text:
Just graduated with a master’s degree, but I internalised nothing
I just graduated with a software-engineering master’s degree with a good grade from a top-five university in the UK. I also have a bachelor's in computer science.
I always revised just for exams and just enough to get that first-class degree, without actually learning anything. I basically revise for the exam itself, by looking at past paper answers, and I never study the actual material. I then forget everything after finishing the exam. I've been repeating this cycle since school.
This method has given me a great first-class degree but with practically zero knowledge. As @Sule said, I never internalised the material.
I also never did a single internship because I didn’t need to.
Now, I’m facing a problem: How am I supposed to find work if I barely know how to program? Will employers just accept me because I have a fancy software-engineering master’s degree from a top-five university? I also haven’t worked professionally a single day in my life.
I'm thinking of getting a PhD at this point.

Any reason that this isn't just Imposter Syndrome? Do you have objective evidence that you didn't learn anything?

I'm voting to close this question because I think it belongs on [workplace.se] rather than here.

Answers in comments and general debate about programming vs. software engineering vs. studying computer science have been moved to chat. Please do not post answers as comments and read this FAQ before posting another comment.

@FedericoPoloni The Workplace has a question about the situation from the perspective of a manager.

There does not appear to be an actual question here. Most of the post is complaining; the question "how I am I supposed to..." is rhetorical, and "will employers accept me?" asks strangers on the internet to make predictions about the future concerning people they don't know; that's not possible to answer. Do you have a question that actually has an answer, or are you just complaining?

Don't worry, most programmers barely know how to program. The only way some programmers eventually get good at it is through fixing the messes created by others.

Well done on wasting at least 5 years and around £30k+. Can I advise you to take a role in management?!" :D

Community ruling on the related question is that it is too broad, and this one's even more broad ("How am I supposed to find work?")  This question is highlighted in HNQ, and should not be if it's failing to meet general standards of what's too broad for the SE network.

You asked,

How am I supposed to find work if I barely know how to program?

It sounds like you're looking for a job in industry, versus academia, so I will answer from that perspective.
Employers are generally looking for people who can get things done and will consider the ability to program as a means to an end. While technical skills (i.e. mastery of a specific programming language) will be important, it's never the only factor evaluated, and it's sometimes not even the most important factor. Combine that with the pace at which technology develops, and having a specific technical skill ends up becoming even less important, as that skill may be obsolete rather quickly. Go find a dozen software engineers who have been working in industry for a decade or more since getting a degree, and ask if they're still using the actual content from any of their classes. You may be surprised at the answers. What they will probably talk about is how valuable it was to become a "learning machine" rather than a knowledge repository.
You've described the process you used to get good marks on tests. That's a valuable skill. Employers don't inherently care about test scores, but they will care about someone who can pick something up, and learn it well enough to complete a task. In many programming environments, the ability to learn something, apply it, and then move on to the next thing is incredibly valuable - even if you "forget" that thing as you're picking up future things.
Further, Resumes and interviews are sales tools - you're selling yourself to an employer. Focus on the value you can add and match that value to their needs. There's a job out there for everyone - don't just spam every software job you see and hope one sticks despite your shortcomings - instead, focus on understanding your own strengths and then look for jobs where your strengths are a good fit. Write your resume to emphasize the skills you do have and be ready to talk about them in interviews.
Taking a bit of a tangent, there's a concept in motorcycling called "target fixation." Riding instructors working with new riders will emphasize the skill of looking where you want to go when in a difficult situation. This is because new riders who are surprised by a piece of road debris, or a vehicle out of place, tend to focus on that thing to the extent that the ride right into it instead of avoiding it. Apply that to yourself since you're undertaking the new pursuit of searching for a job: Don't become fixated on what you perceive as weaknesses or you may end up in a mindset where all you have to offer in an interview is nervousness about what you see as your own shortcomings.
As a final point, to address your comment of,

I also haven't worked professionally a single day in my life

I have a feeling that the quicker you can change that, the less significant your problem will seem. Once you have a few years of work experience, you will see life through a different lens - on the one hand, you probably don't want a menial job for the rest of your life, but on the other hand, your first job doesn't have to be the job - it's OK to just take a job and get some experience to give you some confidence and expose yourself to a professional workplace.

Quite.  I used BCPL, Algol 68C, and FORTRAN at university.  I have been paid to write programs since 1980, and the only one I used at work was FORTRAN - and I haven't used that since 1995.

@MartinBonner Fortran here. I feel your pain.

The motorcycle analogy is apt. So many videos of a car pulling in front of a motorcycle where the vehicles each turn in the same direction and meet in the front corners... stop fixating and turn against the direction of the obstacle and you'll miss the collision. Don't fixate on what you didn't learn, but instead on what you did. The OP says he 'didn't learn a thing'... that is patently false. It doesn't matter whether the degree was in England or China... getting a Masters meant there was studying and learning and attending some classes... something was learned.

This post talks about "valuable skills" specifically for programming roles, with recommendations on how these can be sold to an employer, and not getting hung up on weaknesses like lack of technical skills, concluding with a recommendation to get professional experience starting ASAP.  Your comments on a related question focus on finding a (n implied: non-programming) job that is a good fit to one's strengths.  I cross-link with this comment to let any reader who wants to read and figure out if there's a contrast between this & that or not.

Target fixation isn't just with motorbikes - You'll find that if you watch any episode of Canadas worst driver they will repeat "look where you want to go" - not "where you are going".   It's actually a really good life philosophy

Stop complaining and fix your problems.
Doing a PhD is not a solution. You say you internalized nothing during your Masters. What makes you think you'll internalize something during your PhD? If you don't, what makes you think the PhD will help you? You'll just end up kicking the can down the road, and five years from now, you'll have "Will employers just accept me because I have a fancy software-engineering PhD degree from a top-five university? I also haven't worked professionally a single day in my life."
Things to do now:

Realize that you don't have to internalize stuff. "Intelligence is not the ability to store information, but to know where to find it." -- Einstein
Learn all these things that you wish you had learned but didn't. If you barely know how to program, then learn how to program. Go practice. There are plenty of tutorials out there you can find using Google or your local library for you to self-teach.
Find a job. Visit your university's career center, if they have one. If not then you'll have to fix your CV yourself, find the job adverts yourself, and apply. You can still do it, it'll just be harder.

Points #2 and #3 aren't easy things to do, and they're not going to get easier. You can sit around moping about how you haven't learned anything, or you can do something about it. Your choice.

In 2008 I started a PhD, although in pure mathematics rather than computer science. I had had a school and undergraduate career much like you describe, and like you I had ended up with a 1st-class degree. I was always extremely good at passing exams, and my habit was to learn to the exam. I never retained very much information after each exam season was over, and because I was so skilled at passing exams I had never had to work particularly hard at any point in my academic career.
Part of the reason why I started a PhD was that I did not know what else I should pursue. My PhD was a disaster; I could not cope with the entirely different expectations of me since academia was no longer about passing exams (something I could always do without much effort) but about actually studying hard, something I had rarely if ever needed to do before. I responded poorly to this situation, retreating from the challenge and failing to adapt to the new situation. Several years later, I eventually left my course without having gained any additional qualification.
In summary, you should consider carefully whether you will successfully make the transition from undergraduate to postgraduate study; they are radically different and the approach you have described is not one that will get you anywhere. I know this from experience. In any case, I do not think you should start a PhD simply because you are not confident in applying yourself to some other path.
You probably have picked up more than you realise that makes you attractive to an employer looking for programmers, or graduates in the sciences more generally. An employer looking for new software developers, in particular, is not going to expect you to know much about how software development is actually practiced in the real world - even if you have the fanciest degree your undergraduate institution gives out. They expect that you will take some time to learn how to do things the way they want them done. You should avoid assuming that you do not have anything to offer an employer just because you feel you did not retain much specific knowledge.

If you have suggestions for how someone like OP should best be treated by the employer, they are welcome here.

Employers (mostly correctly) infer that if you can figure out how to pass tests at a high level, especially when specifically about something relevant like computer science, then you can figure out how to build a form (or handle the input, or query a database, etc.). You say you don't know anything, but I bet that you could implement binary search a whole heck of a lot faster than someone who's never programmed at all before. Of course, in your first job you probably won't have to - and you might not in any job after that, either. But you could figure it out, which is about the same thing as figuring out whatever it is you'll actually be asked to do in your job.
In fact, it's been so long now since you didn't know any programming at all that you literally cannot recall what it was like to not know any. So as far as you are able to think, you must not know anything - because you have no one who actually doesn't know any programming to compare to, because most people know truly zero programming and don't try to, so you are unlikely to have experience with anyone who actually knows nothing attempting to do it. The only comparison you can make is upwards, to people you assume must know more than you. This leads to a warped worldview, and often manifests as imposter syndrome.
In short - it is a normal human response to the weird and rarefied world you live in. You'll live.
As to what will happen in the first job, anyone with experience working with people fresh out of college (regardless of degree level) expects that in the first 3-12 months you will do little that turns out to be actually useful or valuable. With companies that know how things work, you'll be put on an existing project that has some minor changes to be made, or they'll put you on a special project that really only exists to get new employees up to speed on the local system. Any company that hires you with the demand that you "hit the ground running" is more than a bit silly, but they usually appreciate you pretend to be making progress and dirty hacks are the best they can hope for, and they'll pay you for it nonetheless. If you don't think back in horror at the code you use to get paid to write, you aren't paying attention.
What companies who hire people like you know is that you are at least of above average intelligence, you are used to figuring things out on short notice, and you have lots of experiencing turning out things that sort of seem to work even when you don't understand what is going on. You have years of experiencing doing what you are told even when you don't agree with it or see the point, to please weird and often inscrutable authority figures. You should at least be able to pretend you know what variables and methods are, you've heard of object orientation, you likely get the general concept of what a database is for, etc. - your degree should provide most of the fundamentals, whether you remember them very clearly or not. You'll be expected to cram to prepare for tech interviews (and later on, project presentations), anyway, which you obviously learned how to do too!
Honestly, this describes almost the perfect employee, which is why so many software companies are keen to hire from top universities - they know what they are getting! Sure, ideally employees would actually know what their job entails in full and be good at it already, but many hiring companies don't even know exactly what the job will entail month to month themselves - so how are they going to hire for that? Besides, people with all the skills already developed cost too much to hire and retain - you are not really competing with those people directly right now.
No, this is not the story these big-name universities tell, thus your feeling that your situations is unusual - but absolutely every manager working in IT/software I've ever talked with knows those marketing lines are baloney.
At the same time, that means some companies won't be very interested in someone with an advanced degree and no job experience. That's fine too - you don't need all the jobs, just one at a time. Apply to the sorts of places that hire people like yourself, who are in the position you are in now.
Having no professional experience, even in an internship, means an extra tick of challenge, but it is hard for everyone. Expect to have to spend considerable effort developing and being able to talk usefully about your past experiences. Preparing for interviews means recalling and retelling stories about class projects and assignments in ways that showcase what you learned, which you understandably don't recall easily - you'll have to work at it, and that's a big part of what "preparing for interviews" is.
Getting the first "related experience" job entry is one of the hardest transition periods. It's always this way. Using a PhD as a way to kick the can down the road will not automatically solve the problem, and you'll just have similar challenges to overcome then too.
You may need to take advantage of flexibility to travel and being willing to do work other people would pass over as 'boring'. Insurance and education companies, for example, often have to work hard to recruit people because everyone graduates and wants to apply to the most famous name-brand tech companies and don't even think about applying to them. Some pay less, some pay more, some companies are more pleasant than others, etc.
You'll get the first job because you get it, and that's about it. You put yourself in what turns out to be the right place at the right time, it won't be perfect, and you are unlikely to be especially good at it at first. But it's a start, and "getting good" is something you will have to work at for years - no one is good just because they went to college. With time in a related job where you have a good attitude, develop your skills and experience, and build up a network of people in a similar line of work, the next job can be a lot easier to find.

The bottom line of this is, I wouldn't retain expectations of a crazy paying job from the get go because of the degree; however it should act as a multiplier down the road as experience comes in. Just make sure you apply somewhere you can get actual valuable experience, and work with mentors to leverage that.

Since many answers are addressing industry, I want to add a counter-point here: I wouldn't be so confident in leveraging your credentials to get an industry job, at least not a particularly good one. Nowadays employers test applicants much more rigorously in software interviews versus the recent past. Probably due to the very weak or fraudulent credentials coming from some parts of the world, plus the usual problem of the bald-faced lies about skills people put on their resumes (perhaps heightened by the huge salaries offered nowadays for the right specialized skillset), and what seems like rampant cheating in schools everywhere. I'd suggest try and learn as much as you can of the key things you are supposed to know. A good way to get started is actually do a couple interviews, which will give you an idea what you need to review.
As for grad school, it is first about potential, not skills. They will want to see that you can handle the difficult concepts as you dig deeply into a topic. This is probably best demonstrated by standardized test scores, considered alongside grades. But current fashion is to not require the GRE at many places, in which case they will dig deeper into grades in particular courses. Another very important factor in technical fields is work experience, perhaps ironically. Particularly if it involves doing some R&D that is relevant to your phd program. In part it helps convince them you will not quit to go to industry, plus it suggests you already have strong skills to make for a valuable research assistant.

Programming is not difficult, mate. Being a software engineer is.
That's why any random idiot these days can become a programmer and for as much as they'd like to go around calling themselves "software engineers" or "devs", we all know they're just code monkeys that the smarter guys use to do their bidding.
So, spend some time learning 1 programming language. Java, C#, Python. Something widely used. It doesn't take long. Build some projects.
Even if you don't have the experience, being able to point to a personal project and say "I did this" goes a long way.

Which is why "programmer" is a synonym for "code monkey".

What about dark matter developers, then?

Now, I’m facing a problem: How am I supposed to find work if I barely know how to program? Will employers just accept me because I have a fancy software-engineering master’s degree from a top-five university? I also haven’t worked professionally a single day in my life.

I entered the UK workplace a few years ago with a Maths degree having never coded before and having never had a job outside of voluntary work in a charity shop. So you having a degree in a related field means that you can't have less practical knowledge than I did, and you probably have more than you think you do. Regardless, it's not the barrier you think it is. Starting on a graduate scheme or as a Junior Software Engineer should mean that the company is willing to put some resources towards you in terms of mentoring, so your programming knowledge and your best practices knowledge will quickly pick up in that period. (A slightly idealised summary, but whether by code review rather than by outright training, you'll have input from senior members of staff).
You're free to be honest that you're not coming in with incredible programming skills, but don't sell yourself short either. Many employers won't care about the university you got your degree from (I graduated from a top-5 uni in my field with a 1st, another guy in my intake had a 2:2 from a former poly), rather your willingness to get stuck in and learn and contribute is what will sway them.
On a lighter note, you know how to use StackExchange, so you know how to solve most rudimentary problems that will come up in your future employment!

If there were particular mentoring strategies that worked well for you, to make this "not the barrier you think it is," you are invited to describe them here.

I’m guessing you still have the learning materials from your previous degree or have access to them. I would start by pulling them all out and going through them by yourself. If you’re smart enough to stumble your way into a first class degree then you should be able to teach yourself the material and then practice programming, and if you’re still facing some difficulty, you should then probably ask for help. You must have had friends on your program who did well and actually internalised the material. Just ask one of them... and remember, you have no room for shame; swallow your pride and ask for help... Short of doing the degree again, I don’t see any other way out of this.
To be honest, a lot of people have to pull out notes from previous studies when applying for certain jobs to refresh/reteach themselves things they may have forgotten. Since you’re in a more intense situation, maybe take six months to a year out, if you can afford it, and teach yourself.
A PhD, I think, should be out of the question at this stage. It’s way more rigorous than your past degrees have been and seems like jumping out of the frying pan and into the inferno.

If anything, I would consider taking some online courses on programming before jumping into a Ph.D, if you want to be able to program. I also second the concern that this could be  imposter syndrome. Taking some courses online (not through a university) and taking the time to learn the programming languages may help you realize you know more than you thought you did, or it will help you catch up and get you where you need to be. Either way it is beneficial.
Complete applied projects while learning to showcase during interviews and prove you have the knowledge and capabilities even though you don't have the experience. This combined with the Master degree should open many doors for you.
Also, there are roles in software development that do not require you to be the one doing all the coding. Have you taken any courses on project management or business analysis? If you do not want to be the one programming, there are plenty of other roles to be filled in technical fields. You may want to research other roles.
I understand how stressful this scenario is and I wish you luck.

But do you want to work that?
I don't really find any of your stuff you said to be a problem. Go and apply to be an intern somewhere, they do not require knowledge. Since you have the "talent" to learn fast and understand things, in no time you will get to the point where you can have the job you want. As the other people said - there are so many tutorials online that you can learn from if you want, this + being an intern somewhere will help you fix all your 'problems' since you will learn so much. You are not the only one tho, I know a lot of people who get A on all subjects in computer science, but they do not know how to code, and they work in a supermarket. The choice is yours, no degree will ever teach you to be a good programmer, practice and understanding of the code and when to find something that you need will.

Only few people are prepared to "work" right after finishing school (and I don't mean that you're not a good professional, just that you have no experience yet). Always be honest in your interviews and don't worry about that too much, all of us already had this problem, we all faced the same situation. When someone like you is hired, your working colleagues should expect that you need some time to adapt and learn how to work.
The good thing is, everything is in your mind, although you don't think so. As soon as you need them, they will pop out from your memory and things will get better. Also, you should have a fresh mindset, which gives you an advantage because you will see things that people who have been working for a long time can't see immediately.
Don't get afraid, that's normal. Believe in yourself and good luck :)

Education isn't everything. You have to apply it, and decide for yourself if you need to study more, or continue working and learning on the job.
Can you believe that I wouldn't have known what a WEB API was if I just followed my courses, finished university, and finished grad school? I learned most of my CS topics while working
I think I can help with this because I am currently in your shoes ... or was.
I am currently getting my BSc while studying Computer Science at a top university.
However, I do not plan to get my masters, or even if I do, I do not plan t o have any hopes from "achieving" anything out of it
Here is why:
A master is obtained after your BSc, which should've taught you how to code. When you say you don't know how to code, that sounds really strange to me because coding is the first thikg we did in University. Sure we learn some useless theory here and there, but we definitely learn coding, ddesign patterns, testing, etc.
So when you say you don't know how to code, I think you are lying to yourself.
Secondly, when I went to intern at a place, my manager himself said that Master in CS is useless. It just shows that you are willing to learn more, and were able to do it, but rarely will have an impact on your role. Because the skills the employers look for, just don't matter when you take a masters. Perhaps in other fields like Business or Medical, it makes a difference,  but if your goal is to be a developer and not contributete anything research wise, then master is pointless.
People can disagree with me, but I am spitting facts here, based on industry standards.
So back to your question. You do know how to code, if you didn't you would'nt have got a BSc.
If you are not confident, get a introductory job, or go to youtube, create some projects, and learn.

Can you believe that I wouldn't have known what a WEB API was if I just followed my courses, finished university, and finished grad school? — Yes.  Quite easily.

Is that why (you?) downvoted? I'm just trying to get the point across that some simple industry standards won't be taught in school, so you can't expect having a masters and expecting to have learned much of anything of importance

No, I downvoted because having a BSc does not imply knowing how to code.  I have certainly met CS graduates who can't program in any useful capacity, myself included, and I'm a CS professor.  And I have heard many tales of students squeaking through my department's undergrad program, even with reasonable grades, doing as little as possible on their own and relying on friends, github, CourseHero/Chegg/Koofers, and StackExchange for everything else.  Perhaps OP is merely suffering from impostor syndrome, but it's naive to believe that they can't be telling the truth.

If you are telling me that a BSc can't teach you to code in this world, then what can? Surely you will not be the best coder, but university is designed to at least give you a more then average introduction to the art. Out of BSc, you should be able to understand concepts, apply them, and translate them into code. I don't know where you teach, but If I just graduated from a BSc and asked my boss what an if statement is, or how to write one, I think I'd be fired on the spot. If students rely off of CourseHero and such, that is clearly plagarism

Stackoverflow is meant to help you, but even the answerers understand when the student is just blatantly asking for answers as part of a school assignment, and as such will note this when providing feedback

@KSplitX I don't think that JeffE is saying that a CS degree can't teach you how to program, just that graduating with that degree doesn't guarantee that the person actually did learn how to program. Some departments and systems are better than others at weeding out the people who aren't actually learning, but it is totally plausible to me that some of the people I graduated with had next to zero ability to actually program

What @KevinWells said.  I completely agree that a CS degree can teach you to write code, and that anyone with a CS degree should be able to write code, and that copying from CourseHero, StackExchange, and the like is plagiarism. But not everyone with a CS degree actually does learn to write code, at least with the proficiency that would interest most employers. (Also: "knowing what an if statement is" is to "knowing how to write code" as "knowing what a pronoun is" is to "knowing how to write".)

So you are just "spitting facts"? "Based on industry standards"? And this is from having spoken to some guy you did an internship with. Great source to base such an authoritative answer on.

I agree with @JeffE. I think you illustrate the point perfectly. But it's just hard for me to believe that no one would know the basics even after graduating. What did you learn in those 4 years then?
And I am not just saying the masters thing just because one person told me. In fact if you do a search for "master's degree in cs reddit", you will see many links that show how the requirement for masters in CS is slowly fading, since companies mostly care about the coding skill

I can tell you the university I was in, does not cover coding whatsoever in its computer science bachelors, as they consider that engineering. It covers the mathematical theory behind computer and system design and the theoretical basis behind programming. However it does not teach any programming techniques or languages on the grounds they change too often to be worth it. (I wasn't a CS student, I was in computer engineering but I confirmed this with the faculty staff)

@Vality At my university there weren't two separate departments for computer science and computer engineering, and our computer science degree was heavily programming based, but I'm sure if someone were totally disinterested in actually lerning how to code they could have figured out how to coast by through mooching off of team mates for larger projects and using the internet to piece together the rest. It was a small enough department that one of the professors would probably notice and bring it up with them or the other professors, but it isn't impossible

Well computer engineering is different right? The OP mentions degree in computer science. Perhaps the education system is to blame for this

Here's the thing about work: you don't do it under exam conditions. You know you can pick things up fast - you have a first class degree from a top 5 university by virtue of doing that. That is a skill you can use, once you have got through an interview.
I've got about 10 years of working in industry, and a good reputation. I am also not great at internalising syntax, and often feel like I'm starting again after a few months away from a language.
What I have though is a set of crib sheets and reference books for languages I commonly use. My employer is fine with that - they care that I do the work right, not whether or not there is a crib sheet pinned to the divider next to my monitor.
If you can work out how to solve a problem in a given language in reasonable time, it does not matter how well you have internalised the language. In fact, being able to pick up obscure languages fast and apply them can be a valuable skill.

Education is there to teach you how to learn, develop your knowledge, and find what you're interested in doing in the future. It is not there to prepare you for the real world; that's what internships and traineeships are for, amongst entry-level jobs in general.
An employee who learns things quickly and efficiently when given the right guidance is what companies are looking for. It takes some longer than others  to get to this point, and to have the confidence to consider themselves worthy of a position they were educated for.
I wouldn't panic just yet - you haven't entered a work place yet. However, when you get to the point where you feel like you hit the wall I suggest that you don't give up, because perseverance is a skill you will need in every job.
Apply for places and show your true self in the interview. Try to be as much  prepared as possible. Don't judge yourself harshly just yet.

This isn't really an answer, but it's not really a comment either, but it's more of an answer than a comment, so here it is.
In programming, there's way more to know than can be retained.
I've been a professional dev for almost 7 years, and have used almost 20 distinct languages in around 25 years since I started learning programming. I still have to look up the way to use "substring" every time I use it, since it's different between JavaScript, PHP, C#, Java,  etc. As many times as I've used "substring" in those languages, I just can't remember which one does what and parameters plus param order.
Simply, you don't need to internalize everything, only what's currently needed. This is especially relevant to newer programmers/coders/devs/engineers. As you develop your career, the things you thought were necessary in school may not be what's actually necessary in a job. As you gain more experience, you'll internalize the things you really need. Anything you forgot can generally be Googled. You'll also learn more from senior devs than professors, and you'll teach other devs in turn.
Don't worry so much about what you think you know. That will change over time and why an interview is often more enlightening than your resume.

I would like to add my two cents.
I think that at this point, the most important decision to make is - what is it you actually want to do to earn money. It is very hard to proceed without making this decision.
Your options are:

Code
Manage
Teach
none of the above

You can try actual coding by participating in an open source project. This will give you a taste of what it actually is.
You can go into software project management. This is a totally different skill. May be this is what you are good at.
With PhD you will be able to teach programming, albeit without ability to do so. Working in academia requires a totally different set of skills.
The last option is very interesting.
I know lots of people with dual majors who kinda program, but they are closer to the business side of it. Say, with a major in Accounting you could build and support accounting systems. With a tax license, you could build and support tax systems. With some systems knowledge you can do systems integration.
My point here is that commercial coding is not the only option for a holder of a Software Engineering diploma.
Hope this helped.

It is hard for me to believe you. I just graduated as a Software Engineer and well, we programmed and programmed since first year. Our exams were different every year on different programming problems (of course, maths exams, dbs, some theoretical parts in concurrence or whatever, do not fit in here). But having not learned to program in a full degree + masters, it just makes me think the university is not that top as it should be.
Taking that aside, I got the question for you. Do you like programming?.
If you do, you'll have no problem in learning and soing stuff at home by your own. Free coursera practical courses, etc. I do not really see the deal here...

You should believe in yourself. If you really like to study for a PhD, go to study. If you don't like it, start an internship and accept the challenge from now on, because this day will come sooner or later.

This does not answer any of the questions at hand. How is he supposed to do an internship if he has no experience. Etc.


text:
Is participating in professional meetings helpful from a CV point of view?
My professional society (a physical sciences one), arrange an annual meeting where almost 10,000 people attend and almost one third of them present. The benefits of participating are overwhelming, but I was thinking whether or not such participation is useful on a CV, especially that what you present is not going to be published (although normally you present your work which is to be published or has just been published).
Note that this is a meeting, not a conference.
EDIT: by participating I mean presenting.

What exactly do you mean by "participating" here? Just attending or also presenting?

I mean presenting.

What's the difference between a meeting and a conference?

The key factors here are that it's a contributed presentation (not invited) and it's in a huge meeting with many presentations of differing quality.  It sounds like you may be talking about the APS March meeting, but similar things are true in many other cases, such as the AMS/MAA joint meetings in January.
How valuable such a presentation would be on your CV depends on how far along you are in your career.  If you are coming up for tenure, then you'd better have far more impressive things to list on your CV, and presentations like this would be inconsequential.  (The only value on your CV would be in demonstrating continuing scholarly engagement if your job is almost entirely focused on teaching.)  If you are a college sophomore, then presenting at a meeting like this would be noteworthy.
To a first approximation, if you're an undergraduate then these presentations are worth highlighting on your CV (unless you are lucky enough to have something more impressive to emphasize), while if you're a grad student they are worth listing but probably won't be very important.  However, it's worth asking a mentor for personalized advice.

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My manuscript status says that one referee sent a message but not a report
About three weeks ago, I submitted a paper to a highly reputable physics journal. (I had another paper recently published in this journal as well.) I have been checking the status continuously, and today I saw the following as a follow-up to a referee request:

message received (not a report)

I am curious about this status update, as I have never encountered it before. What does this notification mean – rejection of my paper or acceptance?  It would be really appreciated if anyone could share experience on this.

PRL? The referee probably declined to review the article. The Editor will likely try to find a new referee now. Good luck!

@Bubble Any possible reason why a referee would decline to review?

Most likely time constraints or they don't feel that they're sufficiently knowledgeable in the field to asses the quality of the article.

It means that they received some communication from the referee other than a report.  Different journals have different workflows for referees.  Some do not send the manuscript until a referee has agreed to referee the work.  Some let the referee see the manuscript and give a short-ish deadline for the referee to decide whether they can eventually send a report.  Some other journals (such as the journals of the American Physical Society), send the manuscript and ask for the referee to send them back a report, without ever asking for the confirmation that the referee can do the job.
I suspect the journal works using the second system.  This is significant, because the first response that the editor might receive from a referee may be the final report.  Or it might not be; the potential referee might write back to decline the assignment or to ask for more time.  So it is important to identify whether a response received from the referee is or is not a report--and that's what you are seeing.

Thanks heaps for the response. Actually it is a APS journal. Last time when I sent them my manuscript, referees had directly sent the reports (no initial message). Therefore, after seeing this status update I am nervous. :). On the other hand, as per my understanding, this cannot be a rejection, because in that case referee supposed to send a report.

If I am not mistaken, this status message in the APS system can also be caused by referees agreeing to review (which they do not have to).

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Taking a break between master’s and PhD in Physics
To any PhD holders or candidates out there, how common is it to take a break after your master’s before applying for a PhD course? I currently have my master’s and due to bond fulfillment have a research attachment for a few years.
Would my PhD candidacy be any more difficult/less viable because I’m both older and have been away from academia longer than those who have gone directly from an MSc to a PhD course?

What country are you in?  Customs often vary by country.

@jakebeal I'm in Australia, but I would like to know the customs for the US and UK too since I've done my undergrad studies in the UK and am intending to go to one of those countries for a PhD.

Many people find it more difficult to pass their PhD exams if they take a significant break.  It can often be helpful to have things fresh in one's mind for the exams.  However, this, of course, can vary by the individual.

Good answer for the US, but I think there are no exams in the UK.

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Is it good reputation for a researcher to publish an article belonging to different research field?
I have a BA in International Relations and  MA in Water Management which is the field I want to do research. However recently one of my former professors in my current workplace asking me for colloboration in research related to international relations. Now I am in a difficult position as I do not know what to do. Do you think it is okay to have this kind of publication?

Many times, having an interdisciplinary view is considered positively these days. It may depend on the specifics of the research topic, but I see a lot of possibilities for combining international relations and water management.

If the paper is good, then having the publication is good.  If the paper is bad, then having the publication is bad.

Since the fields are so far apart, a publication in one might not help you in the other, specifically. However getting some research experience is both worth the effort and will be looked on positively. In addition to being relevant to some field, research involves a process requiring focus and discipline.
I'd only recommend against this if the time involved would take you away from your mainline trajectory.
The publication won't hurt you. The experience will help. But it takes time and effort.

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Bibliography format with multiple citations from same book? (APA)
I'm writing a paper where I've included multiple citations from a book, each citation is not a direct quote from the text but rather a in-text citation.
According to APA guidelines, these citations should be at the end of the paraphrased text such as:

My text here blob blob blob (Rubin, 2013).

Since these citations do not include page numbers (direct quotes do, according to APA guidelines) and I have three (so far) when I insert a bibliography with Word these look like this:

Rubin, K. S. (2013). Essential SCRUM. Ann Arbor, United States of America: Addison Wesley.
  Rubin, K. S. (2013). Essential SCRUM. Ann Arbor, United States of America: Addison Wesley.
  Rubin, K. S. (2013). Essential SCRUM. Ann Arbor, United States of America: Addison Wesley.

So, my question is: Is it okay to have these duplicate entries in the list of references/bibliography at the end of the document or should I add the page number to both in-text citations and references, even though they're not direct quotes within the document but in-text citations instead. I hope that makes sense.

Hi, what did you find when you consulted the APA style guide?

@shoover Hi, I couldn't find anything related to list of references/bibliography. They give you guidelines for citations at the end of references/quotes, for example, put letters to distinguish them: My text here blob blob blob (Rubin, 2013a)., My text here blob blob blob (Rubin, 2013b).

I think References are in chapter 7 (APA 6).

Normally duplicates are avoided. Also, your duplicates do not have a page reference and are therefore useless in this respect.
Whether or not you have to specify the page number, I would personally check with your supervisor to avoid misunderstandings.


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Having your name added to a research paper
If I conduct experiments including behavioral tests and laboratory tests and I analyse data. I also proof-read and help writing said research paper that later goes on to get published. Is it unreasonable for me to assume that I should I be an author?

Just to make things clear, is "someone" you?

Yes and to clarify I was not considering being put down as a co author but just having my name added. There was a presentation that was done at an international conference and my name was on that abstract but the papers related to that abstract which did get published did not have my name on it.

"I was not considering being put down as a co author but just having my name added."  Added as what?  As an author of the paper?  Wouldn't that make you a co-author?

Authorship, if that is what you are asking about, normally requires that you have intellectual contributions to a paper, not just work and effort. If you did all of those things under the close supervision of others, then you should be acknowledged somewhere, but perhaps not as a co-author. On the other hand, if you were the instigator of some of those, or if you otherwise contributed to the direction of the paper, then you might be due authorship.
But such questions are subtle, and, as Noah Snyder says, this should have been worked out early on in the research process.
There are various lists of what is required for authorship. For example, see this one from Harvard University and note that AND is used for the individual criteria.

It's always unreasonable to assume someone else is going to do something that you've never discussed. Talk about authorship early on in this process! From your description it does look like they probably should have added you as an author, and it might not be too late, but you're going to have to actually talk about it.


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How can I enumerate the past research to show my research is noteworthy?
I'm working under a professor as a research assistant. She is preparing a proposal for research she wants to do with unmanned vehicles. A part of this proposal is showing that the past research doesn't focus on large numbers of vehicles, and the ones that do are not as intelligent and use "swarm behavior". Her research will focus on large groups or intelligent vehicles, and wants to show that she is doing something that is rarely researched. She's tasked me with putting together a list of the past research in this field noting the number of vehicles each paper experimented with and whether it was low level swarm behavior or something more intelligent.
As I'm putting together this data, how can I show there's a hole in the current research without citing hundreds and hundreds of papers? Does what I'm doing have a name that I don't know about?

As I'm putting together this data, how can I show there's a hole in the current research without citing hundreds and hundreds of papers?

You are being asked to cite hundreds and hundreds of papers (if that's how many there are).

Does what I'm doing have a name that I don't know about?

Depending on exactly what you are doing, this is most likely a "systematic review," or (less likely) a "meta-analysis."

If there is already a paper with a sufficient bibliography you could also point to it, rather than listing everything again.

As the OP does not indicate that statistical values (for example on UMV performance metrics) are relevant, I don't think a meta-analysis is of any use here. Also typically for proposals you don't do these analyses, you do a focused literature review.

@jadepx That's why I said "depending on exactly what you are doing." I meant to imply that it was more likely to be a "systematic review," but I wanted to include "meta-analysis" since it seems like OP is fairly new and that might help them locate resources.

It is not possible to enumerate all works.   First, in the area of unmanned vehicles, there are upwards of 10K+ papers.  Second, it is impossible to check whether you have covered all papers.  Moreover, each day, there will be new papers posted online.  Lastly, authors may call a concept by a non-standard name, which means you will miss their papers.
My strategy:
First, determine the key contributions that you wish to make.  List all potential gaps or ideas you think are new.
Second, from your list, draw up a bunch of keywords, e.g., 'vehicles+platoon+swarm+intelligent'.
Third, search for these keywords, and read the Abstract of papers to determine whether they are closely related to your ideas.  If there are too many keywords, you may not find any works.  Then it is time to remove or change some keywords.   Alternatively, you may find too many papers.  Then it is time to add or change keywords.
Fourth, form a mind map of what the general research aims or setups of works in your area(s).
Fifth, write down identified gaps and how your work relates to prior works.  This is where you will say 'To the best of our knowledge, ...'

Although some other answers have suggested a comprehensive systematic review, I do not think that is feasible or even desirable for your purpose of providing evidence for novelty for a single project. Let me suggest a different strategy that might be more practical.

You should search for articles on this topic published in the past two or three years. Presumably, such articles will have tried to do some kind of review to demonstrate their own novelty, so read these sections carefully to see if there are any articles that they have identified that are similar to what you are doing.
Look up any articles referenced by the first round articles that seem relevant and then likewise carefully read their novelty sections to see if there is anything similar. Repeat this process iteratively until you are satisfied that you have found what is considered to be "new" in the relatively recent literature.
The previous steps are a good start, but are not sufficient. So, next, among the most relevant articles that you have located (all of which have been published relatively recently), try to contact the authors of those articles and ask them directly by email if they have anything to recommend to you related to your topic. Recently published authors should be quite knowledgeable, so if they reply, they could quickly cut your work short for you. To increase chances of replying, I recommend that you email each author of each highly relevant article individually (not as a group). Hopefully, even if just a few reply, you should get some very valuable pointers.

Concerning the last step of contacting authors, be sure to get your professor to agree first, and to get her to preapprove the email that you send out--you do not want to divulge more details about your project than she is comfortable with.
One point to note about contacting authors is that when your article is eventually sent out for peer review, there is a good chance that some of those authors whom you have contacted might be selected as anonymous peer reviewers. This might or might not be a benefit. The positive side is that, if they respond, at least you wll be sure to include references that they include important.

You might want to start by testing whether the hypothesis is correct.  Try and actively look for papers that are similar to the proposed work.


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How to React to Incorrect Claims by Reviewers?
As this has happened to me several times for different papers now, I am not describing a specific case here, but the abstract aspects that were common to all situations.
Occasionally, in the "Tasks" or "Materials" section of the "Evaluation" or "User Study" chapter, papers of mine contain statements such as:

"Figure ... shows one of the tasks from the user study. The correct answer was ... ."
"For the user study, we had prepared eight tasks. They were given in the form of natural-language questions. Users were supposed to use our novel concept to input the appropriate parameters as described by the questions. Questions ranged from simple (such as '...?', see Figure ... for the solution) to complex (such as '...?', cf. solution in Figure ...)."

In these cases, the figure captions once again mention the figures depict questions and/or solutions from the user study.
Occasionally, these are met with reviewer comments such as:

"The paper does not provide any example of the tasks presented during the user study. It would greatly improve the quality of the paper if the authors could at least provide one such example. Without this, I find it very hard to get a clear idea of how the study was conducted, and thereby, I also cannot tell how reliable the results presented in Section ... are."

I base my reasoning on the idea that this reviewer comment is, plain and simple, incorrect, as I did provide concrete examples of tasks. If I am somehow mistaken about this, please do let me know.
While such statements were certainly not the only reason for voting to reject, some of the reviewers who wrote something along these lines made it rather clear that they saw the alleged lack of any task examples as one of the most critical issues with the submission.
My question focuses on the situation that such a paper is getting revised - either, because it was accepted after all, and I am preparing a camera-ready version, or because it was rejected, and I am trying to improve it before submitting it elsewhere: What is the appropriate reaction with respect to such comments?

Ignore the statements and do not change anything about the respective examples in my paper. This might be a viable way to go, but it leaves a bad taste to completely ignore some reviewer statements, even though they are clearly comprehensible and should be straightforward to implement.
Re-word the sentences mentioning the examples. I might do that, but I am wary of making things worse, as I already consider the respective statements in my paper quite unambiguous as they are.
Add more examples, and possibly at different locations. This could make it harder to miss the examples, but in CS conference papers, space is an extremely scarce resource.
Ask the editor. Especially in cases where the paper was eventually still accepted, this seems quite extreme to me. I feel contacting the editor should be reserved to truly exceptional and severe issues, not "every-day worries" of all authors who are preparing their CR-versions.

Note that I am not asking how to deal with the review decision. Even though it is slightly annoying if a rejection is indeed based on incorrect reviewer statements, I am ok with resubmitting a revised version elsewhere. I am specifically asking how to revise the particular parts that were incorrectly criticized.
Some peculiarities of my field to note that might not be obvious:

Only some conferences have a rebuttal phase. If they do, it is not guaranteed (or even reasonably likely) that especially reviewers who criticized a paper a lot will actually read the rebuttal and possibly even amend their review. Also, these rebuttals are usually limited in length (e.g. to 500 words), so you can usually mention only a selection of all issues raised by reviewers.
CR-versions are rarely accompanied with explanatory letters to the editors (or, more precisely, the program committee) in my experience.

Submission usually happens by means of web-based submission systems which allow the upload of exactly one PDF file, which is sometimes automatically checked on formal factors, such as number of pages (so even tacking an extra page with explanatory notes in front of the paper will not work).
If an opportunity is provided to upload some additional files, this is usually meant for uploading sources and supplementary material such as videos that will be put on the proceedings CD. It is not clear whether the material will be sifted thoroughly enough so letters to the editors will be found in time and treated appropriately.

My field is related to HCI.

Therefore, contributions are sometimes graphical in nature. Consequently, figures sometimes do not just provide information about the contribution (statistical graphs, exemplary architectures), figures are often a crucial part for showing the contribution. In other words, sometimes, the depiction is the contribution, or it shows how the novel concept presented in the paper does something.
User studies are used to test how well human users can get along with the novel concept. Therefore, tasks are often written as questions. Study participants then have to find the correct answers to these questions by using the novel concept being tested. This usually means that they have to interact/make inputs with/in the implemented prototype that shows the novel concept. This is meant to mimick how the concept would be used in real life, where users would use the respective novel HCI technique for retrieving information, as well.

It seems like your situation very much hangs on your specific CS discipline: strict page limits, single round review cycles, rare rebuttals. A lot of things that would come to my mind in other disciplines won't work for you.

I assume you are in CS (me too). I am not sure about your subdiscipline, though. Because the examples you use "Figure ... shows one of the tasks from the user study. The correct answer was" or "For the user study, we had prepared eight tasks". Those examples do not sound like the typical CS paper.

@Alexandros: My field is HCI-related, so contributions, concepts, and/or parts of user studies are typically graphical in nature. As I think I once mentioned some time before in some other post: In my field, some figures do not merely describe data about the contribution. Some figures show, or are the contribution.

As a casual reader, not familiar with your field, I find your example sentences a bit confusing. For instance, I find it difficult to associate a correct answer to a task, or to consider a task given in the form of questions. I also find it unclear the sentence "Users were supposed to use our novel concept to input the appropriate parameters as described by the questions". Maybe, the reviewers shared my same perplexities.

@MassimoOrtolano: That is an interesting remark. I have expanded the last paragraph in my question to point out the usual way user studies are done in my field. Hope that clarifies it for you. (That notwithstanding, my user study sections in the papers usually provide some more introductory information, such as "In the user study, users were given a number of questions. Each of the questions constituted a task, and users were asked to provide a correct answer.")

I almost never ignore a reviewer comment.  Even if the reviewer is simply wrong, the way in which they are wrong usually points out a way that some significant subpopulation of readers is likely to misread the paper.
Given this, when a reviewer seems to have simply overlooked a chunk of the paper, I will generally fiddle with the wording, the structure or the introductory material in order to make it pop out more clearly.
For example, with your "eight tasks" example, I might do any or all of the following to make the presence and visibility of the material more blatant:

Make sure that the introduction has a "the structure of this paper" subsection that includes the word "example" in it.
Do the same for the section including the tasks with a "structure of this section" paragraph at its beginning.
Add a subsection header for "Examples of Tasks"
Put the question examples into a bullet list, rather than prose

Remember, the reviewer may be incompetent and sloppy, but many of your readers will be also.  You want to get your point across to as many of them as possible, regardless.

+1 for "the way in which they are wrong usually points out a way that some significant subpopulation of readers is likely to misread the paper"

+1 for same! This is a guiding light, even without reviewers. If your friend reads the paper and something is not clear to them, they're not going to be the only one.

A simple rule of thumb can help to handle reviewer comments:
"The reviewers are always right, even when they are wrong."
This means that when reviewers make wrong assumptions or draw wrong conclusions, apparently the article is not clear enough and allowed them to do so.
Mostly, in my experience, the solution that works best, is to restructure the article to prevent readers from drawing wrong conclusions. Make the text clearer, improve the structure, avoid being overly verbose.
The reviewers will appreciate such an approach more than you trying to point out in the reply-to-the-reviewers why they are wrong, or just ignoring their comments.
When your article was rejected immediately, then use this approach to improve the paper for a new submission, and prevent running into the same issues.

Could you expand your answer with a concrete example, please? When there is a chapter "User Study" with a sub-chapter "Tasks" that contains the statement "There were eight tasks, for example: ''", and the conclusion by a reviewer is "No examples of tasks from the user study were provided.", I truly do not understand how I can improve the structure or make the text clearer. I would be interested in seeing how other authors handle this, without risking that at the same time, the text gets less clear for the other reviewers who found all the information.

@O.R.Mapper, one thing you can do is scatter more pointers to the example(s) throughout the text. That works especially well if, as your original question suggests, a task is exemplified in a figure. The figure belongs to a specific section of the text, something like "methods", but already in the introduction you likely say something about the fact that you had subjects who performed tasks, and there you write in parentheses, "for examples see Sec. xy and Fig. z".

@O.R.Mapper: it is difficult to provide advice for your concrete paper, since I did not read your paper, nor the reviews. It might be that the specific chapter is perfectly fine, but that the overall paper structure can be improved, or that the paper is too lengthy, or that the paper deals with too many details, or that the audience of the journal and the paper do not match well, or something completely different.  I understand that it is frustrating when reviewers comment about something that you consider to be completely evident (trust me, I have been there).

Alternatively, it may be that the concrete nature of your examples are not as concrete as you may think they are - try to re-enforce the substantiality of your evidence, and highlight it as plainly as possible.

@Zibbobz: "concrete" is meant as "literal" - the exact words that were shown to study participants were also written in the paper.

The following is predicated on the assumption that the reviewer comments indeed concern mostly editorial matters which can be resolved through modest amounts of text editing (your examples look like that), and do not raise any substantial issues (an example of which would be where reviewers ask you to carry out additional experiments which would take a serious amount of time). In the latter case i would suggest to get in touch with the editor to discuss whether or not the additional work can reasonably be expected to be done within the time frame given for revision (if any).
I think that two things happened: the reviewers were either sloppy or they did not have the time to read the paper un-interrupted and forgot some parts of it, and secondly: you apparently made it easy enough for them to forget parts that are relevant.
Not knowing your papers, i can only give general suggestions to avoid the second issue or reduce its impact. The first is to have a proper structure in your paper: have separate (sub-)sections clarifying different aspects of your technical approach. In my sub-field of CS it is for example very common to have a (sub-)section describing the system model, which can have further sub-structure describing the fault model, load models etc -- even when I as a reviewer forgot some detail about certain assumptions or details of the experimental setup, i know where to look when such a section is there and stands out. And secondly, you can sprinkle cross-references to the relevant sections in various places ("The user did well in task X (see Section x.y for the task description) because ..") instead of repeating the task descriptions.
Fixing / re-organizing your paper along these lines should definitely be part of your reaction, don't just ignore such comments. I would recommend against bugging the editor about editorial issues -- the onus is on you to make things clear and to keep reviewers happy.
To summarise, I think your overall approach should be based on the assumption that all is your fault and not the reviewers. I am not saying it is, but i think the outcome overall is better if you treat it like that.

The examples for tasks were usually provided in a "Tasks" or "Materials" sub-section of the chapter "Evaluation" or "User Study". In my subfield of CS, the common structure for papers is often "Introduction - Related Work -  - Implementation - Evaluation - Conclusion and Future Work" (not necessarily with exactly the same titles). Your suggestion with cross-references sounds promising.

"forgot some parts of it" seems to be somewhat unlikely when the desired examples appear in an outstanding form such as here, namely as a separate figure.

Being a researcher myself and having seen how the review process is done, I know that there are reviewers that give the review task to their students and these students who are not experts evaluate papers written by other serious researchers. Of course, later on the original reviewer also does a check on the reviews written by the students, but I think this is a huge blow to the quality of publication.
Of course, I cannot tell how much common is this practice. May be very little. And since you complained that you frequently get those negative reviews, I believe you are not a victim of these non-qualified reviewers.
On the other side, as another answer mentions - a reviewer is always right.
So, from your description, what I would suggest is, try to create clear description of your examples. For example, write subheadings, "Example 1", "Example 2" and this way, there is no chance even a half careful reviewer will miss it.
Remember, these days most of the reviewers are overburdened with other work, and if your paper is not very clearly readable, chances are you will get negative remarks, even when you think you don't deserve it.

If the article is accepted and there is no rebuttal phase or step and you really had a section that called out the tasks, ignore that part of the review. If there's an opportunity to rebut, or this is a journal where the editor needs a response, then write back to the editor that you have already provided example tasks, cite the page number and section, and quote the text. There's really nothing more you need to do or should do.

To be honest, I don't think a comments like

the paper does not provide any example of the tasks presented during
  the user study. It would greatly improve the quality of the paper if
  the authors could at least provide one such example

are incorrect. Although you described your surveys briefly, the reviewer may still want to actually have a look at them. If I were you, I would publish the surveys on the internet, and include a link to them in the paper. This way, anybody could easily see what your "eight tasks" are, and convince themselves that you did a great job :)

I do not understand. I did not just describe the surveys briefly, I showed actual questions from the survey.

The poster wrote in his question explicitly, that there was an explicit example of a task. I don't see how insinuating the opposite is helpful in any way.


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What is the effect on a supervisor if a graduate student has been found to have plagiarised?
In a well voted comment in a question about responsibility to detect plagiarism it notes that it rests with the author. This well voted answer on a now on-hold question about removing plagiarized parts of a thesis states the following which could read to imply some responsibility for the supervisor.

If you think/know that parts of your thesis are plagiates you and/or your supervisors seem to have failed.

Regardless of the above in regard to responsibility of detecting plagiarism if a student does plagiarise, I assume it must have some impact on the supervisor.
Has there been any cases that have shown what is the effect on a supervisor (career wise/reputation etc.) if a graduate student has been found to have plagiarised?

This is what the effect looks like,

When reading "the effect on a supervisor", the first case coming to my mind is that of Haruko Obokata, whose supervisor had to commit suicide for her misconduct. But this is not plagiarism.
It is hard to define precisely the affect on reputation. There is a case, where a PhD student, then post doc in the same group, plagiarized 11 papers. His supervisor was the co-author in all 11 papers, but it seemed not to affect his career. I'm not sure about his reputation.
Here are the details of the case: http://carl.cs.indiana.edu/6S/plagiarism/

Obokata's supervisor didn't have to commit suicide, in fact many Japanese were surprised he did (while others wondered if there was something between him and Obokata that would have caused such an emotional response).


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Part-time PhD workload compared to part-time undergrad workload
Does a part-time PhD workload differ significantly from part-time undergrad studies?
I'm intending to go on to postgraduate studies next year. I'd prefer to go straight to a PhD if possible, but will consider Masters if it looks like the more tenable option. I've worked full time for the past 9 years while completing first a certificate, and then a BSc which is currently being wrapped up, both via the Open University in the UK.
During this time I haven't found my studies to be overly burdensome, even when taking two or three modules concurrently. I don't mind spending evenings and weekends reading, researching, and performing practical coursework. (Don't get me wrong, it's hard work, but worth it!)
This question: Is it possible to work full time and complete a PhD? discusses the relative difficulty of working full time and pursuing a PhD. My question is slightly different, though, as I'm already used to having less personal time than others might expect.
Should I expect my personal time to diminish significantly when I continue on to postgraduate study, compared to life as a part-time undergrad student?
I'd particularly value answers from previous full-time-working part-time OU students who continued on with a part-time PhD.
My intended discipline is Computer Science, and I'd like to attend a University in the UK, particularly Sheffield, but as I haven't completed my BSc and begun applying for postgraduate positions yet, I can't be sure of the location.

In what discipline will you be getting your PhD?  What university?

@mrmeritology: I've edited in the answer to your question. New last paragraph.

A bit late with this answer but hopefully will be helpful. You ask;

Should I expect my personal time to diminish significantly when I
  continue on to postgraduate study, compared to life as a part-time
  undergrad student?

Judging by my personal experience the short answer is yes.
Here's a bit more detail though. I am studying in Ireland, so not to dissimilar to the UK system. I work full-time and also did an undergraduate degree, part-time, before progressing to post-graduate study. My degree and post-grad are not related to my work but something I have a lot of passion for. I found with my undergraduate degree I had a lot more free time. Lectures were 3 nights a week for year 1-2 and 2 nights a week in years 3-4. Speaking for myself on top of lecture nights I found I could usually get away with doing a bit of extra work at the weekend.
Two years ago I started a History Masters(which I have just transferred to a PhD) and found that almost all my free time is now used with doing my PhD work. Saying that it's important to have other activities outside of your full-time work and study. I follow my local football team so usual have a evening off each week.
As you mention you have not decided on location so I'd like to add something about my experience. My workplace is about a 5 minute walk from my University. I think this makes all the difference to me. I can leave work at 5pm, have a coffee and be working on my PhD by 5.30. I also have my own dedicated desk space there which is a benefit with regard to having a space to leave books etc. Together with working in a family business this also gives me the flexibility to be able to arrange meetings with my Supervisor at working hours times and to pop over to the university during the day if I need to. So if possible I think it would be good to consider location of your institution in your decision making.
Just to sum up my weekly time spent on my PhD (and this can always vary depending on other commitments.) About 4 nights a week 6pm to about 10.30pm, Saturday 11am to about 10pm and Sunday about 1pm to 7.30pm.
We have the OU in Ireland too. The university I go to is as StrongBad describes in their answer a bricks and mortar university. In my own situation I have found every department that I have dealt with to be very understanding to the part-time nature of some of its students and to be honest the only situation I can think of I have been disadvantaged by not been a full time student is the opening hours of some of the offices. That said most functions of the college can be done online now or I can email the respective office.

This is a really fabulous answer. Thanks!! Do you mind me asking what topic you are focusing on?

Note: I did a Masters full time and half of my PhD. For the last year of my PhD I got a job as a professor, so the work I do for my thesis overlaps with my research work.
I think you'll find that the course load won't be much different from your BSc. For me, it was actually less work.
However, you will spend a huge amount of time on your thesis, particularly if you go for a PhD. The problem is that you will be doing research, not just the class assignments. And research is inevitably uncertain. You don't know the right answer (or if there is one) going in. So you should be prepared to spend a lot of time trying to solve problems and come up with explanations for your results. Insight and invocation usually require thinking about something over a long period of time. If you're constantly distracted from your research, it can be hard to come up with solutions to the (many) problems you'll encounter.
Since you mentioned your doing computer science, you probably won't have to spend time "in the lab", which is a huge time sink (my girlfriend is a biologist, she spends 6-10h a day doing experiments). My PhD topic is highly computational (I spend most of my time programming) so I do things from home or anywhere else I can take a laptop to. I imagine you'll have the same luxury. Even so, I'm still having trouble balancing my teaching load with research. It's very hard to have insights when I can only think about my topic for 2-4h a week, or not at all for months at a time.
In short, the problem is your thesis. It's possible if you don't depend on spending hours a day collecting data. It really helps if your thesis topic overlaps with your job. Be prepared to dedicate many hours to thinking about your research topic. As with everything, it depends a lot on how you function personally.

I think there are two aspects of your question. The Open University (OU) and its faculty are very familiar with the difficulties and challenges that part time students face. My guess is that the additional workload going from a full-time-working part-time OU undergraduate student to a full-time-working part-time OU PhD student is substantial, the OU has the support mechanisms in place for you to succeed.
As a full-time-working part-time student moving from the OU to a brick and mortar school, will likely be a shock even if you stayed as an undergraduate. The OU is really designed to do what you are doing and while part time studies can be done at a traditional universities, it is not what they are good at. The increase in difficulty and time commitment at a traditional university for full-time students as they move from be an undergraduate to a PhD student is substantial. Coupling that with the loss of the OU support network, is going to make it even more difficult.

Should I expect my personal time to diminish significantly when I continue on to postgraduate study, compared to life as a part-time undergrad student?

Your personal time does not need to diminish, but the "attacks" on your personal time are going to increase greatly. You are going to need to have a good working relationship with your advisor to define boundaries that are mutually agreeable.

This answer is great. When you discuss support mechanisms, though, what specifically do you mean? Course forums, tutor time, other? Typically I find myself working as a bit of a loner with only occasional tutor contact, if any, beyond assignment marking.

From my experience I can tell you that the workload for a PhD is equivalent to a full time job. So if you want to do it "as a hobby", it will become really hard to sustain.
I've been working for a company during my PhD program. If my job didn't have minor overlapping with the PhD thesis content, I could not have done it.
My professor said that about 80 % of all "external" PhD students are never going to make it.
So yes, it is possible. But you will spend 120% of your spare time with your PhD thesis if you want to finish it. If you don't, you won't finish it.

Thanks for taking the time to answer. I think you directly address this question: http://academia.stackexchange.com/questions/8747/is-it-possible-to-work-full-time-and-complete-a-phd. Prior to your current PhD role, were you performing part-time undergrad study at all? How did it compare, in terms of time required?

In my experience, even undergraduate theses by "external students" are successful very rarely unless there is a rather intimate relationship to their day job.

Don't forget that some problems take "calendar pages not sitting hours" as somebody graphically told me. There are things that require sitting down and doing them, others require some familiarizing, and then thinking them over for a longish time (even while doing some totally unrelated tasks) before they click.
Access to the advisor (and other faculty), research group, lab facilities (perhaps even for an occasional all-nighter), well-stocked library are a must. Often you'll have access to publications in electronic form only through the university's network, need to take that into consideration.
And select a thesis topic that you are passionate about, enough to have it drain almost all free time for a year or so without you complaining too much. The time drain will happen regardless, better not be bitter about it.


text:
Review invitation of an article that overly cites me and the journal
I was invited to review a paper for a well-known SAGE Journal in my field. The editor of the journal invited me specifying that “I was highly recommended as a reviewer” by the authors.
The review is single-blinded; I can see the authors’ names. I do not know the authors and I have never worked with them. Their article is of average quality.
It quickly becomes apparent that they cite a high amount of my publications in the field (twelve publications), although other authors demonstrated comparable findings. The article has fifty references and nine come from the journal under discussion.
Can this be seen as an intrinsic conflict in a way that I should not review this piece?
I have the feeling that the authors want to charm the journal and me by adding many references from both of us – although many of them are just marginally related to the manuscript itself.

I can second the feeling you have. Seems suspicious. If you choose to review, point out the other relevant literature (even if rejecting the paper).

@quantacad I accepted the invitation initially and then saw the reference list.

The authors may have indeed tried to gamble that you will like their paper because of the citations and will be a reviewer because of their recommendation.

I don't think this is intrinsically suspicious... Although it does depend on what field you're in. If you happen to have the best quality papers in this area, and most papers in this area are published in one journal then of course you'd have a large number of citations; as would the journal

“I was highly recommended as a reviewer” by the authors." a reputable journal really shouldn't do that - the editors should be able to identify reviewers for themselves.  At worst it is a recipe for pal-review and has caused editorial failures numerous times in the past (resulting in changes of editorial policy and/or terminating the journal).  See e.g. https://www.sciencedirect.com/science/article/pii/S0921818117306586 (I was tangentially involved in this case).

@DikranMarsupial The review process is something of a random experiment anyway, and there could also be people around who have an interest to put a paper down without the editor realising. I think there's nothing wrong with asking the authors for recommending reviewers. In some situations it may help because reviewers are hard to find, and in some situations it may balance things out. What is wrong is to decide about a paper based on such reviews only, or to not keep in mind the fact that a reviewer was recommended by an author when making the final decision.

@ChristianHennig "I think there's nothing wrong with asking the authors for recommending reviewers." I pointed out a case where this resulted in a complete failure of the review process and the journal abandoning reviewer suggestions.  I think that indicates that there is something very wrong with it - it invites "pal review".  If you can't identify suitable reviewers, you are not competent to act as an editor (or it is outside the scope of the journal).  If an editor wants to appoint "pals", they would be easily identified from the references (they would have been in the case I mentioned).

There is nothing wrong though in authors mentioning people who shouldn't review the paper (perhaps due to conflict of interest or prior bad behaviour).

@DikranMarsupial If I read the link correctly, in the case you mention, no reviewer other than those recommended was invited. I agree with you that that's not OK. Also of course if specialist Associate Editors exist, they should be used. The Editor can't be specialist for everything in principle covered by the journal. Your case study is interesting but the problem there wasn't in my view just that authors could recommend reviewers.

Sadly it isn't the only case where this has happened (on the very same topic), just the best documented.  I agree though that a lazy editor was part of the problem in that case.  You don't need to be a specialist to be able to identify suitable reviewers - you just need to know where the mainstream is in the subject area and have enough knowledge of the field to be able to spot "fringe" views.

Every reviewer has some conflict of interest. For example, when the manuscript cites the reviewer, this biases them towards accepting it, as they benefit from being cited. If the reviewer is not cited, this biases them against it, as they like to be cited. There are no completely unbiased reviewers, but most reviewers are not relevantly influenced by such minor biases.
The more crucial question is whether there are any hidden biases, which should be declared (e.g., if the reviewer collaborated with the authors long ago), or even totally prevent the review (e.g., if the reviewer is currently collaborating with the authors).
Your case is only slightly above the baseline bias that almost every reviewer has. Furthermore it’s completely transparent to the editor that this extra bias exists and they have chosen you nonetheless. Therefore you do not need to declare a conflict of interest or decline to review.
On the contrary, if you are critical of some of the citations of your own publications (as you appear to be), you are probably better suited than many other reviewers and can demonstrate that you can act against your potential extra bias. The same applies to the citations to the same journal. (Also, it appears that if you are able to make these statements, you have already done half of the work for the review.)
Also see: Is it OK to review a paper which builds on my work?

"you do not need to declare a conflict of interest or decline to review" But still can do it, if you have strong feelings about it. Technically, you are under no obligation either to review or not to review and free to make any choice you want.

There could be a less nefarious explanation for what's going on.  Of course, the truth probably lies somewhere in the middle.
When learning about or getting up to speed in some topic X, there are usually many "pathways" one can take.  There may be hundreds of research papers and dozens of review papers about topic X, and one doesn't need to read all of them to get an understanding of X (indeed, one would not have time to read all the papers).
It's a normal course of action to read a particular paper, and then to continue to other papers cited by that paper, or search for other papers by the same authors, etc.  So when an author (or group) embarks on a research project about X, during the background research phase, they may well unintentionally end up reading lots papers by a particular author or authors, papers from particular institutions, papers about a particular sub-field of X, etc.  And then, when they write their paper, this bias will carry over to their citation choices.
It's entirely possible that this is what happened here. Maybe the authors of this paper you are reviewing read a paper of yours, and then through the natural course of conducting background research, ended up reading many papers of yours.  And then they suggested you as a referee, because by now they were well aware of your name, from reading so many of your papers!  It's entirely possible that all this happened subconsciously (at least to some degree).
The bias towards a particular journal is harder to explain, especially since nowadays literature searching is done via inter-journal means (e.g google, arxiv), but this may be field-dependent. (In my research area, nobody ever searches for articles on the website of a particular journal, but maybe that is the norm in some fields)

authors: Vladimir F Героям слава


text:
How often should one check the status of a manuscript?
How often (e.g. frequency) should one check the status of a submitted manuscript?
I understand that daily checking is a waste of time while never checking the status might also bear risks (e.g. when a manuscript is not assigned to reviewers for many months or when an editor is getting unresponsive). What frequency might be considered effective and reasonable?
This refers to academics who have multiple papers in review simultaneously, not just one or two.

If it's been a very long time you might want to send a quick email to make sure that a response hasn't been written and then lost in the system.  This is admittedly rare but it has happened to me at least once.

I think this depends a lot on the field/journal.  In pure math, I think once a year is common, and somewhat more often is reasonable if you are or will be applying for jobs.

First, of all, in the unlikely case that checking the status on a daily basis does not affect you, you can just do that. Depending on the system, this takes less than five seconds, so the total impact on your time efficiency is negligible.
In most cases, however, I recommend to check when the progress of the manuscript would affect your decisions. In particular check when the manuscript being stuck in a certain state would make you contact the journal. Now, these times strongly depend on the journal, so you’ll have to find these out yourself. For further reading on this, see: Is my paper under review (or similar) for too long and if yes, how should I react?
For example, taking a journal where editorial decisions take a few days and reviews three weeks on average and the editorial process is presented in fine detail, I would check:

After a week to ensure that the manuscript isn’t stuck in the initial check (the step that mostly filters out total bogus, bad files, etc.).
Two weeks after after the initial check has been completed, to ensure that the manuscript has entered peer review.
Every two weeks after that to react to situations such as reviewers refusing to review en masse, the manuscript being stuck with the editor again after reviewers refuse, etc.

At the end of the day, you have to compromise between how checking affects your productivity and how relevant a timely publication is to you. So, you can multiply all times by two and things still are fine.
To keep your mind off the situation, I recommend to set yourself an automated reminder, lest you succumb to checking every hour.

+1, though I would say the main issue is not how relevant a timely publication is, but checking whether it has got stuck in some uncertain state - in which case you can email the editor and this might prompt them to sort things out.

@gib: I don’t see a conflict there. If timely publication is relevant to you, you want to notice problems such as the manuscript being stuck as early as possible. Otherwise, it doesn’t make much of a difference if you notice this one week late.

Never. Once you submitted your manuscript, you have done everything humanly possible. Now it is time to do productive stuff like write your next article or just relax.

So, if your article is stuck in some clerical limbo, you’ll never notice and just do nothing?

@Wrzlprmft How will you be able to tell a "clerical limbo" from the little information most editorial systems give you?

@WolfgangBangerth: I don’t doubt that some editorial system tell you next to nothing, but then the initial question is void, as there is no status to check. Most systems I know actually tell you a lot. For example, I once happened to check upon my manuscript during “decision letter is being prepared”. I received the decision within minutes, but had it taken a week, I would have acted. Of course, you can never be certain, but there are situations where you can reasonably assume and get your manuscript unstuck with a polite inquiry (and sadly this does not happen only every once in a unicorn).

These systems tend to give useful information when the editor uses it correctly. But clerical limbos are much more common when the editor ignores that system, at which point checking tells you exactly nothing. All you have to go on than is time since submission, and I know that without checking...

@MaartenBuis: In all the papers I ever submitted and reviewed, all standard operations I was a part of certainly happened through the editorial system. I have never seen such a system from the editor’s side, but I would expect that taking any process outside the system would be technically tedious, if not impossible (e.g., how would you enter a peer review into the system that you solicited and received outside the system) and also an administrative nightmare, since there are no records if an editor is suddenly unavailable or was suspected of any misconduct.

Look at questions on this site. There is huge variability in how this type of software is used.

@MaartenBuis: I cannot remember any questions on using editorial systems as an editor. That being said, I would not be surprised if editors circumventing editorial systems were common in some field. But the point is that there are at least some fields in which editors don’t do this which renders your advice (to just to succumb to one’s fate) not generally valid.

At the initial stage, (before getting assigned to associate editor and sent out for review), probably a week or two.

at the onset, when firmly with administration, daily or every other day
when it move to editor, weekly or more
when it gets to associate/senior editor, fortnight or more

When it's sent out for review, (apart from status check after 4-6 months depending on the field), "it is time to do productive stuff" (@maarten-buis)

doing more research
conceptualising and writing the next paper
writing up grant proposals (and reports)
... ...

Perhaps, it might be worthwhile getting acquainted with the typical workflow of a journal: What does the typical workflow of a journal look like? How should I interpret a particular submission status?
This might be worth noting: How to check how fast the review and publication process in a journal

What exactly do you mean by “apart from status check after 4-6 months depending on the field”? There are journals out there where two months of nothing happening are a clear sign that something is wrong.

Essentially, once it's sent out for review, you can wait till after 4 mths to check. At earlier stage before the manuscript is sent out to reviewers, one can check often. | I have paper under review going four months and it's perfectly normal based on the journal rank. By 'under review', it means the manuscript has been sent out to reviewers. When I, also, receive invite to review, the I get given 3 to 4 months, except it's a special issue. There're some to allocate 20 days to 2 mths forme to review.

Four months is nice. Once I had waited for about 3 years and emailed. Finally, I contacted the editor in person (at a conference) and said I'll withdraw my paper nest week unless nothing happens.

Essentially, once it's sent out for review, you can wait till after 4 mths to check. – Well, that’s my point: This does not hold in every field. Most journals soliciting reviews from me give me three weeks and they manage to get more or less that. Almost all the manuscripts I was involved in went from submission to first decision in under six weeks and none took as long as four months.

@Wrzlprmft (you wrote ... 'Well, that's my point' ...). Absolutely, hence the answer was explicit from the onset ... 'depending on the field'. I trust we can lay this to rest. In between, even within a field or sub-field, there're differences depending on journal rank (not to even talk of nuances of review process)

@semmyk-research: If you write “4-6 months depending on the field”, this is read as “four months in some fields, six months in others” not as “one month in some fields”.