to do before you start writing. It lets you think about the particular style and how you might structure your article and really gives you a good idea by looking at other articles have been published in that journal that you want to publish in. We'll talk briefly about data collection and analysis. This isn't a statistics course, so it'll be fairly high level. But I'll talk about different ways we might think about getting data and some key principles in terms of analyzing it. To be able to analyze it, you will certainly need some additional statistics skills beyond what we talk about here. But I will give you some very high-level things to be going and finding more out. The next step is the writing process. So this is at a very high level, thinking about how we start and how we go about doing the writing, all of this article. I approach this by talking about how I do my own writing, but also how I think it will be helpful for you in terms of writing for the review is of the journal. I then get into more specific details around things like language and style and referencing in the writing details section. The next step is about responding to peer reviews. So I talked a little bit about the peer review process. And if you get a peer review set of reviews back for your article, how you can go about responding to them. Finally, I have a section on what's next. So I divide What's next into what's next if you have just finished this course. But also what next? If you have worked through the course, written an article, submitted it, and hopefully got a published. What makes thin. So there's kind of the immediate what nixed that after today. But also the next further afield after you have written and submitted in perhaps even published an article. So the writing process can be a challenging one, could also be a little bit of a lonely one. So you can do all of this by yourself. But certainly for me, I've found that I have been much more productive and ends up with much better articles when I have had collaborators to work with. So I would definitely encourage you to consider looking for collaborators where you can write to give a, it could be that you have skills to combine. And synergy said perhaps one of you is good with statistics, the other one is better with writing. Or it could be that you have similar skills, but you just divide up the work between yourselves. So certainly something to consider is, rather than going it alone, to be able to write, to give it with someone else. And so that's the plan for this course. I hope that you enjoy it and find it valuable. There will be a project there for you to be able to interact with me and let me know how you go. Hopefully this will be the start of you writing and publishing Johann article. 2. Resesarch Questions: So the first thing we need to do is establish what we're going to write an article about. So we might already have a general topic in mind, but we need to get more specific than this. And so in doing this, we will normally establish what we call research objectives. Sometimes just want objective and then some research questions. So the research questions will be what guide us through the rest of our process. They are the things that we are trying to answer. In some disciplines, we would also add what's called a research hypothesis. And we went to look at some examples of these shortly. At this stage, we can also consider how we did the research. And this is going to tie in with our objective and questions. So the main different types of research we might consider, our empirical emitter analysis, which is a form of empirical theoretical research and just general literature reviews. The empirical research would involve clicking either quantitative, which is numeric or qualitative, which is non measured data to be able to answer questions. So this could be things like a survey, could be interviews and focus groups, data out of a database, things like this. Emitter analysis is a form of empirical research. But instead of using or collecting data, it's actually research on research. So a meta-analysis is we analyze all of the articles that have already been peer-reviewed published about a particular topic or a particular research question. And you are trying to establish patterns across all of that research. Theoretical research can take different forms in different disciplines. So in a subject like mathematics and might be doing things like proofs. Where as in maybe a subject like philosophy, we are going to be using theory and we're going to be talking about different components of whatever part of philosophy we are going to be writing about. Literature review is going to be the most simple of all of these, but it can be very challenging to get published. So just writing an article that describes the other articles without doing the analysis of a meta-analysis is something that subdisciplines and some journals will publish, but many will not. They won't see it as adding new information to the discipline. So it's something that you could consider. But I would say most likely you would be looking at empirical research if you're already an established research and then you may have more knowledge and be able to talk more and theoretical ways about your subject. So that's certainly a possibility. But for most of this course, we'll be thinking more about the empirical and to a lesser extent, I guess the literature reviews style of article than a theoretical article. Okay, so let's start with a research objective. So the research objective is just a general statement about what we trying to find out. And once we've got that, then we can turn that into a research question or possibly a series of research questions. It's going to look quite similar to our research objective, but it will be phrased as a question and it will probably be a little bit more specific. So I will have a look at an example shortly. But if you imagine that we might have one overarching objective with a man, might be we have three different research questions. In some disciplines will then have a research hypothesis. And that's where we take that research question. And we actually add some directions so we in advance are thinking about, we might see a difference between particular variables. We might see one measurement being bigger than another. Things like this. So it's adding some direction to research question to our statements. This is used more in some subjects than other subjects, but as something to be aware of. Okay, So let's look at an example. And this is an example that I have taken out of the article that I've referenced there. For more information about research objectives and research questions, I would definitely encourage you to go look this up. It is freely available, so it's not behind a paywall or certainly at the time I'm recording it. This is the case and it gives you some extra information. So in this article they use this example where we have the study. We can see that it is a medical study. We can see that there is an objective. So they're trying to investigate clinical efficacy. And say once they had their objective, then they formulate the research question. You can say that the research question now is phrased as a question. And it's just a little bit more specific, so it's just added a couple more details about what it is that they going to do. Then they have a research hypothesis. And we'll notice what the research hypothesis, it's now got some direction. So it's saying Pang levels are reduced. So this is what they are predicting will happen. They'll then click the data and they'll perform this statistical tests to establish with a, that was the case. You don't need to be correct on your research hypothesis. It's just stating a prediction in advance. So this is going to be based on the literature that you've read. It would be based on other knowledge or expertise in the field. Sometimes the research hypothesis might be that we don't think that will be a difference. Sometimes it might be that one thing is higher or lower, then there is a difference. It's going to depend very much on what we know about what we're trying to find out. And also it's quite disciplined specific site in medicine, in areas like psychology, some of the social sciences. We might say this more often. Then perhaps say in statistics or some of the hands-on says something that changes by discipline, also by journals. Some journals will expect to say this others, I'm not as worried. So when we're thinking about our research question, there is this acronym, finite size, feasible, interesting, novel, ethical, and relevant. So this is a nice starting point before us. So with the Fina acronym, feasible means that we can actually answer this question. So there's no point asking a research question if we can't answer it. Interesting means that it's going to be interesting at the very least two people in the field. So not all research is going to be interesting to the general public, and that's certainly a bonus. But at the very least, it should be interesting to people who read this particular journal and are in this field. Novel means that it adds something new. And this can be one of the biggest challenges in writing an article is that your work actually add something new that hasn't really been done before. If you're a PhD student, then this is really the definition of your PhD, so it's little bit easier. There are also cases where you might have work which is called replication research, where I'm just really doing the same experiment someone else has done in order to demonstrate that I can get the same findings that they did. And there are fields, particularly areas like medicine with us as important, it's important to be able to do the same experiment and recreate the findings. Someone else did. Any research you do should be ethical. So that hopefully I would like to think as without saying, but it is here as part of our acronym and relevant side. There's plenty of things that you could do research on that are really just not particularly useful or important, aiming for something that is relevant. As we worked through our research, we can have our objectives and our research questions change. It's something we should establish up front so that we know how to design our study, how to walk questions to put in a survey. If we're doing a survey, what data we need to collect. So we need to establish these up front. But sometimes as we do a literature review in particular, we might be presented with information that makes us change our mind. Or 12 adept a slightly. So we will start with some research questions. But certainly over time, there is, it's not unusual for someone to come up with slight variations of them as they work through their research. 3. Literature Review: The first step in any research process is a literature review. A literature review is a comprehensive search of scholarly sources. So that's things like journal articles, books, conference papers that relevant to your particular topic, your research objectives and your research questions. So when we're looking for sources, we want to make sure that they are irrelevant. We want to make sure that they credible. And this is particularly important where there is now a lot of what's called predatory journals, which are journals which do not actually have a proper review process they designed purely to just make money. So people will pay some money and I would just publish whatever. So I really important in the way of credible sources and ideally sources that a well-cited, not all of our sources need to be well-cited, but we need to make sure that we are capturing the most important and most commonly referenced journal articles and pieces of research in our area. So at the very least, some of adequate should be very well cited. When we come to actually write up a literature review, the length of it can vary a lot depending on what general we're writing for. But the amount of time that we put into searching for articles is still going to be pretty similar. It's really important that we have a good working knowledge of the relevant information in the relevant research that has already happened in our area. So when we're doing this, the first tool that we would normally go to is Google Scholar. Google Scholar is great because it's available to everyone. And you can do a series of searches to look for relevant articles. Have access to university databases thin. These can be very helpful as well. If you're a member of a large public library, you might also have access to research databases and this y, but certainly Google skull out. We'll get you going with searching for relevant articles. You should style with such Tim's that are very broad and gradually make them more and more specific as you hone in on articles that are relevant to your research question. So when you find a reference stopped by reading the abstract and determine whether this is actually going to be relevant to what you are studying. If it does send relevant, then you want to source it. And I've got some information on the next slide about how you can go about doing that. And so I then read the article really carefully as you go take notes on the key points. You might like to include this in a spreadsheet. There are notes apps, there are also referencing software apps that can be used to do this, whatever works best for you. But basically you want to have a list of the things you've read, the key points. And as you go, you want to start linking those together as well. When you write the literature review section of your article, you want to be able to link the information that you've found in the different articles. When you read an article 1, really helpful thing to do is to check the key woods, the keywords going to help you with future searches. The other thing that you can do is look at the reference list. So when you're reading an article that is particularly useful to you, it's more than likely that it is going to refer to other articles that will also be useful for you. In order to source articles is a few different ways you can go about it. If you connect it to university, the university library will normally have databases. Some public libraries have this to a lesser extent as well. Google Scholar is a very good way of finding articles, but it doesn't always link to the full text. So you might be limited to ones that I'm behind a paywall. A new tool which is just very recently been released as cool research rabbit. And so I've got a link there. I've also got a referral card that you can use to sign in. It currently only has a couple of sources, but it doesn't really need visualizations. So I'd encourage you to try that in addition to Google Scholar, I hope I've a time it will start to access more and more articles because it's a pretty neat to. Pubmed is great for open-source medical articles. And J store has a lot of older articles. This some sites like Research Gate, which kind of like a research vision of social media. Sometimes you can access articles there. But the last thing, and I wouldn't encourage you to do it as a fifth step. But if you can't, otherwise source and article you can always contact the research is directly. They will often have what's called preprint proofs with I've had to proofread and it's the last version of the article before it goes to press. And though we add a scene that to you. So particularly if you are doing this and you don't have access to university library, that can be pretty helpful. Most researchers get back to you note all of them though. And it can take time. So if you can get things out of database, that's it anywhere I would stop. But contacting researchers can be a useful way of getting additional, not only the articles, but sometimes additional information as well. Sorry, we're doing a literature review. When do we stop? Well, the short answer is kind of Nineveh. If you're doing a PhD, you will certainly relate to this where there is just more enroll, erase it, it's being produced every day. You could just keep reading. Realistically though, we're not going to keep going forever. So what we need to be able to do is say, I've read all of the most important articles on this topic. So I went, I feel confident that I can say that. And when I'm reading articles and I no longer am looking in reference sections and seeing new ones that I should be looking for. That's a pretty good sign that I've been Nas and thorugh and I've checked off, at least for now, the relevant research. The first few articles you will find will lead to lots more. But you should get to a point where you just start seeing the same references over and over. And those normally the key ones in an area. Psi. Hopefully at this stage you will now be able to write a comprehensive literature review. So you'll be able to link the themes and the information from the different articles that you've read. And as you do that, you also want to be out to identify what is the gap. So all of these people have done this research, but there's something missing in your article that you are riding is the thing that's missing. So as you write a literature review, That's really what you're looking for. Side depending on your data collection and what kind of research you're doing. You might like to start writing your literature review right now. In some cases, you, for things that are happening in a lab, you might just move straight on to data collection. But suppose you're doing a survey, you might watch a survey. It might be out available for a couple of weeks for people to complete. During that time, you could be writing your literature review. Literature review will also help shape or reshape research questions and research hypotheses. 4. Where to Publish: In this section we are going to look at where you might choose to publish. So this is something we want to look at fairly early. So that when we actually do the writing all of our article, we have a good idea of the style and structure and contents that'll be suitable for the general we're interested in publishing in. So in order to work out where we might publish, one of the things we can do is consider watch journals we saw regularly during a literature review. If we kept seeing the same journals overnight in a literature review, that suggests that they could be suitable for our work as well. Since an literature review, we're looking for the articles that are most relevant to our work. The second thing we want to do, if we can, is to ask a mentor, a supervisor, or someone who just might be a little bit more experienced in the field. So I being able to talk to someone and if you didn't have a network of such people, even reaching out someone like Twitter or LinkedIn. And saying, Here's this pace of research on thinking about writing. What are your thoughts on this particular journal? Or just in general, where do you think could be a good place for me to publish? And hopefully if you have someone that's little bit more experienced, they can give you a little bit of guidance. So you want to look at your research questions and what you're planning on doing and say, Well. And does this fit with a particular journals, aims and themes? Journals will typically have a set of themes or topics that they are particularly interested in. And when you submit an article, the first thing that will happen as the editor will look at your abstract, maybe skim through the article to determine whether they think it's a good fit for the journal. Something that's also really helpful is to look for special issues. So especial issue is where there's a very specific theme to that particular issue. And it can be really good if you have something that fits really nicely in the special issue. Not only does that help you determine we might submit to, but special issues will normally have a Judahite that'll be coming out of this time. So it can help push to work alone. And sometimes it can increase the chances of being published. Because for a special issue, people will really need to have done work that fits closely to that very specific thing. So this one is little bit hot to describe. But basically there's a Goldilocks zone in some way. We don't want to, I am too high, we don't want to, I am too low. And this is where talking to a mentor or took insulin with little bit more experience can be very helpful because we want to publish in the best general we can. But it's got to be one that will publish us. So Generals have particular levels of esteem. There's a number of different general ranking systems that will tell you kind of how, how good a journalist in terms of a particular ranking metric. And we want to have a high ranks gentle. The very highest ranked journals are the ones that are generally also the highest, most difficult to get published in. So we want to find one that is as high ranked as possible, but we'll publish us. We also want to make sure we avoid predatory journals. If you jump on to Google or YouTube search for predatory journals as a phrase, then you will see plenty of information about these on YouTube. I have a video where I talk about how to identify one. Basically, these are journals that don't have any academic rigor. And they are really just there to try and capture phase. So they will try and charge you in order to publish your paper. It's not the only way to determine if a journal is predatory. Some of the very top ranking generals also charge a fee. But if a journal is not a highly esteemed famous, gentle, and it's charging a fee. There's a good chance that it could be a predatory journal. And you really want to avoid those in terms of your reputation as a writer. There's nothing to be gained by saying, I published this pipette. And then when people look, it's in a dodgy looking journal. So you want to have a legitimate, reputable journal, the publishing in. The last thing you might consider is with it to publish open access. So there are some journals with a fully open access and then there's others that are not fully open access, but they give you the option of Open Access. This is nice because it means your work is not behind a paywall and so it can help more people get access to you would there are some cases where the open x is the component that gets charged for. And so that's something you would then need to consider. But it's certainly something that when you can, I think is really good. Being able to have more people access your research rather than putting it behind a paywall. 5. Data Collection and Analysis: In this section we are going to talk about data collection and analysis. So this is assuming that you are doing some sort of empirical research. You're going to need to have some data. You need to analyze it in order to answer your research questions. So some things to consider. One is with AI, you will focus mainly on quantitative or my knee on qualitative research. So how are we going to be looking at numbers and meshes? Or are we perhaps going to be doing things like interviews and really focusing on things like themes and stayed. We also want to think about with, we are going to use primary data, which is data that you will click yourself. Or secondary data, which is data that has already been collected by someone else. If you aren't experienced with data analysis and collection, this is where you should be getting help and you should be getting it early. So something that I have seen far too many times is I'll have someone come to me and I would like some statistics help. But it turns out that the way that they wrote this, if I, the way that they collected the data or the sample size is just no good. So this just really nothing I can do for them. And will that if at the left put in is really a bit of a waste. So I would encourage you to reach out whether it's to me, whether it is to someone else, whether it is by up-skilling yourself with more courses. But the more you can learn about data collection in statistics, particularly if you're doing quantitative research, the Beta. So when we talk about quantitative and qualitative, we can talk about it in terms of the general research. We can also talk about it in terms of specifics of the data. So quantitative research, basically quantitative means measured. And so it's often used as a substitute for numeric. It gets a little bit hazy when we're talking about categories. So categories we came count up it as something that's mentioned. But you will find some people have categories in the definition of qualitative. But quantitative is really where we have, we have numbers and we have measures. So this could be things like closed questions from surveys. It could be information that comes out of databases, that could be web scraping, they could be simulation, they could be experiments. If we are looking at a mid or analysis, then it will be all of the different statistics from all of the different research papers and ohmmeter analysis. Qualitative, on the other hand, is traditionally thought of as things like interviews and focus groups. But if we have open-ended questions now survey that's going to be qualitative data normally will focus one direction or the ABA. So I'll say if I might be mainly closed questions with a couple of open questions or vice versa. So the normally be a focus depending on what kind of things we want to find out. There's also been recent advances in things like natural language processing. So if I wanted to collect a whole lot of tweets and I wanted to say I do a sentiment analysis, find out how people are feeling. Then again, this is kind of a little bit hazy in terms of quantitative versus qualitative. Because the sentiment component, and that's certainly qualitative. We can't really attached just specific numbers, but the way that the processes happen is actually statistics. The other thing we might consider is what's called mixed methods. So mixed methods is where we have a combination of quantitative and qualitative. So I might have a survey that I might follow the survey app with some focus groups. And so H will get different types of data, but hopefully help reinforce each other. Before we think about collecting that and I would shoot investigate secondary data. Maybe someone has already collected this data and that's going to make life a lot easier for us. So if I'm looking for secondary data, that's a lot of different places that I might look depending on what I want to find out. The National Statistics Agency. So here in Australia it's the Australian Bureau of Statistics, but every country has their own version and they tend to collect a lot of data. So I would certainly stop. I'm looking there of other government departments. So with your local government, state, federal, depending on the structure and your country, government departments also collect a lot of data. Sometimes they make it publicly available. There is a number of different data repositories around the world. So I've got two links here of examples. One is the UK Data Service. The other one is a registry of international research data repositories. And basically this is where someone has done some research that I've clicked in some data and now the sharing it. So it becomes available for you to go and get that data. And this means that you don't have to spend all that time and all that effort to click the data. Quite possibly they have had some funding, they've spent a whole lot of money, put a whole lot of effort into collecting the data they want to see it used. So data repositories can be amazing for getting much more powerful data, much bigger datasets than you could possibly do by yourself. Google has a data set search. I've used it a little bit, offended, little bit, dismiss. It's not, not perfect. But if you jump in there, do a Google search for terms related to what you're interested in, you might find some data that's publicly available that Google has indexed. So I'd certainly recommend that as an avenue for checking. You might look at other researches. Perhaps there's other researchers have collected data that they can share with you or you can collaborate with them. Certainly over the years, every so often I've had data where I've been quite happy to share and work with people. Because it started that for instance, I had one looking at the ages of international rugby players. It's public data. I clicked it, it or I had a research assistant clicked a lot of it off sites like Wikipedia and the websites for the national teams collated together. So there was some effort that went into it. But after that, then it's just data that's there. And so she had that a couple of times for other people to be able to use. Private companies can also click data as well, so they less likely to share it and list there is something that they are going to receive in return. But that's certainly another avenue to consider. The private companies that either full pay have collected this data. Or in some cases they might just have data and they aren't doing anything with it. And so someone coming in and actually doing some research would be really helpful for them. So that was secondary data. If we think about primary data, primary data is data you collect yourself. And when we're thinking about data that you collect yourself, if you're collecting data from people or animals, so you have human subjects or animal subjects. Then in most countries you are going to be required to get ethics approval. And America it's called IRB, the Institutional Review Board. And this is a requirement for a lot of journals. So a lot of journals will confirm that you had ethics approval before you collected your data. If you're at a university, then you have a Ethics Committee for your university, you can go through that. If you are not any university, there are other options. So there is for health research, there is normally certainly in the Commonwealth countries, public health ethics committees. So the, either the state government or the federal government will create ethics committees for health research is to get ethics approval. There is private companies that provide ethics committees and ethics checking as well. And then alternatively, you might also look at having a collaborator that is at a university in they can process the ethics before you through the university committee. This is going to be really important that you do this before you start clicking. So it's pretty much a universal that ethics committees will not approve if you start clicking before you have your approval. And lot of journals will not publish your work if you don't have this ethics approval. So once we've gotta ethics approval and in fact HE, as part of the process, we need to explain our sample design. So we need to think about how will we clicked this data? Have we would go about collecting the data. We need to ensure that it is representative of our population of interest or as close as we can get it. So we want to have minimal bias and needs to be able to answer our research question. So we need to be able to click the sample of whatever it is. So whether it's people, whether it is some sort of other measurements that are going to be sufficiently representative. They can answer our research questions. Some of the considerations. And each of these could be a course to itself, but these are things to be aware of to do more research on. So what does the sample size? Do? I have enough people in my sample? This is particularly important for quantitative data and quantitative research. So if I'm doing a survey, how many people do I need? And this particular calculations I can do to check on whether I have enough people. But even if we're doing interviews and focus groups, there is still a requirement that we get enough. And for interviews and maybe it's eight or 10 or 12, It's not large numbers. But we do want to make sure that we have enough, particularly that we're covering different groups. So whether it's gender or age groups or different groups of interests, making sure that we have interviewed across the different groups that we might want to talk about. The collection method is going to be very important. And this ties in with what's called the sample frame. So the sample frame is the group that you draw your population, drew part of the population that you draw a sample from. Ideally, it is exactly the same as your population, but often the sample frame will be a little bit different in this potential for bias there. So you can imagine if I do an Internet-based survey, I can only get data from people that have the Internet and fill it in. For some populations, this might not be suitable. If I'm trying to collect data from older people, then the hips and thighs, I'm not going to be the best way of going about it. So we need to think about what is the best tool and then how can I connect with the Paypal or the information that I need to click for my study. We want to ensure any sampling we do is random. And again, I've taught whole university courses just on sampling. So just being aware that sampling and sampling methods is a thing is enough for us for its day. But that would be something we would go out and consider. We would have to do some reading and say, okay, how can I randomly select people for the study? And we need to make sure that whatever measurements we use. So whether it survey questions, whether it is measurement devices or tools, are they collecting the right data, right level of accuracy to be able to Hans and my research questions. If I don't ask all of the questions in order to be able to do my analysis, then it's all a waste of time. So really important that I check that if it's a survey, ask all the right questions. If I'm taking measurements, I'm taking all the mission and so I need in order to be able to answer my research questions. So then we're going to move to the data analysis. And again, this is where seeking help, getting, getting some additional education, some additional assistance is going to be really important. Something I always encourage people to do is have a look at how have other people in the journal you are targeting done the analysis. So there are some things that will be Coleman all of the time. But there's also going to be particular things and why is it presenting data that are going to be more specific to your discipline and to the journal you are targeting. So having a couple of articles that you can refer to and say, okay, well this is how they presented their data. I'm doing something very similar, so I can use that as a guide. We will normally have some data visualization. So we'll say I have some graphs that can communicate information either about the data, will relationships and patterns in the data. We will have some descriptive statistics. So this could be things like means and standard deviations, percentages for our categories that tell us about the data set. And then we're going to have inferential statistics. Inferential statistics is what we use to answer our research questions most commonly. So this is where we use our sample to infer things about the population. So we might say statistical tests and methods, lie regression, chi-squared, all sorts of different statistical tests that get used to try and determine whether there's differences, whether those relationships with those patterns, things like that. This point I will plug my getting started with course, which is here on Skillshare. That is a way for you to get started with statistical software. There's certainly going to be a lot to learn beyond that, to be able to do these things that I've just discussed. But it's an excellent starting point. 6. The Writing Process: In this section we are going to look at the writing process. So I thought we would start by just reminding ourselves about the structure of a typical journal article. So remember, not all of the sections will appear in every single article, but certainly most of them will. This is a very typical structure for an article. If you're not sure about any of these sections, would definitely encourage you to look back at my reading, an academic article, Skillshare course. I took this from there. And in that I talk in more detail about what each of these sections are. Hopefully by this stage though, if you have been doing a literature review or doing some sort of academic articles, this is, this is pretty familiar to you, so you have a pretty good idea in what is in each of these sections. So when I'm writing articles, what I like to do is start with a skeleton of headings. So I would stop even with that list of hitting this from the previous page. And then I would add and subheadings. Different journals will have different rules about how many subheadings you can have in section headings. But I would start with some headings and even just little descriptions of what, what kinds of things that I'm going to talk about. So I really started with a skeleton or a wireframe and boot in the detail as you go. So start with the headings, then little bit of detail. They more detail than more detail. There's a particular order that I would normally work in once I've got my structure and I've got my headings, I would normally start with a little bit about my research questions and objectives, but I wouldn't write the rest of the introduction. So I would just have a little bit about this is why what the study is. And this is why I'm trying, is what I'm trying to find out. Why I'm trying to find out. I would leave the rest of it. But I like to have those written down in the article because it's a reminder that's something for me to keep coming back to as I'm writing, emphasizing what and why is giving me something that we want to do really clearly throughout. So by having those, they are from the outset, that's going to be really helpful. Then I would normally work through my literature review. I might have already done this while I was taking time collecting data. If my data collection took time, the literature review is going to be a comprehensive as it needs to be for our particular general. And this will vary in terms of length, but really sitting the same. So what have other people done in this area? And why does my article need to be published? What's that gap that these articles haven't Calvin that I'm going to be talking about? Then we can do the methods and the results. So here's how I did it. And he is what I found out. Then I would do the discussion. So not all papers have a discussion and we'll have a conclusion. Sometimes it's a separate section, sometimes it's not. Where you link your results back to the literature. Sorry. You can say, well, I found out this and if we compare that to what was in the literature previously, he is how it's the same. Well he is how it's different. So in linking what we did with the previous literature in the field and then coming to some sort of conclusion. Then I would come back to the abstract in the introduction. So I wouldn't be leaving my introduction and particularly my abstract to the very end. And I find that this makes it easiest because the purpose of each of these is describe what's going to happen in the paper. So if I've already written most of the paper, then it's much easier to write these sections and described because I'm just describing what's already there. Rather than if we start out by trying to write an introduction and an abstract way with saying what we think we will write and then it might change. And then lastly, we'd go through we do any additional formatting. We would ride acknowledgements, appendices, things like that. Throughout all of our writing, we want to be really clear about what we're doing. So what is it we're trying to find out? Why are we trying to find out so that justification and how are we going about it? So we want to be as explicit as possible. So I think it's really helpful to have several articles from the journal way trying to get published in that are similar to what we are trying to ride. That will really help you with getting the style as well as the formatting and that same kind of voice. So what does an article that goes into this general look like and sound like? How does, how do they form at the time was how do they talk about this statistics, things like that. So having some that you can use as a guide is going to be really helpful. Always think about justification and evidence. Everything that we're doing if we're talking about our own work, this is what we did. This is why. So always coming back to, why did we do it? Why did we do a save I, why did we ask these questions? Being really clan? And that's something is a review of that I'm always looking for. Is that justification? So has this author justified why they have done things this particular way? You should write as clearly as you can. But don't waffle. So don't just write more words for the psycho writing more words, right, Cannae, but as succinctly as you can, dynasty him that the reader or the reviewer going to know what you know. So make sure you spell things out. Make sure that acronyms are defined. You can assume that the papal and knowledgeable in the discipline, but don't make assumptions beyond that. Make sure everything is nice and clear and explicit. If you can try and get some feedback before you submit. So I particularly if this is your first article, then see if you can send it to a friend. Maybe if you're a PhD student, get another student to read it. Perhaps a supervisor or mentor, maybe even reach out. It's maybe a little bit of an asked to get someone, a stranger to read the whole article. But even just reading a little bit of your article, just to really get a feel for it, get some feedback. This can be someone who is technical and in your field that's going to be helpful because they will be able to give you feedback about the specifics. But sometimes it can also be helpful to have someone that's completely outside of your field. So for my PhD, my mom read it infect, she read it aloud, which I think is a really good proofreading for catching grammatical errors. She had no technical knowledge, but she was able to identify some expressions that were clumsy, some grammatical issues, just things that I had looked at at the so long that I missed myself. So I think it's really helpful being able to get feedback if you can get someone to do a proof rate as well. These are all things that will mean that they're not issues for V0, for an edited, say, reject you're a paper from, as you're writing. Really important for me to emphasize is Knowlton to go through a few drafts. So you'll write. And particularly when you haven't written very many articles, it's likely that you write your reread it and you might have to do quite a bit of restructuring just to get the structures, to get the flow, to get it to all my experience. It's something that will improve over time. But it is going to be really helpful for your writing. Also, if you're getting feedback as you go, whether it's from a supervisor or a mentor or a friend, that we'll probably adjust what you want to write as well. And lastly, and in fact, I probably should have made a fist follow the instructions. So whatever instructions the general has in terms of formatting with a typo in the text, or they go in the end, or they go on a separate document. What format the graphs should be submitted as a separate file? I have a callout or are they gray scale? What is the margins, what is the font? All of that stuff, follow all of the instructions because it's the most common way for a pipe it to get rejected is by someone just not following their instructions won't even get to the review as the editor will look at it and say this person hasn't following the instructions and they will send it back to you. 7. Writing Details: So the first rule of writing articles is to always follow the instructions. And the second roll, a riding, is always follow the instructions. And my IDE same like I'm being a little bit silly hat and might seem like I just wanted to quote a particular movie. But this is really significant serious stuff. So I think I've mentioned earlier that a friend of mine who is a editor for a gentle, said that at least 75 percent of articles that gets submitted he rejects before sending to review is because they didn't follow instructions. Then on top of that, he rejects a few more because they don't match up with the theme of the article. So it's actually only a small percentage that even make it to review is so really, really important. Follow all of the instructions that the journal provides you. Something to look for is a journal submission template. So journals will often have a template whether it's a Word document or light tech or whatever, I would like you to submit as. And it will have a lot of the formatting pre-done for you. So that's why it's a much easier way rather than writing and then trying to figure out the formatting lighter. If there is a template and you can write straight into it, you should always do that. So academic writing is a very specific form of writing. And so we're just going to look at a few more details that even if you've done a lot of writing of say, blogs or other things before, this is going to be a little bit different. And so there's just a few more details that I want to run through of specifics that you should be thinking about or aware of for riding your academic article. So before we get into the super specific, something that I think is just generally helpful is using section headings wherever you can use section headings, I think it always makes an article Clara and easier to read. So that's kind of general, that works on webpages and other things as well. Paragraphs. So when you are writing a paragraph, that paragraph should contain one particular concept or theme or idea. It could be that you and a literature of you talk about several different publications are different articles that you read, but they will all have a theme. There'll be something linking them so that that paragraph has a single concept. And then as you write your paragraphs, you also want to be looking at linking them. So you want each paragraph to naturally flow into the next one. When I read a good article, it is really noticeable that you can just read it and it really flows. Whereas a plethora of radical, there'll be a paragraph and then the next paragraph will have nothing to do with the last one. And then the next one would just be these paragraphs and information that just comes out of my way. So way you can have a particular flow where one paragraph leads into the next, leads into the next, is really going to make for a more, more appealing and beta to read. Cool. And again, I guess this is not specific just to academia, but particularly when you're writing literature reviews in academic writing, there's a lot of things that you may want to say, but saying it in a linked coherent fashion is going to make it big difference to getting adequate exempted. It's going to be important that you're careful with how you use your tenses. So past-tense versus present tense. This is where looking at the style guide and looking at other radicals in your target publication, it can be important because there's not one single standard for this. So when we're talking about the survey that you did, it could be in the past tense, but then your findings, if you are talking about findings that are extrapolated and applied to the population, then those findings might be written in the present tense. You've got to be really careful that this doesn't get confusing for the reader, talking about things in the past versus the present tense. The other thing that can be quite challenging, and this varies a lot by discipline, is the passive voice versus the active voice. So the passive voice is where you are talking very, very objectively and removed from what's happening. One of my favorite ways of describing how to identify passive voice, if you could stick by zombies on the end of the sentence, and it's still my AdSense. You probably wrote in the passive voice because you didn't have a subject. That wasn't a, we are an eye or some, some subject to sentence. And scientific writing. For the passive voice really is considered the norm and removes the researches are removes the authors from the research. This research was done in May 2022. And we can imagine by zombies being added onto the end of it, and that sentence would still make sense. The survey was conducted using Qualtrics. This, this really removing the research is in some disciplines though, they've moved away from this. So areas like education, you are much more often see pronouns. So you'll see that a and we and I, as the author, is talking about them. The research is doing the research. And I quite like this. I think it's makes things more readable. But you will need to stick with the paradigm of your particular discipline and the general day you're aiming to publish it. So have a look at some of the other articles. See that writing other writing in the passive. Are they writing in the active? Do they use pronouns? Do they talk about, we did this. We believe this because that will be guidance as to whether that's okay for you to do this as well. So the last thing to be really careful about as you're referencing. So as you write, anytime you making statements, you should make sure that you are providing references to justify it. Anytime you're talking about other people's work out, other people's findings really important that you reference it. Every journal has its own style. So there are some common styles like APA and MLA, but there's a lot of variations, but I found often generals will have their own video, syncretic style. And it will be up to you to make sure you are conforming to it. There are software tools like a note once a terror that will help you with your referencing. But they can be a little bit hit and miss certainly for a large publication, if I was writing a thesis, I would definitely encourage someone to use referencing software for a shorter article. You don't need to. You might like to, but certainly for a shorter article might be if you've got, say, ten or 15 references, maybe 20. This is something that is manageable just within Word or just within wherever you are writing. So I wouldn't, wouldn't get too hard about really referencing software in this, you're going to have a lot of references. Once you start going Sigh beyond 25 references, it's very easy to make mistakes and formatting or to lose things, or to have references that don't line up. And that's where it's really important to have the software. So I've got an example here of referencing. So in the reference section, this is IPA. This was actually my very first article that I had published some time ago now. And so we have the waters, we have the name of the article itself, then the name of the journal, and then the addition in the page reference. Different formatting will have slightly different variations on this, but all of that key information will be the way we do it. Then in the text, we would refer to this one is Walker et al. 2005. So the et al. If you want to refer to a casually It's kind of with friends or with colleagues. It's just walk and the other people. And we do this as a shortcut when we have three or more authors. So when there's a lot of authors, we don't want to have to list all of them. Then we get to use that as a shortcut. 8. Responding to Peer Reviews: So one of the most important distinctions of academic publishing is the paper review process. So the pair of views will have looked at your article. Reviews can take time so you need to be patient. But what will happen is you'll normally get one of four different outcomes. So one is except, and that's great news you are going to be published sometimes you need to do a little bit of checking and formatting, but that is the best possible outcome. It's normally pretty unusual better to have an article that has no changes, no fixes, no problems whatsoever. The most common is normally one of the next two. So either you get except with some minor changes and you'll get a list of comments from the reviewer to change. Or you might have a major changes which is also known as a revise and resubmit. This is also a possibility that you just get an outright rejection. So either reject and it will also happen even before the review. So particularly for the very top tier journals, It's all one of the editors staff will have a look at your article. And if I don't think that it's suitable or that it fits, you'll just get a rejection straightaway. And with those, It's not at all a reflection of the quality of your article. It is just that it doesn't fit well with the general insight thin. It's a case of finding another journal and seeing with they might publish in state. You can also get rejected, however, if you haven't followed instructions. So I know one editor who made the comment that 75 percent of articles that come in get rejected from his desk because they didn't follow instructions than not properly formatted. Does typos in the abstract also it's a little sloppy things that just make it no, with the energy of sending to review is. So number two and number three are the most common way that a except with some minor changes or a major changes. And you shouldn't be despondent about this. Even if you get a reject, you shouldn't be despondent. This is just the opinion of one A1A or 18 is going to Kepler review is. But what I would recommend is to take on board the feedback. So what did the review is say? Let's see if we can make some of those changes and fixes. And then maybe sin to another journal once we've incorporated some of those changes. So if we have a revise and resubmit or we have a minor changes, it's going to be really important that you follow the instructions of your journal that you've submitted. And they can vary a little bit. Some like to get a document with Track Changes. Some have otherwise that I would like you to communicate. So something that I would encourage you to do is have a spreadsheet or a table that has all of the reviewer comments and how you responded to them. Even if you don't explicitly get us for this and often you will. But even if you've done, this is really helpful both for you to ensure that you have covered off all of the comments, but also for the editor to see how you've responded. It's okay to disagree with some of the points. There might be things that review aside that you don't agree with. But it's going to be really important that you can provide evidence in justify why you disagree and why you don't want to change that particular aspect of what you have done. So important to always be polite and respectful. I mean, that really just anywhere in life, I think that's pretty good advice. But when we're dealing with editors and reviewers, always being polite and respectful, even if you disagree. So disagreeing is okay, but you want to do it in a very planned way. One last comment is that if you get a revise and resubmit or a major changes, this does not mean that if you make all these changes, you will definitely get published. So you do need to look at what is asked of you and decide with that amount of work is with it. So it could be that you just have reviews and they completely disagree with your paradigm or how you've done your analysis. And even if you make all of their changes, you're still not going to get published in this journal. So it could be that you look at those comments and you can respond. But if it's a really large amount of work, you need to weigh up the value of doing that work. This is perhaps submitting somewhere else because it's no guarantee that what you do will guarantee that you get published. Okay, so that's it for responding to reviews. In our final section, we will look at what next. 9. What Next?: Okay, So you've come to the end of the course today. What's next? So I guess there's a couple of different what's next? So one is for right now. So right now you can start thinking about topics or questions of interest. What is something you might want to write an article about? If you're already a graduate student, then you might already have a topic and data. You may already be halfway through this process. And which case hopefully the point is that I've given will help just push things along AND gate you have it aligned with writing your article. If you earlier in the process and you might look at connecting with other researchers. Now there are other people who are interested in the same thing that UI and maybe you can work together. So if you, what's next? You have gone through the course, you've written an article, it's being submitted. There's normally a white side peer review takes time and said there's normally a period where you're going to have to wait before you hear if you have had your article published or not. And maybe in during this time you want to start another article if you've enjoyed the writing process and the research process. Once that another one. And then there's what's next for people who have submitted and they have had their article accepted. And this thing is celebrate, well done. Congratulations you now published academic author. I would definitely encourage you to tell people about it. So I get on LinkedIn, get on Twitter. If you've done something that has a human interest element to it, do a press release in since men photo the press, you normally want to do that coinciding with the actual adequate coming out. It's not advisable to do it in advance. So you want the sometime maybe in the week that the adequate becomes publicly available, maybe some news articles about what you have done. And it's completely up to you, but certainly in terms of your own reputation, in terms of being able to get recognized, pips get into more work, become known as an expert in this area. These are really helpful steps. Even if you don't want to do too much promotion, I would definitely encourage you to set up a Google Scholar account. So you can set up a Google Scholar account for you as an author, and then you can track the citation. So every time someone references your article, eventually Google Scholar will pick up on that and you will get a little graph showing who has cited you. And if you've enjoyed the process, then start again, come up with some more research questions. You have Xist, interesting secondary data or you've collected data that is interesting. They could be more things that you want to explore. So hopefully, you will be able to take what you've learned in this course and at the very least published your first article. And if you love it, then could be something where you just start writing. So all the best. Please let me know in the discussion how you going if you have research questions, I'm very happy to discuss and give me some feedback in there. Otherwise, good luck with your publishing.