<issue_start>username_0: So with the job market being as it is, I'm considering the prospect of leaving academia after my PhD. The problem that I have is that the name of one of my Areas of Specialization has been co-opted by some new age mystics and if you search "X" after seeing that I specialized in "X", you're more likely to think I specialized in some arcane form of crystal healing than the work I actually did.

My other AOSs sound fine, even semi-impressive to the layman, and so don't really concern me. This one, however....

So, two quick and related questions:

1. Am I right to think that my AOSs at least would still remain when listing my PhD on a non-academic CV/resume? Or just "PhD in field X"? [(The question on CV for leaving academia didn't provide too much specific guidance here.)](https://academia.stackexchange.com/questions/17347/cv-for-leaving-academia-after-phd)
2. Is it ethical to leave one of my AOSs off of the CV, assuming I leave the others untouched? In a sense it is misrepresenting what I did during my PhD, since I really did a lot of work in all three of these areas. On the other hand, listing this troublesome AOS might misrepresent what I did even more--- crystal healing and such.<issue_comment>username_1: This seems like an obvious opportunity to briefly explain yourself on your CV by listing the formal names but then stating what that actually means in parentheses. As an example:

```

PhD, Some Named Institution (2007-Present)
Areas of Concentration:
 - Science thing 1
 - Science thing 2
 - Crystal healing sounding thing (Chemical Engineering)

```
Upvotes: 3 <issue_comment>username_2: If you are applying for jobs in industry or consulting, your Area of Specialization is much less important than the *skills* you have developed and your *proven record of performance* (producing results, completing projects, writing and publishing papers). You could omit your Area of Specialization completely and just list your major and your skills, e.g.:

* PhD in Biochemistry. Skills: Experiment design and analysis, statistical analysis, computational modeling of protean evolution.
Upvotes: 1


<issue_start>username_0: Recently, someone analyzed [computer science professors at top universities](http://jeffhuang.com/computer_science_professors.html) and found that over half of the professors at the top 51 universities graduated from a top 10 university. [Others](http://chronicle.com/article/What-Are-Low-Ranked-Graduate/136823/) have also brought this up. From my personal observations, most schools do hire graduates from better ranked schools.

1. Is this because of the competitive job market? *We have so many good applicants, we have to narrow it down some how!*
2. Or is it simply that these schools produce the most PhDs?
3. Has this always been the case?
4. How rare are exceptions to this? I know of a few people who graduated from a top 75 school and got hired at a top 50 school. But what about bigger gaps? The top 10 schools seem to just swap graduates, do they ever hire from a 50+ ranked school?

**Update 2018:** I have accepted a tenure-track position at a top 75 department at an R1 university immediately after graduating from an unranked department at an R2 university. It does happen!

This may or may not generalize to other fields and countries.<issue_comment>username_1: The top ranked doctoral programs get the cream of each year's incoming graduate application pool because they can offer access to the top professors, top research libraries, and have tons of money to spend on tuition waivers, stipends, summer research money, etc. They can effectively outbid other programs and choose the people who seem to have the most promise (or are advantaged in having Famous People write for them, etc. etc.).

Graduate students at top ranked programs don't have to spend as much time doing non-research activities such as teaching and waitressing to pay the bills as they're getting most of their living expenses covered. They instead can focus on their research and publications, resulting in a flush CV by the time they graduate.

This leads grant agencies and hiring departments to assume that the graduating students at the top ranked programs are indeed the best of the best. They certainly have the imprimatur of the Best Programs® and Famous People® are writing them letters of support.

This is almost certainly a flawed assumption, but when faced with 200 grant or job applications, it's a shortcut many search committees make. Ideally they should just look at the candidate's qualifications without considering the school or the Famous People® who wrote for them.

But even if we redacted program names in applications, the very fact that having gone to a top-ranked place gives people a huge material difference/advantage in resources available while they are in the program, and this is evident in their CVs which are long with lots of publications and talks in the Right Places®.

In a totally fair world, we'd do what google does and throw away (or at the very least redact) CVs and letters and instead interview people one by one. But try to convince a provost and a search committee to go along with that. It would take too long and cost too much.

Interestingly, as fewer and fewer people get jobs straight out of graduate school and everyone now has to have a post-doc or visiting position, this has served as a slightly equalizing factor as hiring schools can look at performance there as a better indication of inherent ability.

Note 1: People can and do move from lower ranked to higher ranked schools, but usually they don't do it in their first job. Rather, from a low-ranked they get hired at a mid-ranked school, then through publishing and publishing and publishing, they get hired away into a top-ranked (perhaps going through one or two job hops along the way).

Note 2: Top ranked universities (as well as everyone else) have overproduced so many PhDs in pretty much every field that there is market saturation. Even graduates at top-ranked programs are having trouble finding jobs -- even as adjuncts and NTT faculty. In a true market economy, the suppliers would be forced to lower production in the face of oversupply, but academia is not a market economy and having doctoral students is seen as a source of prestige for both faculty and institutions alike. Unless we can increase demand (by forcing schools to hire TT faculty instead of contingents, or other means) or reduce supply, we're all screwed but the folks graduating from mid- and lower-tier schools are screwed the most.
Upvotes: 5 <issue_comment>username_2: People are occasionally hired by far more prestigious universities than the ones they studied at. For example, there's a tenured professor in the Princeton math department (unambiguously among the top 5 departments in the U.S.) who received his Ph.D. in 1999 from Kansas State (which wouldn't necessarily make the top 75). Where your degree is from is a negligible factor in hiring decisions compared with how outstanding your research is.

On the other hand, research excellence is highly correlated with which doctoral program you attend. The top programs tend to get the students with the most talent, determination, and preparation, and they usually provide the most support for these students to succeed. Of course this is just a statistical assertion, not an absolute law. However, in mathematics in the U.S., the number of students graduating each year from rank 50-75 universities whose job applications are as impressive in research as those of the average top-5 graduate is tiny. If you're hiring based on research promise, then even the most unbiased search should lead to hiring mainly people from higher-end schools. Of course there's presumably some prejudice as well, but I don't think it's a substantial factor at research universities. (I have no first-hand experience with hiring at teaching-oriented schools. In particular, I don't know how overrepresented graduates of prestigious universities are or which factors are responsible for it.)
Upvotes: 7 [selected_answer]<issue_comment>username_3: <NAME> addressed this issue for sociology back in 2004 in the American Sociological Review and the article has now became quite a well-known piece of scholarly work within the discipline.

<http://asr.sagepub.com/content/69/2/239.short>

He basically argues that while departmental prestige is quite loosely correlated with the scholarly productivity of its graduates, being high-prestige school graduate gives one the necessary social and network capital to be placed within the institutionalised system of prestige sustained through the accumulated and "closed" interlinkages between top departments. Although the bulk of his analysis examines sociology placement records, he also provides some comparative data on the hiring of history and political science faculty, and finds that the relationship is quite robust while those latter disciplines tend to reinforce status hierarchies more so than sociology.
Upvotes: 3 <issue_comment>username_4: Here's a numerical perspective on this. Let's take the position that students graduating from highly-ranked schools have competitive advantage against other students (i.e. they are "better", and will generally be hired when their applications are compared with students of less prestigious schools). Now, consider how many positions are available at each level:

* Undergraduate: Typically, a college will have hundreds if not thousands of students in each year, of varying majors. In my major (math), let's say 5% of the class has it. At my school there were 1000 students graduating, so let's say 50 math majors (actually, it was more like 80).
* Graduate: Typically, a graduate school department will have tens of students per year. A small number of tens; at my undergraduate institution (Chicago), the corresponding graduate school has about 100 *total* students, for about 20 per year. So, with similar figures at other schools, only 0.4 of math majors can go to graduate school. Fortunately, not everyone wants to.
* Post-doctoral: Most math departments only have a handful of postdoc positions; let's say 10 (which is actually on the high end). So only 0.5 of graduating students can get postdocs. Of course, there are teaching jobs available at schools that don't produce PhDs, but those are "lesser universities".
* Tenure-track: In any year, any department might have three of these. Or one, or none. That means that 0.3 of postdocs will go on to a more permanent position.

At each stage the number of people accepted to the next level is a small fraction of the total number of applicants, and so the schools can pick and choose whom they take; of course, they will take the "best" applicants, which (according to my conventions) will generally come from the highly-ranked universities. The alumni of just the top 10 universities are sufficient to fill all positions at all universities that are at all desirable (to researchers, that is).
Upvotes: 4 <issue_comment>username_5: Universities typically hire the best people they can. And sometimes they can be found as graduates of lesser universities.

One of my favorite professors, who went from Yale to Ohio State, indicated how this could happen. His opinion was that a top 10 percent student at Ohio State was just as good as a top 10 percent student at Yale. So a top 10 percent student from Ohio State who applied to a high level university could be very competitive with a top 10 percent student from Yale, provided that research, letters of recommendation, and other aspects of the application were competitive.

Where the professor saw value in a Yale degree was that an average Yale graduate would be accepted in many places that an average Ohio State graduate would not be.
Upvotes: 2 <issue_comment>username_6: Look at:

* <NAME> et al., [Career on the Move: Geography, Stratification, and Scientific Impact](http://dx.doi.org/10.1038/srep0477), Scientific Reports 4, Article number: 4770 (2014)

From its abstract:

>
> We find that career movements are not only temporally and spatially localized, but also characterized by a high degree of stratification in institutional ranking. When cross-group movement occurs, we find that while going from elite to lower-rank institutions on average associates with modest decrease in scientific performance, transitioning into elite institutions does not result in subsequent performance gain.
>
>
>

Inside, there are plots quantifying transition from institutions of different rank.
Upvotes: 3 <issue_comment>username_7: Another statistic: according to Wikipedia the 62 institutions of the [Association of American Universities](http://en.wikipedia.org/wiki/Association_of_American_Universities) (AAU) issue 52% of doctoral degrees in the U.S. So, in the U.S. system, even if we discount any effect of institutional ranking, these schools should still account for half of the hiring of doctoral recipients. Of course, there is also an effect of university quality, so the AAU schools should account for more than half of hires. On the other hand, of course there are exceptional faculty who did not attend top-ranked schools. But the statistics suggest we shouldn't be surprised to find many faculty from a relatively small number of schools.
Upvotes: 2


<issue_start>username_0: Many of the journal references in the bibliography of my thesis contain bird names. Journals use birds names in the titles of papers in at least four different ways:

1. Titlecase, eg Teal
2. Titlecase plus scientific name, eg <NAME>cca
3. Lowercase, eg teal
4. Lowercase plus scientific name, eg <NAME> crecca

These different ways of using bird names makes my bibliography look untidy and inconsistent.

Should I adjust the titles of the papers in my bibliography so all bird names are used in a consistent way? Or should I use paper titles exactly as how they are given?<issue_comment>username_1: As a general academic principle you should *not* adjust the titles -- or other essential bibliographic data\*, e.g. the form and ordering of the authors' names -- of papers that you reference in any way, with the possible exception of necessary typographical concessions for "exotic" characters.

(For instance, in my branch of mathematics is it common to use the cyrillic letter [Sha](http://en.wikipedia.org/wiki/Sha) for something named after a Russian mathematician whose name begins with this character. If you simply don't have cyrllic characters available, you have to do something else. But even in this case it would be better to try to take a little trouble to "get cyrillic characters".)

So my answer to your question is **no**: it is obviously not your fault that different papers you cite refer to teals in different ways. So if there is any untidiness and/or inconsistency, you are simply faithfully replicating it, as you are obliged to do.

This answer comes from someone with precisely zero avian-specific academic knowledge. So it couldn't hurt to get a second opinion from someone in your field.

\*: I confess that I sometimes mess with "inessential" bibliographic data. For instance, most journals come with a volume number followed by a number of the issue within that volume, and I usually omit the second number: you simply don't need it to access the paper. I don't specifically endorse this practice and mention it only for "professional honesty", but in my defense I just checked around and I am far from the only one who does this.

Moreover in some fields there are different formats for referencing. In my field (mathematics), on the one hand we are not too picky about the format, and on the other hand we have standard repositories of all papers: MathReviews/MathSciNet and Zentralblatt, from which I assume that most contemporary authors simply copy the bibliographic data (and then the philistines among us delete the number of the journal within the volume). It *is* a good idea to choose a consistent format throughout all your bibliographic references: e.g. put last names first always or never, and so forth. But still: the title is not yours to monkey with, as far as I know.
Upvotes: 3 <issue_comment>username_2: You should never add or remove words from the title of papers you cite. The reason you add citations is so that your readers can find these papers, and the title is one of the most important pieces of information. While it might be obvious to you that "Teal" and "Teal Anas crecca" mean the same thing, this might not be the case for others, e.g. scientists outside your field.

The issue of capitalization is a little less cut and dry. Different citation styles treat titles in different ways (title case, sentence case, or even all-caps), so you have more freedom here to be internally consistent. In addition, some automated reference systems mess up capitalization, so in my experience this is frequently something you have to fix by hand. If there is no semantic difference between "Teal" and "teal", I would pick one and apply it consistently.
Upvotes: 3


<issue_start>username_0: The [Wikipedia rules](https://en.wikipedia.org/wiki/Wikipedia:COI#Writing_about_yourself_and_your_work) about citing yourself state:

>
> Using material you have written or published is allowed within reason, but only if it is relevant, conforms to the content policies, ... and is not excessive.
>
>
>

While the Wikipedia rules allows self citation, is it ethical to self cite?

Short example: there are two good papers on the same topic, *A* and *B*. Is it ethical for the authors of paper *A* to include a reference to A and not B in the "References" section at the end of the article even if it is not cited in the article. On Wikipedia, it is pretty common for things to be just listed at the end and not mentioned in the article itself.

My questions are:

* At what point is it appropriate to edit references to my own papers/preprints into Wikipedia? (Maybe even add a paragraph claiming the same breakthrough I claim in my own paper.)
* What should one do when noticing that otherwise unknown and very new preprints pop up as (uncited) references in Wikipedia articles?<issue_comment>username_1: 1. it should be peer-reviewed, otherwise wikipedia would be working nearly as a primary source (anyone could write something on a blog and use it as a reference, laughable).
2. once it's peer-reviewed, the references should be reasonable, they should support what is written in wikipedia and what is written should have a general interest in the article itself. Maybe many people would see my paper on topology if I put it in the Pope's article, but that's basically vandalism.
3. every paper has a set of references and describes the state of the art in some area, some of those references may be self-references. That is mostly the type of content that should be provided in wikipedia.

>
> it has never occurred to me that there's a high potential of the same
>  kind of abuse by academics.
>
>
>

*If well used*, this should be helpful for both academics and wikipedia.
Upvotes: 3 <issue_comment>username_2: Never.
------

Let someone else do it.
Upvotes: 3 <issue_comment>username_3: You should cite your own work if it truly adds to the quality of the Wikipedia article. It's true that it's in one's self-interest to get the publicity you described from having one's work cited on Wikipedia, but it can also be constructive. After all, who is going to know the subject better than the person who wrote a peer-reviewed journal article on it?

If it really is shameless and unethical self-promotion, people will see it and know, and so will the Wikipedia admins, who will revert it with prejudice.

Even though Wikipedia has rules against original research, once research is peer-reviewed and accepted by the scientific community, it doesn't really matter who adds it to Wikipedia. An example of a scholar writing about his own work can be found at <http://en.wikipedia.org/wiki/Talk:Wheel_theory>
Upvotes: 2 <issue_comment>username_4: I think this question really has two parts, the **ethical** question and the **practical** question.

First of, the **ethical** question. Let me say that I am surprised that you see the issue whether it is *ethical* to self-plug your work on Wikipedia as an entirely different issue than whether this is *allowed* by Wikipedia policy. Wikipedia is a private web site run on private donations, and is entitled to define how they want to do things around their piece of the web (much like we do here at Stack Exchange, to the chagrin of plenty a new user). I think it is impossible to argue that it is ethical (for academics or anybody else) to (mis-)use their service in a way that violates their own rules for your personal gain. Hence, to answer your updated question:

>
> It's a question about what is considered ethical in academia
>
>
>

This is not, precisely due to the reason that you say you are not interested in: *it is not allowed by Wikipedia*. It cannot be ethical to use their service, but don't consider their rules.

Second, your question also has a bit of a **practical** part. You claim that it should be really easy to self-plug your work on Wikipedia, and that it will be hard to trace and prevent. (You also seem to imply that this impact on the ethical question, which I think it has not - whether something *can* be done is pretty much irrelevant to whether it is ethical to do it)

I have a bit of a case study for this. A large European research project I was involved with some time ago once got asked by its reviewers to add their own papers and other outcomes to relevant articles "to increase visibility". After some internal discussion, the project obliged and started with some really defendable and arguably independently useful edits (taking very stubby articles and improving them with peer-reviewed content from our own papers, and adding references). *All of those changes were rolled back within minutes*, with the explanation that the edits looked too much like self-advertisement. We tried again, even more conservatively, and the same thing happened again. It turned out that the self-policing in Wikipedia works *much better* than anybody in the project anticipated. We gave up on the issue quickly.

The morale here is just that Wikipedia is aware that people could try to do this (and I am sure many do), and are very vigilant. I am sure you are able to edit in your links given enough energy, but it may be much harder than you imply it is.
Upvotes: 4 <issue_comment>username_5: The three columns of wikipedia are [Verifiability](https://en.wikipedia.org/wiki/Wikipedia:V), [No Original Research](https://en.wikipedia.org/wiki/Wikipedia:NOR), and [Neutral Point of View](https://en.wikipedia.org/wiki/Wikipedia:NPOV). In my opinion (and this is established in a large part of the wikipedia community, imho), you should avoid adding your own citations, since it is hard to have a neutral point of view wether your citation is really that important.

What you can do instead (and what I have seen), is that you suggest adding your citation (or some paragraph about your work) at the **talk page** of the article. Have patience and see how other react to your suggestion.

If on the other hand you see questionable sources, you might remove it. But again if you feel unsure if this is appropriate use the talk page of the article.
Upvotes: 3 <issue_comment>username_6: If you think that an article of yours would be a useful reference, you can mention it on the Talk page for the relevant article or an associated Wikiproject, and suggest to other editors that they consider adding it to the main article.
Upvotes: 3 <issue_comment>username_7: A few thoughts:

\* having expertise in the subject of a Wikipedia article is (or at least should) be welcome;

\* that expertise may well be exercised through detailed reviews of the article on its talk page;

\* references not cited in the article text have a lower probability to stay for long;

\* references supporting statements made in the article are most needed;

\* if one of your papers qualifies for supporting such a statement, suggest the edit on the talk page first, and if nobody objects within a week or so, feel free to do it;

\* apart from supporting statements in the Wikipedia article, images or other media from your research article might be useful as an illustration in one or several Wikipedia articles (including in other languages); this only works with openly licensed stuff (see [overview of such uses](http://tools.wmflabs.org/glamtools/glamorous.php?doit=1&category=Open+access+%28publishing%29&use_globalusage=1&ns0=1&depth=5&projects[wikipedia]=1&projects[wikimedia]=1&projects[wikisource]=1&projects[wikibooks]=1&projects[wikiquote]=1&projects[wiktionary]=1&projects[wikinews]=1&projects[wikivoyage]=1&projects[wikispecies]=1&projects[mediawiki]=1&projects[wikidata]=1&projects[wikiversity]=1); link loads slowly);

\* there are ways to write an entire paper such that it can be published as a Wikipedia article ([details](http://wikiambassador.jiscinvolve.org/wp/2014/03/28/publishing-scholarly-wikipedia/));

\* there are ways to follow added or removed citations systematically ([example: DOIs](http://events.labs.crossref.org/events/types/WikipediaCitation))
Upvotes: 2


<issue_start>username_0: I am a senior year undergrad student from a prestigious institute in India. I intend to pursue a PhD after graduating. While researching universities, I stumbled upon the fact that many of the top schools have a minimum GPA requirement. For example UCSD has 3.4/4 as its minimum requirement.

My GPA is 7.2 on a scale of 10. It is quite above average in my school, but it translates to a 2.9 on a scale of 4 which looks pretty bad. DOes this mean that my application is likely to be rejected outright?

Also, I heard that most universities don't consider converted scores (by WES, for example) in a good light. I have research experience in my undergraduate years to offset the GPA. I really hope that the universities have a look at that.

Should I not apply to schools with such a requirement?<issue_comment>username_1: There's no absolute here—it really depends on the program in question. Some departments are stricter about cutoffs than others. It depends a lot on the number of applications they receive, and how selective they need to be. However, I know that many good departments don't screen on GPA alone.

However, even if you're GPA is not "elite," that's not the end of the world, so long as you have the research experience and the letters of recommendation to support you. (A student from our department was recently admitted to a top-10 engineering program in the US on the basis of his research experience—his GPA was pedestrian at best.)
Upvotes: 4 [selected_answer]<issue_comment>username_2: Fundamentally, graduate schools are looking for evidence that you can successfully complete the program and graduate. So to get in, you have to make a convincing argument that this is the case.

Your GPA is unimpressive, but there are a few things that can make up for it. Two of them are test scores and faculty recommendations. What you need to do in both cases to rank much higher on these metrics than the typical "2.9" student. Then the fact that "my GPA ... is quite above average in my school," will start to count for something. Specifically, it may get your graduate school thinking, "This "2.9" GPA is at least a 3.2 or 3.3 on our scale, maybe more."

You're still not home free, but this is where your research comes into play. If you can convince the school that you have exceptional research potential, they may think, well, this guy is a "doer" who will "ace" the thesis, and get 3.2-3.3 in his courses, just enough to get the 3.4 average. Or it could be that the required 3.4 represents "insurance" against a graduating requirement of 3.2 or 3.3.

You'll probably want to get more and better advice from a faculty adviser. But if you do apply to the school of your choice, the above represent things to keep in mind.
Upvotes: 1


<issue_start>username_0: As the title says, do student reviews of teachers actually ever matter?

At least in the U.S most universities I know of have their students evaluate their teachers at the end of each term. I do know that things like tenure, if they do research, or if they are just an instructor plays a role in how weighted these evals are but even so, does anyone know if anyone actually cares or does anything with the reviews?

I've had many teachers of all types and some were notoriously horrible. Every year hordes of students would write lengthy reasons why the teacher was bad, give them very low marks, etc... And yet the teacher has remained.

I do know some teachers who do actually care (the teachers get them a semester later) and they can look at what the students liked/ disliked, etc... Which seems like the only way these evals are used. At least the way it feels to me, the administration (the ones who require these reviews), simply collect them, put them in a file, and never speak of them again.<issue_comment>username_1: Yes the reviews matter in a number of ways. They are generally considered by tenure and promotion committees and consistently awful reviews can prevent tenure/promotion even for someone with excellent research and service. Committees look both at the average/median and the spread/extremes of any numerical scaled questions as well as the open comments.

The evaluations are also used by some people to actually improve their teaching. This is obviously much harder to enforce, but in my experience no one sets out to be a consistently bad teacher.

Very rarely would a teacher be fired based on student evaluations since they have a number of inherent flaws. First the scores and comments tend to be much better in electives than required classes. Scores also tend to be better in small group teaching versus large lectures. Some topics also tend to score higher than other topics regardless of who is teaching. There is also the issue of bias. Student comments can reveal a shocking degree of sexism, racism, and homophobia. Finally, the timing is really wrong to evaluate how much the students learned and how important it was. Asking for an evaluation before the student can see how the class fits into the entire education, and future job, misses so much about what a teacher is trying to do.
Upvotes: 5 <issue_comment>username_2: In my department, teaching evaluation numbers are available to the executive committee for use in recommending raises (or non-raises) in faculty salaries. At the college level, these numbers are a required part of the file recommending people for promotion, and the file must also include the numbers for other recent instructors of the same course or similar courses (because it's known that some types of courses generally get better evaluations than others). One of the associate deans is expected to call the committee's attention to any serious problems with a candidate's teaching.

In general, extremely high or extremely low teaching evaluations, if consistent over a number of semesters, have a real effect. Near the middle of the range, they don't matter much.
Upvotes: 3 <issue_comment>username_3: No, for the most part these surveys don't matter. They were marginally relevant 40 years ago, when they first appeared, and have become even less relevant now.

They're generally not useful to the teacher in improving his/her teaching, because they're just numerical ratings. If students give me 3.7 out of 5 on "grades were fair," that doesn't tell me anything useful.

If the teacher already has tenure, they don't affect the teacher professionally.

At the community college where I teach, they don't matter for getting tenure, because tenure is a rubber stamp. At fancy schools, they don't matter for getting tenure, because tenure is based on research.

They also don't matter because they've been overtaken by technology. Students check web sites like whototake and ratemyprofessor; they never see the surveys, whose results are usually not made public. For public schools in the US, myedu.com will tell them grade distributions for various professors.
Upvotes: 2 <issue_comment>username_3: It depends on the university/college and the department.

It is sometimes joked that a good teaching award is nicknamed the "Kiss of Death". But by my anecdotal experience, this joke is not so far from the truth at some places. So presumably at such places, the weight placed on student evaluations (when deciding tenure say) is zero. Or perhaps even negative (!) - i.e., literally the worse your students think of you, the better for your tenure decision.

In contrast, at good liberal arts colleges, they are more heavily weighted.

It all depends on how much the particular department cares about teaching. It is difficult to generalize, even restricting attention to the US.
Upvotes: 3 <issue_comment>username_4: At my institution my professor told me that non tenure track profs are suspended if they have an unsatisfactory overall rating, which surprised me. For tenured profs it doesn't seem to matter so much. Tenure track profs might be hindered by consistently low ratings.
Upvotes: 2 <issue_comment>username_5: My experience as an University Lecturer is that academia have an entrenched bias verbalised as: "Those who can,do and those who can't, teach".
 Student feedback of a negative nature should be used to alert faculty that the staff who are teaching may need some professional development in ped/andr-agogy.
Upvotes: 2 <issue_comment>username_6: I have seen teaching evaluations being used to deny promotion to full professor.

That said, they are not always that useful. When I get my evaluations every semester I read them and sometimes they help me improve. But often they are so clearly biased that I get nothing from them: as an example I remember one that said "midterms are nothing like the assignments", and this was a week after a midterm where 3 out of the 5 questions were taken verbatim from the assignments.

I have also been in position to observe that beautiful and/or funny people get above average evaluations, as do easy markers. These facts don't help committees to take the evaluations too seriously.

As for ratemyprofessors, in my own case the comments there are not representative of what you see in the full sample of the in-class evaluations.
Upvotes: 3 <issue_comment>username_7: Student reviews may or may not matter depending on the institution, department, and professor.

For a research-active professor at a research institution they will most likely not matter at all in any respect unless they are really outliers...like worse than anyone has ever seen in the department. Even then, I think the result would be the department chair asking them to change.

On the other hand, at a teaching school or for a teaching professor (say, a clinical or adjunct) they can be extremely important and could result in termination.

Those are the extremes, and anything in between is also possible.
Upvotes: 1 <issue_comment>username_8: I think the answer depends on the teacher. If the teacher hopes to cover the subject well and is friendly with everyone, the rating should be average and the objective is achieved. But if the teacher wishes to engage the students either to get feedback on the subject taught or to better understand the various needs of the students to further tweak their understanding, then all feedback especially the negative ones, are useful. Alternatively, you can see that some teachers use "kiss the ass" approach in their teaching otherwise negative feedback would affect the renewable of their contracts. In reality, not everyone can claim to understand their students especially those who does not say much during and after classes. I think the feedback is a good outlet for such students and teachers alike. But not all teachers are willing to take risk in teaching. Hence, it is not surprising that teachers are increasing more difficult to to be taught especially those who spend 100% teaching compared to those who have certain % for research and teaching.
Upvotes: 2 <issue_comment>username_9: Yes and no. If staff member X is the protegee of influential higher-up Y, then no bad feedback can hurt X. Up to a complete walk-out by 30 students in protests of X's complete lack of preparation, arrogance, and ignorance.

(Yes, this is a true story about X. Rest assured that yours truly was not involved or affected in any way by it, so this is not sour grapes or anything, although, yes, this sort of thing deeply disgusts me.)

On the other hand, if staff member Z is up for the chop for some political reason, then negative student feedback can obviously be a stick to beat Z with.
Upvotes: 0


<issue_start>username_0: Warning: Extremely long post. Not really even the full story but one must stop somewhere.

My problem is the following:

I am a pure mathematics PhD student in (a remote part of) Europe and am part of a Doctoral Programme, which means that financially I am in a good position (relative to other grad students anyway). This is the same university in which I completed my undergraduate education. I was chosen together with a handful of other applicants from a pool of over hundred candidates (all natural scientists, not just mathematicians). I'm on my first year.

During my stay I have struggled to find a suitable problem (In fact I have overheard graduate students leave work early in my university because the feel that they didn't have much to work on). Basically my supervisor suggested some problems, I didn't like them, I tried desperately to invent my own problems to fill the void and to find something in the intersection of my interests and my supervisor's interests (and expertise). I realize now that with many of those problems neither I or my supervisor could really judge whether the problem was good or not (or whether it was known or not). During the summer the possibility that this arrangement is nonsensical started to dawn on me and I started to wonder if I should just consider moving to another university in another country to do a PhD.

My interests have sharpened and shifted somewhat during my stay as I got a better understanding of the current state of the field. On a couple of occasions I tried to tell him about my interests. Quite recently my supervisor told me that I need to start working on something and offered some problems that I didn't care about. Inspired by some advice of Sir <NAME> (["Advice to a young mathematician"](http://www.math.utah.edu/~zzhu/Advice_to_a_Young_Mathematician.pdf)) and AMS blog post ["Tips for New Grad Students"](http://blogs.ams.org/mathgradblog/2014/08/29/tips-grad-students/?utm_source=rss&utm_medium=rss&utm_campaign=tips-grad-students#sthash.cMEdMTAn.dpbs) I brought up the possibility of changing supervisor/university/country. He was certainly not relieved, and was concerned about the reputation of his research group, among other things.

I have discussed my concerns with doctoral programme coordinator and the person in charge of the PhD studies in our faculty. I am considered extremely fortunate to be part of the doctoral programme and losing a student would be unfortunate for the faculty. Changing supervisors or universities is something that doesn't generally happen here.

To an outsider the differences between my interests and my supervisor's would probably appear like splitting hairs. Indeed this is the position of my supervisor. The topics are likely to be outside of his expertise. He has offered to study together some of the subjects that I am interested in and to later study abroad with a more knowledgeable professor (the supervisor does have connections). He claims he will eventually find suitable problems if we study the topic together. Basically I envy students who get to study in a big active university or get to work with a guru who dispenses expertise and problems matching students' interests. I would be glad if I was offered even a low hanging fruit problem if it at least would teach me something in a modern and interesting field. It seems backwards to me that to learn a field together *with* the supervisor, instead of learning the stuff *from* the supervisor.

Our relationship has suffered as a result of this debacle. I think he is frustrated about my doubts.

So should I:
Go seek the frontier where the actions seems to be (I believe the things that interest me are being actively studied):

Pro: Potentially more efficient and stimulating PhD experience.

Pro: Potentially more prestigious university and/or supervisor.

Con: Changing universities is risky, the fact that I got funding in one university doesn't mean I will get it elsewhere, etc.

Stay where I am and try to make it work:

Pro: Safe in the short term.

Con: Uncertain if I will get suitable problems and sufficient knowledge to tackle such problems and continue a career in research.

Con: I have learned that people doing their undergraduate and graduate studies in the same university do less well.

Con: The track record of the supervisor to get PhDs to good places is not great.<issue_comment>username_1: I don't really know your situation, so this is just a first impression but: slow down. Take a breath. You're describing frustrations with things not working out...but you're still in your *first year of the PhD program*. Where I come from, students find advisors and problems much more gradually than this. If you were given problems "quite recently", then how do you know you don't care about them? If you don't care about the problems suggested to you because you have your own problems that you want to work on: find out if your own problems are viable, and if so find out who can help you with them. But if you don't have anything else you're dying to work on, I'm tempted to say: spend at least a month or two working on every problem your advisor gives you before you decide it's not for you. Why be so picky?

However, if you feel sure that you are not interested in anything your advisor is doing, then...sure, go study with someone else. The "reputation of the research group" is not really a sensible thing to be worrying about at this stage. Look, I went to (what is, along with a few others) the top PhD program in mathematics in the US. Nevertheless in the five years that I was there I watched students: (i) drop out of graduate school entirely, (ii) switch to a math PhD program in a different university and/or country, (iii) switch to a different department at my university, (iv) switch fields and/or advisors within my math PhD program. I never heard a peep about any of this damaging the reputation of the department or the university. People change programs *all the time*. Someone who is telling you otherwise may not be looking out for your best interests...

**Added**: Maybe my answer is US-centric. Other questions and answers on this site have suggested that European academia may be less flexible on these matters. If so: maybe consider going to school in the US. In every US PhD program in mathematics I know about, you apply to the program as a whole rather than to any research group or to officially work under any one faculty member. Then you have a period of 1-3 years to find your footing, pass some general qualifying exams and decide who you want to work with and then more time to decide what you want to do for your thesis. The whole process can take longer than in Europe, but in your case it sounds like you would find it more pleasant than your current situation.
Upvotes: 3 <issue_comment>username_2: First of all I agree with @P<NAME>'s answer. Changing supervisors is not the end of the world, it happens all the time and it is your right to do so. But the question you should ask yourself is why should you change?

I assume that your supervisor is an expert on the "great" math area you want to focus on, otherwise you would not have chosen him. By that assumption, expecting your supervisor to spoon-feed you a specific problem that you will like 100% and all you have to do is just solve it and get a PHD is an unrealistic goal in any PHD program. Supervisors suggest possible problems or usually specific scientific areas to focus on, close to their expertise. Then the problem is gradually refined as time goes by, as the student works intensively on the suggested area. This is a gradual process that does not happen magically overtime. In that sense, you cannot simply dismiss ideas (ideas are hard to come by) without sufficient knowledge of the research area ("could not really judge whether the problem was good or not") for some vague idea on what you want to do, without actually be able to judge if the problem you are suggesting has any merit or not. Choosing a problem is something that needs research maturity which frankly you do not have. At least in your first year of a PHD, you should trust others (your supervisor) to "show" you the way. You should at least start by his suggestions, do the required research literature search, get a firm grasp on the problems he is suggesting and not just "brush them off", because "you do not like them".

Note that your supervisor also seems like a nice guy, who is willing to study more on a area he is not familiar with, to help you. Not many professors a) admit their lack of knowledge on a subject b) go this far to help an inexperienced student like you. And believe me, this is an important quality for any supervisor. Also, lack of knowledge on a tiny area now, does not mean that when he actually does his "homework", he will not be able to guide you towards the new area. Professors and researchers change directions and progressively expand to areas less familiar to them when they "run out" of problems on their main expertise and this also something that happens quite a lot.

So, I suggest caution. Your funding is good, your supervisor seems nice, your university / department is reputable. Do not blow them all away for a mislead ambition on what problem you consider important or not. You can always walk away but you do not need to do it now, before you examine your options carefully.
Upvotes: 4 <issue_comment>username_3: The **most** important thing is to have great communication with your supervisor. More than just "we talk respectfully to each other" - you need to feel backed up and supported and understood by your supervisor. You need rapport.

If you don't have this, even at the beginning when everything is easy, then you are on a trip for disaster later as things get harder.

Reading between the lines, my sense is that this important rapport is not there.

If it seems hard to change now, wait till 2 years down the track when you discover just how poorly understood you are by your supervisor.

However, before you decide if this means you should change **supervisor**, you need to assess where the gap is. Maybe you need to change **you**?

Some of your statements are a little worrying.

>
> It seems backwards to me that to learn a field together with the
>  supervisor, instead of learning the stuff from the supervisor.
>
>
>

What is is that you think you will be learning? In your PhD you are learning *how to do research*. It is an apprenticeship, not a life work. It's your first, not your last.

You will be learning **from** your supervisor *how to do research.* Together **with** your supervisor, you will be learning about some *small new element* in a field of interest, in the process.

>
> He has offered to study together some of the subjects that I am
>  interested in and to later study abroad with a more knowledgeable
>  professor (the supervisor does have connections).
>
>
>

On the face of it, this is a generous offer. Can you look back at it and see if this generous person might actually be a good partner ... or whether in fact he's making this offer only to try to save face from losing you?

This is the crux of it, in a way. If you can appraise the difference, you will be able to make the right decision.

>
> Basically I envy students who get to study in a big active university
>  or get to work with a guru who dispenses expertise and problems
>  matching students' interests.
>
>
>

This would be a bad reason to change. The grass is always greener on the other side - you have no idea what debarcles all those folk are dealing with!

Priority #1: establish whether you can have rapport with your supervisor, take it from there.
Upvotes: 2 <issue_comment>username_4: Another thing, when you find a job, it is not always exactly what you wanted to do. It is difficult to find a job where you are happy all the time. I imagine as a post doc, you get to work with problems that you are not super excited about. Is it realistic to find a job where you are super happy and everything is fine? I doubt that? Life will always be like this; you will work with things you are not really interested in.
Upvotes: -1 <issue_comment>username_5: For what it is worth....

y experience also supports the idea that professors and programs are more flexible in the U.S. After working in academia with a Master's degree in the U.S. and now working on a PhD in Switzerland, I have experienced and heard about how much less flexible the professors in Europe are (mind you, there are exceptions on both sides of the Atlantic).
Upvotes: 0


<issue_start>username_0: I have checked the originality of my PhD thesis in mathematics using [Turnitin](http://turnitin.com/). The similarity was 31%. Is this percentage acceptable by most committees?<issue_comment>username_1: TurnItIn uses a complicated algorithm to determine whether a piece of text within a larger body of work matches something in its database. The TurnItIn is limited to open access sources and therefore has huge gaps in its ability to detect things. Further, while TurnItIn can in some cases exclude things like references and quotes from the similarity index, it sometimes fails. Overall, when my department's academic misconduct committee looks at TurnItIn reports we essentially ignore the overall similarity index. We do not completely ignore it in that it guides how we are going to further examine the document.

We employ 4 different strategies based on whether the similarity index is 0, between 1 and 20 percent, between 20 and 40 percent, and over 40+ percent. A piece of work with a similarity index of 0 is pretty rare and generally means that students have manipulated the document in a way that TurnItIn cannot process it (e.g., if a paper is converted to an image file and then converted to a pdf, there is no text for TurnItIn to analyse). A similarity index less than 20 percent can arise from work that contains no plagiarism with the similarity being quotes and references and small meaningless sentences. The key here is "meaningless". For example, there are only so many ways of saying "we did a t-test between the two groups" and it is reasonable to assume that someone else has used exactly the same wording. A piece of work with a similarity index less than 20 percent can also, however, include a huge amount of plagiarised material. A similarity index between 20-40 percent generally means there is a problem unless a large portion of text that should have been skipped was not (e.g., block quotes, reference lists, or appendices of common tables). A similarity index in excess of 40 percent is almost always problematic.

You really should not depend on the overall similarity index. First and foremost you should depend on your own following of good academic practices. If you have followed good academic practices, there really is no need for TurnItIn. If you want to use the TurnItIn report, you should look at what is being match and ask yourself why it is matching. If it found something your "accidentally" cut and paste, or "inadvertently" did not reword appropriately, fix it and use that as a wake up call to improve your academic practice. If everything it is finding are properly attributed quotes or common tables (or questionnaires, etc) and references then there is no problem.
Upvotes: 4 <issue_comment>username_2: I have some familiarity with Turnitin, though that was way back in undergrad. The thing about similarity engines is that they aren't perfect.

It's important to consider exactly how [Turnitin describes itself on its FAQ](https://turnitin.com/static/resources/documentation/turnitin/sales/Answers_to_Questions_Students_Ask.pdf).

### What does TurnItIn actually do?

>
> Turnitin determines if text in a paper matches text in any of the Turnitin databases. By itself, Turnitin does not detect or determine plagiarism
> —
> it just detects matching text to help instructors determine if plagiarism
> has occurred. Indeed, the text in the student’s paper that is found to match a source may be properly cited and attributed.
>
>
>

When we were testing Turnitin in high school (probably a decade ago) with a short writing prompt (~page or two) with a single source, the entire class ended up getting 15 to 20% similarity score, because not only did our sources match, but our quotes matched. No surprise there, really.

Now, consider how large Turnitin's database has grown. If this FAQ is to be trusted, you're comparing your paper to more than 80 thousand journals.

>
> Turnitin’s proprietary software then compares the paper’s text to a vast
> database of 12+ billion pages of digital content (including archived internet content that is no longer
> available on the live web) as well as over 110 million papers in the student paper archive, and 80,000+
> professional, academic and commercial journals and publications. We’re adding new content through new partnerships all the time. For example, our partner CrossRef boasts 500-plus members that include publishers such as Elsevier and the IEEE, and has already added hundreds of millions of pages of new content to our database.
>
>
>

If I recall correctly, you can see exactly where your paper has similarity with others, so you can pull that up.

### Sources of Similarity

My bet is that your paper cites papers almost identically to how another paper cites theirs. The great benefit of commonplace citing techniques like APA and MLA is that they're consistent.

If you cite, for example, the general APA format from Purdue, and someone else cites it, they're going to match at almost 100%.

>
> <NAME>., <NAME>., <NAME>., <NAME>., <NAME>., <NAME>., & <NAME>. (2010, May 5). General format. Retrieved from <http://owl.english.purdue.edu/owl/resource/560/01/>
>
>
>

The chances of you citing a paper that has never been cited before when compared to the world of science is, let's face it, probably 0%. Someone out there has cited your sources at some point. With sources being at times up to 10% of the paper's length, that's an easy portion we can knock out.

The other portion likely has to do with the vernacular that is used to describe a situation. Let's go with the following statement, written entirely off the top of my head.

>
> Java is an object-oriented programming language.
>
>
>

Pretty simple statement, and true enough that [it has been mentioned 260,000 times already, in that exact wording.](https://www.google.com/search?q=%22Java%20is%20an%20object-oriented%20programming%20language.%22&ie=utf-8&oe=utf-8&aq=t&rls=org.mozilla:en-US:official&client=firefox-a&channel=sb)

Similarity for that statement is 100% if it were to check for that. But when you make it loosely checked for similarity (i.e. remove the quotes from the search), you get [several million hits.](https://www.google.com/search?q=Java%20is%20an%20object-oriented%20programming%20language.&ie=utf-8&oe=utf-8&aq=t&rls=org.mozilla:en-US:official&client=firefox-a&channel=sb)

Does that mean I plagiarized? Nope. Would TurnItIn flag it? Definitely. Consider how likely everyday people great each other with "How was your weekend?" Are we plagiarizing each other's greetings? Nope. We pick up similarities in how we control language to understand each other, and that shows in papers, where we describe confidence intervals, methodologies, and processes the same way.

Perhaps even more terrifying in considering the similarity score, is that it will likely evaluate the two following statements similar:

Statement 1

>
> The double helix of DNA was first discovered by the combined efforts of Watson and Crick. Watson and Crick would later get a Nobel Prize for their efforts.
>
>
>

Statement 2

>
> The double helix of DNA was not first discovered by the combined efforts of Watson and Crick, but by Franklin. Watson and Crick would later get a Nobel Prize for her efforts.
>
>
>

Two very similar sentences. 80-90% similarity word-wise. Meaning-wise? Completely different. That's why the human element is required. We can tell those two statements tell an entirely different story when read. These small similar sets of wording add up quite quickly, and a 30% similarity in your case, given the level of research probably done in whatever your field is, and the amount of sources you have probably cited (100+?) is unlikely to be anything to fret about in this day and age.
Upvotes: 2 <issue_comment>username_3: >
> Is this percentage acceptable by most committees?
>
>
>

This is the wrong question to be asking, since academic decisions are not made based on a numerical measure of similarity from a computer program. The purpose of this software is to flag suspicious cases for humans to examine more carefully. It will identify passages that appear similar to other writings, but it can't decide whether that constitutes plagiarism.

For example, part of your thesis might be based on previous papers you have written. In some circumstances, it may be reasonable to copy text from these papers. (You need to check that your advisor approves and that it doesn't conflict with any university regulations or the publishing agreement with the publisher.) Of course you would need to cite the papers and clearly indicate the overlap. It's not plagiarism if you do that, but Turnitin doesn't understand what you've written well enough to distinguish it from plagiarism. So it's possible that Turnitin would flag lots of suspicious sections, but that your committee would look at them and see that everything is cited appropriately.

If you haven't committed any plagiarism, then you don't need to worry about this at all. If you genuinely write everything yourself (or carefully quote and cite anything you didn't write), then there's no way you could accidentally write something that looks like proof of plagiarism. There's just too much possible variation, and the probability of matching someone else's words by chance is negligible. The worst case scenario is that Turnitin flags something due to algorithmic limitations or a poor underlying model, but human review shows that it is not actually worrisome. (Nobody trusts Turnitin more than they trust their own judgment.)

I'll assume you don't know you've committed plagiarism, but it is possible that you honestly wouldn't know? Unfortunately, the answer is yes if you have certain bad writing habits. For example, it's dangerous to write while having another reference open in front of you to compare with. Even if you don't copy anything verbatim, it's easy to write something that's just an adaptation of the original source (maybe rewording sentences or rearranging things slightly, but clearly based on the original).

If that's what worries you, then you should take a look at the most suspicious passages found by Turnitin. If they look like an adaptation of another source, then it's worth rewriting them. If they don't, then maybe Turnitin is worrying you unnecessarily.

But in any case a plagiarism finding won't just come down to a percentage of similarity. Any percentage greater than 0 is too much for actual plagiarism, and no percentage is too high if it reflects limitations of the software rather than actual plagiarism.
Upvotes: 4 <issue_comment>username_4: I have used websites in the past to help with similar content, they will give you a report of what was found online and help remove/reword the similar content so you don't have to worry about your document being marked as plagiarism.
Upvotes: -1 <issue_comment>username_5: From my experience with Ithenticate (the version of turnitin for journals and conference proceedings), I'd say that 30% similarity most likely indicates significant plagiarism or self-plagiarism (recycling of text.) I would certainly investigate further to understand exactly where the similar text was coming from.

If the similar text is taken from sources written by other authors, then I would investigate further by reading the text carefully and comparing it with the sources. There are certainly false alarms raised by this type of software. For example, common phrases like "Without loss of generality, we can assume that..." and "Partial differential equation boundary value problem" will be flagged. Standard definitions are also commonly flagged.
However, if I see long narrative paragraphs with significant copying, that's clearly plagiarism.

It's traditional at many universities to staple together a bunch of papers and call it a dissertation. Conversely, it's also very common to slightly rewrite chapters of a dissertation and turn them into papers. Either way, this is "text recycling."

Now that text recycling can be easily detected, commercial publishers are cracking down on it for a variety of reasons. First, the publisher might get sued for copyright violation if the holder of the copyright on the previously published text objects. A different objection is that the material shouldn't be published because it isn't original.
As a result, text recycling between two published papers (in conference proceedings or journal articles) is rapidly becoming a thing of the past. This has upset many academics who have made a habit of reusing text from one paper to the next. Some feel that if the reused text is from a methods section or literature review, than the copying is harmless. Publishers typically take a harder line.

The situation with dissertations is somewhat different. In one direction journals have always been willing to accept papers that are substantially based on dissertation chapters with minimal rewriting. Since the student usually retains copyright on the thesis itself, there's no particular problem with copyright violation. Since dissertations traditionally weren't widely distributed, publishers didn't care that the material had been "previously published." I don't really expect this to change much in the near future.

In the other direction, there are two issues: First, will the publisher of journal articles object to reuse of the text in the dissertation as a copyright violation? You'd need to check with the publisher. Second, will the university be willing to accept a dissertation (and perhaps publish it through Proquest or its own online dissertation web site) that contains material that has been separately published? That really depends on the policy of your university and the particular opinions of your advisor and committee.
Upvotes: -1


<issue_start>username_0: I have been working towards a degree in mathematics and in computer science for the last two and a half years. That corresponds to the following bit in my résumé:

>
> **Education**
>
>  B.A. in Mathematics (2012 - 2016 expected)
>
>  B.S. in Computer Science (2012 - 2016 expected)
>
>
>

However, I recently found out that I can graduate next semester with a major in mathematics and a minor in computer science. If that was my plan, I would write this:

>
> **Education**
>
>  B.A. in Mathematics (2012 - 2015 expected)
>
>  Minor: Computer Science
>
>
>

However, at the moment I am undecided about which path I plan to take.

Which should I include in the résumé? I am considering just writing down whichever one would seem more impressive, but I don't want to be deceitful.<issue_comment>username_1: The best way I worded my resume was
Stating the school you when to, the city,state
Bachelors of Some Thing
Additional Fields of Study: Minor in Computer Science and Engineering

In terms of your resume, I would start out stating your revelant course work in a list but make it into a table (hide the borders when your done) that you can hide in MS Word.

After that put your volunteer and work history

after putting that put all the skills and qualifications.

I added something a bit extra which was I speak Chinese (Mandarin, Cantonese), Spanish, Japanese, and English (my second language was English)

Math majors are much needed in CS and in biology. That's a very good path.
Upvotes: 0 <issue_comment>username_2: Facing an uncertain graduate date is a common issue, particularly for many Ph.D. students who aren't sure exactly when they are going to defend. The thing that you want in your C.V. is to communicate as clearly as possible what are your skills *and time of availability* to the people considering taking you on for your next career stage after graduation. Thus, put your current best estimate in; if you want to indicate an option to join a position earlier, put that in as well as an option.
Upvotes: 2


<issue_start>username_0: For a class project in machine learning, I am considering building a set of predictors where the feature set includes information about the topic, keywords in the title, the authors, the date, etc., and the outputs are probability of getting published, expected citation impact, etc.

I would like to choose a single journal such as *Nature* for example. Will it be possible to collect the necessary data to accomplish this? Anyone have tips on where I can find statistical data about particular research journals?<issue_comment>username_1: By stating that you forbid students from using their cellphones in a lecture in a formal manner, you are making a rod for your own back. Some (many? most?) students will continue to use their cellphones during your lecture. Unless you draw attention to this when it happens, students may feel that the rules you have specified in your syllabus are, instead, suggestions, and some of the other rules may similarly be broken.

If your goal is to increase attention, there are other techniques. For instance, make it a habit to engage with the class by asking (easy) questions. Direct one of these at a habitual cellphone user. Even if the user is fiddling with his/her phone at the time, wait until the silence in the class becomes more engaging than facebook/twitter/email. He/she looks up. You have an enquiring face. What's the answer? Don't know. Oh. Anyone else? Point made. Move on.
Upvotes: 3 <issue_comment>username_2: >
> What is the best policy to deal with students using their cellphones
>  inside the class?
>
>
>

In my opinion: Just ignore them. As long as they are not disturbing the class I don't see a point in doing anything.

There are many different reasons for using a mobile phone during class, maybe they have to check something you said in the course material, maybe they just want to check their time or maybe their learning speed is faster than your teaching speed.

What you are trying to fight here seem to be two things:

1. The students are distracted by their phones.
2. The students are distracting someone else by talking to them.

The first thing is, in my opinion, not your problem. They are old enough to decide for themselves if they want to pay attention or not. You are providing them with the opportunity to learn something and if they take advantage of it is up to them.

The second point is (again, only my opinion) a valid point. However, I think you have the wrong approach here. You can't possibly know if banning mobile phones achieves that goal. The reason for using mobile phones is, most of the time, boredom (for whatever reason) and if not allowed to distract them with their phone they might try to distract them by talking with their neighbor. Therefore, a ban of mobile phones **might** be the cause for more side chats. If you want to reduce these chats maybe you should try it more directly.

>
> Is it OK to prevent students from using their cellphones during the
>  lecture by stating that in the syllabus?
>
>
>

The question should be: Is it OK to try to prevent students from using their cellphones. Here you have (as already said by @username_1) a problem of enforceability. Students are still going to use mobile phones (most of them (including me ;-)) don't even have a watch anymore) and then you have the problem that it will be hard to enforce your rule.

Again, I think you are trying to fight two things with your mobile ban: Distraction for themselves (which is, in my opinion) non of your business (and most students would just switch to something else to distract them) and distraction of others by talking to their neighbors.

If you want to fight the second point you should, in my opinion, try to enforce this directly, e.g. by asking them if they have a question (or, if it happened more often, to tell them to shut up or, in the worst case, just kicking them out) or, as @username_1 suggested, ask them an easy question.
Personally, I think it is impossible to distinguish if they are discussing something relevant to the course (which, in my opinion, is great and should not be banned) and irrelevant chats which are a (minor) distraction and should be banned, therefore I tend to ask if there is a question.
Upvotes: 4 <issue_comment>username_3: One of my high school math teachers used to make us leave backpacks, phones, even calculators in the front of the classroom during his lecture. This allowed us to spend less time on lectures, but with more dialogue, and gave all of us a feel for how to help each other. Sure, some of us were smarter than others, but when smart students got bored they could raise their hands and ask tougher questions, and when students fell behind, other students who were closer to the same level could offer their own explanations. That wouldn't have been possible if we'd had access to cell phones or even search engines, and it allowed him to more effectively pace his lecture according to class needs.

I don't think there's a universal answer to this question - it's like asking for a 'best' chess opening . . . but a few things to keep in mind:

* Cell phones don't just hurt attention span, they hurt class feedback, causing not only a clueless student, but a professor who is largely clueless about 'why' the student is clueless.
* People with phones don't have any idea how distracted they are. Not remotely. Even people who know will repeatedly underestimate the problem.
* The same students who complain about your anti-phone rules during the first week of class will blame you for their lack of understanding during the last week of class.
* Students who are smart enough to get bored of the lecture are often capable of identifying the needs of other students and helping to move the class forward - unless preoccupied by cell phones.

And on the flip side, a student who is *determined* to use a cell phone but isn't *allowed* to use it will invest extra focus in hiding the activity. At that level of determination though, I'd have to agree with Al<NAME>'s assessment that the student really does deserve to fall behind.

Good luck!
Upvotes: 3 <issue_comment>username_4: Regarding the use of cellphones in class-if I were an instructor, I would make it clear on the first day of class that they don't need to be on cell phones during the class. It can distract others, plus it shows disrespect for the learning environment and the teacher. Stating the issue of cell phones during the lecture by stating that in the syllabus is an excellent approach and needs to be enforced!
Upvotes: 2 <issue_comment>username_5: One of my colleagues says that any student found using a phone during class will have their final course graded lowered by two letter grades. While that seems draconian to me, one of my students says NO ONE has a phone out during his classes. Don't know if he has ever had to enforce it, but the threat seems to work.
Upvotes: 2 <issue_comment>username_6: (am not a professor, but am well versed in common sense) My approach would be along these lines:

As long as such activities are not impeding the ability of other students to learn, I would ignore students who are focused on their phones. It is completely within their rights to choose to ignore a lecture, or material that may help them pass a course.

If, however, said phone activity is causing disruption I would ask the student to either put the phone away, or finish the activity elsewhere.

You cannot save everyone, best to focus on those who clearly want to be there.
Upvotes: 0


<issue_start>username_0: I am co-teaching a relatively large class with two other colleagues in a big university. Each semester, most students are amazing, trustworthy, and well-behaved and it is a pleasure to work with my students. But there is a very small group of students each semester who cheat and I don't know how to deal with them.

The university has a detailed, strict, and elaborate policy for dealing with cheating. We send students suspected of cheating to a special committee where they decide if the student actually did anything wrong. The committee demands a copious amount of evidence before it convicts any student, yet at the same time, the university policy is so restrictive that we cannot collect evidence. For example, we are not allowed to do anything that indicates or suggest a student may have cheated. We are not allowed to mark their papers, move them during exams, or even talk to them. This means that most students get away with cheating if they are sent to the committee. Students who have copied identical answers from a neighbor over and over in quizzes got away with it in the committee. This process is so pointless that the course coordinator does not report most of the cases to the committee anymore.

I don't mind that a few students get away with cheating but the universities' restrictive policy shuts all the doors to any further discussion with the students. **I am not looking for ways to punish my students. I want them to understand why cheating is unfair to other students and, hence, unacceptable.** I want them to understand integrity and honesty are far more valuable traits than getting good grades in college.

Any suggestion on how I can communicate these ideas and their importance to my students?

---

Edit:

I am sorry for not being clear. My question is not about how to prevent cheating. It is bout how to have a conversation with cheaters.

We do what we can to prevent cheating. We randomly seat students, make two copies of the exams, assign a good portion the final grade to labs, and use various other techniques. This question is about reaching to the cheaters and having a discussion with them.<issue_comment>username_1: Since you speak of "a small group who cheat," it sounds like most of the students do understand the policies and importance of honesty. That remaining small group who cheats? Nothing that you do or say is going to convince them not to cheat.

Likewise, university policies often make it hard to actually punish cheaters, because they begin with the presumption of innocence, which is generally a good idea.

A better way to approach the problem is to adopt a "layered defense" strategy of a number of small actions that reduce the cost/benefit ratio available from cheating. Some of the sorts of strategies that I have seen include:

* Increasing the separation between desks
* Randomized assigned seating, which is likely to break up cheating conspiracies
* Printing less questions per page, with lots of white-space for working the problems, so that an answer will not be visible for as long a period of time
* Problems that are based on "showing your work" rather than obtaining the right answer.
* Problems with many possible solutions, that convert copying into plagiarism.
* Putting more credit into projects and labs, rather than exams.

None of these alone will solve the problem, but the more of them you can enact, the harder it is for cheaters to prosper. Some of them may even help the non-cheating students, by forcing them to engage more deeply with the material. The balance, of course, is that it all takes time and effort from the instructors and TAs, so you need to make your own cost/benefit analysis as well.
Upvotes: 5 <issue_comment>username_2: Your question was how to "communicate these ideas and their importance" to your students.

Sadly, you cannot. These students will cheat as long as it works for them, as you have already observed.

You can cut down on cheating by using username_1's suggestions in his answer.

I teach in the field of computing. The idea (of Jake's) that works best is supervised practical labs. Give the students homework, but make them come to the lab and produce a program. If they've cheated on the homework, they won't be able to do it. When they fail the lab, which should be a significant part of the grade, perhaps they will learn why they should not cheat. (My experience is that even that doesn't work. It *does* help cheaters pave their path to the exit.)
Upvotes: 4 <issue_comment>username_3: Randomize the questions on the quiz so that they can't cheat off their neighbors. You're approaching the problem administratively, when I think you can deal with it pedagogically.
Upvotes: 3 <issue_comment>username_4: If you are worried about whether students copy each other answers on exam just split them into groups, with each group having different (but similary difficult) questions, then arrange seating in such way that neighbours will be in different groups. This will make cheating much harder.

This arrangement is quite popular in Poland.
Upvotes: 2 <issue_comment>username_5: * Don't present it as a plagiarism/honesty problem so much as an originality/understanding problem. Problems need victims. The victim of my plagiarism problem might be a willing or eager one. Or maybe I paid him. Or maybe I don't care. The victim of my originality problem is myself, and my future, and my career.
* Have them peer-review each other. Most students care about a professor's opinion, but they're stuck with each other for the rest of their lives, particularly if they're all going into the same profession to get published by the same journals or build the same industries. They can convince each other that tests are silly, temporary metrics and that cheating is no harm, no foul . . . but concepts of character and dignity will hit much closer to home for students who have to produce comments about each other's originality.
* Have them produce questions about each other's codes, proofs, theorems, or whatever the subject matter is. If it's a technical class in which many answers are likely to look identical whether they are produced honestly or not, commenting on each other's work might be redundant. But producing questions requires creativity in *every* field, and answering those questions for each other requires basic conceptual understanding.
Upvotes: 4 <issue_comment>username_6: If you print the tests with the questions distributed randomly, so that question #7 on one test is question number 17 on another, and the correct answer to each question is also randomized, that seems to me a good solution to students looking at one another's answers.
Upvotes: 2 <issue_comment>username_7: Serious question: why is cheating unfair to the other students? Do you bell your grades? If a handful of students get 90 who should have got 70, will all the rest of the students see their marks drop 1 or 2% to compensate? If you don't officially bell, do you do so mentally (class average on that midterm was 82; I had better make the second one a little harder) ?

If not, then how is it unfair to the other students that some cheat? It is unfair to **themselves** since they will have the mark but not the knowledge to go with it. They will probably blow a job interview or two. They may struggle in next year's courses that assume they know this year's material. They are hurting themselves compared to genuinely learning the material. They cheat for one of two reasons:

* they don't care if they learn the material or not; it is of no value to them and they only want the mark
* they are unable to learn the material in the time they can allot to doing so

If you want to change their behaviour, you'll need to change one of these two things. Either show them how what they are learning will be of value to them, or find a way to help them learn it better.

Examples of the first:

* Today we will learn to normalize a database. This is a common technique when [whatever] and CSC 203, DSC 307 and most grad courses here all assume you're thoroughly capable at this technique
* The next few lectures cover this history and motivations of the X technique. I've heard that students who know this material well do very well in job interviews for Y positions, because the interviewers are always asking about this topic
* By the end of this term you will know how to ABC. This is the most common task assigned to new hires who've just graduated from our DEF program, which is why this course is required for all of you. While I hope you all get high marks in this course, what's really important is that you master the technique: there's about an 80% chance that you'll spend your first working year doing this, for an employer who won't help you if you find it difficult. The TAs and I are here to make sure you're comfortable with it by the time you leave us

Sure, this is work. As an adjunct myself, I don't always know what things I teach actually matter in what other courses the university offers - I don't have the curriculum memorized. I do have a little more insight into the job picture than some other profs. Still, you can figure this stuff out - ask the TA if you have one, for example.

Now the second part. Some cheaters are privileged self entitled brats who can't be bothered to put in the work. (My father taught someone who brought a servant to labs to do the actual physical work of the lab and couldn't understand why anyone would object.) Ignore them: whoever should have reached them at age 4 did not, and you probably won't now. But some are scared: if their average drops they'll lose their scholarship. They're finding it hard to keep up because they have a job as well as studying. Their parent or significant other is ill. They are hanging on to their position rather precariously and they do rash and wrong things because they think they have no choice. You can gain some insight into that mindset in another question: [I was caught cheating on an exam, how can I minimize the damage?](https://academia.stackexchange.com/questions/30539/i-was-caught-cheating-on-an-exam-how-can-i-minimize-the-damage) especially some of the earlier revisions where the OP explains why they decided to cheat.

So if you think someone has cheated and you don't want to use the official system, simply hand them a note that says "See Me" and a time and place such as "30 minutes before class, in our classroom" or "5pm today, in my office." When you have them alone say something like this:

>
> I think you were really struggling in that exam. I have learned to spot facial expressions over the years and you did not have the material for this course cold, nowhere near. You may manage to pull off a decent mark, whether by guessing or some other approach, but I don't think you know everything you need to know. Don't think I'm calling you in to get you in trouble. I want to help you. What do you need to learn this material thoroughly? Would you like a one on one session to go over the test questions and be sure you understand how to solve them? I have some resources that provide the same material we cover in class but from a different perspective, would you like those? (Perhaps some prefer videos, some diagrams, some hands on practices etc.) Have you talked to the student resource centre about test anxiety, test taking techniques, studying techniques etc? Did you know that if you have demonstrable issues with, for example, multiple choice questions I can work with the student resource centre to construct an exam that's a more accurate measure of what you personally know?
>
>
>

The entitled ones probably won't even come to the meeting, but if they do, they will decline all your offers and get out of there as fast as they can. The desperate ones? **You just might reach them.**
Upvotes: 4 <issue_comment>username_8: >
> *I want them to understand why cheating is unfair to other students and, hence, unacceptable*.
>
>
>

If I wanted to reason with a handful of cheating students, I wouldn't start by trying to convince them that cheating is unfair to *others*. I'd try to convince them that cheating is unfair to themselves.

Too many students have gotten into a mindset that they attend college primarily to obtain a degree. Instead, they should be there to attain an education. (There's a difference – and this difference often affects student attitudes and behavior.)

Students who aim to get a degree without caring about their education don't worry about how much they learn – they only care about what goes on their transcript. These students have no problem missing class, so long as they feel like they can get their hands on any "testable" material after the lecture. If they miss class for some reason, they will often ask, "Did I miss anything important?" (Translated, this means, "Did I miss anything I will need to know for the exam?" Sadly, it never seems to mean, "Did I miss anything that might come in handy for my first job?")

These students also have less qualms about cheating on an exam. It's all about getting a good grade on the test, which leads to getting a good grade on the transcript, which will lead to a good job down the road.

You might try reminding these slackers that they'll eventually be competing with students who did the work right and learned the hard way – and that some employers like to ask some tough questions during hiring interviews. Students who took their *education* seriously will probably have better success during those job interviews.

And even if they are lucky enough to bamboozle the HR interviewer and get a job offer somewhere, these students aren't necessarily out of the woods yet. Challenge them to gaze into the crystal ball, and imagine what will happen *after* that: when the company who hired them gets disappointed with their new employee, and more senior coworkers start to marvel at how that kid who had all those As and Bs on his transcript doesn't seem to know jack about anything, and can't write a decent memo to save his life.
Upvotes: 4 <issue_comment>username_9: I think, the real problem here is not the cheaters but the helpers.

You stress out that the cheaters do not understand that cheating is not fair.
Well, it does not have to be!
Because life itself is not fair and this is exactly the point of view of a cheater.

A student who lost his dad 4 days ago, a student who is sick and a student who is fully-fit taking the same quiz is not fair.
What I mean is, cheater could have his/her own reasons for cheating.

Hence, the problem becomes telling the helper that cheating is unfair.

But *which part of cheating is unfair?* Now let's say cheater C, helper H and a non-cheater N is taking the quiz.
It is unfair because a N either studied hard and took the same grade with C or did not study and got nothing even though C got a high grade. Well, in this case, H does not care what happens because he/she is *helping* a friend.

What I would do (actually did several times) is:

* Ask questions that can be answered in so many ways and distribute the full points of each question equally between the same answers. e.g. if question is worth 10 points and 5 students have the same answer, each get 2. This also encourage students to improve their creativity. That will prevent helper to continue helping and cheater to take minimum benefit.
* Give extra points to cheaters! When the results are announced, the helper will surely want to check his/her paper. But will not be able to find anything wrong and cannot ask to check the cheater's paper as well. Now, the hepler either will admit that he/she helped or will say *no* to further help requests.

In the long run, however, I decided not to care so much because university does not care as much as I do.
Upvotes: 2 <issue_comment>username_10: I simply disagree with those who believe that there is nothing you can do and these students will continue cheating.

There can be many reasons behind this behavior:

* some may fail to understand the importance of the course/topic
* some may be desperate to get high marks because they are not in a good academic standing
* some may have other issues, including family issues, etc.
* some may be taking too many courses that they cannot allocate enough time for each
* some may simply find it culturally acceptable.

I guess your best bet is to first identify the reason behind this behavior. Communicate with your students in a constructive way. Put yourself in their shoes and see what is the actual source. Only then you'll be able to effectively address these issues.

Clearly, finding the reasons is time consuming and requires a lot of effort from your side. But based on your question, I am assuming that you care about your students and are willing to take the necessary steps.

There are various ways to deal with each of the above situations. I'll be more than happy to briefly go over some of them if you are interested.
Upvotes: 1 <issue_comment>username_11: In my own teaching, I do not distinguish between "cheaters" and "helpers" in the way that you seem to suggest. The helper and the helped are both cheaters.

That said, the helpers are likely to be better students (since they can help), and thus are likely to have further ambitions (graduate study, well-paying jobs) for which they can use your goodwill later. My own attitude (and that of some like-minded colleagues) is that formal grades are always given as a matter of course when someone completes the work defined for a certain course, but my further mentoring, letters of recommendation for graduate school, support for local awards, etc., are optional at my sole discretion, and must be separately earned by demonstrated scholastic ability as well as appropriate conduct.

I thus do nothing with regard to grading when I know that a student has cheated (either as the helper or the helped) but have no proof, but that student will not later get a letter of recommendation, or a friendly tip about an exciting job opportunity at a great company, etc., from me. My colleagues and I who serve on local committees for awards during graduation, etc., also vote down any student whose ethics are suspect. This is not published policy as such, but good students know that this is how things work, and it keeps them in check.
Upvotes: 1 <issue_comment>username_12: It sounds to me that part of the problem is your university's policies, such as on collecting evidence and departments not reporting incidents. You may be able to collect evidence in a more roundabout manner (Can you make copies which you then mark up for evidence? Can you require that all graded materials be returned to you?). If you're still finding no way to effectively dissuade cheating and are getting no support form the university, you may need to consider looking for a different place to teach that actually cares.

One component of preventing cheating is making exams or projects where cheating is going to be very difficult. Having exams where students have to apply knowledge instead of just reciting memorized facts generally cuts down on students even being able to cheat (possibly with a fact sheet provided). Or, do like one of my art teachers did and actually assign a short portion of the exam period for collaboration. It'll honestly be a bit more like the "real world" if the end goal is application of facts instead of memorization.

As far as communicating good values to these students, I've had very little success at doing so myself. One statistic I've seen is that about 75% of undergraduates (and 25% of grad students) in one study self-reported cheating in college courses. For many students, the ends justify the means (consider tuition costs!). Ethics definitely would have to be presented to the class so they actually affect students' internal cost-benefit analysis. What will you be looking for that could get flagged as cheating? How would a future boss respond to fudged numbers or trying to submit someone else's work? How can applying yourself actually make tuition be worth it (or at least be less of a grievance)? How is this field applicable in the real world outside of the classroom?
Upvotes: 2