Why the PhD Model Fails Without Real Apprenticeship (Full Transcript)

[00:00:00] Speaker 1: Is the PhD system broken, or, as I want to argue today, was it simply built for a world that no longer exists? Welcome to this week's Fast Track Live. I'm Professor David Stuckler, and today I want to walk you through some of the core critiques of the PhD system, the assumptions it's built on, and what it means for you as researchers today. And as ever, we've got time for questions at the end of the session, including the video questions that you sent. We've got some really good ones on how to find topics and how to convert theses into publishable manuscripts. But let's come back to the PhD system and dive in, because as people have come back from the Christmas holiday break, I keep hearing a lot of things from PhD students that have shocked me, and especially the one that they've been telling me that some get as little as one hour of supervision a month. Just one hour. And if that's really the case, which I have to say is a bit unthinkable or unfathomable, how is it we can possibly act surprised when the same researchers who are getting one hour of supervision feel stuck, anxious, or just drift endlessly for years? So when people step back and ask, is the PhD system broken, my answer is yes, but not for the reasons that a lot of people think is the main issue. The problem I want to point to is the structure. It's how our research training is designed and built for a different era. You know, I often say that doing a PhD is like getting a driver's license. The difference is when you go train to get your license, you're put in the car with an instructor, who's there with you, who has the brakes, has a roadmap, and knows where to go. Instead, what we do for driver's training is you're often just handed the manual and told to go study it carefully, and then you're put on the highway and told to drive alone. So what I want to do in fleshing out this argument is I want to go through some of those critiques. I want to look at the assumptions, and then I'm going to make some suggestions about what I think could be an upgraded PhD model and what that would require. Before going too far, nice to see some of you. Akpera, Fayal, hey, good to have you with us. So what are the usual critiques of the PhD system that you often hear? Well, they're multiple, but they often focus really heavily on outcomes, like we've got too many PhDs. There's not enough academic jobs. We have long times from start to completion. There are skills that don't really translate necessarily cleanly outside of academia, and in some cases are even perceived as detrimental. All of those are real, real critiques, but I'd argue they're downstream effects and not the cause. And yes, there are other issues that cross-sect, like low pay, poor job market conditions. Often people are being paid less than minimum wage, and they do struggle to find jobs. I think there's inequities as well, structural inequities, but they don't really explain what goes wrong inside the PhD itself. So to really dig into that, let's look for a second at the training model. And really what's embedded deeply in the training model of the PhD is an assumption of apprenticeship. You probably kind of think of the classic Ivy League, Ivy Tower, where you might be working, sitting at the feet of a guru, burying yourself in books for extended periods, but having somebody show you a craft. And there's two conditions that are really required to make apprenticeship work. It requires frequent supervision and short feedback loops. And that's because you are taught as an apprenticeship, not just what to do in broad theoretical terms. Somebody will actually show you how to do that. And so for supervision, you need it frequently because you need to see how decisions are made. You need to see how problems are thought through and solved, what the standards are. And short feedback loops means that you can catch errors early and you learn why something doesn't work in practice, not in theory. And all that takes judgment. And so coming back to the driving analogy, right, you'll often – many of you who got training for your driver's license like I did, you're sitting alongside the instructor who has a brake. And so if you're doing something wrong, he'll slam on the brake – him or her – and slow you down. And he or she will tell you where to go, when to merge, when you're doing something dangerous that could get you into a wreck. And this is how people learn to drive. And it's a necessary step for beginners, a necessary phase of learning to get to their driver's license and learn a real skill. And research is a skill. So the problem at its core that I see today with this apprenticeship model – and I don't think we should dispense with apprenticeship model, don't get me wrong – is that there's a few things, structural changes that have happened that made this apprenticeship model that dates back, but we can really point to at least the 1970s when the conditions that supported it and those assumptions started to erode. And so one of the shifts is that supervision time has collapsed. And that's that one – I mean, one hour – I still come back to that because I've heard this from several researchers now. If that's happened to you, let me know in the chat how much supervision time and face time you're actually getting with your supervisor. I'd be very curious to know. I think other people could relate to that. But what's happened is supervision time has collapsed. And if you look at a lot of universities, the student-faculty ratios have gone in the wrong direction. And so it's like if you had a driving instructor and he just said, okay, let's check in every four weeks. Go drive around for a while and we'll see how it goes. But if you're just learning to drive, you don't know if you've done it right. There's some kind of signs that say respect the speed limits. But especially for researchers just starting out, I often hear from a lot of beginners they don't know if they got it right. They don't have confidence. They don't have their feet. They don't know when they're on solid ground. And this leads to a lot of one of the challenges that without that instructor feedback, you go in circles and you struggle and you lose confidence. The second problem is against this backdrop of declining supervisor time. Apprenticeship itself has an incentive problem. So I can relate to this as faculty. You're rewarded for grants and publications and citations. That's what gets you promotion, not deep, careful, intimate mentorship with your PhD students. And so you see some students, if they fit into that professor's research pipeline and they're helping that professor achieve their goals, then yes, there's a true symbiosis, a true confluence of interests. And oftentimes those mentees get more attention. Or if there's a mentee that genuinely comes with good ideas and is a standout and is a star, they will get more attention. But in many cases, that just doesn't happen. You might be assigned a supervisor, somebody who may not have your best interests at heart. They're representing their institution, not necessarily your career. A supervisor is not a mentor. And if you don't fit into their research at all, they may not even see cases where people are in adjacent fields of their supervisor. So it's very hard for them to equip with resources. But more structurally, it pulls them away from what they have to do to get ahead. And that can lead you to feeling like you're a burden to your supervisor, can lead you to have unanswered emails, feel like you're knocking on the door and nobody's home. And it leads to not enough time spent together, generic feedback. And sometimes even worse, what I see is that because the supervisors don't necessarily have time or incentive to look properly, they rubber stamp things just to move it along in the system. Because it's much harder as a supervisor to fail someone or send them back that burns more time and energy that takes away from your incentives to publish and get grants and get citations than to invest in properly mentoring a beginner. And it's not that the supervisor, I don't want to point the finger and say that these are bad people. They're bad actors. It's just, unfortunately, the system makes this logic rational for some of them. And the third thing that's kind of compounded these conditions is that the pace of research has just accelerated. The volume of literature is overwhelming, expectations are higher. And that doesn't necessarily work for people just starting out, which is inherently a little bit slower. So you do need tighter feedback, not faster systems. You don't want to put beginners who are just learning to drive on a superhighway with heavy traffic and less instructors. But that's often a bit what they're being plunged into. So I'm just going to take a breath and, hey, guys, just say I appreciate your support. Thanks. Good to have you with us. And Amy, Chris, it's not common in this area. What can be done? I'll get to some of my suggestions on what I think we can do about this. But if you do relate to any of this, do let me know in the chat. It really helps others who sometimes are struggling with that very same thing. So what this leads to is structurally, I think, a problem, a milestone that researchers find themselves in when they're learning this craft as PhD students. So in universities, they're taught methods and tools and techniques. But what's left out is the part that's usually passed on through this apprenticeship. And that is judgment. And that judgment is hard because sometimes there's not a right or wrong answer. It's not black or white. There are tradeoffs to be made. And so questions such as, is this topic viable? Is my draft good enough? Am I using the right method to answer my research question? These are high stakes decisions in a PhD process. And they used to be trained implicitly. You can't learn that easily. You can't get it from a book right now. They're trained implicitly through close supervision and mentorship. And as that breaks down, more and more, we're seeing researchers just expected to figure it out on their own. And that works for some, but I would say a minority overall. So people, when they don't have that judgment, they naturally go try to fill that gap on their own. And what can that lead to? Hunt around on YouTube. That might be how you ended up on this channel. They use AI, outsource judgment to AI, or start collecting tools. I see people with these huge dissertation tech stacks to make them feel confident like they're making progress. And they don't need any of that. Because none of this can really replace real feedback from the driver and head driving instructor. So what's the answer to this? Well, there are critiques out there that look at the structural conditions of PhDs and say, well, we should train for your PhDs, or maybe abolish it, or got it, rethink it as we know it. And yeah, doing a PhD just doesn't work as casual, part-time, low-contact arrangements. We're not going to train high-quality researchers here. I think we've got to shift from an implicit apprenticeship model to an explicit apprenticeship model. I think we've got to bring back the core assumption that's hidden and make it visible and connect our trainings and support to align with that. And that would involve two things. One, it would be outcome-focused. I think outcome-focused is really important because it sets the standards clear and verifiable and objective. And what would that mean? Clear publishable outputs, clear milestones along the way. And you see this direction happening in more programs that emphasize PhD by publications or maybe shift from book-style PhDs to publication-based PhDs. And I think that also helps create better alignment with supervisors. The other thing is that the kinds of training that we need to offer has to build in mentorship. It has to build it in. So part of this is having training that makes explicit research judgment. Yes, it's not black or white, but it is a skill and our training can show people how to do that. So for example, in doing literature reviews or choosing a topic, there is a method to doing that. There is a logic to that judgment that it won't substitute all of the judgment, but at least we'll give training on how to find a topic. And what I see of a lot of researchers is no one's trained on how to find a topic. They might be handed one or they might just say, oh, look around, figure it out. But I often say finding the right topics determines about 95% of your success. And again, it's one of those areas of judgment where people are just expected to figure it out. And remember, this is the arc of your career where you're going from consuming information to producing it. And the very first place where that shows up is trying to figure out your topic. The next place that shows up is trying to do a lit review, which is another one that is put out and you're supposed to, many have to do a lit review and have no training at all on what a literature review is supposed to be. And that's frankly, it's even worse because now you're trying to drive a car and you don't have a dashboard to tell you how fast you're going and when to slow down, when to speed up and the driver instructor is not in the car. So that's structural mentorship means to be our training, to be beyond just methods and tools, but to actually train and create systems that train this judgment. And of course, there's just no substitute for, I believe, real one-to-one support and mentorship along the way and supportive community. So systems, structure, feedback, community, all fundamentally viable. So rather than abolish the PhD and the critiques that veer that direction, I think we need to reclaim the model of implicit mentorship and make it explicit. So guys, what do you think? Does this resonate with you? I want to bring here, we've got one of our research group leaders, Susan Muir, who's joining us from Jamaica. Susan, I'm bringing you on with us and we'll chat for a few, we'll take your questions and then we'll go to the submissions that we have this week. So, hey, Susan, good to have you join us.

[00:16:16] Speaker 2: Hey.

[00:16:17] Speaker 1: Yep. You're here. You're with us. How are you doing? We've worked together for a little bit.

[00:16:25] Speaker 2: I'm fine. I can't see anything. So I guess maybe I don't. Yeah, hold on. I'm fine. Let me turn my...

[00:16:31] Speaker 1: Good. Good, good. Susan, I don't think... Can you hear me, Susan? Yeah, I can. Okay, good. Yeah. Does that relate to you, what you see at your university and with some of your research? Yeah. Yeah.

[00:16:47] Speaker 2: I think what you said is really apt. I have two sets of thoughts. I definitely think that many parts of the educational system is broken and perhaps the PhD is the worst of the entire formal educational system. My thoughts is that there's both in terms of not everybody who's done a PhD will go into academia. And so what about the preparation for people who will not be able to get into the academic fields? So there's that, which you haven't addressed. But in particular, I agree with you. It seems to me that most people I've met at my university who have done a PhD, there are just many missing elements. And the people who are currently doing a PhD, like even at my university, I don't see all the things that you just mentioned happening, like the opposite necessarily happening. Like in my case, and if I should go to my case right away, I started a PhD and part of my thinking is, should a PhD always have a lot of coursework? You know, like the American model seems to be, you do a lot of coursework to prove that you can pass exams. I really think that a PhD should signal you're an expert in a topic that you showcase by publishing. So I tend to agree with you. I think that's the best way going forward, but that would radically alter how PhDs are being done now. Those are some of my thoughts.

[00:18:28] Speaker 1: Really helpful thoughts, Susan. Yeah. Implicit in this getting the driver's license is, think about what the PhD is. It's almost a kind of microcosm of peer review. Like normal peer review, you write a paper, you submit it to a journal, it goes out to experts who check it, see if it passes muster and merits being published or not. Well, the dissertation process of a defense is almost like a mini kind of kiddie pool version of this in a way, and I don't mean that kiddie pool in a demeaning way because it's not getting published. It's just sort of an academic exercise. But you write your dissertation, your supervisor says, yes, you can submit this. It goes out to independent experts who then probe you, ask you questions, and they decide has this merited a contribution to the field? So in a way, if you're clearing the bar to publish in peer review journals, you are showing that you're operating at the frontier of your field to where other independent experts are validating that capability. And that is kind of embedded in the PhD by publication pathway, which I think is a very – I think that is – well, if I had it to do over again, I would have done that today. I just think it's more efficient and it moves us to a world where you have – you're more competitive on the job market by getting papers out already. And it's more efficient. It cuts the fluff and goes to write what the outcomes are. So Susan, let me turn to, for a second, your critique, that broader critique about the labor market. Some people say it's – the PhD is like a pyramid scheme where we've got 10 people coming in, there's slave labor for the faculty, and no one's going to get jobs. That is a different – it's a related problem. It's not about the training model itself. It has to do with investment in research and what is available. And absolutely, the markets have shrunk. I mean you know that I'm really committed to research literacy. So I think the world is a better place when we have people who can find truth in noise and especially in a world that's getting more and more driven by AI slop. So I think more and more we want to encourage and promote research literacy in our societies. That's a transformational ability. So I'll put my hand up there. I don't agree with just vastly cutting down the numbers of PhDs. If anything, I think this world would be a better place if we had more of them. But I do think we need to fundamentally change a lot of the way training is being done. Let me open up to – with our audience here. We've got a few people joining us. And again, if you can relate to this, what's your experience of the PhD been like? Sometimes we tend to have a fallacy where we look at the individual level for explanations for success and failure, missing kind of the structural or environmental conditions that powerfully shape our lives that are in ways beyond our control. And Dadaraji says here, if a supervisor says, check for other PhD theses to find direction. And so this is kind of what I'll sometimes see. So often working with people doing a PhD, I'll suggest, well, look for a PhD thesis that's similar to yours and shows what the guidelines are and what they're expecting. Ideally, those guidelines would be made very clear, clear milestones, clear guidance. Again, that's why I like having publication as the bar because that is – the standard is then clear. But yes, Dadaraji, this is often the case. The ideal situation in a mentorship or apprenticeship model is they're going to show you what the direction needs to be. And if you are in the car with a driving instructor, the driving instructor is telling you turn left, turn right, go straight. They're not letting you just drive around aimlessly. So I think you get these symptoms. Again, some of these expressions happen is that – I don't know your supervisor in particular, but they're structurally disincentivized to investing lots of their best time and energy into – – a PhD. Yeah. Any thoughts on that, Susan, from Dadaraji? You're a supervisor yourself. Have you done that? How do you approach your supervision?

[00:23:09] Speaker 2: Well, I supervise masters and undergraduate students. And I tend to give a lot of close-on. I find that in my university, it's mixed. Some people are very hands-off and do very little for the students. You know, the minimum requirement, some are very hands-on. So I try to never do that again. But I know a lot of supervisors don't do that because you don't get paid directly for that. At my university, we focus on teaching. And so it's – I know it's sad, but there are quite a number of universities in the world that teaching is actually what matters. And research matters less. Even though technically to be promoted, you need to do research. But for every day, it's not what's vital. I think to tell a student just to go and read, I think students at every level need some guidance. And I think what you're saying is surely there should be clear instruction. Or maybe if there were some books, but seeing as I'm fast-tracked, you know, this program you have, if that wasn't some kind of book that we could read, you could say, oh, go read this book to know how to direction. But I don't know of that kind of book where you could say to the student, read this book to learn the direction.

[00:24:37] Speaker 1: Yeah.

[00:24:37] Speaker 2: So I really think supervisors need to let the student go through that process.

[00:24:42] Speaker 1: I think that kind of support, though, on research judgment – and, yeah, maybe I should write a book after writing my last book. I don't think a book could do that. It took a lot of life out of me, I thought, never again. But, yeah, it's just some of that – I guess I tend to – I think a lot of that decision support needs to come one-to-one or through regular supervision interaction.

[00:25:12] Speaker 2: Because as you figure out the research question, as you figure out the research gap, as you go into the lit review, you can't do it from a book. You have to interact with the students so they get feedback. I agree with you completely. Feedback is so critical to people understanding what's the next step.

[00:25:35] Speaker 1: I know you give a lot of feedback and go the extra mile, but like you say, you get no pat on the back or reward for actually doing so. There is this whole edifice of the academic system, even in peer review itself, where academics end up doing a lot of volunteer work, like peer reviewing for journals. It's unpaid work. A lot of that extra support and supervision from the perspective of many supervisors, that can feel to them like unpaid work. We're here because we're passionate about research. Not everybody is here because they're passionate about teaching. That is a challenge. The other thing to note, the quality of supervision can vary considerably because supervisors aren't given any training to supervise. If anything, they got some training on how to do research, but in schools, people are taught how to teach. That is not the case when it comes to research. The best researchers are not necessarily the best teachers. This creates another tension. We have Eli joining us from Shanghai. Hey, Eli. Good to see you. Welcome. We are talking about whether the PhD system is broken. Really great to get your thoughts on this. We have one saying here, doing a PhD at Brunel and working full-time in industry and enjoy the methods training when I go on site and get ideas in class setting. PhD by publication can't provide this. Definitely, I agree. There's no doubt that getting the methods training is critically important. I don't think anybody disputes that. That doesn't necessarily correlate or drive directly the ability to implement independently a research project, which is tough. That's where the gap is. You do get methods. You do get tools in universities. That's critically important. But my argument is that the apprenticeship part has fallen away. My suggestion to you is I don't know what stage you are of your PhD, but try to ensure you have that good alignment with your supervisor and mentor to get that support and judgment along the way, like the driving instructor sitting in the car with you. Savas, good to have you join us. Glad that you enjoyed the topic. While we're here, Susan, I'm going to pull up some of the submissions we had today. Can I ask a question? Oh, yeah, please.

[00:28:16] Speaker 2: I have a question for you. I have started a PhD. Many people have said to me that I have the potential to do one and to be a really good researcher. I have a lot of interest in becoming better at research. Obviously, one of the things to do is to achieve. As I have gone on the web and looked at the options for PhD-backed publications, there seem to be very few. Do you have any tips to determine the best place to do a PhD-backed publication? Any thoughts on that?

[00:28:59] Speaker 1: Yeah. Look, it's an emerging category. The places, I think, are pretty good. There are several out there. Typically, the flow of that works is you package your papers up first. You do a series of papers, package them up, and then you submit those to a university to evaluate it and see if that would pass muster. They accept you. They think so. You write an introduction, conclusion, and then they organize a defense. The difference in the process is you finish the papers first, and then you package it up and say, this demonstrates I've contributed to the field, and then it's a little bit pro forma to go from there. If you're interested in that, Susan, let's have a chat. I've got a dedicated training on PhD-backed publication that walks you through that entire pathway and how it works. Okay. There's different institutions. Standards vary. Like I said, it's an emerging category. It's one that I see in terms of outcomes orientation that I think would clear up a lot of the confusion and struggles that researchers face along the way. That is a nice model. We have CO26871, system is broken indeed, and goes and says- I have another thought. Hang on. Let me take this one and then come back to that. I'm an instructor who teaches three full-time courses and students love me, but my research colleagues don't value teaching as much, and that spills down to mentoring their PhD students. I often see this. There might be a faculty member in a department who the PhD students know is really great, and somehow all the PhD students gravitate to that faculty member because that person, out of the goodness of their hearts, is providing a lot of support and mentorship. Yeah, that sounds like it resonates a bit with your experience too, Susan. Yeah, Susan, come back out. You were going to jump in.

[00:30:52] Speaker 2: I know this is probably a wicked problem, but how can we as a whole collective world address the major issue of what you're recommending, that there is apprenticeship at the PhD level, that there is active supervision? I mean, because on a key level, we can decide to try to make sure we own supervisors that will do our good, you know, by checking it out. I think- As a system-wide, do you have any thoughts on how to improve the entire system?

[00:31:32] Speaker 1: So, really good point. Yes, as an individual, I strongly recommend everybody to establish a good rapport with a mentor. It's like walking into a job. You're going to want to know who your boss is going to be. So, if you want- if this apprenticeship model really holds, you need to find the right guru and the right mentor you're going to work with. And I just see so many students lost at sea because they don't have a mentor. And I'm fortunate. I've had many, not just one, but multiple important mentors along the way in my journey. So, that's the individual side. Yes, the system side is- look, as individuals, it's hard to change a system. I mean, it's going to be hard to reverse those conditions that have been breaking down the apprenticeship model, like declining student-faculty ratios. I don't see that changing anytime soon. The incentives for researchers, well, it depends on how universities are getting paid. And right now, again, with funding going down, it puts more pressure on faculty to get grants and bring that in. So, there's a structural incentive misalignment that, again, is not very easy to change. And the time pressure that just ramps it all up, I don't see that going the other way. I think what we're going to probably be looking at in the future is going to be looking at institutions or other models of support that sit alongside universities and provide that complementary training, likely in partnership with them. But I think this is a space that's emerging and evolving and is ripe for disruption. Let me come here back to Falluza. Falluza says, is there a restriction on what type of journals you publish in for the PhD by publication? Yeah, again, this is one where standards vary. I can speak, for example, to Portsmouth. It does not have to be a Q1 paper. And this can be one of the frustrating things, that there is an implicit judgment. What is more important is that you're the lead author. It's not a scam journal. It's an indexed journal in the field. So, you go into Web of Science or PubMed or one of the others, and it's listed there. But, again, those standards vary. It's an evolving space. And I would check with the universities. You can do a quick Google search of PhD by publication, and you'll see a number of institutions that offer them. There are quite a few in the U.K. But, yes, it doesn't have to be Q1. Of course, it helps always, but not necessary. Ahmed asks, as a PhD student researching diversity watching at MSCI ACWI firms, I don't know what all those acronyms are, should I focus on publishing or learn additional skills for a strong academic career? Complete uncertainty what will happen. Look, at the early stages, publish, publish, publish. It's really true. That cliche, publish, publish, publish, is so important, out the gate. And people, it's easy to critique for academics, oh, paper mills, all this pressure on quantity. But you've got to stand out among the crowd and demonstrate real capability, and publishing does that. So, getting papers where you're the lead author is like money in the bank at this stage of your career. And early wins lead to future success. It's a very well-studied phenomenon known as the Matthew effect in science, where literally the rich get richer in science. And those early wins multiply. So, yes, that's why we start and encourage people to go for low-hanging fruit. Get those quick wins. Get points on the board, because that will open up many more career options. It's not the time to try to do the decade-long project that's going to win a Nobel Prize. Nobody wins a Nobel Prize at this stage of their career. So, yeah, really good question, Ama. Thanks for sharing that. Do you have any thoughts on that, Susan, going into this yourself?

[00:35:55] Speaker 2: No, I think that what you have covered is really on point. I mean, the only thing I think we have not mentioned is that I think the PAC systems are different in different parts of the world and country. And so the PAC systems are more broken in some places. I think we have covered the important points.

[00:36:18] Speaker 1: Let me take a couple of our video submissions, because this really covers this element of research judgment that's missing. Because I see this coming to us in questions all the time, and I appreciate you guys submitting it to us, because part of what we try to do here is share and pass on that research judgment with you in this live format. But here's one we've got from Abdiris, who sent us a message. I'll try to get this on the screen. He wrote, I'd like feedback on how to properly write a strong research problem statement and research questions. I also want to learn how to correctly develop an economic model from a research idea, including identifying dependent and independent variables and linking theory to the model. This feedback will help me improve my research skills for my postgraduate studies. And so when I read this, and we're talking about the PhD system broken, these are fundamental research skills, very applied practical research skills, how to identify a good research question and create a problem statement. Again, too many researchers are just left on their own trying to figure out. But I'll get to the substance of the question before. But yeah, Susan, any thoughts on this?

[00:37:35] Speaker 2: Let me see. Sorry, I'm not seeing the screen so well. Oh, OK.

[00:37:39] Speaker 1: He's asking about how to properly write a strong problem statement and research questions. And he also wants to correctly develop an economic model from a research idea.

[00:37:50] Speaker 2: Yeah, the thing about writing a problem statement and research question is you really have to first scan enough of the papers in the field in order to know what. OK. You can get problems from many, many different places. But to write really good research questions, you need to know this. And in order to get to the gaps, you have to do quite a bit of reading. And I don't know where this person is in his grasp of the field. The first thing I would suggest that he does is maybe go to some systematic reviews, several papers, what they say is the gaps. That when he writes a problem and the gaps, you don't want to do a project where that gap has done before.

[00:38:42] Speaker 1: Yeah.

[00:38:42] Speaker 2: You really want to check that. So just speaking blankly is kind of difficult just without getting more context.

[00:38:51] Speaker 1: Spot on.

[00:38:52] Speaker 2: He definitely needs to do some reading.

[00:38:55] Speaker 1: Yeah. So exactly. Again, in an apprenticeship system, the mentor would be handing on questions, handing on the project, co-piloting that project and supporting it with error correction intervention along the way. Again, driver in the car next to you. In this case, yeah, Susan's intuition is right. Every PhD has a spine. And that spine is anchored by a research gap, what's missing in the field. That needs to connect directly to your research question. Your research question should come into contact with that gap. That should also link to what you want to show. So this is all part of the spine. This should all align. And it's an alignment sequence that we use. So if your question is not answering what you want to show, you've drifted in maybe your purpose and core area. And all this drift creates friction and creates breaks. From that, you usually will consolidate that, those three elements, into a thesis statement or problem statement or a thesis aim. And that needs to then bridge to the methods that you're going to use. Your methods need to be able to deliver on – it's kind of like you wrote the check with your research question gap, and your methods need to be able to cache that check and answer it. So that's one thing to get right. The second thing you mentioned about developing an economic model from a research idea, identifying the independent and dependent variables, this involves causal diagrams. We have some really great training on directed acyclic graphs. And you need to kind of model out – look these up on Google, directed acyclic graphs. And you want to model out your causal logic. That's really important for economic modeling. I think it's really important for any research project in the social sciences. It will really help refine your thinking and refine your theory about what affects what. Because at the core of social sciences, generally, is there's an effect of an X on a Y. And you can set that up, as you're saying, in independent, dependent variables with causal diagrams. So, yeah, Abdira, thanks for sharing that. I do hope that helps. I want to come to MK's question here. She says – and I know this is hard for you to see, Susan, so I'll read it out. She has a challenge. I have a challenge when I understand more what my mentor says. And he finds my work contributing to knowledge. Wait, I'm not sure I understand you here. But supervisor gives no clear direction and says you are not contributing to knowledge. Ah, right. So, you have a mentor who says you're doing great. And the supervisor says not. Oh, this is a tricky one. This is a tricky one. It is. That is a really tough one. I mean, this comes to – I mean, again, you have crystallized supervisor is not a mentor in a very clear way. You need – this is an unfortunate situation where you need alignment with your supervisor. And one of the ways to get better alignment with your supervisor is go to Google Scholar. Look what methods do they use. Go to their profile on Google Scholar. I would say 9 out of 10 researchers I work with have never even looked at the Google Scholar profile of their supervisor. See what their recent papers are. See – that will tell you what debates and things they find interesting. It will tell you what methods they like and they understand. And so here when you're saying it's not a contribution to knowledge, this goes back to the whole anchor of the PhD spine of what's the gap. So I would try to get you to get clarity with your supervisor on the gap and your research question coming in contact with it. And that's where your – this PhD spine really helps you to understand where the misalignment is in the chain. But that's where it's coming from, MK. And if you want to share a little bit more about that, that would help. But even just having the language around the gap and the research question will help you be more efficient in getting to that alignment and communicating with your supervisors. So thanks for asking that. I'm going to take one more question, then I'm going to pivot to one of our video submissions from Russell. But let's take this one from Yogesh Vagela. Any suggestions on how to be most productive in research while juggling teaching, administrative work, and doing research? Susan, I think you can relate to this because this is exactly you.

[00:43:18] Speaker 2: Yeah. Yep.

[00:43:23] Speaker 1: What do you think?

[00:43:25] Speaker 2: What do I think? I think I could – I'm going to give you some suggestions which I need to apply to my own lab. I think what is time block? So, and where possible, like put away all distractions. If not every day, at least three-plus days per week. And that would be two-plus hours, you know, and then you have like short minute breaks in between. But you must put priority to the research. So just like how you take time for your teaching and you're marking any time for the admin, you have to slot times.

[00:44:02] Speaker 1: Yep. Yep.

[00:44:03] Speaker 2: One more thing I would say. It's really good to have some research groups that you can interact with others who are doing research if at all possible.

[00:44:13] Speaker 1: Yeah. Yeah. It's really motivating to have a group. When I was in a PhD, we had a real cohort that we actually all were working together in the same space and we helped each other. That also has sort of dissipated with a lot of research, especially post-COVID with research moving online. Less of that true cohort effect happens. I think what Susan said about time blocking is important. Block off like hour to hour and a half blocks in your week and defend it to the death. Phone off. Socials off. Email off. And work those mental muscles to concentrate because everything else in the world, TikTok, Instagram, is pushing you to short-term concentration. This takes long-term concentration. You can't do research in five to ten minutes in and out. You're going to have mental resistance because you don't – I mean, I'm not saying you personally, but a lot of us don't have the same attention spans because of these quick hits that we get all the time, little dopamine spikes here and there. So you actually are going to feel resistance and doubt if you're doing that for the first time, but it's like a muscle. You can improve that attention span, that ability to tolerate deep work by training it actively. It's never going to happen, though, if you don't block off those deep work segments. The other thing I'd say is our optimization of one strategy. You've got to find your three-month milestone. The one thing that you've got to do that if in three months, you know, what's going to move the needle for me career-wise? And we like to plan papers on a three-month timeline. It doesn't work for all fields, but it does for most, especially in early stages of careers. So think about what that three-month milestone would be. Like, Yogesh, if we come back and we have this conversation here towards the end of April, what would you need to do to be feeling really, really good? What would be that outcome that you can hit? So I hope that helps. Okay, I'm going to head over here to Russell. Thanks for sharing that with us, Yogesh. And hopefully, you guys can hear this. Okay, so here's Russell. I'll try to get the volume up. Okay, here we go.

[00:46:12] Speaker 3: Hi, Professor Stratler. My name is Russell Ahmed. I'm 42 years old. I'm a bit late to the party, and I'm completing my Bachelor in Business Administration from a private university in Bangladesh. And in order to complete the degree, I have decided to submit a thesis instead of a project to work. And this is why I got stuck for the last two years. And even though I have a topic chosen, but I could not just start the thesis. I did not get any help from my supervisor as well. And this is where I had a question that, Is your research roadmap course suitable for Bachelor level students? And what outcomes are realistic at this stage? Also, do you offer any reduced fee options for students from lower income countries like Bangladesh? Thank you very much.

[00:47:07] Speaker 1: Okay, this is really helpful. I think because you've just shared a lot of the things that we run into, not getting any help from a supervisor. Susan, you see it too. You hear this all the time. So you have a topic. But turning that into a step-by-step roadmap plan is what's missing. Well, we just talked about that alignment spine. So you have a topic. It's good to have a topic neighborhood. But you need that topic neighborhood. We use a PICO model. There are other models out there. I don't want to get fully into it. To help turn that topic into a question that you can engage. Usually what you want to have, though, is you do need to map out the gap. And you want to connect that to a clear research question. So you've got to take that step from broad topic area to clear research question. Ideally well-defined boundaries and parameters using a PICO model. Then you need to connect that, completing that alignment spine, to methods that can answer it. So it's hard to get more concrete because I haven't seen this here, exactly what you're looking at. But, yeah, go from the topic to clear research questions. And move from there. And if you want to share at our upcoming workshops more specifics about your topic, we'll be able to diagnose quite quickly what you need to do to convert that to be publishable and into a step-by-step roadmap. You asked about roadmap. Check out our live session last week on how to set up roadmaps to find those three-month milestones. You say more suitable for a bachelor. No, this is indispensable for high-level research. Because if you don't have a roadmap, you don't know where you're going. So, definitely, this is, again, feelinglost.c tells me you haven't made a research roadmap for yourself. So I really encourage you to go back and watch that live session. If you are interested in checking out some of our support, here's a link here. And we do have some potential support available. So check that out. See if that applies to you. And you can join a fantastic research group. Susan, you want to say a little bit about the research group that you lead? Sure.

[00:49:23] Speaker 2: Yeah. So I'm a part of Fast Track Research Collective. And in Fast Track Research Collective, we have people from all across the world. And then we have research in different disciplines. So there's a research group in public health and a research group in computing. There's a research group in social sciences, psychology, and lots of other topics that I don't remember right now. And what's really good is somebody earlier had asked about how do they get from their topic to their research question. What's excellent about Fast Track is you get to see topics not even in your field. And people get their synopsis, get to read it. Your brain works because you get to see how to form research questions in other fields. And I can't imagine. It's something for myself. I learn quite a lot. It's very mentally stimulating. And the research groups really help to provide both emotional support as well as can answer questions you have in your actual field. What I'm really looking forward to is having more. Today, we actually had three people in the computing group. And it was really fun for us to talk about our goals. Some are similar and some are different. We just had a really good time talking about our goals for this year. And it can be really helpful.

[00:50:56] Speaker 1: Yeah.

[00:50:57] Speaker 2: I found it both locally and in that being part of a research group is helpful. By the way, it's not always perfect. It can be all kinds of challenges, but it's still worth it. It's more worth it than not worth it.

[00:51:10] Speaker 1: Yeah. I mean, the groups are self-organized, and some are coming together more than others. We're about 200 members at the moment. So some groups are more heavily subscribed than others. And, yeah, I anticipate that's going to continue to grow. Because like you said, it's been something that's been really special to have people in your field from different walks of life, different parts of the world, coming together. Not in a competitive spirit, but really all there to help each other be the best researchers they can be. I'm really proud of that. It's really special. And speaking of one, Jeff, I can see here, is joining us, who I think was there with you today. Jeff is saying, there's fewer 18-year-olds to start college. Many overexpanded universities are changing to respond to this. So the traditional age of starting a PhD has greatly changed. Yeah, that's very true. There is a – well, in an AI era, some have argued that the value of a degree is declining. And I think demonstrated capability, such as through publishing papers, gains more value. Because that can be verifiable, that can be attributed to you. Where with lots of AI slop and the level of, say, undergraduate degrees and others being substituted out by AI, there are bigger concerns about will AI replace a lot of those jobs. I do see the merit in the critiques that university degrees at the undergraduate level may be losing some of their value. So yeah, thanks for sharing that with us, Jeff. Yogesh says, thanks to you both for your insightful answers. Cool, glad that was helpful. I've got one more here from Sar Samuel George. I just want to see if I can get that one up, so two seconds. And we'll get his video here. Hopefully we'll be able to hear this.

[00:53:12] Speaker 4: Okay. My question is I have an undergraduate and postgraduate thesis that I did work on in the university. How can I work on it to be published and what are the procedures and steps involved in doing that?

[00:53:34] Speaker 1: Okay. So yeah, the volume was a little low, but basically what I understood was how can you convert your thesis to a publication? And so this is where you need some help. You need somebody to show you how to do it. The first thing I see sometimes when people have done a thesis, they think it's a natural step to publish. But sometimes things that get published as theses aren't – they might tick the box for a thesis, especially if it's at an undergrad or master's level, but it doesn't mean they're publishable. And in fact, I would say it is exceptional that they're publishable. Most undergrad theses and most master's theses are not. And even very – I would say even – I don't have data on this, but I would say only a small fraction of PhD theses actually get published in peer-reviewed journals. That's another conversation. But yes, you need somebody to give you real feedback and mentorship on this to, again, identify what's the gap and what is the value out of your paper. The process we use to calibrate that is to go in the literature and look at something we call your conceptual nearest neighbor paper. That's the paper that's the closest to yours. And you want to – Susan, you've heard me say this a million times. You want to calibrate what they did, where did they get up to, and figure out what have you done specifically over and above their paper because you'll need to cite them in your introduction and establish that value out of your paper. This is implicit judgment. Again, it's something that is hard to train to say, right, because there's value involved in this. Is this a big contribution or is this not? And that can be very hard for a novice researcher who's just starting out to see. So you want to cross-check that and get some feedback before going too far or spinning your wheels or where I see researchers who will have something that's just a dead end and they get reject after reject and they can't figure out what to do about it. And the problem traces to the original topic question and what the value out of the topic was. By the way, top two reasons for rejection, not a good fit in the journal, and not enough value out or novelty from your paper. So, yeah, share that with us. Happy to take a look and diagnose very quickly what your prospects are for publishing, which journal, what tier of journal you could probably get into or not, and what would be needed to go from where you are to get that to publication quality. Hope that helps. So without actually looking at it, we can't do a whole lot more than that. Let's take a few more questions and say, Francis, hey, Francis, you're joining soon. Started your PhD in October 2025. Awesome. We'd love to welcome you. Noel says, let me take this opportunity to invite our university establishment initiative here in Malawi. That sounds pretty cool. Noel, we'd love to hear a little bit more about that. Always very interested if you know some innovative models in this space that help with this shift from implicit apprenticeship to explicit apprenticeship. I'd really love to learn more about those. Dadaraji says, thank you, Prof and Susan. Dadaraji, good to see you. And, yeah, Dadaraji, I'll be seeing you at some of the next workshops. I have one coming up tomorrow for people who are at the pioneer level in our community. We have different levels. Try to make research fun. Susan, I think, has the most points of everybody in the community. So you set the bar very, very high. And Anna asks if there's a course to improve scholarly writing. Do you want to say something about that, Anna? Oh, sorry, Anna. Susan.

[00:57:23] Speaker 2: Yeah. So Professor David has a really good where he talks about peer and other things. I'm not saying the whole thing. But, for example, within a paragraph, you have to make sure. Some of it's kind of obvious, but it doesn't get done by most people. You make a point, you give evidence and examples, and then you either repeat or you link it to the next paragraph. And then the structure of the entire thing you're writing, the beginning of every paragraph needs to link together so the whole thing reads well. Actually learning to write well for academic purposes or for any other publication is not a simple thing. It's something that you have to learn. You need to learn. And FastTrack is a really good place to learn it. And you need both the principles and the feedback, as well as the camaraderie from other people. Those three things are all in FastTrack. I would definitely recommend it wholeheartedly.

[00:58:20] Speaker 1: Well, it's one of those things that's not, again, it's implicit. I talked a lot, and I like to ask researchers, have you ever been taught any academic writing training? And it's one of those things, again, they're just left to figure out. And so if you don't have a writing system, you're just kind of, and you can't bring high-level academic research. So, yeah, definitely. You can see on my channel, 100% free, our peer writing training. And I often do say, give me five minutes, and I will transform your writing. If you don't have a system, you can't improve. You're just kind of fumbling around, and you don't know what's better, what's not better. But there is a logic to how scientific papers are written. Also go and check out on my channel, I've got a playlist on how to write a paper step-by-step with some good videos that show you how to write the discussion section, the introduction section, the method section, and goes through actual papers across fields and shows what is in those sections.

[00:59:17] Speaker 2: And something that's really good is that he also teaches you how to read papers, how to read quickly and how to read slowly. That's really excellent.

[00:59:26] Speaker 1: That's true. I see people drowning in papers. But ultimately, Anna, I think there's no substitute for getting feedback from a mentor on your paper where you don't just get your paper marked up. So when I was a grad student, I got my paper marked up with lots of track changes. And what I had to do is I studied those carefully. I tried to understand why were these changes made. I remember the first time I had them, I kind of resisted them. Like, I was like, oh, they don't know what they're doing. I do it better. And that was the wrong idea. Then I shifted and studied it closely. And from that, I learned to create a writing system that can be transferred and taught. So definitely check that out. Ahmed says, million dollar advice. Thanks, Prof. Awesome, Ahmed. Glad that that helps you. Eli asks how one can join the workshop. Yeah. So there's a lot that I try to do as much as I possibly can here publicly, but there are more kinds of intimate feedback happens privately. So if you're interested in checking that out, follow the link here to the collective and join our research groups, get feedback, tap into some amazing courses that train research judgment, research literacy, and publish papers. It's a lot of fun. It's the support I wish I would have had when I was starting out. So guys, I think we're coming to a good stopping point today. Susan, thanks so much for joining us. A lot of fun to have you here. And I'd love to hear from you guys. Many of you are on Team Replay, watching from around the world. We can't hit every time zone here. But do let us know your thoughts on your PhD, your experiences, if this resonates with you, if you're getting good supervision and mentorship to truly thrive. And if you have innovative models you'd love to share with us, we're always looking to learn as well. Pop that here. Anna says, do we need to have a manuscript for review? No. I would say most of the researchers come at a very beginning stage. We have some with full manuscripts, but that's definitely not necessary. In fact, I think it's a whole lot easier to start from the beginning so you ingrain good habits from the start and don't go down dead ends. But yeah, Anna, good to see you. Susan, great to see you as well. Guys, we will be back next week, so stay tuned. If you're not on our email newsletter as well, I send you some of our best tips and trainings and where to find them. And I will see all of you next week, and Susan, I'll see you tomorrow.

[01:01:54] Speaker 5: Okay, thanks.

[01:01:55] Speaker 1: Bye for now, everyone.