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Stipend vs employment contract in Saxony (Germany)
I have found some information online regarding the differences between going for a PhD with an employment contract or a stipend, in Germany. The differences are mostly related to the time you can research stuff not exactly in line with your thesis, social safety and mandatory working hours. The salaries do not seem to change much.
In my case, I was offered the option to choose between stipend and employment contract for a post-doc position, not a PhD, in the German state of Saxony. I couldn't find much about this topic online. My field is physics, I'm 29, unmarried and no children. This is my first post-doc.
What are the fundamental differences? I'm particularly scared of the mandatory working hours associated to the employment contract option. I do work a lot, often from home, but I really value the freedom I currently have of simply skipping a day at work and working on a weekend, etc.

Totally off topic, but feel free to contact me about hiking/biking/outdoors tips in the Sächsische Schweiz, Erzgebirge & surroundings :-)

@cbeleitesunhappywithSX I must admit I'm quite excited to climb in Elbsandstein! Thank you! I'll be getting in touch! I'll be living in Dresden.

Recommendations:

Calculate whether the scholarship offer is a fair offer (see below).
If not, the employment contract is the only feasible option.
Check whether the institution insinuates that a scholarship is basically the same as the employment contract wrt. to your contractual duties. If so, that is (at least to me) a big red flag about an inclination to institutional abuse of power. And that means that you should also think carefully whether you want an employment contract with that institution.
At least, check the customs of your group-in-spe and how much freedom postdocs have there. Your group leader may be in a more or less good position to give you more freedom than the institution normally does.

Note I use "scholarship" here for the German Stipendium. AFAIK, the English stipend/scholarship do not directly translate to the German Stipendium.

Others have already told you that the social insurance treatment is very different. I'd like to expand a bit further on this.
IMHO the best (fair) starting point for comparison is to consider the scholarship equivalent to the employer's gross (Arbeitgeberbrutto) of an employment contract for which no income tax is due.

Scholarships for scientific work are not subject to income tax
Check with my tax office that the particular contract that is offered fulfills their criteria for this, though. One of the criteria is to check whether the contract is actually a scholarship and not an employment contract.
Health and long-term care insurance is mandatory whether you are employee or not.
Not being an employee and being young and without family, you may be able to get a cheaper private health insurance than the governmental one.
You can also go with the governmental health insurance (called "voluntary" or sometimes "voluntary mandatory" tariff, there will be no health check for this). In that case, your fee will be the same percentage as employer + employee percentages together, approximately 1/6 of your income. But while for an employee only the wage is counted, in the voluntary tariff all sources of income count (small time freelancing as a side line, interest/dividends, rental income?).
If you are coming from a foreign contry, you may be able to bring a health insurance with you. Health insurance for young academics going to work abroad for a while can be surprisingly cheap.
Unemployment insurance is for employees only. You don't have to pay, but you'll also not be eligible for benefits later on. Currently relevant: these benefits include the Kurzarbeitergeld (short-time compensation). OTOH, a scholarship is not bound to working hours, so the scholarship is anyways paid also if you cannot work due to your workplace being closed because of SARS-CoV-2.
I'd argue that you should put at least a comparable amount aside into an additional emergeny fund.
Pension cass is not mandatory. If you want, you can make voluntary contributions, though, and in that case you can largely decide how much you want to pay into pension cass. Such contributions will count both as contribution years as well as according to the amount paid in.
Again, if you choose not to contribute it is probably a good idea to put at least a corresponding amount (between 1/6 and 1/5 of your income) into your own retirement fund.
The pension cass is also responsible to decide whether a given contract is an employment contract or a scholarship - you can ask them for clarification. If they find it is not a scholarship*, there will be a big stink though, since you just exposed your institute-in-spe trying to commit social insurance fraud.

Whether these points put you at an advantage or a disadvantage will depend on your actual circumstances.
(I've had the luck to get a scholarship as PhD student that was actually fair according to this calculation - but it was the only one scholarship program that paid so much that I'm aware of. When I write "I'd argue": acually I have been arguing when that funding agency was cutting the scholarships that a fair comparison would tell the scholarship holders that while it is ultimately their own decision, they should consider the social insurance percentages as ballpark for how much they should put aside for rainy day/pension)

You will not be covered by the work accident insurance mandatory for employees. Part of this is not a disvantage: as long as your institute has employees, the place anyways needs to be safe according to work accident insurance rules.
But: you have a work accident there will be differences to you. Your treatment will be paid by your normal health insurance. But work accident insurance patients may be treated preferentially wrt. waiting times (OTOH, there is no free choice to which doctor to go initially). This includes any accidents you have on the direct way from home to work and back.

There are usually some specific advantages for scholarship holders over employees:

Many scholarships have associated training programs on various topics
Many scholarships give you additional project/book/travel money that noone but you can spend. In that respect it's like a mini-grant for you only.
You are more free in your scientific work than an employee.
Of course, many professors leave great freedom to their employed postdocs, but not all do. A scholarship legally means that you must be free in this respect.
@mmeent has a point that some institutions have a bad reputation of abusing scholarshiops, though: not only of not paying what would be fair according to the calculations above, but also by insinuating that the scholarship holders are bound to directions of the institute like employees. In other words, abuse of power.
Since you are not an employee, e.g. the copyright of software you write stays yours - it will not be automatically transferred to the university.
Same for inventions.

Again, many institutes are happy if their postdocs take software they wrote with them and go on taking care of it rather than risking more abandonware - I had one such institute that put the software under a FOSS license for this reason and I still take care of the software almost 10 years later. But I've also been at an other institute where the standard license is best described as "no bit leaves the house".

Since you may change to academic employment: at least within Germany the wages depend on your relevant work experience. Scholarship may not be counted automatically by prospective employers, but you can ask your institute to certify (write a letter) that they consider your scholarship as equivalent to you working.

Employment contract

mandatory working hours  associated to the employment contract

In the past, this again was something that was pretty much up to your PI/professor (and when I had the scholarship the professor didn't make a difference between scholarship holders and employees - he argued that this would only create more and unnecessary friction among people who substantially did comparable work).
However, there is a newish court decision that employers must properly document the working hours of all employees. Properly tracking working times of PhD students and postdocs will create huge difficulties with overhours. Whether anything will happen in practice is a totally different question.
From the "work a lot" aspect, you'd probably be fine as employee as well because if you have overhours, you are supposed to take them off as soon as possible. This includes taking days of during the week. What is more difficult is that your employer may not be allowed to let you work the times you do now (long hours, evenings and  Sundays may be problematic)

pension cass contributions are mandatory for employees. However, if you do not reach the required minimum of 5 years of contributions, you cannot get a pension and instead you can get the employee half of the contributions paid out as a lump sum. If you have more than 5 years of contributions, you will be eligible for the corresponding pension payment once you reach pension age. Regardless of where you are (within the EU, "your" pension cass will also pay out the German part)
As an employed post doc, academic freedom does not apply to you: you are bound to the directions of your employer.
Many academic PIs let their postdocs do their own research, but some PIs or institute directors like to excercise their power...
In Germany, a fixed term contract can not be canceled by either party once the probation period (6 months) is over. (An agreement where both sides agree to void the contract is always possible, though.) The employee has the right that the employer agrees to void the contract, though, if they have a better offer. But they need to actually have such a better offer.

* there is some concern that since the pension cass will receive mandatory contributions if they find it to be an employment contract they are not exactly unbiased in these decisions in general (that's not only about scholarships, also about other contracts such as freelancing).

Wow, that's truly comprehensive. Regarding properly tracking working hours, I feel like this is actually impossible for some groups of people I know. For instance, I know people working in particle physics that need to wake up at 4AM to track experiments sometimes. They obviously do this from their homes. That's absolutely fundamental work, and should count as working hours, but they're not at work... Attempting to keep exact track of these phenomena looks impossible to me.

@QuantumBrick: German labor law doesn't care whether you are at home, working from home is perfectly possible. They could sign in and out via web interface or have their supervisor enter that time later on. But checking emails at 11 pm or online checking your experiment at 4am does have the difficulty that labor law prescribes a gap of at least 11 hours between finishing work one day and starting the next working day, and that 11 hour clock is reset with even a minute of work... So far, noone in academia cares, and also the authorities see more urgent need to intervene elsewhere (construction)

Many comments that you make, are only relevant if the stipend comes from a third party. (Such as coming with a training program.) The choice here is between being paid in the form of a stipend or normal salary from the same "employer". Many of the normal advantages of being on a "scholarship" or grant do not apply in such a case.

@mmeent: No, in my experience the scholarship will usually com from a different funding agency (but I'm curious: please let me know of your counterexamples). The really crucial distinction is that a scholarship holder is not subject to directives of their hosting institution, while an employee is bound by the directives of their employer. So the scholarship holder has to have this freedom, the employee may have it by goodwill of their employer. And yes, there are training programs for employees as well, and also someone employed on a project grant can have travel money etc. via this project.

@cbeleitesunhappywithSX One example is the Max Planck Society. Max Planck Institutes can offer (foreign, non-EU) post-docs employment on a stipend or under a contract, and sometimes offer this as a choice to postdocs. In both cases the funds come from the relevant MPI division's budget, and in both cases the post-doc answers to the division's director. I assume other institutes may offer similar constructions.

Also note that while scholarships typically include a stipend, not all stipends come from a scholarship.

@mmeent: I know that the MPG had a particularly black record in this respect (https://www.faz.net/aktuell/feuilleton/forschung-und-lehre/forschungsstipendien-schwarzarbeit-in-der-max-planck-gesellschaft-11775142.html) also because they did not remotely pay what I consider fair according to the calculation above. But I (maybe naively) thought that was largely over with the DFG rules about employment. The legal situation is very clear, though: if someone works under direction, that is an employment contract regardless of what the contract is called and the employer not paying/withholding social

...insturance is plain social insurance fraud, i.e. a criminal offense. I just read their current brochure for postdocs and it almost makes me puke to be honest: not only because they very deliberately create the impression that the scholarship holders should be under direction (which they cannot legally be) but they also create the impression that a postdoc isn't a fully qualified professional (I may say that I already find it upsetting to insinuate a PhD student were not a fully qualified professional). For those not familiar with academia in Germany, the qualification here is a magic word

Let us continue this discussion in chat.

One of the biggest differences is that if you are on a stipend, you will not be building up any pension benefits (and other social benefits). This makes it a lot cheaper for your employer to hire you at the same net salary.
This is not a big deal if you plan on staying in Germany only for a few years. But if you do decide to stay, the missing years of pension build means you are missing out on quite a lot of money.
(This even the case if you don't plan on retiring in Germany, as the missing years can make the difference in having reached the threshold for having build up a "vested interest" in your pension fund.)
In practice, there is very little difference in working conditions (in an academic setting) between having a full contract, and working on a stipend.
So, if the choice is between a stipend or a full contract, with both leading to the same net income, then the full contract is (almost) always the better choice (for the employee).
The stipend option is only really interesting if the net income from the stipend is actually higher to compensate for the lost benefits.

Thank you for your answer! The part about skipping a day during the week and compensating it on Saturday is also possible with an employment contract, you think?

In academic positions that seems pretty normal, and should not be a problem. (Unless you have duties that specifically require your presence, like teaching) Only if you have a really old school German as your direct supervisor, can I see this ever being a problem.

@QuantumBrick: If you have an accident while you are at work and should not be at work or the other way around, it could be also be a problem with your insurance.

@user111388 This is highly likely to happen, given that my hobby is rock climbing.

"net" salary makes sense only for wages/salaries. Amount paid out would possibly be a better description.

Normally the only thing that is truly mandatory in the contract is the total number of hours.¹ And in academia even that is mostly a fiction which just happens to magically add up precisely at the end of the contract. The rest is up to your employer. If your boss insists on everyone being in the office 9-5, then you'll have to do that, but I've never heard of that. Normal rules I've seen in academia range between "be there when you have an appointment" to "try to at least show up for some time each day you are officially working". Also keep in mind that a normal TV-L contract has 30 days off each year which gives you a lot of room.
But since you are in negotiation for a contract and the details vary between places and bosses anyway, just ask. Ideally per mail, then you'll get something in writing and no-one can complain later.
¹There are a lot of small details here, like no more than 10 hours per day, mandatory breaks, etc. But nothing to worry about.

That's good to hear. It seems it's just like it is in my home country, then: pretty much work whenever you want, but show your results. When the employer found out I was elligible for an employment contract, he offered it with a huge smile, so I think he expected me to receive the news as if it were really good. It's all making sense now...


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Reviewing a potentially interesting, albeit unreadable paper
I am reviewing a paper for a major journal with very high impact factor. Some of the authors are very well known in the field and have several other papers published in this particular journal, such that their objectives and results are likely valid ("likely" is the best you can get in this field, so don't get hung up on this). However, they are not native English speakers and the paper is almost completely unreadable.
Usually, I would immediately reject the paper. Due to their reputation, however, I forced myself to stay with the paper for a couple of weeks. From what I could understand after several attempts, their results might indeed have the potential to be published in this journal, but the editorial board is typically very strict: If I send a report claiming that the paper needs to be pretty much fully rewritten, they will likely reject it. I do need, however, a fully rewritten version even to be sure that I properly understood what they claim, and then to reinforce or change my mind about the paper's relevance.
I am thinking about sending a report where I state what I believe the paper is about, and if this is the case then it might be relevant, but I cannot be sure because it is currently unreadable. If the authors revise it, then I will be happy to read it again. The journal might still reject it, and I'd feel bad because this is essentially blaming people for not knowing English. I then wonder if there is any other way, e.g. contacting the editors directly instead of writing a report. Would this be better? Are there other options?

If they reject it, is there a chance to resubmit?

@Sursula For the first decision, there is.

" I then wonder if there is any other way, e.g. contacting the editors directly instead of writing a report." It's not clear to me why you think that there is a substantial difference between writing a report which says the paper is unreadable and contacting the editors directly to tell them that the paper is unreadable. (One difference would be that in the latter case there will be no report to relay to the authors, but this is presumably not your motivation here.)

Re: fairness, many native speakers write unreadably and need editors too :)

You shouldn't feel bad about "blaming people for not knowing English", because you aren't doing that. The editorial board might be (by rejecting a paper just because the English needs extensive revision) but that is not under your control.

Seems like an open-and-shut case of "revise and resubmit" to me.

@LukeSawczak And on the flip-side, many non-native speakers have better command of the English grammar than native speakers.

Why not publish in their native language, then?

There are many journals, so if this one rejects the work, the authors can hopefully learn from the comments and then submit elsewhere. Don't worry, you won't kill their work even if your comments/recommendation lead to rejection.

Reviewer bias in single- versus double-blind peer review

Scientific peer review has been a cornerstone of the scientific method since the 1600s. Debate continues regarding the merits of single-blind review, in which anonymous reviewers know the authors of a paper and their affiliations, compared with double-blind review, in which this information is hidden. We present an experimental study of this question. In computer science, research often appears first or exclusively in peer-reviewed conferences rather than journals. Our study considers full-length submissions to the highly selective 2017 Web Search and Data Mining conference (15.6% acceptance rate). Each submission is simultaneously scored by two single-blind and two double-blind reviewers. Our analysis shows that single-blind reviewing confers a significant advantage to papers with famous authors and authors from high-prestige institutions.

You're describing something that double-blind review is supposed to prevent. If the paper is unreadable, you should tell the editor, regardless of who the authors are.

I then wonder if there is any other way, e.g. contacting the editors directly instead of writing a report. Would this be better? Are there other options?

The result would be the same - the editors receive a "there's potentially useful science here, but the English is incomprehensible" response from you, and then it's up to them to decide what to do (remember editors can choose to accept a manuscript which reviewers recommend reject for). Practically speaking the difference if you write to the editors directly is that they'd have to submit the recommendation for you, which is a minor administrative hassle, but still an administrative hassle.

I am totally aware that I only tried hard to read the paper because I know the authors, and that this is due to my bias. Good for them. My existential doubt was more like "given that I have read the paper, which I would not have read if I didn't know the authors, I have come to the conclusion that it might actually fit this journal, and I need to say this without killing their chances". So the bias is in my effort, not in my choice. I am indeed leaning towards accepting that the paper might be fully rejected because I think they are probably incapable of rendering it readable.

@QuantumBrick but if they are incapable of bringing their paper to a readable and understandable state, then it really should not be published and it is correct to suggest rejection.

@Sursula Yes, I agree. I was worried about rejecting a potentially good paper but I didn't fully consider the fact that the paper in its current form is really unreadable. It's too much. So I shouldn't be afraid, because there's a good change they cannot make it better.

@QuantumBrick "Good for them" is not the point. The point is "bad for everybody else", everybody who you would not have given this special accommodation.  Out of fairness, you should treat everybody the same.

@lighthousekeeper You don't deal with near-irreproducible experiments without taking a look at who wrote the paper. The double-blind vs single-blind thing is cute until you meet with people claiming extraordinary effects due to elaborate experiments that can only be performed by a couple of groups in the world. You treat a paper submitted by a group with a solid reputation very differently than from a group no one has ever heard before - and you should. What people have to understand is that not all fields of science are the same, and what people refer to as "scientific method" is very fluid.

@QuantumBrick You are conflating two separate discussions - one is about trust, the other about the bar for an acceptable paper. The latter should never depend on the involved people. There are also issues with the former, for example, cases of high-profile researchers being found out as fraudsters -- after all, a high-profile researcher might feel a particularly high pressure to continuously deliver astonishing results, and this could be even more harmful in an area dealing with near-irreproducible experiments.

@QuantumBrick: Your statement has validity from a journal's perspective, but that level of crank-filtering ought to have happened by the editor before contacting reviewers.

@QuantumBrick I think the history of Rupp is not known to you.
https://arxiv.org/ftp/arxiv/papers/0709/0709.3099.pdf
"You treat a paper submitted by a group with a solid reputation very differently than from a group no one has ever heard before - and you should" Of course you do, because the group with the solid reputation has a traceable history of succesful reviewed experiment.
Which is exactly the damage many fraudsters inflicted to science: flying high without good dosis of scrutiny on their first published high impact papers/results.

@EarlGrey I was not familiar with Rupp, but I'm familiar with many others (currently the big name in this "field" is Ranga Dias). This subject has gown out of proportion in these comments: my bias was in reading the paper, and my acceptance criteria remain the same no matter the author. The two points were carelessly thrown together in some of the above comments and I won't dare to enter this debate. Everyone knows this too well already, and we are currently witnessing a major batch of retracted papers by big names.

And, as a last note: People will always find ways of beating the system and profiting based on fake stuff. It is inevitable. The model we currently have favors double-blind review for theoreticians and single-blind for experimentalists, and some modern journals like SciPost offer these options both to authors AND reviewers (revealing the identity of reviewers is likely responsible for massively improving the quality of reports). I dare say that the model we have is a result of infinitesimal improvements over the years, and that things were considerably worse before. This is a long subject.

@QuantumBrick "given that I have read the paper, which I would not have read if I didn't know the authors, I have come to the conclusion that it might actually fit this journal" If it's a good, on topic paper with interesting ideas, then it's all the more tragic that nobody who reads the paper will be able to understand those ideas because it's unreadable. Tell them as much so they can revise and resubmit.

@Ray Indeed, this was essentially the content of my report :-)

Converted from a comment by another user:

You can of course always contact the editor. However, precisely because it is a high IF journal, it is probably read by many people. Inflicting a "likely" correct and interesting but unreadable paper on them is a disservice. Research is communication, and the accepted language is usually English. You are not blaming people for not knowing English. You are performing a valuable gatekeeping service. The editor might suggest to the authors to have their next paper proofread before submitting. This is unfair to non-native speakers, but sometimes there is no "fair" solution.

I share this opinion. Just let the editors know your honest opinion on the paper; it is up to them to decide what to do. Even if the paper is rejected, this is not the only journal in the world.
I suggest not to contact the authors independently: this would break reviewer anonymity, which is an important safeguard to have (especially in cases like this one, where you are essentially giving a negative opinion on a paper by a well-known author).

It isn't your job as a reviewer to try to decode a badly written paper, nor to second guess editorial responses.  Write an objective review saying what you said in the question "potentially interesting but almost unreadable" to the editor.  What the editor then does is not your problem.

Easy.  Write some version of what you just did here. Say something along the lines of, this work is technically competent, addresses an important issue, is an important observation for the field, comes from a group who have made many important contributions, etc etc. You can then justify your statements with the scholarly details. You then state that the one major weakness of the paper is that the standard of written English is very poor; so poor that it took you a long time to get through it.  (Don't say it took weeks, though). I serve on the editorial boards of several journals and I would not reject a paper on that basis. I make it very clear to the authors that they need to get help from somebody who can actually write in understandable English, and I give them at least one shot at fixing it. On most online review websites there is a place where you can send a message that only the Editor will see. If you're really concerned about this you can write there that you really want to see this paper get published, but that the English is awful.

If you do not understand what the paper is about, do you think one single journal reader will? And certainly none of the readers will try for several weeks to understand a single journal article. If they do not understand it, they will put it aside.
So what is the use of accepting and publishing a paper nobody will be able to understand?
Tell the publishers that the content seems to be interesting and worth for publication, but it has to be rewritten.

Ah, the good times of reviewing papers... I miss none of them, so much painful reading. I am not going to provide any particularly smart or new answer, but I feel that sometimes we get so hung up into complex considerations and we don't see that the best approach is simply to go back to the basics. What always worked  for me was to begin by asking myself the most basic questions. Do the authors make the problem they are facing clear and the contribution of the paper in that respect?
If this is already hard to detect, it's a rejection. If these points are reasonably clear, then proceed to the second level: do the authors clearly explain their procedure to arrive at those results and provide a (reasonably) fair analysis of their importance? These two questions are harder to answer as they usually involve some very in-depth specific knowledge in areas in which the authors themselves might know more than anyone else.
Even in that case, though, the path for a reviewer is not too difficult. In my opinion, one should always keep in mind that a paper is not the "discovery" itself, but it's an instrument used by the authors to communicate the discovery to others. So, in a sense, evaluating it should not be thought as conferring or not some honors to the authors, but rather as maximizing the benefit for the readers. If the paper does not fulfill that function because is unreadable (I would say for the average reader of that journal, a criteria which might be possibly relaxed by considering a more restricted group, depending on the subject), I think one should definitely ask to resubmit.
Remember, if you do that, you are not dissing the authors, you are just helping many readers learn something potentially important without going through the same pain that you experienced. In a sense, you should see yourself as the hero who takes one for the benefit of group.

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Asking good questions in lab courses
We are re-writing a bunch of our lab manuals for a first year circuits course.  We want to make a mix of focused questions ("what was the voltage across X?") and thought-provoking questions.
At the moment, the "thought provoking" questions in the current lab manuals are all variations on "comment on the differences between your pre-lab and your experiment".  These invariably get students to just chime off a litany of "errors in the equipment" without really thinking it through.  What I would like to see the students doing is a thorough comparison and making a value judgment, and mentioning their observations.
I feel that the issue I'm having is that the focused questions are way too specific (just write down the number) but useful for learning certain things like how to take measurements.  Thus they are valid questions if not outstanding ones.  The thought provoking questions, though, are vague and don't get us what we're really looking for.  Can anyone suggest some in-between questions that give students a hint at what we are looking for without just asking them out right?

What -> why, maybe. So, why is the voltage X across Y?

I can tell you how I've been seeing this handled at the K-12 level.  (I don't know if this is a good way to do it at that level or at the college level.)
A math problem is posed.  Then the narrator outlines how a fictitious student, e.g. Marisol, reasoned.  Often, this reasoning is flawed.  Then the student is asked to evaluate Marisol's reasoning.

I haven't really tried that in our class, but it's worth thinking about, thanks!

The problem with what I am about to suggest is that these don't apply to first year uni. But anyway, here are some examples.
The lab involves a Wheatstone bridge. The question could be something along the lines of "explain how a Wheatstone bridge works within the context of this experiment."
The lab involves mapping out the electric field around a pair of electrodes. This involves specially prepared (and expensive!) paper that is very slightly conductive. The question (actually copied from a 2nd year lab) is: Can equal potential surfaces intersect? Why or why not?
Generally what you want to do is pick questions that are within the range of ability of the students. And that will get them to pull out information they should have. And ideally, that will require them to put that information together in ways not necessarily explicitly in the text.
However, be careful not to overload the students. If you wind up giving them X amount of work where the lab course is only (say) 0.15% of the course mark, then X should not be a lot more than 0.15 of the work expected for the course.  You should not be assigning things on a lab that will require them to be doing huge amounts of calculation or library research.

There are multiple ways to do this!
From your question, I deduce that you are asking how to evaluate students' thought processes without explicitly asking. One way to introduce this (and perhaps the most effective) is to ask them, not to show their work, but to explain using words. This helps them figure out exactly their thought process and also gives you, as a Professor, an inside look into their brains to tell exactly what they are doing wrong and you can, as a Professor, help to fix their mistakes if they got it wrong.
@aperente001 Also had a good strategy for this, which was to have an example of a problem done incorrectly and asking them to identify this mistake and correct it.
Another way is to give a multiple choice question and to then ask why it was correct, just make sure to emphasize that "Because it is the correct choice" is not an answer.
My final suggestion is to try using problems (or questions) that are open ended vs. those that are multiple-choice (if the questions are not terribly difficult, try to make the most difficult questions multiple choice using the above strategy)
Open-ended questions require work, and if work is shown you can draw a conclusion of what exactly went wrong.
Thought-provoking questions are the best kind of questions, and using words instead of work is the best way possible to accomplish this.

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What are some strategies for using automatic grading technologies to get students to express their reasoning?
We currently use an online quiz tool to give students questions in some of our engineering classes. These questions might be simple or very challenging, but at the end of all of them the students are required to put in "the answer" - a numeric value, or rarely a formula they've derived.  These quizzes are run every week, and are basically a sneaky way of getting students to do homework problems.  In that, they are very successful.  The quizzes are basically open-everything - they can google things, talk amongst themselves, ask us anything etc.
However, we are becoming aware that this type of quiz leads students to race to find the right equation, plug in the right numbers, and move on.  As an example, one of the questions from a recent circuits quiz was relatively straightforward in terms of the circuits concepts, but required careful planning of the math in order to avoid any errors.  We've been tracking the questions that we are asked during the quiz, and almost universally the students 100% understood the circuits concepts but were making math errors.  This is actually a good thing - we want to encourage students to learn to structure their reasoning in a careful, well-planned way, so we are OK with students struggling at it.  However, the question doesn't allow for any way to give feedback on it.   The answer either is or is not numerically correct.
Obviously we can have the students submit to us and we can evaluate them directly, but that isn't the point.  An automatic grading system isn't ever going to be able to give students the same level of feedback as a human TA, but I feel that we are not using it to its fullest potential to give students feedback on their process.
What are some strategies we can use for question design in automatically graded quizzes that might help here?

Are students allowed to revise incorrect answers?

Does the system tell you which are the most common incorrect answers? If so, do you tend to see that the students are making the same few mistakes?

I think you've hit the limit on what automatic grading technology can achieve at this current point in time. Generally, this technology is only going to allow you to automatically evaluate questions with pre-defined answers. This doesn't work for theory or structuring. It probably isn't going to, either.
However, you can use it to evaluate concepts. I'm not exactly sure how your class works, but here are some example concept questions.

Given [Situation X], what methodology would you use to solve [Problem Y]?

The answer would be from multiple choices.
You also combine this with over method comprehension. Let's do true/false.

[Method X] is the process of..... (True/False).

From there, you can then start going through some actual calculation questions. If structured correctly, you can deduce the information you're trying to achieve.

If the student does well on the conceptual questions and bad on the math questions, they likely made some arithmetic errors.
If the reverse is true, the student probably just memorized the formulas.

These situations aren't always going to be true, though. They will never be as accurate as a human evaluating a student's process. But the estimates may still prove useful.

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


text:
How much of my teaching evaluations to bring to an interview?
I'm interviewing for a lecturership (purely teaching, maybe 10% research).  I've taught one course before and I have received a thorough (positive) evaluation from my students.  However, my institution feels that more information is better, so my evaluation is 28 pages long.  Do I bring the whole thing, one copy per interview committee member, or would just the summary section (where the main numerical results are) be enough?

Is there any reason not to bring several copies? It seems like a situation where it is better to bring too much than too little.

Perhaps? I'm thinking that handing each member of the committe a huge pile of papers, including things like assignments/other work, might be a bit much?

Have they specifically asked you to bring evaluations to the interview? If not, I see no reason to bring them at all.  Just in case, you may want to have an electronic copy, which you could send to them if they want to see it.  In this day and age, I doubt that anybody really wants to have it on paper.

@NateEldredge I am not really sure.  I believe I was just told to bring any materials I feel will help the hiring committee make a decision

@MichaelStachowsky I would assume, unless specifically told otherwise, that "bring any materials" means "make sure any materials are on the laptop you're bringing with you".

Teaching evals are super important to lecturer search committees.  But nobody wants paper.  Email it to the search committee or upload it to their application site.


text:
Tools for planning learning as a time-dependent activity?
I'm looking into planning tools for labs and lessons.  I'm wondering if there is an established tool, similar to a storyboard, that lets me plan from the perspective of skills the student will gain as they progress through an activity.  What would be really ideal is if the tool also includes gates, where students who have not gained a particular skill can't move past a certain point until they've attained mastery.
Logically, I could just draw this out, but if there is an established tool for it I'm sure someone else would make a better, more coherent thing than I could.
Edit: as an example, I'm working on a lab right now where students will learn to build circuits.  The lab might be planned like this:
Activity 1: teach students to use the voltage source
Activity 2: teach students to incorporate  the voltage source into a small circuit, teach students to build a circuit
Activity 3: students must build their own circuit without guidance.  They therefore must be able to use the voltage source and build a circuit.
In the above example, students can't progress to activity 3 without activities 1 and 2, and activities 1 and 2 would teach them the required skills.


text:
Strategies to manage long-term course development
I'm in an interesting position in that I get to work with multiple instructors on multiple courses.  I'm usually tasked with coming up with draft assignments, rubrics, and other learning material.  So far I've been approaching this on a basis of "oh, the instructor asked for X, so I'll do X".   Each new project is essentially its own thing.  However, I'm noticing that:
a) my colleagues do the same thing, so we are all the curators of huge, generally unorganized and possibly duplicate databases of course material
b) I basically forget about a piece of material once I send it to the instructor.  There's not continuity, evaluation, or improvement.  If the instructor has feedback, I'll incorporate it at a later date, but I myself am not really spending the time to generate a plan for continual improvement of the learning material.
What are some strategies for managing this type of development over multiple courses and multiple semesters so that I can maintain, upgrade, and evaluate my learning material without spending so much time in administration that I can't develop anything new?

I think the problem is inherent to the nature of the work you're doing.  If you had responsibility for specific courses, then you'd be naturally motivated to keep these materials organized, and to go through them from time to time to make improvements and fill gaps. Alternatively, you could start thinking about which items would, together, form the basis for a good book or website.


text:
Use of external resources as teaching aids
I am teaching a course in calculus.  Things are generally going quite well, but since this is the first course I've ever taught I'm certainly not doing a perfect job.  As a result, I sometimes come across lecture topics that don't go so well, either because:

I didn't do a good job of explaining in lecture, typically because I made a mistake or glossed over something or
The concept itself is just difficult, and requires a lot more time to understand than I can devote in lecture.

In these situations, I make sure that I communicate to the class that there was an issue, and I often look for or create resources like video lectures or supplementary documents that clarify things.
If I want to be 100% sure that the message I deliver is in agreement with how I'm teaching the course, I make the material myself.   For instance, if there are multiple, conflicting definitions of the same term, I tend to make my own material and post it for the class in order to ensure that my definitions are consistent throughout my entire course.  I've done this several times and my resources are well received.
However, there are resources out there that are just clearly better than anything I can whip up, at least in the time I have.  Khan Academy is particularly fantastic and has great videos, activities, etc.  Rather than re-invent the wheel, I will provide links to these resources when the topic is either not critical or where the resource aligns very well with how I've taught the concept in class.  I always make sure to properly give credit and do not take credit myself for things I did not create.
I'm not sure why, but somehow this feels like "cheating". I'm also concerned that it will be perceived as laziness on my part by the students.  So the questions:

Is this cheating? Should I be making my own material, in order to 100% guarantee that what my students see is consistent with how I'm teaching it?
If not, is there anything I should be doing to ensure that students understand that these resources are just one part of the course, and shouldn't be exclusively relied on?

Do you write all your own textbooks for the courses you give? Why should using a good video from YouTube be any different from using a good textbook?

It's a good question.  I've learned this semester that having a textbook is good, but not great, and honestly I'd rather write my own course notes.  However, a significant lack of time (and, to some extent,  expertise) prevents me from doing so.  As a result, I've used the textbook as a guide.  I feel that if I were to make my own, it would align much better with how I want to teach the course.  Obviously, making my own book for every course is an immense, probably not possible, task.  But making supplementary material for every class isn't that unreasonable

When I took Linear Algebra, in preparation for the final exam, I went to the library to get a book to do some more preparation with.  It got me completely confused, because it assumed and proved opposite sets of things from the course.  I would have appreciated it if the instructor had given a short list of compatible enrichment resources.  That was before the internet. // Please keep in mind that some students do better with print enrichment resources and some do better with video resources.  The ideal is to offer multiple modes so students can find what works for them. // Don't neglect...

...to ask students for feedback after trying something.  However, I wouldn't just ask for verbal feedback during class.  A short questionnaire, either paper or web based, would probably be more useful.  Also, you can encourage students to send ongoing feedback through email and office hours visits. // Your questions: (1) no; (2) just tell them (verbally and in writing.

Giving an extra resource from another properly referenced and acknowledged source gives an explanation with a different flavour - I do this and so do my colleagues - do all students use or appreciate - no but some do, so it's worth it. Best of luck you have a good attitude.

If you are new to teaching, then I give my highest recommendation that you read Steven Krantz, How to Teach Mathematics, published by the American Mathematical Society. From the 3rd Edition, Section 2.7, "Handouts":

It is tempting to write up a lot of handouts for your course. If you
  give a class hour on Stoke's theorem and feel that you have not made
  matters clear, then you might be inclined to draw up a handout to help
  students along. You also might suspect that this extra effort on your
  part will improve your teaching evaluations and, in particular, that
  students will appreciate all this additional work that you have put
  in. Well, it won't and they don't. Only prepare a handout when it will
  really make a difference. Students feel that they already have enough
  to read. Inundating them with handouts will only confuse them...
What I can do is examine my own conscience and tell you what I see. If
  I give a lesson that is not up to snuff, or if I do a poor job of
  explaining what curvature is, or if I goof up a proof in class, then I
  can salve my conscience by writing up a handout. It takes about an
  hour, it is a way of doing penance, and it is a way of working past
  the guilt of having screwed up in class. In my heart of hearts,
  however, I know that what I should do is strive to give better
  classes.
Just speaking for myself, I find it more comfortable and convenient to
  put ancillary material for the course on the Web. This seems to be
  less "in your face," and the students think of it as a resource that
  they can consult if and when convenient. Class emails are also a
  useful device for supplying extra information or small corrections.

For myself, I would say you certainly don't have to feel guilty about directing students to outside resources. Possibly we don't do that enough in our discipline. It is definitely not "cheating"; it is simply being a professional and knowledgeable scholar. On the other hand, I might also argue that real-deal mathematics does involve reading, and to wean students away from crutches like videos that will only get them so far.

Hmm, interesting to see this advice being given to math instructors. In college math courses, I always felt like the lectures were rushed, with way too much material trying to be covered, and always thought it would be nice if the professor would put together a handout that elegantly presented and summarized the main points. I also felt like this would help me in my note-taking, because I could focus on example problems, rather than having to transcribe the main ideas. I was always disappointed that this never happened. I guess everyone's been told not to do it.

Maybe it's just me, and I'm just weird in that I can learn effectively from reading printed material. But I still disagree with the blanket statement that "it won't and they don't." There are certainly students who will disregard a handout, but there are students who'll disregard anything; you can't cater to them, and no single style fits everyone. (Granted, it would be less necessary if undergrad textbooks were better. But most of them are, frankly, awful. Plus, in a large university, textbooks are often dictated by department and don't necessarily follow the professor's chosen syllabus.)

I would have to agree with @CodyGray.   I think what the author is trying to get at is: if you did a bad job teaching it, you'll probably do a bad job writing about it.  This is a fair point, but not one that I totally agree with.   I've made some blunders during my lectures due to, for example, a rushed set up of a problem.  When I wrote the supplementary material, I made sure to take as much time as I could to ensure the setup was correct, and students appreciated it.  However, I can see that if I had rushed the handout, too, it would have been poorly received.


text:
What should a PhD in physics put in a CV?
The countdown to ending my studies has begun, with less than a year left to finish my PhD. I'm currently very confused about whether or not going for a post-doc, considering that I have recently found out that physicists can do something outside academia. I might therefore look for a job in the private sector.
I work in a mathematical physics sub-field called quantum chaos. I have been programing in Python and Mathematica for the past 3 or 4 years. Although my research does not include data analysis, I do have some small experience in neural networks using Keras, which I believe would not be too hard to fine tune. At the end of my PhD I will have published no more than two papers, both possibly in Physical Review A (impact factor 3), but maybe one will be accepted in Physical Review Letters (impact factor 9). I will also have participated in two or three international conferences. I do speak some four or five languages.
So what? I understand that if I apply for a post-doc my achievements can be seen as standard, and I already have a CV aimed at presenting my research work. The problem is: what should I put in a CV aimed at triggering the private sector's attention? I see my work as immensely irrelevant. I understand that physicists are quick to find patterns and solve problems, but they must be employed to get a chance to show it. Are they really going to care if I add that I have experience dealing with harmonic analysis in cotangent bundles or that I have shown that a certain coherent state propagator is not actually an element of a Bargmann-Segal space? I have absolutely no experience working in any sort of industry, and the only assets I can offer are a reasonable knowledge of Python and Keras and the languages I speak. Any imaginable CV I write will probably make an employer laugh at me. Do I even have a chance here?

This is why it's a good idea to think about these things during, or preferably before, your PhD. You're picking up skills, but how useful those skills are and how you're going to use them is a big question. Fortunately, you're not out of options, and you've probably learned more than you think. Some thoughts:

You should absolutely list Keras. With the amount of hype machine learning has been getting having experience with neural networks is a big deal. I'd go much more than that: list everything you know about data analysis. It doesn't matter if it's something as simple as linear regression. List it all, give details.
You should absolutely list Python as well. In fact, list all the programming languages you know. You don't have to be an expert in all of them because you can learn the others quickly. Are you able to read C/C++ code? Java? R? You can also list Mathematica.
You should absolutely list all the languages you can speak. These skills aren't easy to pick up. If you can speak Japanese for example, that might make you the only viable candidate for a company that's looking to send a consultant to a Japanese client.
What else did you learn in your research? Did you learn any algorithms that might have wider applications? For example, did you learn how to parallelize code? Did you learn how to use a Linux terminal? Git and Github?
Did you engage in science communication and / or teaching? If so definitely list this as well, since it indicates you can mentor others.

You should also visit your university's career center. They'll have experts who can help you.
EDIT: One more thing, take a look at the advertisements you're responding to before sending in a CV. Do you know any of the things they request? For example looking at one such advertisement, there's this:

Ability to query a SQL and/or NoSQL database efficiently

If you know how to do this, you should absolutely list it on your CV as well.

I did not think about these things earlier because I did my MSc and PhD without even paying attention. I wanted to learn more about nature and had never thought about leaving academia until last month - and I will probably not leave it. Your answer is, however, exactly what I needed.

""CV"" is for academia.  "Resume" is for outside the ivory tower (government, McKinsey, Goldman, Google, industrial companies, etc.)
Postdoc or professor jobs will expect a "CV" which is a longer document listing all your publications, conferences attended, etc.  It can often be several pages long.
The rest of the free world just expects a standard "resume" like in all the "how to write a resume" books.  Instead of listing your publications, you can just say X peer reviewed papers written as a bullet point.
This is 1-2 pages even if you are 60 years old and extremely high ranked.  While there will be some differences in the content, it really doesn't look that different for a CEO, secretary, industrial scientist,  HR manager, or whatever.  For someone under 40 (arbitrary, but my guideline), don't exceed 1 page.  Right now you will maybe be straining a little to come up with bullet points of work or quasi work experience.  But this will change as you progress and will be the opposite problem!
This is very, very far from a fresh novel problem (people graduating and needing to write up CV/resume).  There is a HUGE amount of advice out there. Lots of books on this.  Your guidance center can advise you on this also (even giving you feedback on your document itself).  Also good to compare/contrast resumes (or CVs I guess) done by people currently interviewing.
P.s.  It's normal at places like Google, McKinsey, Goldman, NSA, etc. that they would take an entry level Ph.D. and then have him do something different from his direct experience.  (Same thing applies for chemists and engineers in more mechanical industries.)  They just see you as a fresh smart face.  You've cut your teeth on some topic but very unlikely to keep working in same exact subfield.  (It would be great if you could for your sake and theirs, but it is really just rare from either side to find perfect matches.  Employers end up going for the "good athlete" versus the skilled player.  Given the physics and the programming, everyone knows you are smart and can do something.)

I am indeed wondering what I did that could be called "work", since for me it was "fun" all the time. Your point of view really made me a little optimistic, though.

Some effort at "translation" may be required.  This is normal when changing fields (and a move to industry is often changing field from pure research).  For example consider how ex military have to write a resume to translate their experience into something someone in corporate America cares about.  (Lots of great articles with advice on this.)  But seriously, if you look on the Web or network or use your career center I bet you can see lots of people positioning Ph.D. physics experience in a way that is relevant to industry.

Some possible bullets (you won't have them all, but may have others, consider this a thought starter):  (1) won conference award, (2) presented X times to academia, industry, etc.  (3) attracted students to lab group (4) secured or assisted in securing funding (5) wrote progress reports (6) did Y peer reviewed papers (7) founded collaboration (8) developed new method/apparatus, etc. (9) taught courses (mention positive feedback and or an award if possible).  ETC.

Just brainstorm and write bullets in Word. That is the good thing about nowadays versus typing before Word processors.  It is very easy to edit/hone.  And very easy to cut text.

Your private sector CV needs to be different than your academic CV. I can give you a little insight into this. The best way to think about it is that your private CV highlights your skill set and your academic CV highlights your publications. I recently decided to accept a position in academia rather than go into industry but I still applied to both.
My resume is a page long, my CV is longer than a single page. My resume was ordered as such-

education/work experience
Recent examples of work
technical skills (programming, analysis, etc)
soft skills (spoken languages, leadership, etc)

As for what you can do with a physic phd, my friend ended up taking a job at a bank. More than one physics phd is not interested in doing 2-3 post docs before finally having the street cred for an R1 to hire them. This is especially the case when they can make nearly double (or more) going straight into industry.

I have friends who took post-doc positions in Machine Learning in order to build a more industry oriented CV/resume. I think a PhD in physics, together with a post-doc in ML, is definitely going to attract a lot of attention (I might copy their strategy).

@QuantumBrick And there are plenty of ML post doc positions as well. If you are doing simulation work in physics, you have a pretty good base to make the transition. And there is a good chance you are already familiar with gradient descent.

I have been working with numerical simulation, yes. All I know about gradient descent is that, well, it's basically just the chain rule. I spent some time thinking about ensembles of weights form a statistical mechanics point of view and all my friends said "mate, don't lose too much time theorizing... This field is about getting stuff done no matter what".

@QuantumBrick Thats a good perspective. There is a ton of low lying fruit that is more about "where can I appropriately apply this technique" rather than "how can I improve it". For example, generative adversarial neural nets (GANs) were just developed a few years ago. There is a huge field of applications for those. Currently, the best use is to know when and where an ML technique is and is not appropriate. Grab a post doc at a name-brand school (stanford, duke, MIT, etc) and you will be pretty set.

I see little reason, actually, to limit yourself to a single CV. You can have a comprehensive one, of course, that covers every interesting thing you've done, but you can also provide tailored CVs to particular purposes, leaving out the things that you believe to be irrelevant to a reader.
This implies, of course, that you aren't posting the CV to a general public site for everyone to see.
You need to be honest, of course, but the CV needs to include only relevant things. Those are naturally different for academia and industry. In fact, for industry, different potential employers might see different CVs depending on the work they do and whatever it is that you do that might be relevant to it.
Alternatively, you could provide, for a particular employer, a different organization of your CV, listing the most relevant things in a special section and the other stuff (or most of it) in a later section. The reader will focus on the relevant stuff, I think and will give up on the esoterica.
I was once advised by an employment counselor to not say that I held a PhD when looking for an industry position. There were no academic positions available at the time and, in industry, an MS was thought of as more valuable than a PhD.

I do have a MSc too, but I think being is physics it is worthless. My country's standard line of study is BA -> MSc -> PhD, the whole process taking around 10 years. Since I might leave to Europe to look for work, I think it is perfectly possible to omit the fact that I'm over-qualified.

@QuantumBrick Don't miss out the MSc, or any previous qualifications.  They tell a fuller story, and avoid mysterious gaps in your history (which employers can be suspicious of).  Your new employer might have a use for something specific that you've done in a course, or even at high school.


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Is there any evidence of a benefit to students answering questions in front of the whole class?
In my programming tutorial, I often ask a question to the class along the lines of "what is my next step?" or "should I do X or Y?".  In previous years I've had lots of student participation, but this year I get nothing.  I've adjusted my tactics accordingly - I no longer ask the class for a response.  Instead, I propose a practice problem, give them a short time to answer it on their own or with peers, and then show my answer to the problem.  Usually, students will ask questions about my approach at this stage, but very rarely will they offer insight into how they thought they should be solving the problem.
I had the feeling that the students didn't like my tutorial (or me), so I asked for and received anonymous feedback from them and it turns out they think it's great, with only a few helpful suggestions for how I can be more effective.  So I wonder, is there any actual benefit to asking questions for students to answer openly in class, or is that just a recipe for awkward silence?

I like the way you dealt with the problem.  Awkward silences are... awkward! // Here's an additional idea (which I have never tried, I'll be honest): as homework, ask the students to devise a short quiz on a certain topic.  Collect them, and then select some of the quiz questions to be asked verbally at the next class session.  Type them up and give one to each student to pose to the class.  Have them give their answers either verbally or by writing on the board.  Warn them ahead of time that you'll be doing this, and

say, "If anyone has severe shyness that would interfere with asking or answering, please email me or come to office hours."  In other words, don't force anyone to participate if they're not comfortable.  Also, allow students to trade questions with a neighbor if they want to.

I like the idea of having students come up with their own questions, and posing them to the class.  I'm not 100% sure that this particular class will do it, but it's worth trying!

There is an actual benefit of asking questions for students to answer openly in class, even so most of the times it definitely is a recipe for awkward silence.
There is a list of ten benefits from "Uses for Participation." (The Teaching Professor, 23.9, 2009, 4)
Personally, I think the benefits 9 and 10 are most important:

Participation can be used to develop important speaking skills [...]

Participation gives students the opportunity to practice using the language of the discipline [...]


text:
Papers with "towards X" in the title
I am working on a research project whose eventual conclusion is probably several years away.  However, I have some intermediate results that are:
a) Useful for practitioners in the field
b) Useful as stepping stones towards the eventual complete solution
I'm thinking of writing up these results in a paper with the title: "Towards a closed-form solution of grasp statics".  My question is, is it correct to use "towards" here to indicate that the paper is presenting a piece of an as-yet incomplete solution?

As formulated, this is awfully close to a shopping question. However, MathSciNet and Google Scholar show a lot of presumably reputed papers starting with "Towards…"

What is a shopping question?

@user37208 since when? I'm very American ("Southern by the Grace of God", as we like to say) and I would use towards.

"Towards" and "toward" are synonymous cognates in every variety of English.  Some varieties tend to use one more than the other, but both are used frequently.  The choice of which is preferred in a given context is entirely a matter of personal preference and style.

Using "towards" in a title is perfectly acceptable, as indicated by the large number of papers that you can find with this word in their title.
I've also used it myself, in just the sort of manner that you are considering, and found no objection from reviewers.

I have one starting with "toward" too (which reminds me of this): we have thus at least two cases from users of Academia.SE. Caveat emptor: we haven't reach the goal and I moved to something else: handle "towards" with care.

Although I agree with the other answer that "towards" in a title is fine, I don't believe it is acceptable for the as-yet-unsolved major topic to stand alone as the entire title.
In particular, if while working toward a closed-form solution of grasp statics, you publish several papers containing useful partial results, a reader should be able to distinguish them by title and not merely the year of publication.
Most probably once you identify the differentiating factor for this piece of work, you'll still name the major problem, but without using the word "towards".  Perhaps something like Separability of force-volume integrals arising in analytic models of grasp statics (I really have no clue about your field, I'm just throwing in some mathematics terms)
In summary: DO name the problem you're working towards, but if possible, make your title descriptive of the portion you've done, and try to avoid the word "towards".


text:
Are there any benefits from publishing research on subjects different than one's degree/profession?
Are there any benefits from publishing research on subjects different than one's degree/profession, like being in the healthcare field but publishing about biology or psychology?
Thank you

The danger is: if you don't know the area, then you will be repeating the mistakes of the past.

Is your question about whether it is beneficial for someone in a medical field to do basic biological or psychological research? I don't think that is the same as publishing on a different field but that's the way of interpreting your question that makes the most sense to me.

Sure there are benefits for society if you publish good results in any field. But wait, probably you meant some other kind of benefits?

I once applied for a research job in industry, on forecasting retail sales using time series analysis. I had zero knowledge about forecasting, but a couple of papers where I did inferential statistics in psychology. This was sufficient to convince the company's co-founder (a statistics professor) I'd be able to work my way into the statistics of forecasting. I got the job and still have it ten years later.

Yeah I meant economical/job benefits to the one publishing. That's inspiring Stephan, I wish I'd get a similar occasion sooner or later.

I have done this, and as I found, there's a few benefits:

You may be able to introduce a new concept to a field, and see that idea grow.
It shows a level of flexibility and the power to change. For example, "your field" might not be static. I've given talks in conferences that I never would have thought were my field, and I currently have a job in something that's not "my field" - and some of that is due to multidisciplinary papers.


text:
Is a publication with co-authors worth less that a sole-author paper? Does this explain people's reluctance to include someone as a co-author?
Is there a lower value to publishing with other co-authors instead of just oneself? Why are some people so reluctant to acknowledge your participation and contribution?

There's already a got answer, so I wanted to just point out that in my field (engineering) it is almost never the case that someone has single authorship. Usually students or PhD students write papers and the team leader and professor will be involved as kind of internal referees until they are content with the paper, so their names will appear, too.

Worth less to whom? Lower value to whom?

This is, in my (admittedly limited) experience, heavily dependent on your field.
In some fields, single-authorship is the norm; I believe a lot of highly-theoretical mathematics and some social sciences go this route. In other fields, such as astrophysics, this is almost never the case, as the work is often conducted among dozens of researchers working on multiple continents.
From what I can tell, publishing with co-authors tends to signify one or more of the following things:

The work is highly multidisciplinary (even within a single field) -- some research requires many experts in many different domains working together.
The work is "labor-intensive" -- some research requires a great deal of preparation that would be infeasible for a single researcher. For example, in my field of computer engineering, there's usually a significant amount of coding that goes into the research, which is most easily/quickly accomplished by many students and postdocs working together.
The work is large in scope -- larger, more ambitious projects require a higher level of support and more minds working together.
The work involves someone famous and everyone wants a piece of the pie -- okay, admittedly I made this one up.

That's not to say that single-author paper don't fit into one or more of these categories. These are just some rules of thumb that I've seen so far.

As for why some people are reluctant to "acknowledge your participation and contribution": well, this ranges the gamut of everything from the evils of:

Narcissism
Ego
Desire for fame/prestige

to the more mundane/less evil problems of:

Disagreements on what constitutes a large enough contribution to claim authorship
Misunderstandings as to what is being contributed (by one or both parties)
Traditions on what is deemed worthy of acknowledgement in publication.

In short: human nature.
If you're concerned that you aren't being credited for your work, you need to speak with the other party ASAP and set out clear guidelines moving forward as to where credit will be given and for what. Get this in writing -- timestamped and signed preferably, email is great for this.

There may have been a tendency in pure mathematics towards single-author papers long ago, but this has changed drastically in recent decades. However, multi-author papers still have a SMALL number of authors; having more than 3-4 authors on one paper is still fairly rare in mathematics.

University regulations can also be a factor. For example, we have the directive that quite some involvement in the work is required for coauthorship, while elsewhere they might just put their Nephew's name on there just because.

You missed one of the major things that seem to discourage people from co-authoring: the overhead involved. Edit conflicts (version control is still far from being widespread), disagreements over style and storytelling, unclarities about who is responsible for what and which decisions need to be made together (particularly as it comes to submitting), lack of understanding of the other authors' contributions (particularly in a cross-subject collaboration, where authors can have completely different goals) and plain old timezone incompatibility slowing down communication. More ...

... important than ego in my experience.

here is a grad student perspective:
I actually find that it is more time consuming in my field to work with co-authors. I have to wait for feedback, navigate busy schedules, navigate diverging perspectives and approaches. It takes me a couple months or so to draft up a solid empirical paper but then it can take months to progress its way through the inner working of a large R01 research center. I actually think that for student's the trend toward large research teams is a double edged sword. Having 4-8 co-authors significantly extends the time it takes to get it out for review. 1-2 co-authors is perfect I have found. I also think it is quite silly to penalize or raise questions over sole authorship or even judge students who can see a project through from start to finish. Say you have a dataset and you know how to code the data and run the statistical analyses. If you have an outside person look over the code and read the study to verify accuracy this is sufficient I believe to publish a sole piece. As a grad student we are in our mentor's shadow constantly. It can be extremely difficult to differentiate yourself from your mentor. THis is not the case when using secondary survey data and can truly carry out your own study. I am a very productive grad student (16 publications) where about 40% have been solo authored work. I would have never been able to get through the bureaucracy that is large research centers and sustain this level of productivity. On the other hand, all of my papers benefit significantly from co-authors and the final product is always extremely refined. So I think we cannot establish hard and fast rules to govern this type of process. As researchers we are burdened by so much unnecessary hoopla. It is so cumbersome, especially the needless paperwork, self-promotion and negotiating that is academia. I am always shocked because it seems to me that tenure committees are intent on establishing as many obstacles as possible to get in the way of our work while also expecting more. A good CV in my eyes should show a mix of high and low collaboration work. With a clearly demonstrated path that is focused and shows independent thought.
A big problem with grads now in public health, applied sociology to an extent, social welfare and these other professional fields is that they have become producers of globs of students all doing similar work with about 2-5 publications (2 or so first and the rest co-authored). And it is expected to do a post-doc on top prior to entering the tenure track. So it is increasingly difficult to differentiate yourself from other students. My opinion as a solution to this is a return to a BALANCED approach. Demanding students to produce 1-2 SOLE authored pieces during graduate school that firmly establishes their voice as a scholar. Then 3-5ish additional pieces that demonstrate collaboration with primary mentor and others in the field. A similar composition with greater quantity should be expected in the TT and PD tracks.
The last thing I would say is that it is important to emphasize a career stage approach to this. I think for grad students producing several sole/first authored papers is particularly important. In the TT it is important to be first author on a lot with grad students and a smaller number of first author pieces. Then in the Tenure position placing your name last on many publications with 1-3 authors is ideal and for very large productions can have more authors. These are not rules but rather how I would recommend we shift moving forward. Just my own perspective as a grad student.
This would allow for committees to better understand who they are getting with grad students. All in all the existing standards/norms around publishing to just glob out as many co-authored papers as possible is significantly hurting the social and professional sciences.

There is one and only one reason to not include someone as a co-author. If the prospective co-author did not contribute any vital input to the work then they should not be included. Not all agree with this, including a former post-doc 'advisor'. Back story:  I refused to include him as a co-author on work that he had no involvement in.  He reciprocated by scrubbing me from a paper for which I generated all the experimental data. (I quit the lab prior to work up. I don't handle charlatans well.)

You probably meant "one and only one legitimate reason". As your story demonstrates, people may have other reasons, such as retaliation.

Is there a lower value to publishing with other co-authors instead of
  just oneself?

This will vary heavily by field - and indeed a lot of fields struggle with interdisciplinary research because of it. For example, in my field it is routine to have very large authorship lists. This occasionally causes issues with fields where single-author papers are more common in how they parse the value of a particular paper.
Similarly, in my field single author papers are not usually "mainline" findings that would drive the field forward, but interesting side musings, methodological papers, etc.

Why are some people so reluctant to acknowledge your participation and
  contribution?

There are, as with anything, a number of possible reasons that are all non-nefarious:

They have a different notion of what your participation and contribution were
They have decided that the formal author guidelines put out by some journals are what they're going to stick to, come hell or high water, and they don't think you qualify
"Stretching" to include you would also necessitate the inclusion of a large number of other people whose qualification for authorship is marginal

The first is, in my experience, the most common reason who someone who thinks they should be an author isn't.


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How can one find journals paying authors or reviewers?
How can one find journals paying authors or reviewers?
I've read about some old examples (probably about a relatively small university I can't recall) but I'm wondering if is there a directory or shared keyword or do they just go by word of mouth?
Can I write on topics I don't have a PhD about but I'm otherwise competent on?
Thank you

I don't think that such journals are still around. Nobody would pay for them.

It's usually other way around. In some journals, you pay when you want your paper published.

Publish in Russian. Quite a number of Russian mathematical journals that are eventually translated into English pay their authors.

On payment for review: a few economics journals http://academia.stackexchange.com/questions/68191/why-dont-researchers-request-payment-for-refereeing/68199#68199 and a small number of others here and there http://academia.stackexchange.com/a/20932/27825

Write for almost anything else than scientific journals and you can get paid.
Also, if you are not doing research / don't have a PhD in a topic, something else than scientific publishing is much more easier.

Good answer, except: the OP didn't mention science.

1 My answer is not exclusive to science. 2 it is Academia here, we talk about science. If someone wants to be a writer, he/she should understand contexts.

"2 it is Academia here, we talk about science." That is exactly my point -- academia is not synonymous with science, nor is academia.SE.  I took your use of "science" to be a synecdoche for "academia".  If you really mean science, then your first statement is false, because of the enormous number of non-scientific academic journals for which authors are still not paid.

Thank you for the comment. It helped to clarify the issue and gave tremendous good advice


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How to get students to connect the pre-lab to the lab?
This is a very frustrating issue we are seeing with our students.  Students get access to the prelab one week in advance of the lab.  In the prelab, the students often have to use theory to predict a result in the lab.  Almost all students get the prelab correct, and they know that they are correct because it is an online quiz type thing, so they get immediate feedback*.
When they get to the lab, they are asked a question like "what is your expected voltage, and how does it compare to the measured voltage?"  A very large number of students, I'd say around 40%, will invariably ask "how do I know what my expected voltage is?"  However, this would come from the stuff they did in the prelab.
So, how do I get the students to recognize that the prelab isn't just an assignment, but is actually a vital part of the lab?
*OK, so realistically it's possible that the students are all just taking one person's answers and therefore aren't really thinking about it, but my experience with this class is that would be the exception, not the rule.

Don't do the pre-lab.
Divide the lab experience in two or more sessions, where they have to do the calculations first and the measurements soon thereafter.
And avoid online quiz with feedback: the answer is plausible if it's compatible with the measurements, not because the computer says so.
For long calculations, I sometimes use an intermediate solution in which they have to perform the calculations as homework, but they read what they have to do in the lab instruction manual, so that the two things appear connected. For example:

In this way, they are forced to read the whole lab manual first. And of course I tell them and write them that the calculations are part of the lab.


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How to teach students to ask Polya-type questions
I've recently read "How to Solve It" by Polya.  In that book, the author basically explains the method that I use in my own teaching - asking relevant, prompting questions to get students to reason through a problem.
However, I have a problem with this method (including in my own teaching) - the real challenge should be to get the students to ask those questions themselves.  I'm not doing anything other than asking "the right" questions to get the students to move forward, but they aren't spectacularly difficult questions to come up with on your own.
I fear that all I'm doing is pushing the responsibility back on myself by taking away the really hard part of problem solving: figuring out the path you need to take.
So how do you teach students to ask good questions while problem solving without the need for teacher assistance?  We can limit the question to STEM problem solving if we'd like, but I'm sure this problem exists in non-STEM fields.

Maybe a silly question, but have you tried teaching the method?

Yes but it doesn't go well.  Mainly this is because I don't really know how to generalize the method.  For example, I know that in a particular problem a good question would be (whatever), but I don't know why I know that...

Do you give questions that promote the analysis, or are they focused on the "correct" path?

I don't think I fully understand the difference, @SolarMike, and perhaps that's a problem I need to solve myself.  Could you ellaborate?

You said " I'm not doing anything other than asking "the right" questions to get the students to move forward" and that is why I asked is that the questions targeted towards the solution or questions to promote analysis...

Then I suppose I'd have to say that my questions are more often than not posed toward the solution.  For instance, I might ask "can you find the power used by the circuit", which seems to lead the students quite a bit.  That's an interesting thing to think about...

Like most things, students need to be actually taught to do it. And "taught" doesn't mean having it explained to them, but rather practicing it via some sort of planned exercise or activity.
It is an interesting idea, though.
What I would do is to periodically hold a brainstorming session with students, assuming that the scale is reasonable. Take a problem that they haven't solved and ask for questions about it. Don't answer the questions, but ask for more questions - beyond the horizon questions - outrageous and maybe only potentially useful questions. Spend time on just gathering questions, making something of a game out of it. Note that I've done similar sorts of "gaming" activities with adult doctoral students, so don't assume that this just works with youngsters.
Talk to them about what sorts of questions are generally useful. What is a smaller problem than this that we know how to solve? What is a related question? Where could we find information about this question? What do these words actually mean, individually and it conjunction?
After you have a bunch of questions, try to have the students sort them in some way. Which are useful for this idea? Which are useful for extending the idea, or a related idea.
If you practice this with them they will start to become more comfortable thinking that way, though you can probably expect more classroom interruptions in the normal course of things.


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What is the term for intended consequences of an activity other than intended learning outcomes?
Question might be a bit strange.  I am looking at a series of activities that we run every year.  These activities have some intended learning outcomes (ILOs), but these outcomes are stated in terms of what students will know or be able to do at the end.  I'm trying to explain not just the ILOs but rather the intended experience that the students will have.  For example:
"Students will keep up with their homework and review course material throughout the semester, rather than cramming during exam times"
This isn't really an ILO, but it is an intended thing that students will do this due to the nature of the activity.  Is there a term for this type of thing in pedagogy? "Intended Student Experience", perhaps?

Would "Expected experiences" do?

Ignore previous comments, I think I misunderstood what you want.

Presumably the distinction is between those intended outcomes that can be measured in some reasonable way at or soon after the end of the course and other intended consequences that can't be measured effectively. Any distinction will probably do the job, even "Other intended outcomes" or "Unmeasured intended/potential outcomes" or "Hoped-for behavioral changes".
Just make the distinction clear both in how you intend to both have students arrive at the outcomes (perhaps not the same for the two categories) and how you distinguish between the categories.

Your example seems more like a rule or expectation rather than an objective or learning outcome. It would be difficult to measure this directly as you can only  surmise that students don't study and are cramming instead.
If you want them to study you need to embed study activities into the curriculum. For example, reviewing material in class, study guides, quizzes, chapter summaries, presentations by students, etc.are all ideas.
The general point is that constant assessment compels constant studying while giant mega exams such as midterms and final exams encourage cramming because they aren't seen as imminent for many students

I fully agree.  The specific thing I'm looking into was the assumptions that were made about these activities that led to their creation.  In this case, the particular set of activities was assumed to promote studying throughout the term rather than cramming at the end.  I'm then going to analyze whether or not that really happens.  I need a useful section heading for all of these assumptions. Perhaps...just assumptions?


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Should I explain a bad grade that is not directly related to the program?
I am applying for a M.S in Statistics in North America. I received a "C+" for my undergraduate topology course.
I am not sure whether I should explain that or not for two reasons. First, topology does not seem to be related to statistics anyway. Second, even if I explain that I was not feeling well, I have no evidence (since it takes forever to see the doctor here), so explaining it might actually make admission officers think I am lying. What should I do?

Explain even though I do not have proof from doctor
"Explain" but not mentioning the cold, just say something like "I will grow" (which I think it's technically lying?)
Say nothing

"topology does not seem to be related to statistics anyway" This is not true. Topology can be used to study geometric features of data.

Are you saying that where you did your undergrad, the final exam has that much effect on the final grade?  If so, yuck -- what a terrible system.

I'd say that there is little to gain by attempting to explain the C+ grade. If you are offered an interview for the position, or are otherwise invited to discuss your application, you could then ask the interviewer if they have any concerns over your grades. If they raise the topology grade, then you can explain then. If not, you've offered the opportunity.


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Tuition fees vs enrolment fees?
What is the difference between tuition fees and enrolment fees? The University I'm planning to apply for MA studies, requires Non-EU students to pay 1500 euros per semester for tuition and 150 euros per semester for enrolment.

Tuition fees are the cost of the degree you want to study. The enrollment fee is just the amount of money you have to pay to enroll yourself into that course.


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Doing a MA / MSc in your hometown despite the fact that it's not challenging?
Couple of years ago, I have been in a situation where I almost had to make a decision whether to wait for an opportunity to come in the future, or to do a MSc in my home city which was average (if not below average) in quality. Luckily, I managed to win a scholarship and did my degree abroad, on a well equipped and well-known university.
However, if a candidate keeps being rejected the necessary scholarships for him to do MSc abroad, is the MSc program really worth it despite the fact that you know you won't get a good knowledge at your homecity University? Should a student that wants to do a MSc or MA degree in a chosen field do the MSc at home despite the fact that his home institution is not 'scientifically well-situated'*?
*In lack of better words, here I mean that the department at the home University has lecturers that aren't really knowledgeable. Also there are not (m)any international collaborations and there is no possibility for you to be challenged because nobody knows the new methodologies you are planning to use.

What are you careers goals? This post is similar to another question about the impact on schools for post-PhD.

Something is better than nothing.
If a student, for whatever personal reason, needs the degree either now or never, he should always take the local program. If it is possible to wait a year, study, retake exams or makeup weak grades, do that and then reapply everywhere. But if it's "that" local degree or nothing, go for the degree.
Any weak degree is a bummer, but it still opens doors. It instantly creates eligibility for a new tier of jobs nationally and internationally. It makes one eligible for teaching, supervisory roles, and for PhD programs. If a student goes in knowing the program is weaker, he or she should have a self-defense plan. Supplement classes with productive personal projects. Perhaps working cross-discipline with a stronger local department. Example: my university has a weak biology department and high quality mathematics/statistics department. I recommend the bio students become experts in non-parametric tests and try to get method-specific publications to give themselves leverage.
Other ways of making the best of a bad degree is to find the one or two good quality advisors who will 'understand,' getting an internship, attending conferences, joining professional student organizations and using them to build contacts.
Admittedly, this answer could be modified in the face of age, family commitments, and financial hardship of the student in question. In the majority of cases, however, the 'weak' educational investment would still pay the greatest dividends.


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Being personal in motivational letter
I'm starting to prepare my application for scholarships to do MSc in Europe. One of the requirements, of course, is the motivational letter. I was interested: how personal should the essay be? How many hints about your passion in the chosen MSc programme are ideal? I don't want to sound pathetic and unrealistic in my application and will try to convey as realistic motivational goals as possible in the letter. But are there boundaries where being too personal in your statements will be considered a negative thing?

Is a motivational letter explicitly required or is it a statement of interest/ research statement?

@astronat Motivational letter, not more than 3 pages in length.

Related: https://academia.stackexchange.com/q/36725/20058

Passion is good, but passion alone does not make a successful student. You also need to talk about your academic achievements and interests in a realistic manner, and emphasise how your qualifications and aims make you a good fit for the particular MSc you're applying to.
Emotive statements which use time honoured clichés such as "I've been interested in physics ever since I took my first trembling steps into the subject" should definitely be avoided.
Academic writing should be crisp and clear and ultimately there is little room for sentiment. If you can convey your motivations in that style your statement will likely be much better received than an incoherent or overly emotional letter.
Note: the answer to this may be somewhat dependent on the local academic culture (you don't specify where in Europe you're applying) but I think it's broadly true that too much emotional writing will have a negative effect.